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Site Logistics Planning for High Rise Building Construction on Congested Downtown Sites
by
Hiba Mahboob Ali
A thesis submitted in conformity with the requirements for the degree of Master of Applied Science
Department of Civil & Mineral Engineering University of Toronto
© Copyright by Hiba Mahboob Ali 2018
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Site Logistics Planning for High Rise Building Construction on
Congested Downtown Sites
Hiba Mahboob Ali
Master of Applied Science
Department of Civil & Mineral Engineering
University of Toronto
2018
Abstract
Construction planning for tall buildings becomes more complex with small land parcels in urban
cores, fast-paced schedules and a growing number of domains involved in decision-making. This
research consists of evaluating the literature regarding construction planning techniques,
decision-making models, constraints in the current construction industry and holding interviews
with domain experts to summarize their implicit knowledge regarding construction site logistics
planning. It was found that there is no existing tool that adequately optimizes a construction site
plan as all research is carried out in isolation, only optimizing a certain piece of equipment or
operation. In this research, a multi-domain decision making tool was developed to assist project
planners in site planning on complex construction projects so multiple domain decisions and
impacts are simultaneously realized, and a framework for construction site planning that can be
applied to the industry was introduced.
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Acknowledgments
During my bachelors at the University of Toronto, I was sure I would not pursue a masters’
degree. In 2nd year, I met Professor Brenda McCabe in the construction management course. Not
only did I love the course and identify her as a mentor for myself and all the females in the
program, I also knew I would only do a masters’ degree under her supervision. Time passed, and
my feelings towards research did not change. I was sure I couldn’t do it.
After graduating from my bachelor’s, Professor McCabe saw the potential in me to be passionate
about construction management and took me in as one of her research assistants. It is with deep
gratitude and utmost unbelief that I say my success is entirely due to Professor McCabe, her
unwavering belief in me, her patience, guidance and her passion for improving everything
around her. She has inspired me since 2nd year, during monument meetings, weekly drop-ins
from us whenever she was available to chat about life, and through the last 3 years of my time as
a research assistant. Thank you for being so sincere, always encouraging me and for guiding me
through the hardest times in my life without losing faith in me.
Thank you to Professor Pressnail for agreeing to be my second reader in such short notice, for
accommodating my presentation time. Thank you for enabling me to graduate and asking the
most interesting questions during my presentation. You have made me so excited to work in this
field of knowledge.
Thank you to my research group, some who I got to start my journey off with and some who I
barely got to spend enough time with and still had the opportunity to become friends with. Thank
you, Yuting Chen and Hesam Hamledari, for taking the time to talk with me, and teach about
their research, things at the university and life in general. Thank you, Patrick Marquis, for
partnering with me on literally everything and going through it all with me, from the very start.
Kamellia Shahi and Eric Li for motivating me and checking in on me. Pouya Zangeneh, for
being the best desk buddy and making everything just a bit lighter. Finally, thank you Arash
Shahi, for laying down the groundwork for so much of our success at conferences and for all the
feedback for me.
Thank you to my friends, who stood by me, as I put my life on hold to get it all back together,
encouraged me in ways I didn’t know I needed, and monthly glared me into getting it done—
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whatever it might be. Thank you to my parents and my sister who have had the utmost patience
and understanding during my time in university and pushed me towards always striving for
better.
Thank you to Rescon, Daniels and Menkes for motivating this research and providing time and
resources for the information required to develop the framework developed in this research.
Finally, I want to thank Nelly Pietropaolo, who goes out of her way to make sure school is
running and my god is it running, but also makes sure her door is always open for anyone who
wants to talk. Thank you for all the times spent talking about events, volunteering, how to get
involved, camping, but most of all just life. Thank you for making my time at the University so
memorable.
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Table of Contents
Contents
Acknowledgments .......................................................................................................................... iii
Table of Contents ............................................................................................................................ v
List of Tables ................................................................................................................................. ix
List of Figures ................................................................................................................................. x
List of Appendices ........................................................................................................................ xii
Chapter 1 Introduction .................................................................................................................... 1
1 Introduction ................................................................................................................................ 1
1.1 Objectives ........................................................................................................................... 2
1.2 Methodology ....................................................................................................................... 2
1.3 Industry Partners ................................................................................................................. 3
1.4 Organization of Thesis ........................................................................................................ 3
Chapter 2 Challenges of Site Logistics for Tall Building Construction ......................................... 6
2 Challenges of Site Logistics for Tall Building Construction ..................................................... 6
2.1 Abstract ............................................................................................................................... 6
2.2 Introduction ......................................................................................................................... 6
2.3 Model Inputs ....................................................................................................................... 7
2.3.1 Object Storage Location Definitions ...................................................................... 8
2.3.2 Object Definition .................................................................................................... 9
2.3.3 Time Element ........................................................................................................ 10
2.3.4 Constraints ............................................................................................................ 12
2.4 Program Functions ............................................................................................................ 13
2.4.1 Model Logic .......................................................................................................... 13
2.4.2 Object Supply and Space Updating ...................................................................... 14
vi
2.5 Model Output .................................................................................................................... 15
2.6 Shortcomings .................................................................................................................... 15
2.7 Future Developments ........................................................................................................ 16
2.7.1 Special Considerations for Tall Buildings ............................................................ 17
2.7.2 Proposed Model .................................................................................................... 18
2.8 Conclusion ........................................................................................................................ 20
Chapter 3 Interaction Diagrams for Multi-Domain Decision Making Processes ......................... 22
3 Interaction Diagrams for Multi-Domain Decision Making Processes ..................................... 22
3.1 Abstract ............................................................................................................................. 22
3.2 Introduction ....................................................................................................................... 22
3.3 Research Method .............................................................................................................. 23
3.4 Literature Review .............................................................................................................. 25
3.4.1 Information Exchange Models .............................................................................. 25
3.4.2 Equipment Management ....................................................................................... 26
3.4.3 Construction Logistics Planning ........................................................................... 27
3.4.4 Discussion ............................................................................................................. 29
3.5 Decision Making Tools ..................................................................................................... 30
3.5.1 Weighted Decision Matrix .................................................................................... 30
3.5.2 Decision Tree Diagram ......................................................................................... 30
3.5.3 Influence Diagrams ............................................................................................... 31
3.5.4 Bayesian Networks ............................................................................................... 33
3.5.5 Interaction Diagrams ............................................................................................. 34
3.5.6 Decision Making Tools Comparison .................................................................... 36
3.6 Interaction Diagrams ......................................................................................................... 37
3.6.1 Developing the Construction Site Logistic Interaction Diagram .......................... 38
3.6.2 Construction Site Logistics Interaction Diagram .................................................. 40
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3.6.3 Case Study: 87 Peter Street, Toronto, ON ............................................................ 42
3.6.4 Improvements from Existing Models ................................................................... 46
3.7 Conclusion ........................................................................................................................ 48
Chapter 4 Site Logistics Planning with an Interaction Diagram ................................................... 51
4 Site Logistics Planning with an Interaction Diagram .............................................................. 51
4.1 Abstract ............................................................................................................................. 51
4.2 Introduction ....................................................................................................................... 51
4.3 Research Method .............................................................................................................. 52
4.4 Literature Review .............................................................................................................. 53
4.5 Planning Process ............................................................................................................... 54
4.5.1 Traffic Management Plan ..................................................................................... 55
4.5.2 Soil Remediation ................................................................................................... 56
4.5.3 Shoring Design ...................................................................................................... 57
4.5.4 Temporary Site Power .......................................................................................... 57
4.5.5 Crane Plan ............................................................................................................. 58
4.5.6 Hoist Plan .............................................................................................................. 58
4.5.7 Concrete Pump Plan .............................................................................................. 58
4.6 Interaction Diagram .......................................................................................................... 59
4.6.1 All Factors ............................................................................................................. 60
4.6.2 Traffic Management Factors ................................................................................. 62
4.6.3 Crane Factors ........................................................................................................ 63
4.6.4 Concrete Pump Factors ......................................................................................... 65
4.6.5 Hoist Factors ......................................................................................................... 66
4.7 Relationship Significance ................................................................................................. 69
4.8 Conclusion ........................................................................................................................ 70
Chapter 5 Conclusion .................................................................................................................... 71
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5 Conclusion................................................................................................................................ 71
5.1 Research Contributions ..................................................................................................... 71
5.2 Limitations of Research .................................................................................................... 73
5.3 Future Research ................................................................................................................ 73
5.3.1 Programming from Tacit Knowledge ................................................................... 74
References ..................................................................................................................................... 86
Appendices .................................................................................................................................... 91
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List of Tables
Table 1: Model Logic Summary ................................................................................................... 14
Table 2: Papers Modelling Types of Material Storage and Model Updating ............................... 28
Table 3: Weighted Decision Matrix Example .............................................................................. 30
Table 4: Traditional Nodes ........................................................................................................... 32
Table 5: Relationships ................................................................................................................... 33
Table 6: Interaction Diagram Features ......................................................................................... 35
Table 7: Benefits and Shortcomings of Decision Making Tools .................................................. 36
Table 8: Situation where Relationship Significance Varies ......................................................... 70
Table 9: Step 1 – Retrieve All Inputs ............................................................................................ 77
Table 10: Step 2 - User Inputs ...................................................................................................... 77
Table 11: Step 3 - Choose Equipment Combination .................................................................... 77
Table 12: Step 4 - Calculate Total Lift Times for 4 Scenarios for Each Equipment Combination
....................................................................................................................................................... 77
Table 13: Step 5 - Display Results ................................................................................................ 82
x
List of Figures
Figure 1: Site Layouts with Different Time Dimensions.............................................................. 11
Figure 2: Model Comparison of Storage Type and Feedback ...................................................... 16
Figure 3: Proposed Model Framework ......................................................................................... 20
Figure 4: Decision Tree Example ................................................................................................. 31
Figure 5: Influence Diagram Example .......................................................................................... 32
Figure 6: Bayesian Network Example .......................................................................................... 34
Figure 7: Interaction Diagram Example ....................................................................................... 35
Figure 8: Relationship Significance Survey ................................................................................. 40
Figure 9: Construction Site Logistics Interaction Diagram .......................................................... 41
Figure 10: Site Plan ....................................................................................................................... 43
Figure 11: Proposed Site Plan Using Interaction Diagram ........................................................... 45
Figure 12: Actual Site Plan ........................................................................................................... 46
Figure 13: Actual vs Predicted Crane Cycle Lift Times ............................................................... 47
Figure 14: Site Interaction Diagram ............................................................................................. 60
Figure 15: Hoist Outrigged Platform ............................................................................................ 68
Figure 16: Relationship Rating Difference ................................................................................... 69
Figure 17: Crane and Concrete Pump Program Decision Flowchart ............................................ 75
Figure 18: Crane Database Summary ........................................................................................... 83
Figure 19: KNF 336i-16 Load Chart ............................................................................................ 83
Figure 20: Concrete Pump Database Summary ............................................................................ 84
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Figure 21: Concrete Bucket Data Summary ................................................................................. 84
Figure 22: Radial and Tangent Movement of Hook ..................................................................... 92
Figure 23: Vertical Movement of Hook ........................................................................................ 93
Figure 24: All Building Factors Significance Ratings .................................................................. 94
Figure 25: Crane Factor Significance Ratings .............................................................................. 94
Figure 26: Hoist Factor Significance Ratings ............................................................................... 95
Figure 27: Traffic Management and Concrete Pump Factors Significance Ratings .................... 96
Figure 28: Crane 1 - KNF 336i-16 Load Chart ............................................................................. 97
Figure 29: Crane 2, 3 and 6 - Pecco PC 2000 ............................................................................... 97
Figure 30: Crane 4- Peiner SK315Figure 31: Condor FZ 001 ...................................................... 98
Figure 32: Crane 7 - Comedil CTL-250 ....................................................................................... 98
Figure 33: Crane 8 - AVRO LJK 160 ........................................................................................... 99
Figure 34: Crane 9 - Pecco PC 1400 ............................................................................................. 99
Figure 35: Crane 10 - Pecco PC 1200 ......................................................................................... 100
Figure 36: Crane 11 - Pecco PC 3600 ......................................................................................... 100
Figure 37: Crane 12 and 16 - Comedil CTT 331 ........................................................................ 101
Figure 38: Crane 13 - Peiner SK 415 .......................................................................................... 102
Figure 39: Crane 14 - Pecco Sn 406 ........................................................................................... 103
Figure 40: Crane 15 - Pecco PC 3000 ......................................................................................... 103
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List of Appendices
Appendix A: Crane Cycle Equations ............................................................................................ 91
Appendix B: Charts Showing Significance Ratings for Relationships ......................................... 93
Appendix C: Crane Load Charts ................................................................................................... 96
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Chapter 1 Introduction
Introduction
Tall building construction is increasing around the world as urban center population grows and
densification is required. Tall buildings are defined subjectively according to their height relative
to the height of surrounding buildings, their footprint to height ratio, and the technologies being
used (Council of Tall Buildings and Urban Habitat, 2018). Although tall building construction
allows a more efficient use of the land parcels, many challenges are introduced during the
planning, construction and operation phases of the building.
Some of these challenges were recognized by the Building Tall research group and turned into
research initiatives, including the analysis of cladding systems, a benchmarking of the permitting
process for the construction of tall buildings in Toronto, and stack effect management. This
research focuses on the optimization of site logistics planning for the construction of tall
buildings in urbanized areas.
With congested construction sites and smaller land parcels, there is less area at the exterior of the
building footprint to store materials during construction. This was investigated through a review
of the literature. Through interviews with industry professionals, it was found that storage during
the construction phase of a building was only one logistic that needed to be improved. There was
no established industry method for site planning. Instead, each company and expert has their own
process that evolved over time and is passed from person to person informally. This research
focuses on evaluating the literature, interviewing industry professionals, and collecting site data
to create a tool for site logistics planning that streamlines the process across the industry.
Construction logistics consists of decisions across multiple stakeholders, domains and trades.
The project manager is tasked with coordinating the trades, clients, engineers and architects, and
the government. Every decision that is made in any domain has an impact on the options that are
available for other decisions in the project. As there is currently no standardized or documented
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way for site planning to occur, the best decisions for each project entirely rely on the experience
of the project manager.
1.1 Objectives
The purpose of this research is to produce a method for construction site logistics planning that
aids project managers to make decisions. This is to improve communication between
stakeholders in the early stages of the construction project, reduce costs by decreasing change
orders during the construction process, and ensure a project meets its goals.
The main goals are to:
1. Compare methods currently used for construction planning in literature and in the field
and summarize the findings
2. Observe site operations on various projects in Toronto and identify planning procedures
for high-rise construction in Toronto
3. Create a tool that visually shows the impact of decisions across multiple domains for any
decisions with multiple stakeholders, summarizes common site logistics planning steps
across sites and supports decision making
4. Apply the tool to construction logistics planning in Toronto
The scope of this research focuses on decision-making for construction logistics for high-rise
buildings in Toronto. The current trends for construction planning and material storage in urban
areas are explored. Further details about the scope can be found in chapter 3.3.
1.2 Methodology
This research sought to incorporate findings in the academic literature with the experience of
industry professionals to formulate a construction site logistics planning process. First, the
literature was reviewed to summarize the research that exists. Topics of interest included interior
storage, identifying model types and their features, equipment planning methods, project
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management techniques, and decision-making tools. The shortcomings and strengths of these
topics are outlined in the following chapters.
Industry professionals were interviewed to identify perceived areas of research. It was
established that there is no industry-wide process used by project managers to plan a project, and
that most decisions were made based on learned knowledge. Once this gap was identified,
decision-making tools were analyzed to apply a tool for logistics planning use. There were no
tools that achieved what was required for project planners, so an interaction diagram was created.
Factors impacting site logistics decisions for vertical transportation of materials were identified
through interviews and site visits. These were applied in the creation of the site logistics planning
interaction diagram. The interaction diagram was reviewed by industry professionals and
revisions were made for ease of use and specificity. The diagram was then validated through
surveys and feedback from planners.
The final interaction diagram for construction site logistics is presented and applied to a case
study. Decisions made without the interaction diagram are compared to show how it simplifies
decision making for project managers, supplies reasoning for decisions, and summarizes the
impact of a decision on other domains. Future research is identified at the end of this thesis.
1.3 Industry Partners
The Residential Construction Council of Ontario (RESCON) is a board of directors that
represents builders, developers, and its other members on construction issues and purses research
to improve construction efficiency. In this research, RESCON is the industry partner, along with
its members The Daniels Corporation and Menkes Developments. Site logistics planning in
urban areas was identified as requiring a more efficient process as tall building construction
introduces new challenges in planning.
1.4 Organization of Thesis
This document is a paper-based thesis comprising three independent paper chapters, an
introductory chapter that explains the overall research, a chapter that provides guidance in the
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form of pseudocode for the development of a software to support the automation of planning for
vertical transportation, and a conclusions chapter that summarizes the findings and contributions.
Due to the paper-based format, there exists some repetition but efforts have been made to
minimize it.
Chapter 2 comprises a paper entitled Challenges of Site Logistics for Tall Building Construction,
which was presented at and published in the 2016 CSCE Conference proceedings. It summarizes
the limitations found in storage research and practices on construction sites currently, identifies
existing model features in the literature, analyzes their uses, and presents a proposed framework
for a model to automate site planning.
Chapter 3, entitled Interaction Diagrams for Multi-Domain Decision Making Processes, presents
a method for multi-domain decision making in planning, construction and operations. This is the
interaction diagram, a graphical model that shows the impacts of a decision in one domain on
decisions or factors within the same and other domains. An interaction diagram is constructed for
construction site logistics planning with a focus on vertical transportation and a case study is
presented to compare decisions made by using the interaction diagram to decisions that were
carried out during the project. This paper is expected to be submitted to Journal of Engineering
Education.
Chapter 4, Site Logistics Planning with an Interaction Diagram, details the construction logistics
planning interaction diagram developed in Chapter 3 with a focus on the vertical transportation
of materials and personnel. It explains situations for each factor and the impact it can have on the
rest of the project, as well as presenting steps to take when planning a construction project. It
will be submitted to CSCE 2019 Conference.
In the concluding chapter 6, the findings and limitations of this research are summarized.
Contributions to the body of knowledge are listed and future research to follow the findings is
mentioned. A pseudocode for optimizing concrete pump and crane operations using the factors
from the site logistics framework in Chapter 4 and equations from literature is introduced.
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Databases for concrete pump and the construction crane, summarized from manufacturer data,
are presented.
The appendices comprise collected data and references. Appendix A shows the comparison of
real crane lift times compared with predicted crane lift times using equations from the literature.
Appendix B summarizes the ratings for the significance of relationships for the construction site
logistics interaction diagram from surveys with experts. Appendix C shows crane load charts that
were used to build the crane database to be used in the program.
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Chapter 2 Challenges of Site Logistics for Tall Building Construction
The entirety of Chapter 2 is an article published in the proceedings from CSCE 2016: London
conference titled Challenges of Site Logistics for Tall Building Construction. Although there are
many authors, the work was primarily the undertaken by the first author.
Ali, H., Marquis, P., McCabe, B., Shahi, A., Lyall, R., and Francavilla, J. “Challenges of Site
Logistics for Tall Building Construction”. CSCE Conference. London, Ontario, June 1-4, 2016.
Challenges of Site Logistics for Tall Building Construction
2.1 Abstract
The construction of tall buildings has become a necessity in crowded urban cores, such as the
Greater Toronto Area. The result of denser population and shifting construction guidelines,
however, is the decrease of available space for building processes. For this reason, challenges in
planning and storage during construction phases occur. Reducing the cost of storage and the
distance of materials and equipment from the work area, while increasing site productivity
through scheduling and planning, is known as site logistics. This paper examines the existing site
logistics processes as well as site layout and optimization models that can be used for
construction of tall buildings. Advantages and shortcomings of each site logistics planning
strategy are noted and a set of recommendations are provided for better utilization of site area
during the construction of tall buildings. Finally, this paper outlines the use of interior storage
spaces as a viable solution for reducing the construction footprint of tall buildings. Factors that
need to be considered for including interior storage in existing site layout and optimization
models are also examined.
2.2 Introduction
The basis of site logistic planning for the materials and equipment (objects) that need to be
located on-site is a compromise between object size and shape, duration of storage, location of
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use, and available space on the site. Many models have been created for construction site logistic
planning to increase productivity and reduce costs and project duration. These models aim to
create layouts for construction projects that aid in placing objects close to the area of use,
ensuring an adequate supply of objects is available as needed to stay on schedule (Cheng and
Kumar, 2015). The models consider site space, schedule, and constraints as the basis of their
logic.
Early models used a simple framework where objects were placed outside the building footprint
on a first-come, first-served basis (Sadeghpour et al., 2004). Because space was readily available
and therefore not a constraint, the objective was to minimize travel time to bring the objects to
the work areas where they were needed (Tommelein and Zouein, 1993). While very useful in
some circumstances, the constructors of tall buildings in urban areas typically have to deal with
very restricted space, and congestion quickly becomes a serious problem (Jung et al., 2014).
Hence, more recent models have added features that are better equipped to address congested
conditions.
Although several models exist, they are often made for specific situations and cannot be used
seamlessly across all building projects. It is even more difficult to create such a model with the
continuous changes that the construction industry faces, ranging from policy modifications to
varying building environments and new construction methods.
The objective of this paper is to review existing models in the literature, analyze their
shortcomings, and provide recommendations for future models with a focus on tall building
construction in the Greater Toronto Area (GTA). The existing models are further compared
according to their inputs, program functions, and model outputs so a systematic analysis can be
presented.
2.3 Model Inputs
Every model needs inputs to define the situation. Every construction site, however, is unique due
to its location, project details, subsurface conditions, regulatory constraints, labour and material
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practices, and so forth. Fortunately, there are also some similarities across inputs used in many
models. The following section outlines and compares inputs used in existing models.
2.3.1 Object Storage Location Definitions
There are several factors involved in defining layout locations in a construction site. First, the
unique project details, such as site plans and schedules, have to be uploaded to the model. These
are obtained from various forms of documentation including drawings, spreadsheets and reports
(Sadeghpour et al., 2004). Once details of each construction project have been defined, a location
must also be represented.
There are generally three ways that locations are represented. First, predetermined locations can
be used to represent on-site storage areas (Wang et al., 2014). These blocks have a predefined
size and are used to store objects of one type at any point in time (Cheng and Kumar, 2015). This
means that a large space used to store a small amount of material is not available for other
materials as the block is used and therefore unavailable. Second, available space is described
using a grid. Objects can be located across multiple grids depending on their size, shape, and
other parameters (Sadeghpour et al., 2004). Again, once a grid is used, it is unavailable for other
materials. The final approach is to treat the construction site as a continuous space, allowing the
placement of objects anywhere there is space available. In this case, the model is able to
represent the actual area used, thereby making better use of the available space.
These various representations of space allow different levels of granularity for placing objects,
however, each comes with advantages and drawbacks. Models using predetermined locations are
computationally light as there are a limited number of areas where objects can be placed. The
biggest shortcoming is that it permits wasted space if objects are smaller than the predefined
locations. The grid system allows the user to define the size of the grid, thereby providing a finer
locating system if smaller grids are selected. However, no locations between the grids can be
used (Sadeghpour and Andayesh, 2015). A more accurate method for placement lies with the
continuous representation of space as it allows objects to be located anywhere on the site to get
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the optimal location with exact shapes. As expected, this method proves to be the most time-
consuming and computationally intensive to carry out (Zouein et al., 2002).
While many models use only space exterior to the building footprint, some also incorporate
interior space, adjacent space, and temporary off-site locations (Cheng and Kumar, 2015). The
use of exterior space is common, however, the congestion found in urban construction areas has
decreased available storage space exterior to the building footprint. For example, Toronto now
requires all new projects in the downtown area to extend the building footprint to the property
boundaries, leaving no space on the lot for material staging. This has prompted construction
managers in dense urban areas to look for storage space within the building. To date, models
have only used interior storage space as a secondary location in cases of over-ordering (Cheng
and Kumar, 2015). The use of adjacent land, such as roads and sidewalks, extends the site parcel
for easy storage, but requires permits and has associated rental costs. Finally, the use of off-site
temporary locations has also only been used as a last resort where there is no space available on
site and the objects have already been shipped (Cheng and Kumar, 2015). The use of these
secondary locations creates a need for two or three iterations of object handling, which decreases
the efficiency of the site logistics model as time and resources are allocated towards the
relocation.
2.3.2 Object Definition
After defining the location type, the definition of on-site objects is undertaken. Some parameters
that characterize objects include their shape, mobility and typology (Sadeghpour and Andayesh,
2015).
The shape of an object includes defining the object as a point, an orthogonal box or as its actual
shape. The point location only works for very simple sites with sufficient space, or where
predefined blocks are used. In this case, the predefined location must be able to accommodate
the largest object (Li and Love, 1998). The orthogonal geometry models objects as rectangles
and ensures no overlap on limited sites. They lead to suboptimal layouts because only two
orientations are possible, resulting in wasted space (Zouein et al., 2002). Finally, the
10
representation of the objects as their actual shape leads to the creation of complex algorithms, but
is necessary for congested sites (Sadeghpour and Andayesh, 2015).
An object’s mobility ranges from stationary to self-propelled objects. The modelling of
stationary objects, like cranes, is relatively straightforward, however, their location cannot be
changed once in place. On the other hand, moving objects like trucks requires programs to model
trajectories of the objects at various times throughout the project, ensuring that no clashes occur
(Tommelein and Zouein, 1993). In between the two, lie objects that can be relocated, such as
building materials. Finally, the object type classifications include construction equipment,
temporary facilities, construction materials, workspace, and access paths. These are necessary for
specifying handling procedures.
2.3.3 Time Element
There are three types of time breakdowns, namely, static, staged, and dynamic (Sadeghpour and
Andayesh, 2015). The static time representation allows the model to only create one layout for
the entire duration of the project, assuming objects remain at their locations for the entire
duration of construction. The staged representation allows users to breakdown the project into
times representing major changes with respect to site storage. The dynamic breakdown allows
the project to be modelled in real-time, showing continuous changes over the project duration.
The most efficient breakdown happens to be the dynamic approach. It incorporates the
consumption of objects as activities proceed, allowing the reuse of available space for future
storage (Tommelein and Zouein, 1993). Figure 1 shows the differences in site layouts using the
various approaches. Figure 1a shows the size and shape of each object, as well as the start and
end date. For instance, object A requires six grid boxes and arrives on day zero. Object A is
consumed by day four. Figure 1b, 1c, and 1d show the static, staged and dynamic time
breakdown approach, respectively. The staged approach is split at day 3, allowing 2 stages
during the construction project. By incorporating the dynamic approach, the space allocated to
object A during days 0-4, can be used to store other objects once A is completed.
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Figure 1: Site Layouts with Different Time Dimensions
As can be seen by the maximum number of boxes required in each time breakdown in Figure 1b,
1c and 1d, the static approach requires the most area to accommodate all site objects at 17 grid
boxes, while the dynamic approach, with a maximum of 11 grids occupied, requires the least.
The static time representation is not sufficient to create the object layout for complex projects
with limited space since they require the reuse of space. The staged procedure creates solutions
at predefined times of the project stages. It lengthens object on-site duration across the entirety of
a stage, but provides a better solution than the static approach. Finally, though the dynamic
model is the best solution as it changes layout whenever any object is consumed, it requires
12
significant computing efforts (Jung et al., 2014). To minimize these efforts, a discrete event
model can be used to model every change instead of every moment of a project (Tommelein and
Zouein, 1993).
2.3.4 Constraints
The limiting factors of site logistics that allow the optimization within the model are known as
constraints. These constraints are project and object specific, acting as the interaction between
objects and available locations. Although the main objective of a site logistics model is to
increase productivity by decreasing travel times, other objectives such as, providing work areas,
and increasing security also exist (Li and Love, 1998). Due to this, constraints can be set up as
decreasing travel distance, providing buffer zones around objects or areas, creating visibility of
certain objects for security reasons and storing objects inside spaces (Huang and Wong, 2015).
Consequently, the qualitative constraints defined above are translated into optimization formulas
in the form of utility functions. The utility functions add a weight to each constraint representing
their importance in the project. An example of a utility function is shown in Equation 1
(Sadeghpour and Andayesh, 2015). The representation of constraints in the utility function is a
numerical way to analyze trade-offs.
+ Pkw ijij
Equation 1
where w is the weight given to closeness between objects and k is the numerical representation
of a constraint being fulfilled. P is the penalty and ij refer to objects i and j.
In multi-objective problems with more than one constraint, violations are likely to occur as it is
harder to satisfy all constraints (Marler and Arora, 2004; Zolfagharian and Irizarry, 2014). Under
these circumstances, an unconstrained solution with penalties may be preferred (Smith and Coit,
1997; Wang et al., 2014). An example of a penalty may be in the form of object relocation which
may be necessary if objects cannot be placed close to their immediate work area due to existing
on-site objects. Hence, the penalties can be added to the utility function, shown as P in Equation
13
1 (Sadeghpour and Andayesh, 2015). Unfortunately, the difficulty of creating efficient penalty
equations due to optimal solutions being almost infeasible is noted (Smith and Coit, 1997).
The constraints are vital in tall buildings as productivity greatly decreases as buildings get taller.
This is due in part to the longer vertical transportation times for site personnel and objects from
the ground to the construction floor. The objects that limit vertical movement are cranes and
hoists. There are additional restrictions, such as limited work hours in accordance with local
noise by-laws, the need to acquire air rights for crane swings over neighboring properties, and
scheduling deliveries around rush hour traffic. Hence, there is a need to not only optimize the
location of these objects, but also their operations to ensure that objects are moved to required
location in time for use in on-going activities (Heikkilä et al., 2013). The operations can be
optimized using penalty functions as well (Wang et al., 2014).
2.4 Program Functions
Once users have input project specific details, the solution is dependent on the inner workings of
the program. The form of logic used by the model has a direct effect on the solution and the time
it takes a computer to solve the problem. Additionally, the object handling module has an impact
on the amount of space required on a site. The details of these mechanisms are discussed next.
2.4.1 Model Logic
The type of logic used is heavily dependent on the required level of detail, as well as the inputs
of the model. The simplest form of modelling is on an order basis, locating objects at optimal
available locations based on the order in which they are input to the program. This is a first-
come, first-served method, which can cause conflicts in complex projects in terms of the
ordering method actually used. Some proposed ordering methods for the objects include
chronological arrival, size, and on-site duration (Sadeghpour et al., 2004). Unfortunately, as this
is a step-by-step process, larger amounts of objects slows down the program.
A second approach is the incremental optimization technique, usually carried out with genetic
algorithms (GA) (Marler and Arora, 2004). The program creates a solution satisfying some of the
14
constraints. After this, it creates more solutions in increments, replacing the prior solution if the
posterior one is found to be better. The program stops creating solutions when it reaches a
threshold. This method allows the program to obtain a local optimized solution and is suitable for
sites with many objects as added data does not have a significant time effect on the program.
Finally, the program can also be designed to find the absolute optimal solution. Although this is
the best method, it requires the most amount of time, effort and computational power, sometimes
producing results that are only marginally better than the incremental optimization approach. The
approaches used for optimization in some existing models are summarized in Table 1.
Table 1: Model Logic Summary
Source Logic Type Visual Representation
Tommelein and Zouein, 1993 Order basis ✓
Li and Love, 1998 Incremental approach (GA)
Zouein et al., 2002 Incremental approach (GA)
Sadeghpour et al., 2004 Order basis (fuzzy logic) ✓
Sadeghpour et al., 2006 Order basis ✓
Said and El-Rayes, 2010 Incremental approach (GA)
Said and El-Rayes, 2012 Incremental approach (GA)
Heikkilä et al., 2013 Order basis ✓
Jung et al., 2014 Order basis (agent-based method)
Cheng and Kumar, 2015 Order basis
2.4.2 Object Supply and Space Updating
As sites cannot accommodate nor need to store their total objects throughout the entirety of the
project, a staggered ordering method is preferred. An approach that has been extensively used is
the just in time (JIT) ordering method, often associated with lean construction (Issa, 2013;
Marhani et al., 2012). This method allows sites to order only required objects for each phase,
decreasing the stock of objects on-site and thus the need for on-site storage space (Bertelsen and
Nielsen, 1997). This method has been reported to decrease schedule delays and overall project
costs.
In conjunction with the JIT method, space updating can be used. The space updating can be
automatic or manual, allowing the model to recognize available space for future ordering
15
(Heikkilä et al., 2013). A limited number of current models have built-in updating. The updating
allows re-optimization of the remaining site area as changes from the initial plan occur over the
duration of the construction project (Tommelein and Zouein, 1993).
2.5 Model Output
The pre-existing models have had two substantial ways of representing results. Firstly, the results
can be formatted as a spreadsheet, assigning a certain amount of objects to predetermined
locations on certain days. Although the spreadsheet summarizes the results very clearly, it does
not create a visual representation of the site.
A more recent method is a 3-dimensional (3D) model with built-in information, known as
building information models (BIM) (Cheng and Kumar, 2015). BIM can graphically show
locations of objects over the course of the project and allow the user to identify any assignments
they may want to change, as well as locations where objects can be moved to (Wang et al.,
2014). The 3D model is easier to use in presenting the site and analyzing the 3D changes for a
dynamic model, however, it has been found that 2-dimensional (2D) models are easier for users
to understand (Heikkilä et al., 2013). In recent years, the movement away from computer-
assisted drawings (CAD) into BIM software, which allows 3D and 2D imaging from the same
model, has been observed (Cheng and Kumar, 2015). Table 1 summarizes the existing models
that have incorporated visual output.
2.6 Shortcomings
Even with the considerable model mechanisms described, there are limitations in the field of site
logistic modelling. Firstly, there is no industry accepted standard procedure (Sadeghpour et al.,
2004). This is mainly due to the varying programs and techniques used by site planners. The
introduction of an industry accepted model would increase the ease of sharing data between
trades, planners and other relevant personnel.
There is also a lack of real-time updating to the models, which would simulate changing layouts
that take into account the as-built conditions. Furthermore, there is very little use of interior
16
space as storage for modelling. The range of existing model abilities with respect to storage type
and updating are shown in Figure 2 . As shown, there is currently no model among these papers
that uses interior space as primary storage and incorporates updating, which is needed due to the
impacts of any variances between the original plan and the as-built conditions.
Figure 2: Model Comparison of Storage Type and Feedback
2.7 Future Developments
It is proposed that future models incorporate a 4D approach, with automatic updating. The
updating can be carried out using a photo modelling technique. This technique uses 2D
photographs to create 3D models of a construction site (Gore et al., 2012). Updating the model
so as-built conditions are incorporated into the site logistic plan can result in the re-optimization
of site logistics since the as-built conditions may differ from the as-planned ones. This is
important since any changes can result in the initial plan becoming inapplicable without
updating. The use of a drone capturing 2D pictures can meet update requirements without
additional manual labour (Gaich and Pötsch, 2015).
17
Furthermore, manual changes to the simulations must be possible to ensure that expert
knowledge can improve computer generated solutions. This can be aided if the model shows a
few different options including optimal and sub-optimal solutions for the user to choose from.
Finally, the consideration for policies can be integrated to ensure that utilized space is permitted
for use. For instance, some areas on the site may not be usable in the footprint due to a need to
have an offset from surrounding pedestrian walkways. This step will help in the early planning
stages while the building footprint is designed.
2.7.1 Special Considerations for Tall Buildings
Apart from the logistic plan used, there are many factors to consider for the construction of tall
buildings. Some of these factors are presented in this section.
• Complexities of tall building construction introduce new constraints, such as:
o changes to storage space as the construction process progresses, including shifts
in the building footprint due to a podium to tower structure, and accounting for
the time needed for a slab to gain sufficient strength to be used to store materials
(Jung et al., 2014; Cheng and Kumar, 2015); and,
o the delay of interior construction due to the space being used for storage while
maintaining schedule criticality (Said and El-Rayes, 2012).
• Challenges with respect to cranes and hoists, such as:
o Vertical movement of objects, such as windows, precast concrete panels, steel
column and beams, where crane and hoists are limiting resources (Jung et al.,
2014) For example, if the crane is being used to move concrete, it cannot be used
for anything else. The use of a concrete pump frees up the crane for other
activities;
o Assembly and dismantling of cranes in congested urban setting and at great
heights;
18
o Decreased line of sight if the crane is placed too far from the building edge on the
side of a pick-up point; and,
o Increased wind forces as height increases.
• Requirements of different labels for each floor. An example of this is rebar_basement,
rebar_1, rebar_2 and so on. As different amounts of objects of each type are needed for
each floor, the ordering and locating of the objects in batches is necessary; and,
• Considerations to weather and height as duration of construction processes may vary. For
instance, pumping concrete at heights requires a thinner mix or expensive admixtures,
resulting in concrete needing more time to cure.
• Differences between the construction methods and materials used for tall residential
buildings compared to commercial buildings.
With the additional considerations regarding tall building construction and updated model
mechanisms, it is believed that a superior logistic planning model may be created. There is a
need for industry follow-up to gain further information about considerations to building factors.
This information creates cohesion between methods of carrying out on-site activities and the
planning of the application of activities as models can always be lacking without the inclusion of
industry experience. The inclusion of this data would ensure that the logistic model is feasible for
real-life conditions. The use of a database to store expert knowledge and apply it to future
projects is recommended.
2.7.2 Proposed Model
A flowchart of a proposed model can be seen in Figure 3. The steps of the model are outlined.
1. Users input documentation to generate a BIM site model and incorporate the schedule to
assess possible delays of non-critical activities. Any new expert knowledge or urban
policies can be stored in a database so they may be used for current and future projects.
19
2. The material supply schedule should be generated to minimize on-site objects.
3. The numbers of cranes and hoists and their location should be optimized. (Wang et al.,
2014).
4. Constraints can be input by the user at this point.
5. The locations of objects over the course of the construction project should be optimized
through discrete-event modelling and an incremental approach.
6. A 3D model of the optimized layout, as well as the option to display sub-optimal layouts
should be available to the user. This enables visualization and validation of the logistic
plan.
7. At this step, project updating can be input, so the model can optimize the remaining areas
returning back to step 4. This is to incorporate the placement of objects in locations other
than those specified in the initial plan.
8. If the building structure changes after construction has commenced, the updating returns
to step 1. It can skip step 3 if it is indicated in the model that cranes and hoists have
already been placed. This allows the re-optimization of the remaining objects. This
process is shown with the dashed arrows in Figure 3.
20
Figure 3: Proposed Model Framework
2.8 Conclusion
This paper identified mechanisms and approaches that are used in several models in site logistic
planning. The lack of interior space as an available storage solution in most models is identified
as a significant capability gap as it would limit the optimization of logistic plans for congested
tall building construction projects in dense urban areas, where exterior storage is limited.
Furthermore, the lack of updating capabilities was identified as another area of major
shortcoming of existing models, as the plans generated at the start of project would not be
applicable to the site for the most of the duration of the project. The combination of the preferred
mechanisms outlined in the paper, and addressing these shortcomings in existing models can lead
to the creation of a model that is efficient, comprehensive and adaptable.
21
With respect to the congested conditions occurring in dense urban areas and the complexities of
tall building construction, it is concluded that the use of an incremental approach for
optimization alongside the abovementioned considerations will create a model that can
efficiently and reliably optimize site logistics. A sample framework for a proposed model has
been outlined in the paper, which uses 3D analysis instead of 2D analysis so space-time conflicts
do not occur as vertical construction commences. This is especially important in tall buildings
since their structure changes over their height. Furthermore, the proposed model includes a
database to store expert knowledge and urban policies to guarantee all operations are permitted
and efficient. The next steps for this research is to gain knowledge in urban policies that heavily
affect construction site logistics, and to gain deeper understanding in vertical transportation
systems, such as hoists and cranes, and to build a site logistic model that is geared towards tall
building construction in congested urban areas, such as the GTA.
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Chapter 3 Interaction Diagrams for Multi-Domain Decision Making
Processes
Chapter 3 introduces interaction diagrams as a tool for multi-domain decision making and
describes the process of creating an interaction diagram.
Interaction Diagrams for Multi-Domain Decision Making Processes
3.1 Abstract
Site planning in urban centres has become increasingly complicated as construction sites become
smaller, buildings are taller, new equipment is introduced into operations, and construction
schedules are condensed. However, the most complex factor that has been introduced to site
planning are the decisions that are made across several domains and impact the construction
schedule. It has become important to use a multi-discipline decision-making tool so the best
decisions for the overall project are incorporated. This paper reviews current literature and site
operations for planning techniques to establish how construction site planning is carried out.
Decision making tools are reviewed to analyze their benefits and shortcomings in terms of
construction site logistics planning. Since decisions are not made in a strict order, or several
decisions occur simultaneously across domains in construction, a multi-domain decision-making
tool, the interaction diagram, is developed. An example site logistic interaction diagram focusing
on vertical delivery systems on construction sites is outlined in the paper and applied to a
construction site for a case study. The interaction diagram illustrates various decisions across
domains visually for project managers and shows the impact a decision has across multiple
domains and can be applied to unique scenarios for users.
3.2 Introduction
Over the years, construction-site planning in North America’s largest cities has become more
complex due to locational constraints to rising labour and land costs, changes in regulations to
accommodate surrounding activities, and limited availability of large land parcels. Several
23
approaches have been undertaken to improve decision making for construction site planning.
However, a method in which all constraints are considered together does not exist.
There is also a growing need for decision-making to be multi-disciplinary to increase
communication in the early stages of the planning process. Better communication can ensure
comprehensive design and planning and decrease change orders in the project. A linear planning
process often results in clashes of electrical, mechanical, and plumbing services with structural
or architectural building components. These lead to change orders and addendums, which are
costly.
The objective of this paper is to present a decision-making process that can combine several
disciplines and represent relationships in multi-factor decision-making optimization. Decision-
making approaches are explored, including information exchange models, construction site
logistics planning programs, and equipment management programs. These approaches can be
employed together to create a generalized planning method that spans the lifetime of a
construction project.
The research questions are two-fold.
1. How is decision making currently carried out to ensure the best design or construction
across multiple domains?
2. How can considerations from multiple domains be integrated to decrease changes and
inefficiencies between planning and application?
3.3 Research Method
In this paper, several techniques for planning and construction-site planning were explored
through the literature. The scope of the research focuses on determining current trends in
planning processes for the construction of high-rise buildings in Toronto—specifically for the
vertical transportation of materials and personnel—identifying their limitations and analyzing
various decision-making tools for application in construction project planning.
24
For the literature review, a set of queries was used to find papers relating to construction
planning including: construction management, logistics planning, site planning, decision making,
construction design, and resource management. Papers on planning techniques were also
explored using queries including: mind maps, interaction diagrams and multi-domain decision
making techniques. The papers were filtered using a set of inclusion and exclusion categories for
the construction planning papers.
Papers that were included had techniques that were used in construction, planning, or design
stages and improved communication, or operation efficiency in projects. Papers that were
excluded had methods that could not be used in North America, could not be applied to tall
buildings, or did not contribute to methods being used in the last two decades.
The literature review established the techniques which had been introduced in theory. After this,
interviews with experienced project managers were held to collect information about the
planning procedures that were currently being used in the field, their shortcomings, and areas
which require improvement. The example introduced in this paper is specific to construction site
logistics planning reflecting the domain the experts were interviewed for but can be extended to
other applications that require complex systems with multiple factors and decisions.
Data collection from site can be carried out to gain more information about inputs required for
decisions once the decision-making tool is created. In this case, site data for tower crane lift
times were observed and recorded. Finally, the various methods used in literature were compared
to identify their benefits and shortcomings to create a model that site managers and project
planners can implement for construction planning during the design and planning phases of
construction. The model is used to encourage early communication in the design and
construction phase across domains by visually showing stakeholders how their decisions may
impact other domains, and increase conversation with other domain stakeholders to optimize
decisions for the whole project. Although the model shows the decision factors and relationships
for users to make educated decisions, the project manager still needs to make decisions, and
understand the project and the decision-making tool.
25
3.4 Literature Review
Currently, there are no standardized, industry-accepted procedures for site planning that focus on
the complexity of modern projects with complicated design and limited site storage space. This
literature review explores the methods used in the design and construction process over the past
20 years. The review seeks to summarize current planning techniques and find ways in which
the isolated methods can be brought together to result in a comprehensive construction planning
method. These are categorized as information exchange models, equipment management,
construction site logistic planning, and feedback models.
3.4.1 Information Exchange Models
Information exchange models focus on complete data exchange between various models, by
creating a standard for data exchange. This can be seen in industry foundation classes (IFC),
which is a universal language that has been developed to enable interoperability between various
programs by creating libraries of elements from several programs used in architecture,
construction and engineering. Using this language, various users can export their data to the IFC
language and import it into other programs used by other users.
A typical use of the IFC has been seen in building information models (BIM). BIM is a 3D
model that is collaboratively between users, so separate sets of drawings are not required. It can
display the model, information about the model and also update changes to the design in real
time. BIM software uses the IFC language to export building elements from programs in
different domains to one program.
The BIM objects have rules and a library to help translate one type of data format into another
(Lee et al., 2018). BIM uses clash detection to ensure no overlapping elements are introduced to
a project or to allow users to leave notes for communicating required changes in other domains.
It has been used in construction logistics planning as it is an up to date building model, however
its use requires daily model updates, and ongoing communication with suppliers to maintain an
accurate schedule. (Cheng and Kumar, 2015; Kumar and Cheng, 2015).
26
Although data exchange models aim to ensure a complete migration of data to one program, in
the design phase of a construction project, they do not improve decision making due to domain
conflicts and only focus on physical conflicts represented in the models. An example of this is
seen when a building design creates a passive ventilation system as part of the envelope of a
building, which uses opening windows through the building strategically to allow ventilation in
the summer. However, introducing an air conditioning unit to the building or creating window
openings for aesthetics can cause interference with the passive ventilation design. Although this
creates a design that is not working efficiently in practice, in the BIM there are no physical
clashes of building elements overlapping. Thus, data exchange models leave it to the users to
identify operation clashes and only focus on complete data exchange, while having limitations in
identifying an efficient design for the overall project.
3.4.2 Equipment Management
In this context, construction site equipment management refers to the scheduling and operations
of high-cost equipment that impact site activities. The focus is on major equipment used during
construction, including the hoist, tower crane, and concrete pumps. Crane planning in the
literature focuses on minimizing the distance from the site pick up point to the installation
location, decreasing delivery time, creating an efficient crane radius to allow all materials to be
delivered as easily as possible, and minimizing cost (Rodriquez-Ramos and Francis, 1983;
Hosseini et al., 2017). The literature has examined single and multiple cranes on site, various
control methods for operating the crane, lift visualization, and crane operation efficiency to aid in
planning and providing feedback on sites (Zhang et al., 1999; Irrizary and Karan, 2012; Kang et
al., 2009; Lee et al., 2011; Shapira and Elbaz, 2014; Wang et al., 2014).
Hoist management planning deals with on-site productivity since taller buildings result in longer
delivery times (Wei et al., 2015). The factors that affect productivity are hoist velocity, distance
between stops, number of stops, and the load carried by the hoist (Cho et al., 2010). Finally,
concrete pump optimization is restricted to improving concrete mix design to ensure it can be
pumped long distances without strength or slump loss, choosing an adequate pump and hose, and
the experience of the operator (Wei et al., 2015; Ba et al., 2009; Liu et al, 2009).
27
Unfortunately, research into the planning of these resources is typically simplified with
assumptions to allow detailed modeling. This is not always representative of the planning needs
of site managers in real-life applications. For instance, there is often no indication of cost or time
savings that result in a project when multiple vertical-lifting equipment are introduced.
Furthermore, the equations found in literature are not universally representative of the time an
activity may require in real-life applications since site-condition factors are not incorporated (Ali
et al., 2016).
3.4.3 Construction Logistics Planning
Some construction sites have sufficient space for staging materials and are able to use a first-
come, first-served method for material storage. Planners focus on minimizing material handling
time on large construction sites by storing materials at the time of delivery as close as possible to
the area of final use (Sadeghpour et al., 2004; Tommelein and Zouein, 1993). In congested urban
centers, however, construction sites are often constrained in parcel size, limiting the material
storage space exterior to the building footprint.
Alternatives explored in the literature include interior material storage inside the building
footprint and model updating as construction progresses (Ali et al., 2016), as can be seen in
Table 2. Types of storage used on construction site typically include: off-site storage (typically
by using street occupancy or renting land close to the construction site); exterior storage outside
of the building footprint inside the site parcel if adequate space is available; or interior storage,
which is located at the lower storeys of buildings as construction progresses and concrete floors
reach strength (Jung et al., 2014; Said and El- Rayes, 2009; Said and El- Rayes, 2012;
Sadeghpour et al., 2004; Sadeghpour et al., 2006).
Site specific and user specified factors are inputs for material storage planning. These inputs
include defining the storage locations as grid blocks or points; defining material objects by the
shape, size, and quantity of materials to be stored; and, model updating. This last input is the
most complex and can range from a static site plan with only one storage layout for the duration
of the entire project to a dynamic plan reflecting the continuous changes in material needs and
28
space availability as the construction progresses and materials are consumed. (Sadeghpour et al.,
2004; Cheng and Kumar, 2015; Li and Love, 1998; Tommelein and Zouein, 1993, Sadeghpour
and Andayesh, 2015; Gore et al., 2012).
Table 2: Papers Modelling Types of Material Storage and Model Updating
Material Storage Type Model Updating
Static Dynamic
None Gore et al., 2012
Offsite
Exterior Only Said and El-Rayes, 2009;
Sadeghpour et al., 2004;
Sadeghpour et al., 2006
Interior (Secondary) Said and El-Rayes, 2012 Cheng and Kumar, 2015
Interior (Primary) Jung et al., 2014
User-defined constraints between objects and locations include minimizing the distance between
material storage and area of use, providing work preparation areas, maintaining a sight-line of
the materials for security purposes, and specifying types of storage needed for different materials
(Li and Love, 1998; Huang and Wong, 2015). Other constraints can include material supply to
introduce lean methods of construction to the plan and just-in-time material delivery (Issa, 2013;
Marhani et al., 2012, Bertelsen and Nielsen, 1997). This reduces the amount of materials and
congestion on site. However, this increases management challenges and the risk of materials
shortages for a task if there are delivery delays.
Models with feedback involve updating the building model to track construction progress, and
compare as-built conditions to design drawings and the project schedule. This has been carried
out by using pictures from cameras to create photo-based point clouds with GPS coordinates
(Gore et al., 2012). The photos are stitched together to illustrate the building process. A similar
process is carried out by drones to decrease required manpower and create an automated method
for updating. Furthermore, updating BIMs have been used to create crane lift simulations to aid
the crane operator during blind lifts (Heikkilä et al., 2013). The addition of feedback models to
planning and site management aids in viewing site conditions during the project, and timely
changes to the schedule.
29
The site logistics plan is typically a site plan or 3D model with equipment locations shown at
various times during the project based on schedule and material supply (Cheng and Kumar,
2015; Wang et al., 2014). Unfortunately, there is a lack of literature that employs interior storage
as a primary storage location, as required in the current congested sites, and models with material
updating based on material supply (Ali et al., 2016). Furthermore, there are few industry-
accepted models that perform material storage optimization and resource scheduling.
3.4.4 Discussion
The above three areas of planning focus on various construction project phases, ranging from the
early design process to construction progress tracking. The information exchange models seek to
use programming to automate data exchange between domains and identify clashes. The
equipment management and construction site logistic planning methods use the information
exchange models to create simulations on BIMs for a construction project. These can include
crane swing or hoist lift simulations carried out on a building project. Simulations are typically
based on optimization equations developed in the literature through site observations and
practices, such as crane swing time equations.
Over the last two decades, each area has been expanded to increase the knowledge and improve
the planning methods in each domain. The above methods focus on delivering results to users to
show the optimal solution based only on factors that can be represented quantitatively in
equations for a small part of a construction project, which can be applied to the overall site plan
by the user. However, the complex interactions within and between domains, and different parts
of planning and construction are disregarded in place of simplifying the problem to manageable
units. Regrettably, this means that there is a lack of an industry-wide procedure for construction
project planning. With this in mind, this paper explores existing decision-making tools and
outlines a method for creating interaction diagrams that take into account industry experience
and findings in the literature to create a decision-making tool that incorporates several domains.
30
3.5 Decision Making Tools
Decision-making tools have been used in a variety of decisions. In their simplest form, they
weight out the pros and cons of various choices, so the user can make the best decision with the
information they have. As problems have become more complex and it has become obvious that
not every factor in a decision-making problem hold the same priority as others, decision-making
tools have developed to take into account these changes. Five decision tools that focus on the
factors affecting a situations are discussed in this section, namely, weight decision matrix,
decision tree diagrams, influence diagrams, Bayesian networks, and interaction diagrams. These
diagram have specialized purposes and advantages, as discussed.
3.5.1 Weighted Decision Matrix
A weighted decision matrix breaks down various options into factors that a user requires in a
solution. As each factor may hold different importance for a successful solution, weights are
assigned to each factor by the user so that the sum of all factors is 100% as seen in Table 3.
Finally, each factor for each option is rated on a scale by the user. The ratings can be multiplied
by the weights and all the weighted ratings can be summed to show the best solution. Weighted
decision matrices are a simple way to rate different options as they assume that the factors are
independent.
Table 3: Weighted Decision Matrix Example
Criteria Weight Mobile Crane Interior Tower Crane Exterior Tower Crane
Rating Weighted
Score
Rating Weighted
Score
Rating Weighted
Score
Cost 0.35 -0.25 -0.0875 -0.5 -0.175 -1 -0.35
Product Quality 0.40 0.5 0.20 1 0.40 1 0.40
Reliability 0.25 1 0.25 0.5 0.125 0.7 0.175
TOTAL 0.3625 0.35 0.225
Rank 1 2 3
3.5.2 Decision Tree Diagram
Decision tree diagrams illustrate paths a user can take to reach a decision, showing at each node
the various choices the user has. These diagrams become very large for complicated optimization
31
problems since each path must be shown. They also inherently indicate a linear decision-making
problem, which may not be the case in complex problems. An example of a decision tree
diagram can be seen in Figure 4, where the building footprint size and height impact the crane
type used for construction.
Figure 4: Decision Tree Example
3.5.3 Influence Diagrams
The decision matrix and decision tree methods are relatively simple and are used to model
problems with independent factors. However, this may not be true for complex problems.
Therefore, the influence diagrams were developed. Influence diagrams are graphical ways to
represent expert knowledge for decision-making problems. They can be transformed into rule-
based programs by applying probabilistic distributions to the factors involved in a decision
(Howard and Matheson, 2005). Moreover, they can represent the visual logic in an optimization
problem without the restriction of applying mathematical proof by accounting for unknown
32
variables and aid in the gathering of empirical data for factors that have not yet been studied (Pearl,
2005). Traditional influence diagrams simplify the tree diagrams by assigning distributions to
nodes. They are acyclic, having no loops in them. A simple influence diagram is shown in Figure
5.
Figure 5: Influence Diagram Example
There are three types of nodes in the traditional influence diagram and two types of influence
relationships. The nodes represent different types of variables, whereas the relationships identify
how information from predecessor nodes impact target nodes. The nodes and relationships are
summarized in Table 4 and
Table 5, respectively (Howard and Matheson, 2005; Bielza et. al, 2010).
Table 4: Traditional Nodes
Node Function Mathematical Logic Shape in
Analytica
Decision
Node
Represents decisions that the user will
make, given all incoming variables are
known
Indicates the optimal
alternative
Rectangle (Nodes
A and C in Figure
5)
Chance
Node
These are factors that cannot be
controlled by the user and are usually
unknown until the time of the decision
Probabilistic
distribution of an
unknown variable
Oval Node B in
Figure 5)
Objective
Node
This is the goal of the influence
diagram, to optimize this variable for
Utility function of the
problem based on
Irregular hexagon
(Node D in
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the decision-making problem. incoming factors Figure 5)
Table 5: Relationships
Relationship Type Target Node Function
Informational (arrow A to C
in Figure 5)
Decision Node Indicates a linear, causal relationship. Indicates
variables that must be known at the time user has to
make a decision.
Conditional (arrow A to B
in Figure 5)
Chance Node Does not indicate a casual relationship. Indicates that
the probabilistic distribution of a chance node will be
influenced by the variables leading to it.
Conditional (arrow B to D
and C to D in Figure 5)
Objective Node Function dependency for the utility function
This model is useful for the incomplete representation of optimization problems in real-life
application as it takes into account experiential knowledge from industry professionals and
allows them to make decisions in their fields, following a linear path (Shachter, 1986). Experts
often have a better estimate of the results of a situation than can be easily represented by
equations, especially with the lack of empirical data. Creating equations also leads to a broad
generalization, resulting in models which do not apply for a variety of conditions or are too
broad to be accurate for real-life applications.
3.5.4 Bayesian Networks
Bayesian networks, which are mathematical models based on conditional probabilities, require
complete data for optimization problem representation. They are used to determine the probability
of an outcome given the probability distribution of factors leading to the final outcome. Each node
in a Bayesian network is quantified with a priori or conditional probabilities, which can be
determined from empirical data or from experts. While Bayesian networks are capable of handling
uncertainty, the outputs are probabilistic, which does not always help the decision maker when
quantitative optimization is needed for the decision-making process.
An example of a Bayesian network can be seen in Figure 6, where two nodes show factors for
building footprint size and building height, and how they impact the type of crane. Each node has
a probability, and the state of the nodes impact the probability of the state of the final node. The
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associated probabilities for each node is shown beside the node in the form of a table. As can be
seen, the probability for each type of crane is not 1/3rd, but depends on each scenario. The data for
the scenarios can be collected empirically.
Figure 6: Bayesian Network Example
3.5.5 Interaction Diagrams
Interaction diagrams minimize decision paths by representing nodes for each decision with each
node representing only the impact it can have on other nodes through relationship arrows. It is a
visual representation of qualitative information usually only known to domain experts as they
cannot be represented through equations. In this way, the interaction diagram is a comprehensive
overview of all decisions that need to be made in the planning phase. It can be used in
conjunction with influence diagrams and Bayesian networks to summarize probabilistic
distributions of factors involved, as well as descriptions about decisions that cannot be
represented through equations. Hence, the interaction diagram acts as a model to summarize
expert knowledge in a domain that is accessible to a variety of users. The nodes and relationships
are summarized in Table 6. The interaction diagram nodes have varying colors corresponding to
the domain they belong to. An example of this can be seen in the sample interaction diagram in
Figure 7.
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Table 6: Interaction Diagram Features
Feature Shape Function
Factor Category Node Rectangle Represents large groups of
factors in one domain
Factor Node Oval Represents factors in each
domain
Significance Relationship
Arrows
High Significance
Medium Significance
Low Significance
Not Rated/ Disagreed
These arrows show relationships
between factors. The factor at
the beginning of the arrow
impacts the factor at the end of
the arrow. The type of arrow
indicates the significance of the
relationship (the impact a factor
has on another factor)
determined from surveys from
experts in the field.
Figure 7: Interaction Diagram Example
36
The interaction diagram also allows for loops and does not define a path as decisions can be
made simultaneously and do not need to be made only in one order. For instance, a user can
decide to place a hoist in the building before placing a tower crane in the building. The location
of these pieces of equipment have an impact on where the other equipment can be located as they
cannot occupy the same space, however, there is no reason why a user has to locate one before
the other for every site. Finally, the interaction diagram allows for incomplete data for domain
factors and details about the decisions as it is not a path network, relationships and nodes can
always be added as required by the user.
3.5.6 Decision Making Tools Comparison
In Table 7, a summary of the benefits and limitations for the five discussed decision-making
tools is presented. Overall, the weighted decision matrix and tree diagram are models that are too
simple to represent complex planning problems, whereas the influence diagram and Bayesian
networks don’t adequately represent real-life decisions made in the construction field currently
as there are factors without collected empirical data and unknown variables in each decision-
making problem and offer no loops for decision-makers.
Table 7: Benefits and Shortcomings of Decision Making Tools
Decision
Making Tool
Benefits Shortcomings
Weighted
Decision
Matrix
Easy to make
Allows qualitative evaluation of
alternatives
Depends on user criteria weights
Must be updated as ratings or solutions
change
Assumes independence between factors
Tree Diagram Allows for incomplete data Becomes complicated and large due to
illustration of all steps along a path
Does not change qualitative decisions into
quantitative evaluation
Influence
Diagram
Allows representation of different
paths in probabilistic equations for
each node
Can have incomplete data
Must have a path for the user to make
decisions
No feedback loops
Bayesian
Network
Shows path for a decision and
evaluates various options on
probabilistic distributions
Cannot have incomplete data
No loop
Influence Allows for feedback loops No strict path for decision making – user
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Diagram Can have incomplete data
Decisions can be made
simultaneously
Visual overview of multiple domain
factors
must be aware of project
Must be updated for new technology or
domains
Specific to standard or process
The program Analytica added nodes and functionality to extend the usability of the traditional
influence diagram (Lumina, 2018). These include modules that help simplify the major influence
diagrams, by creating sub-diagrams for nodes to illustrate the factors impacting each node, and
feedback loops as long as a lagged time interval is introduced between nodes. The program
allows the user to build an influence diagram using nodes and relationship arrows, and then add
mathematical distributions to the nodes based on their influencing factors. The arrows in the
diagram will change based on the equations that are input, so this allows the users to build the
diagram as more data become available without deeming the entire model outdated or
inapplicable.
Unfortunately, influence diagrams inherently require the modeler to create a path for decision-
making. This is not always an accurate representation of the decision-making progress in real-life
application. As an alternative, an interaction diagram is proposed to be applied with an influence
diagram. The influence diagram can show probabilities and dependence of relationships for
certain paths in an optimization problem, whereas the interaction diagram is a summary of all
factors and the impacts a user decision has on various fields, without restricting the user to a
certain decision path. This is much more realistic as many decisions are made simultaneously or
may be carried out in a different order than the one path identified in an influence diagram.
3.6 Interaction Diagrams
The development of an interaction diagram depends on translating expert knowledge into a
visual model. This requires interviews with industry professionals and a literature review
regarding planning processes used in current domains, followed by a survey to rate the
significance of relationships and eliminate factors that are not agreed upon by the industry.
An interaction diagram uses rectangles to represent large decisions for the user and circles for the
factors that influence each major decision. The relationships between variables is based on
38
literature and expert knowledge, with different weights applied to the arrows to represent
significance ratings of relationships as determined by a survey among experienced individuals in
the field.
The overall goal of the interaction diagram is to show major decisions on a project in one
diagram and to reduce isolation in decisions, and to support experienced individuals in making
decisions systematically. Influence diagrams can be used as modules for major decisions or to
show the inputs of a factor, however, the overall project should be using interaction diagrams for
decision-making as there is no absolute decision or domain that is always most important in
decision-making and requires the flexibility of an interaction diagram to be applicable across a
variety of projects.
3.6.1 Developing the Construction Site Logistic Interaction Diagram
An interaction diagram communicates decision-making factors that are typically only known to
industry experts and trained individuals. Due to this, it is important to hold interviews with
experienced professionals to understand their decision-making process. For the development of
the construction site logistics diagram with a focus on vertical transportation on the site, project
managers and site planners were interviewed several times regarding the process of site layout
planning, including material supply processes, permitting procedures, and equipment logistics. It
was crucial to collect the planning processes on different construction sites as each site had
differing factors that were special to each case.
After identifying the factors from the interviews, any checklists that were already in place and
the most expensive decisions were distinguished. Furthermore, any problems that could occur
were pinpointed and typical resolutions were gathered. These included surrounding
environmental factors, such as construction crane radii being restricted by surrounding buildings,
permitting restrictions due to neighbor agreements, and traffic by-laws that impacted delivery
times and types to the site. At the end of the interviews, the common factors for all sites were
used in the creation of the site logistics interaction diagram since this allows the diagram to be
applied to a variety of construction sites.
39
All the various relationships and their impacts on different parts of site logistics were
summarized in the interaction diagram by illustrating factors in bubbles and showing
relationships between factors via connecting arrows. The details of each factor and any impacts
that it might have was researched in the literature and the by-laws of Toronto. These can be seen
in the references in the interaction diagram and the supplementary notes that accompany the
interaction diagram.
In the development of the interaction diagram, it was identified that each module of the planning
process needed to be represented visually in the interaction diagram to illustrate decisions of
each domain and easily see where interactions between domains occurred. This was carried out
by creating boxes around each domain in the interaction diagram and using different colors for
each domain. This will be seen in the case study below of the construction site logistics planning
interaction diagram.
For the purpose of validation, the interaction diagram was reviewed by expert individuals and the
significance level of each relationships was rated on a scale from 0 (minimal impact between
factors) to 5 (a very high impact between factors). Comments from the individuals were recorded
to determine any discrepancies between the ratings of the relationships. A sample of the rating
survey can be seen in Figure 8.
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Figure 8: Relationship Significance Survey
For all significance ratings that had a difference between expert opinions greater than 2, experts
were interviewed again and clarifications for their ratings were collected. At this point, experts
could also rerate the significance if necessary. Any significance rating of 0 for relationships
indicated that experts did not believe there was typically an impact from one factor to the other.
These arrows were then removed from the interaction diagram and a description of the special
cases where the relationship would be applicable was summarized for the reader. The
significance level for the remaining relationships were illustrated by using different types of
arrows. The legend for the arrows can found at the bottom of Figure 9. Finally, all relationships
and factors were explained in text format to supplement the visual decision-making process
shown in the interaction diagram.
3.6.2 Construction Site Logistics Interaction Diagram
The construction site logistics interaction diagram summarizes factors that influence decisions
regarding high-cost resources on site, as seen in Figure 9. This includes the crane, hoist and
concrete pump. The operations of all these pieces of equipment is influenced by construction site
factors and a traffic management plan. The decisions that are required to be made by a site
planner for the use of the equipment, such as the location or type of equipment impact the
operation of other pieces of equipment in this planning process, however, there is no preference
as to which piece of equipment should be planned for first. The arrows that are the most heavily
weighted have the greatest impact for decisions and should be determined as early as possible in
the design or planning process.
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Figure 9: Construction Site Logistics Interaction Diagram
The all factor category in the site logistics interaction diagram covers factors that do not belong
to any other category, are building-specific and have an impact of the all other parts of the
construction project. For instance, the avoid CP (critical path) activities impacts the location of
the crane and hoist to ensure the pieces of equipment are not located in areas required for the
building to be inhabitable like the mechanical room or lobby area. A single factor may impact
many other factors in the same or other domains. An example of this can be seen with the noise
by-law factor, which impacts the operation times of the hoist and crane, the type of concrete
pump used, and the delivery schedule. The crane, concrete pump and hoist have their factors
broken into factor categories of location, operation and type of equipment, where factors
influencing each category are identified. Finally, the traffic management category identifies
factors that may impact the deliveries to the construction site.
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The interaction diagram identifies areas in which empirical data should be collected to automate
decision making that is currently based on experience or theoretical knowledge. An example of
this is the time it takes a crane to perform a lift. Although equations exist in the literature, their
results vary from the real-life application as many factors found in the interaction diagram are
not considered in the theoretical equations. This includes wind speed and crane-operator delay.
By identifying factors that are not commonly included in theoretical processes by using the
factors identified by domain experts, a user can follow a decision-making process that is more
accurate to the results of a construction site.
Currently, the models that exist focus on isolated domain optimization. This was seen in the
equipment management and construction site logistics planning models. The equipment
management models take a few factors that come from the equipment and the building to be
constructed to optimize the location or operation of the tower crane or hoist. The construction
site logistics planning models focus on optimizing material storage alone. However, these have
an impact on the operation of the tower crane and hoist since the locations of material storage are
the drop off locations for the tower crane and hoist. Decision making tools that exist are either
too simple as seen by the weighted tree matrix and tree diagram, assuming independence or paths
for decisions, or requiring complete information and mathematical representation of problems as
seen by the influence diagram and Bayesian networks. Interaction diagrams summarize
qualitative data and allow for mathematical optimization models in each domain to show factor
influences on other domains.
3.6.3 Case Study: 87 Peter Street, Toronto, ON
The main purpose of this section is to illustrate the application of the construction site logistics
interaction diagram to a construction site located in Toronto that was observed during site visits
for logistic planning. A comparison of the real-life applied decisions that were carried out by
experience project managers and the decisions that are recommended with the use of the
interaction diagram by a novice is included.
43
The building that is to be analyzed is 87 Peter Street, Toronto, ON. It is a 157m tall building with
49 storeys. A sketch of the site and its location is shown in Figure 10. Each decision that is
outlined below follows the format: the decision is introduced, the proposed option for each
decision, its reason and impact are detailed. Finally, the carried-out decision and its reasons for
the site. The final layouts for the proposed and carried out decisions are shown in Figure 11 and
Figure 12, respectively.
Figure 10: Site Plan
The first decision that will be looked at is the crane type. There are two crane types (B3) that can
typically be used; a flathead crane or a luffing crane. The proposed option for this site was the
luffing crane. At the location of this project, there are several neighboring buildings (B13),
which minimize the radius a crane can weathervane (B11) (swing freely). Due to this, a luffing
crane is chosen so a large radius (B10) for lifts can be covered, while the jib can be maneuvered
to avoid neighboring buildings. The impact of the proposed decision is the increase in lift time
relative a flathead crane. As the luffing crane must perform two actions during each lift (pulling
up the load, then straightening the jib so the load can reach its destination), each lift takes a
longer time than a flathead crane would. The crane used was a luffing crane since the initial
erection of the crane was not higher than the neighboring building on the North side of the
44
construction area and a hammerhead crane would not be able to clear the neighboring building
even though the contractor has air rights. The city and neighbors were contacted to receive air
rights so crane swings over the adjacent land could occur. Due to this decision, the lift times
were increased.
After deciding on the crane type, the location for the crane (B2) must be decided. It was
proposed that the crane should be located external to the building, as close to center of this
building as possible, since it is not likely for the crane and hoist to share an apartment suite (A1).
However, it must be noted that elevator shafts and stairwells must be avoided (A3&A5). Since
the building is so small, the tower crane was located external to the building (B3). The impact of
this decision is the decrease between the distance of the crane, pick-up points and drop-off
points, resulting in an overall decrease in crane lift times. The tower crane being located
externally reduced finishing time of required areas for the building. On the other hand, there was
increased time to finish the façade where the exterior crane was anchored. The location for the
crane was the same as the proposed location. This was to minimize finishing time to the slab and
interior of the building.
The next decision is the inclusion of a concrete pump (C). It was proposed that a concrete pump
should be included, since the luffing crane (B3) decreases the productivity of the construction
site, a concrete pump (C) is introduced to the project to deliver concrete and decrease the
payload on the crane (B2). It is also useful as the concrete pump typically minimizes the delivery
time for concrete over the crane as the building gets taller. This would impact the payload on the
crane, decreasing it and maintaining a faster schedule for the site. At the site, a tower crane and
concrete bucket were used for concrete delivery between P3 and the 5th floor. After the 5th floor,
a concrete pump was introduced to maintain the schedule required by the owner for construction.
The final decisions that will be discussed are the inclusion and location of a construction hoist
(D). It is proposed to include a construction hoist. As this is a tall building and a luffing crane
should be used, a construction hoist should be included to decrease the payload on the crane
(B2). It is optimal to locate the hoist on the centre of the long side of the building (D4) to
minimize the distance of deliveries to either side of the building, however, due to site space
45
restrictions, there is no space for a construction hoist to be located at the exterior of the building
without imposing on neighboring properties. Due to this, the construction hoist can be located at
the short sides of the building. The impact of this decision is to decrease the payload on the
crane. There is a need for a traffic route for deliveries to the hoist (E1). Since the crane is already
located at the back of the building, the hoist can only be placed on the street side of the building,
requiring traffic closures to occur during delivery times (E4 & E5). At 87 Peter Street, the hoist
was located on the north side of the building. Neighbors were contacted and an agreement was
made with them to encroach on their property for the duration of the project. Due to this
decision, the hoist did not have to be accessed from the road and, therefore, no occupancy permit
was required to occupy sidewalk or road area. The doors of the hoist were positioned on the
shorter sides of the hoist to reduce encroachment on the neighboring property. The location of
the hoist is the only decision that differs greatly from the proposed decision.
Figure 11: Proposed Site Plan Using Interaction Diagram
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Figure 12: Actual Site Plan
The decisions made using the interaction diagram are very similar to the decisions made in the
actual project during construction. The real-life decisions that differ from the proposed decisions
were due to additional information that a user could not have while using the interaction
diagram, however, the issues were identified during the planning as seen in the location of the
hoist. By using the interaction diagram, a user was able to make decisions and identify
challenges that may require creative solutions. It is recommended that each company tweak this
interaction diagram to reflect their planning process and apply it to new construction projects for
consistency in planning, and programmers include impacts from the factors in construction site
logistics planning models.
3.6.4 Improvements from Existing Models
The interaction diagram seeks to aid project managers in decision making. It visually shows that
the productivity of a site or a piece of equipment is a function of various factors across domains,
as per Equation 2, and that several decisions impact each other. Furthermore, the interaction
diagram takes into account that decisions across several domains are oftentimes made
simultaneously and does not impose a step-by-step order on the user.
Productivity = f (x1, x2, x3, …)
Equation 2: Site Productivity
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Although, the mathematical representation of the factors implies that equations can be used to
represent site operations and optimize productivity and site logistics, it must be noted that an
experienced estimator or site superintendent outweigh mathematical models with their implicit
knowledge. This becomes obvious when a mathematical equation or model is compared to real
life data, as seen in a small summary in Figure 13. The recorded data was gathered from site
observations at various construction sites in Toronto, including 169 Fork York Blvd., 110 River
Street, 130 Queens Quay East and 2560 Eglinton Avenue West. Although, the same object, the
concrete bucket, is observed in the table below, the lift times vary in predicated and actual cycle
times. The predicted cycle times are impacted by the mass of the object being lifted and the
vertical and horizontal distances between the pick-up point and drop-off point of the object and
the crane itself, as per Appendix A: Crane Cycle Equations (Wang et al., 2014).
Figure 13: Actual vs Predicted Crane Cycle Lift Times
Most of the recorded data is within 50% of the predicted cycles times with four recordings as
outliers. Due to these observed differences between recorded data and predicted cycle times, the
interaction diagram relies on experienced decision-makers with mathematical models as a
supporting aid if required rather than a critical part of the decision-making process.
48
The interaction diagram can be customized to each company so an agreed overall decision-
making process can be developed for construction site planning, while users still have the
flexibility to apply their experience to the decisions using the framework-like interaction
diagram. It also enables experts in each domain to represent their tacit knowledge into a method
that can be learned by others. Finally, as new technology is developed, the interaction diagram
must also be revised to reflect the new domains.
3.7 Conclusion
Site planning has become more complicated in recent years in Toronto as construction projects
become more complex and require coordination between multiple fields. There is currently no
existing, industry-wide planning process, however, many companies and experts carry out
planning in systematic ways that have not been documented. The processes found in the
literature are often isolated in domains.
As established in this paper, there are currently processes to improve communication between
disciplines in the design process through the development of seamless integration between
programs using BIMs for clash detection. Planning methods for decision making on construction
projects include equipment management and site logistics planning, however, there is no model
that addresses the relationship site logistics planning can have on equipment operation or any
other domains. Hence, decision-making models were explored to create a system that can
represent the impacts of decisions across the several domains involved in a construction project.
Potential decision-making models include the weighted matrix, tree diagram, influence diagrams
and Bayesian networks. The weighted matrix and tree diagram are helpful with small, isolated
decisions since they assume independence, and a strict path to follow for a decision, respectively.
The influence diagram and Bayesian networks are a good representation of the probability of a
decision outcome given that mathematical models are known for each and the model is complete.
Modelling using influence diagrams is heavily based on a deep understanding of factors that are
involved in an optimization problem, the collection of expert knowledge in the domain and the
modelling of unknown information (Bielza et. Al, 2011; Howard and Matheson, 2005). The
49
shortcomings found in these decision-making tools, namely, the inability to have loops,
incomplete models and a representation of qualitative data, led to the development of the
interaction diagram to illustrate the various decisions involved in a complex project across
domains.
The interaction diagram summarizes all factors and the relationships between decisions across
various fields, which allows for decisions that are carried out simultaneously and not always
carried out in the same order as there is no restricted path. This can be seen in the example of the
site logistics planning model and case study above, where the decisions for tower cranes, hoists
and concrete pumps can be made simultaneously while the user is able to see the impacts a
specific site or traffic plan will have on these decisions, as well as how making decisions in one
domain or for one piece of equipment will impact the rest of the construction site.
Influence diagrams can be used as modules for major decisions or to show the inputs of a factor,
however, the overall project should be using interaction diagrams for decision-making as there is
no absolute decision or domain that is always most important in decision making and requires
the flexibility of an interaction diagram to be applicable across a variety of projects. These
interaction models can be used in the construction industry to illustrate design and planning
optimization problems in building construction, oil refineries, mining jobs, and transport lines by
splitting job types into factors that are typical across similar projects and displaying the inputs
necessary for the user to make decisions. This is a useful way to represent the problem since the
various decision domains can be viewed together and relationships between domains identified,
thus reducing isolation in decision-making. Communication in the early stages of planning can
be increased as users are able to see many domain impacts and no longer have to make only
decisions in their domains without any information on impacts to other domains, resulting in
project decisions that are optimal for the project as a whole. Since these diagrams make use of
domain knowledge and illustrate the decision-making process visually so the decision-making
process is communicated with individuals in other fields, the interaction diagrams serve as an
intelligent system to streamline decision-making processes in projects and justify decisions. They
summarize all the factors impacting a decision and are a better representation of decision-making
50
that does not follow a specific path since multi-domain decisions are not linear than influence
diagrams and Bayesian networks.
Interaction diagrams can be created in each company, field or placed as a policy in decision-
making at a city planning level to create industry-accepted, decision-making systems in each
field. Furthermore, several influence diagrams can be turned into modules to represent influences
of decisions across various domains and used as input in larger programs for planning and
design, as seen in the construction site logistics model above, while the interaction diagrams can
provide a detailed view of factors impacting decisions given different starting points for the user.
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Chapter 4 Site Logistics Planning with an Interaction Diagram
Chapter 4 details the site logistics interaction diagram presented in chapter 3 and outlines a
construction site logistics planning process.
Site Logistics Planning with an Interaction Diagram
4.1 Abstract
Building construction in urban centres, such as Toronto, has become more complex due to
densification and taller buildings, as well as increasing logistics and interactions between
multiple domains and trades during the design and construction phases of a construction project.
There is currently no industry-wide method for site planning and this results in each individual
project manager, each company and each trade making decisions with their own processes,
creating optimization in isolation and not for the project as a whole. This paper presents an
outline of construction site planning and a framework to aid project managers in decision-
making with multiple domain factors and impacts. The developed framework in this paper
focuses on vertical transportation of materials and personnel, and can be modified to include
more domains and new equipment as required by site managers. By using the framework, every
company can have a basis for decisions and create standards for project planning.
4.2 Introduction
Tall building construction in congested urban areas, such as Toronto, has become more
challenging with increased land and labour costs, and changing regulations. To reduce the cost
and time required in the overall construction of a building, improvements in site logistics
planning are necessary. Site planning for construction sites in Toronto, as well as for the most
expensive pieces of construction equipment like cranes and hoists, is typically performed
manually by experienced project managers. There are no existing guidelines that novices can
follow to perform these duties as they usually familiarize themselves with the concepts through
experience and learning from other site managers. Currently, in literature, site logistics
52
optimization is carried out in isolation for each piece of equipment, not considering the impacts
one decision may have on the overall site plan.
The objective of this paper is to present a framework for the decision making that is required in
site logistics planning in Toronto, and to create a model that can support the decision-making
process in future projects and be used in construction education. Although the details of this
framework are specific to Toronto, it can be modified to meet the needs of any location. This
framework includes logistics covering the tower crane, construction hoist, concrete pump and the
traffic management plan. Some steps for planning are introduced in the paper, followed by an
interaction diagram of factors affecting site logistic decisions and the significance of their
relationships.
4.3 Research Method
For the research of this project, the decision-making processes of construction sites in Toronto
were modelled. This involved observing sites with logistics planned by industry professionals
and finding common methods used across all construction sites. The sites observed included 169
Fort York Blvd., Toronto, which consists of three residential towers of 8, 18 and 30 storeys; 110
River St., Toronto, consisting of two residential building tower of 10 and 29 storeys, and 130
Queens Quay East, Toronto, to be built to 35 storeys. The first two sites used construction hoists,
cranes and concrete buckets for vertical transportation, whereas the last site used a concrete
pump for concrete delivery. In total, over 12 hours were spent observing the sites and 24.5 hours
dedicated to obtaining model information from studying site logistics plans. Apart from site
observations, a review of the literature and city and provincial by-laws pertaining to site logistics
planning was completed. The findings are discussed in the following sections.
Expert A is the director of high rise construction at Daniels Corporation. He has been working in
this field for 10 years, with a previous background as a superintendent at Tridel and currently
oversees the operations of 10 sites located in Toronto and Mississauga. Expert B is a senior
project manager at Menkes, and currently manages two residential towers being built at One
York St., Toronto. Expert B has previous experience in the construction industry in Calgary as a
53
general contractor and carpenter. Due to the difference in their experience and current roles,
there are discrepancies seen in their interviews for factor significance rating. This will be further
outlined in the next section. Apart from these two experts, professionals in the field of concrete
finishing and formwork engineering, as well as an additional project manager, were interviewed.
4.4 Literature Review
Project management for a construction site requires planning for several site activities, ranging
from scheduling day to day tasks to making decisions about large pieces of equipment, and
balancing the budget of the project. The Project Management Body of Knowledge outlines
management techniques for scheduling, assigning resources, identifying risk and communicating
with stakeholders for general management (Project Management Institute, 2013). The literature
currently focuses on safety and risk of a construction site (Perrenoud et al., 2017; Pirzadeh and
Lingard, 2017; McCabe et al., 2017). There is also a trend towards simulation for construction
management education focusing on cost and scheduling (Rokooei et al., 2017). Research into the
transferring of construction management knowledge has been undertaken to identify
shortcomings in translating construction experience into shared information (Tatum, 1993).
However, all of these methods do not take into account policies for pieces of large equipment or
the interaction decisions for one piece of equipment have on the rest of the site plan, as they rely
on industry professionals to be aware of the changing policies and intuitively create site
management plans based on experience.
Currently, equipment optimization is often carried out in isolation in the literature. Crane
operations are typically optimized by minimizing the distance to the material lift locations on the
site (Rodriguez-Ramos and Francis, 1983). Sites with multiple tower cranes can be similarly
optimized by minimizing the number of conflicts between the cranes and the distances of all
anticipated lifts (Zhang et al., 1999; Irrizary and Karan, 2012), which can also be assessed
visually (Kang et al., 2009). The crane costs may be used as a proxy for operations and
minimized (Hosseini et al., 2017). Although these methods have considered the cost and lifting
time for the tower crane using site specific building layouts, they did not consider the effect of
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local policies on the operation of the tower crane or the advantage of including other vertical
lifting equipment, such as a construction hoist, to reduce the work required by the crane.
Construction hoist planning typically uses computer simulation to model how hoist productivity
is affected by increased heights and longer wait times for personnel (Wei et al., 2015). Some
programs for construction hoist planning focus on modifying hoist operations based on changing
building envelopes by using inclined hoists (Kim et al., 2016). Hoist operating plans have been
developed based on hoist velocity, distances between stops, the number of stops, and the weight
of materials or personnel to be carried (Cho et al., 2010). Simulations for peak vertical
transportation periods, such as the morning rush for workers have been created to optimize trip
breakdowns (Kamleh, 2014; Park et al., 2001). For these studies, assumptions focus on
optimizing the operation of the hoist without looking at the impacts of choosing the location or
the type of hoist.
Finally, research in concrete pumps are limited to improving concrete mix for pumping and
strength purposes and the characteristics of the pump (Wei et al., 2015). Some studies look at
applications of the concrete pump in tall buildings and some considerations such as the pump
and hose type, and experienced operators to optimize concrete delivery (Ba et al., 2009). There
have also been studies to determine the difference between the actual delivery rate of concrete
pumps compared to the manufacturer’s data (Liu et al., 2009).
All of these optimization efforts are carried out in isolation either in the piece of equipment or
have general planning procedures that must be applied to the construction industry. There is a
need to draw on elements of these categories to create a framework for site planning. The
framework seeks to summarize the effects of the decisions since optimization in one category
may result in a loss of productivity or increased costs for the construction site. Furthermore, a
planning process is outlined to show phases of a site plan that should be considered.
4.5 Planning Process
The planning process of a construction site involves making a site plan of all deliveries and
activities to occur on the site. The site plan documents are submitted to the governing body to
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obtain permits so construction can begin. The planning process typically includes the following
six to seven major steps:
• Traffic Management Plan
o Phase 1: Excavation Plan
o Phase 2: Construction Plan
o Phase 3: Construction Plan 2 (optional)
• Crane Plan
• Soil Remediation
• Shoring Design
• Hoist Plan
• Site Power
• Concrete Pump Plan
4.5.1 Traffic Management Plan
The traffic management plans fall under the construction management plan for the planning
checklist provided by the City of Toronto (City of Toronto, 2017b). It seeks to communicate the
requirements of each site to the city and is approved on a project-by-project basis to avoid
conflicts between the local traffic and other construction sites in the area. Furthermore, the goal
of the construction management plan is to reduce impacts to local traffic and negative impacts to
public safety. For construction sites located in areas with heavy traffic, a traffic study may have
to be conducted to analyze the effects on the neighborhood (City of Toronto, 2006). Due to the
complexity of traffic in Toronto, the City is in the process of mandating that traffic management
plans must be designed by traffic consultants as opposed to project managers (City of Toronto,
2013). The traffic management plans can have two to three phases.
The first phase of the plan is the excavation plan. Since deliveries and traffic are comparatively
simpler in the excavation phase of the construction project, this is a simpler traffic plan
indicating the excavation area, entry and exit ramp locations, site gates for access to the
construction site, temporary construction fence locations, and signage. This plan typically gets
56
approved by the City of Toronto over a shorter time than the construction plan. The excavation
plan is submitted for approval and must be approved before site work can begin.
The construction plan can be submitted for approval at the start of construction for the project,
while excavation occurs. It is usually approved within six to eight months in the City of Toronto.
It is considered the permanent traffic plan for the site since it typically remains in place for the
rest of the duration of construction. This plan identifies truck maneuvers on site and on the road
for deliveries, road closures, site entry and exit gates, staging and material storage plans, and
required signage.
Finally, a phase 3 construction plan can be submitted for approval if the phase 2 plan becomes
inadequate for the construction site. This is usually due to policy or cost changes during
construction. An example of this is a change in street occupancy costs in the City of Toronto
from a flat rate fee of $5.77 + HST /m2/ month to permit fees from $27.67 to $110.68 + HST
/m2/month for roads based on the area being occupied and $6.06 + HST /m2/month for sidewalks
(City of Toronto, 2015; City of Toronto, 2017a). This type of change can drive construction site
managers to implement new traffic management plans on the construction site to reduce areas
that are being rented from the City and reduce site costs.
4.5.2 Soil Remediation
A geotechnical study must be performed on a construction site by a professional geotechnical
engineer, as required by the City of Toronto in the planning application checklist (City of
Toronto, 2010; City of Toronto, 2017b). This study identifies the soil composition and can also
indicate if soil remediation must occur at the location. In Toronto, there are two land
classifications for development: greenfield and brownfield. Greenfield refers to land that has had
no previous development on it. While this typically means that remediation is unlikely, there
have been instances where remediation was required due to salt in the soil. Brownfield land
refers to land that has had previous development, which indicates a strong potential for
contaminants in the soil (Government of Ontario, 2012). Soil risk assessment must be carried out
on the first 1.5 metres (depth) of soil on a site (City of Toronto, 2014b). Depending on the results
57
from the risk assessment, remediation must be carried out on the soil, sometimes requiring a
higher standard of soil to be imported to the site (City of Toronto, 2014b).
4.5.3 Shoring Design
Shoring systems are temporary structures that hold soil in place so construction can occur in the
excavated opening on a site, and must be designed by engineers (City of Toronto, 2014a). The
two most common shoring systems used in Toronto are secant (also known as caisson) pile
walls, and soldier pile and lagging.
A secant pile wall is a system in which holes are drilled into the ground and concrete is filled in
the holes to create a rigid perimeter before excavation begins (Macnab, 2002). These piles are
drilled into each other to create a continuous wall and can have reinforcement in them. The
soldier pile and lagging system consist of wide flange steel columns hammered into the earth
(Macnab, 2002). As excavation occurs, timbers are installed between the steel piles.
Both these shoring systems can use tiebacks, which angle down into the earth and use tension to
hold the lagging systems against the excavated walls (Macnab, 2002). A tieback agreement must
be obtained from the adjacent property owners identifying where the tiebacks will be located, the
de-tensioning procedure of the tiebacks, and protection of adjacent properties in case of damage.
If a tieback agreement cannot be made with neighboring properties or utilities, alternate systems
like rakers must be used. Rakers are steel members that angle to the floor of the excavation to
support the walls of the excavation. Although these are cheaper than tiebacks and require no
agreements with neighbors, they obstruct the area of construction.
4.5.4 Temporary Site Power
Preparing the site for construction requires electrical service for the equipment and natural gas
for winter heat during construction. In Toronto, this requires consulting with Toronto Hydro and
Enbridge (Toronto Hydro, 2018; Enbridge, 2016). The consulting includes planning the
relocation of cables, utilities and fire hydrants to ensure a clear area for construction and fire
safety, and to provide temporary water supply and power for construction (OHSA, 1997). In
some cases, adequate power supply is not available, and diesel-powered equipment must be used.
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4.5.5 Crane Plan
The crane is the largest piece of equipment on a building construction site and impacts its
surrounding area. Deciding which crane will be used depends on the formwork contractor, since
the formwork contractors in Toronto usually own the cranes. The radius and capacity of the
crane is based material loads for the project and the crane load charts; the dismantling procedure
will also influence the crane location and operations. The location of the tower crane and its
boom swing must be identified when obtaining a permit from the City of Toronto (City of
Toronto, 2017a).
4.5.6 Hoist Plan
As a building gets taller, the vertical transportation of materials and personnel becomes the
activity most limiting construction. A construction hoist, which is a tower mounted elevator cage
typically mounted on the outside face of a building, can support the vertical lifting needs of the
site (Wei et al., 2015). It is important to ensure that a hoist is located at a continuous vertical face
where it can climb the building. This may be against the envelope or at a line of balconies, but, in
Toronto, occupancy of a building cannot occur until all openings in the building are closed
(Government of Ontario, 1992). Due to this, locating hoist access on a balcony, which can be
closed off with sliding doors, allows for faster finishing of the building envelope.
4.5.7 Concrete Pump Plan
Another piece of equipment that can be used to decrease the payload on a tower crane and speed
vertical transportation is the concrete pump. The decision to include a concrete pump depends on
an adequate power supply and available space for its installation and operation. It is becoming
more common for concrete pumps to be used to provide concrete delivery at a constant rate, have
a workable slump, and maintain the required concrete strength (Wei et al., 2015).
The above are some steps that are outlined in a construction site plan to indicate the operation of
the construction site. There may be additional steps required based on site details and the city
process for each location. The interaction diagram in the following section details some factors
that may influence decisions for the steps found in this planning process.
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4.6 Interaction Diagram
The interaction diagram is to be used as a guide and checklist of factors that affect decision
making. This can be used by new and experience project managers in the industry, as well as be
a teaching tool for students to illustrate the impacts of decisions in site planning. The relationship
of factors is explained, as well as some observed scenarios where their impact is discussed in
terms of other site planning decisions and the variety in applications. The interaction diagram
includes significance ratings of the relationships to illustrate the importance of decision
relationships.
As each construction site is unique in its geographical and physical features, it is first necessary
to generalize equipment and operation interactions that occur across all sites. Routine
interactions that influence site logistics are summarized in Figure 14. Some categories interact
with each other, and some all factors, shown at the top, have an impact on multiple categories.
For example, the traffic management plan and concrete pump affect the crane and hoist, whereas
noise by-laws affect multiple equipment operations. The diagram has been organized by
grouping categories of factors together by equipment or process. The factors in squares are big
decision points for equipment, whereas the factors in circles contribute towards those decisions.
All categories have letters and each factor is numbered. For instance, the factor shared suites
under category all factors is factor A1. The factors are bolded throughout the following sections.
All factors are outlined in section 4.6.1, while sections 4.6.2 to 4.6.5 discuss category-specific
factors. Finally, section 4.7 explains some factors that cannot be rated due to their impact being
site specific, the varying examples observed at sites, and some procedures to be used in the
situations.
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Figure 14: Site Interaction Diagram
4.6.1 All Factors
All factors do not fit into any of the other equipment or logistics categories and impact several
decisions on the site. They are directly influenced by the individual building. Currently,
residential building construction is funded through the sale and occupancy of units, whereas
commercial buildings are financed by the owners (Hendrickson and Au, 1989). Since the income
for each residential unit is not released to the developer until the unit is occupied, completing the
construction of residential buildings on time is important to reduce borrowing costs. In large
projects with multiple or very tall towers, the developer may wish to stage the transfer of units to
owners rather than wait until the entire project is complete. In order for units to be occupied
before the construction of the entire building is complete, units that are sold must be prioritized
for finishing at the start of site planning so they can meet occupancy standards (Government of
Ontario, 1992). This is represented as the occupancy factor (A4) on the interaction diagram. The
61
influence of this factor includes locating the crane and hoist away from the early occupancy
units.
Fortunately, unit finishing is not a critical activity if planned correctly. A critical activity is an
activity on the critical path, so if the duration of the critical activity changes, the overall duration
of the project will also change. A critical path is defined as “a sequence of critical activities that
form the longest sequence in a project…the sum of the activity durations, taking into account
leads and lags, determines the overall project duration” (Baldwin and Bordoli, 2014). In contrast
to unit finishing, lobby finishing and mechanical equipment installation, under the building
finishes factor (A5), are vital to the operation and occupation of the building. These are activities
that may fall under the avoid critical path task factor (A3), therefore, crane and hoist locations
must be chosen to avoid interfering with these areas of the building. The interference caused by
the hoist and crane can be minimized by placing both pieces of equipment in the same suite,
represented by the shared suite factor (A1). However, special care must be taken to ensure there
is enough area in the units for the crane to be located inside, and deliveries from the hoist to
easily maneuver to other parts of the building.
Another factor that impacts the placement of the crane is the building height (A2). As a building
gets taller, the crane operator’s sight line to the pick-up point becomes obstructed by the building
slab edges. Although, this can slow down lifts due to the requirement of radio communication
with the crane operator to perform lifts, crane operators usually learn the flight paths of each lifts
and can perform them without being able to see them due to repetition. Taller buildings may
interfere with aircraft flight paths depending on their location. This consideration requires
including Aviation Canada during planning to check flight paths and the approved maximum
height for construction in the area to obtain air rights (B7) for the crane. It is also important to
note that the tower crane extends higher than the building and so the allowed height for clearance
should be the maximum height of the tower crane and not the building itself.
The above factors largely influence the location of equipment, however, there are also factors
that affect the equipment and site operation. The first of these factors is impacted by the local
noise by-laws (A8). For Toronto, the noisy by-law restricts site operations on weekdays to be
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between 7 a.m. to 7 p.m. (City of Toronto, 2009) to ensure neighbors are not disturbed. Beyond
site operations, the noise by-laws impact equipment operation and delivery schedules. Deliveries
can only occur outside the allowed time if they do not produce noise and are from a non-
unionized trade.
Another factor that effects the equipment operation is wind speeds (A7) as the crane and hoist
can only operate when the wind speed is below 50 km/h (Infrastructure Health and Safety
Association, 1995). High wind speeds above 50 km/h, sometimes observed in Toronto between
October and May, cause site operations to shut down and delay the schedule (Metoblue, 2006).
As such, the local wind patterns often dictate the location of the hoist. Toronto has prevailing
westerly winds, which means if the hoist was located on the north or south face the winds would
shear the hoist and impede its operation (Metoblue, 2006).
Finally, several pieces of equipment and processes on the construction site require energy and
heating to operate, as addressed by the site power factor (A6). These can be either through
diesel-powered generators or an electricity service connection. It is important to note that
generators produce high levels of noise that can be avoided with a serviced site.
4.6.2 Traffic Management Factors
A traffic management plan is required to outline the safety and logistics procedures of the site
(City of Toronto, 2017b). The street layout around the site and the building layout in context to
the site influence the locations of site entrance and exit gates (E1). These gates seek to separate
the site vehicular traffic from the public and provide safety for pedestrians and public vehicular
traffic in the area. Under the pedestrian and vehicular protection factor (E2), the site must
have a temporary fence around its perimeter and overhead protection or rerouting of pedestrians,
both of which influence where the gates can be located (OHSA, 1997). The available space (E3)
on the site also dictates the traffic management plan as it outlines the traffic route for deliveries
at the site. Inadequate space on a site may result in the need to obtain additional space from the
city around the construction site in the form of sidewalks, roads, or adjacent parking lots, which
involve an additional cost to the project.
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In addition to these costs, road permits (E4) and police escorts may be required for delivery of
loads wider than 1.5m, dictating the delivery schedule (E5) and project cost (Ministry of
Transportation, 2017). Finally, to ensure a smooth flow of traffic and delivery to the construction
project, the traffic management plan must outline the locations of loading docks and pumping
areas for the hoist, crane, and concrete pump. Spacing out the loading areas for these pieces of
equipment will aid in avoiding delivery conflicts.
4.6.3 Crane Factors
As buildings get taller, vertical delivery of materials becomes a crucial part of the planning
process as the longer times to move material over the increased distances causes a decrease in
productivity of the crane. To optimize crane operations on site, crane logistics must be carefully
planned in the early stages. The crane logistics can be described in terms of three categories:
location, operation, and crane type.
4.6.3.1 Crane Location
The crane location (B1) is influenced by a number of factors, as seen in the interaction diagram
in Figure 14. A consideration for choosing the crane is to ensure that the crane’s radius (B10)
and capacity (B18) is able to pick up the heaviest loads on site and deliver them to the materials’
required drop off location (Hosseini et al., 2017). Typically, locating the crane at the centre of
the building footprint can achieve this, however, the crane must not hit any surrounding
buildings (B13) when it is left to weathervane (B11) and must avoid being located in any areas
that might delay the building finishing because they are critical path tasks (A3) (Bodéré and
Grillaug, 2005). Air rights (B7) have to be obtained for crane swings over surrounding land for
the boom and lifted loads to fly over neighbor and city property. For larger sites, more than one
crane may be necessary, as represented by the number of cranes factor (B15). In this case, the
crane locations and erection plan must ensure that cranes can service the entire site without the
jibs and masts of the cranes interfering with one another, as per the crane interaction factor
(B14) (Zhang et al., 1999). Single cranes may also be chosen to be located near the building
footprint’s edge if possible, so the slab does not obstruct the crane operator’s sight line (B5) to
the pick-up point. The sight line (B5) to the material pick-up point (B6) is influenced by the
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traffic management plan as the delivery routes and loading areas are part of this plan. It is
important to note that in Ontario, cranes are typically owned by formwork contractors, and so the
location of formwork storage (B8) should be accessible for lifts.
Finally, the dismantling (B4) procedure must be considered when the crane location is chosen.
A mobile crane may not be able to reach the tower crane for removal if the tower crane is too far
from the road or too high. In buildings that are less than 40 storeys high, large mobile crane can
be used for the dismantling process. The typical dismantling procedure for a tall building
requires the use of a derrick crane located on the roof. The tower crane erects the derrick crane,
then the derrick crane is used to dismantle the tower crane and transport it down the building.
The derrick crane is dismantled and transported down the building using the construction hoist.
Since the dismantling procedure can vary depending on tower crane location and height, a
consultant will typically outline the dismantling procedure at the beginning of the project to
guarantee the crane can be removed. The crane location effects the excavation (B9) procedure
since the foundation has to be poured at the crane location so the crane can be erected as early as
possible.
4.6.3.2 Crane Type
Although the type (B3) of crane is influenced by the construction site requirements in terms of
the loads that it must carry, the availability of the tower crane from the supplier dictates what can
be used on the site. In Toronto, cranes are typically rented from formwork contractors for the
duration of the project. The two choices that must be made when picking a crane is if the crane
will be an internal or external crane, and if it will be a hammerhead or a luffing crane.
An external crane is anchored at the envelope of the building and creates holes in the envelope
that remain open until all construction is completed. An interior climbing crane, on the other
hand, is wedged into openings in the slab and moves up the inside of the building. The climbing
crane requires reshoring for 7-8 floors below it, but frees up the lower floor slabs for finishing
purposes. The external cranes are easier to erect and dismantle than the climbing cranes as the
building structure does not impede them, but have a higher cost than climbing cranes. For some
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buildings, where finishing the slab is more important and the budget allows, the external crane
may be a better choice.
Depending on the neighboring buildings, a luffing crane may be chosen if the radius of a
hammerhead crane would interfere with surrounding structures. The hammerhead crane has a flat
jib, whereas the luffing crane has a jib which can be lowered to reach large radii and lift to avoid
neighboring structures during a swing or weather-vaning. Since the luffing crane is typically
slower than the hammerhead crane, hammerhead cranes are preferred where possible. In some
special cases, the project manager may choose to switch to a hammerhead crane from a luffing
crane once the crane’s boom clears the height of neighboring buildings to save operation time
and cost. It is important to keep in mind that this will result in additional erection and
dismantling costs, and that the decision of type of crane will impact the speed (B17) of each lift.
4.6.3.3 Crane Operation
The type (B3) and location (B1) of the crane impact its operation (B2). If a location is picked
for the crane which requires a larger radius for material lifts, the time required to complete each
lift increases. Inversely, the lifting capacity of the crane decreases as the load is further from the
center and results in the jib deflecting due to heavy loads. In addition to this deflection, lifted
materials can sway if they encounter strong winds. Since there is a risk of hitting surrounding
buildings with erratically swinging loads, crane lifts may not be performed or be performed at a
slower speed (Infrastructure Health and Safety Association,1995). Finally, the ambient
temperature (B16) has an impact on whether a tower crane can be operable or not, as they are
typically operable only above -20°C. It is important to note that the presence of a concrete pump,
hoist and other cranes reduce the overall payload of the crane, dividing tasks over many
resources.
4.6.4 Concrete Pump Factors
The presence and operation (C2) of a concrete pump is one method to reduce the payload of the
tower crane as it dedicates one piece of equipment to concrete transportation and ensures that the
crane is not a limiting piece of equipment on the construction schedule (Wei et al., 2015).
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The concrete is pumped up the building through a pipe connected to the pump. The boom of the
pump is moved with the crane or hydraulically with the use of a remote control. It is very rare for
the pipe to be moved by hand for concrete pumping. As concrete is being moved over greater
distances, superplasticizers are added to the mix so the concrete is flowable, but maintains the
required strength (Kosmatka and Panarese,1994).
The location (C1) of the concrete pump is dictated by the available space on the site. Usually,
the concrete pump is placed at the ground floor of the building. If there is no space for concrete
truck to deliver the concrete on site, or for the pump to be placed, the concrete pump can be
located across the street or on adjacent properties with pipes run underground if necessary to
allow vehicular traffic. Another consideration for the location (C1) factor of the concrete pump
is the placement of the hose and boom, since they can impact the finishing process in a project. It
is preferable for the hose to be run through a stairwell or an adjacent opening beside the elevator
shaft, since running the hose through suites can delay the finishing of the suite.
Finally, the location of the site affects the type (C3) of concrete pump that can be used, mainly
due to the noise by-law (City of Toronto, 2009). If the building is in a residential area, an electric
pump is preferred to limit the noise caused by the construction site. In industrial areas, a gas-
fueled pump can be used.
4.6.5 Hoist Factors
In tall residential buildings, construction hoists are used to move material and personnel up the
building, since the building elevator is typically not operational and cannot be used by site
personnel. From site observations, it was concluded that hoists are typically installed when the
concrete formwork reaches the 10th floor.
4.6.5.1 Hoist Locations
The main consideration when planning the location (D1) of the hoist is to minimize the openings
in the building without requiring additional landing platforms. This is represented by the
balcony/window line factor (D5) on the interaction diagram, typically accomplishing this by
locating the hoist at balconies or where the envelope is consistent, and to reshore the slab to
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provide adequate strength. The location of the hoist is influenced by the available space (D7)on
the construction site, as a building close to the perimeter of the plot may result in the hoist or the
loading dock (D6) encroaching on neighboring property and require special permission. The
location of the hoist should also minimize the distance materials and personnel have to travel on
the floor from the hoist. This can be done by locating the hoist at the centre of the long side of
building (D4). Finally, it is necessary to obtain recommendations from the site superintendent
since they understand the site and the effect the location of the hoist will have on daily tasks.
4.6.5.2 Hoist Type
The type (D3) of hoist that is chosen has an effect on the productivity of the trips. First, the size
(D16) of the hoist car depends on the largest window units that have to be transported up the
building, as hoists typically transport window wall system panels. In addition to size, the door
access (D12) should be able to receive deliveries from the loading dock and deliver loads to the
openings on the building. Sometimes there is only one door if the loading dock can be placed in
the same location as access to the upper floors, however, due to available space, sometimes doors
are required on both sides of the hoist. The type of hoist impacts the speed (D14) with which
deliveries are made, as a self-leveling hoist may be chosen. A self-leveling hoist aligns the floor
of the hoist with the floor slab of the building so the operator does not have to adjust the cab,
thus increasing the productivity.
Another way to increase productivity is to use a hoist with a larger capacity (D13), since this
will decrease the number of trips necessary for transporting materials and personnel. The
capacity of the hoist can also be augmented by increasing the number of hoist cars (D15). The
number of cars will depend on the height and footprint of the building, as a larger building
indicates more materials and personnel that need to be moved. Unfortunately, the increase in
hoist cars results in an increase in openings in the building. A solution that has been observed is
the addition of an outrigged landing platforms for the hoists on all floors to service 6 car hoists,
with 3 masts, as can be seen in Figure 15. This results in only needing one opening in the
building while substantially increasing the number of hoists.
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Figure 15: Hoist Outrigged Platform
4.6.5.3 Hoist Operation
As with all activities for each project, the operation (D2) of the hoist revolves around a
schedule. Outside of the morning rush up and end of day rush down for personnel, the hoist is
used to move materials up the building. Due to this, a booking system (D9) must be developed
so trades can ensure their materials are shipped to their required locations when needed.
Furthermore, a skilled operator (D8) is able to intuitively decide how the hoist lift cycles will be
carried out, since the hoist is not automatic and the hoist operator can change the direction of the
hoist based on requests for pick up (Hwang, 2009). As with all equipment, the reliability (D11)
of the hoist is dictated by the age and maintenance procedure of the hoist. Project managers tend
to rent hoists that are under five years old, as seen on the observed sites, at a slightly higher cost
to avoid hoist breakdowns.
Part of planning the hoist lift plan is to include days when hoist cars are not operational due to
performing a hoist jump (D10). The hoist mast is extended every three to seven floors as seen
on site. This process consists of attaching the cab to the mast using cables and disengaging the
cable that allows the cab to move up and down the mast. Sections of the mast are lowered by the
crane and hoist carpenters attach the section to the existing mast to extend it using clamps while
standing in the hoist cab. When the extension of the mast is completed, the cable upon which the
cab rides is run up the extended mast, and the tension is restored so it carries the hoist car once
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again. After this process is complete, an inspection must be carried out to ensure the hoist is
anchored and operating correctly. The extension can take up to a day, which means every three
to seven floors, one hoist tower with one or two cars attached to it becomes unavailable. These
are some factors that are not seen in the simulations that are developed in literature, depending
on experienced project managers to plan accordingly.
4.7 Relationship Significance
After all the factors and relationships were modelled in the interaction diagram, their significance
was identified based on trends observed at the construction sites and after reviewing their
construction management plans. The relationships were rated on a scale of 1 to 5, very low to
very high importance, respectively. Any relationships that could not be rated due to large
variations in their importance based on the situation or management techniques were left unrated
on the interaction diagram. The differences in ratings are shown in Figure 16. The figure aims to
graphically show the ratings, as well as the differences in agreement between the two
individuals. Some situations that can alter the importance of a relationship are outlines in Table
8. A chart of all ratings can be found in Appendix B.
Figure 16: Relationship Rating Difference
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Table 8: Situation where Relationship Significance Varies
Relationship Reasoning
Shared suites
(A1) to crane
location (B1).
Sharing suites for the crane and hoist location is ideal to decrease the areas that
cannot be finished until the equipment is removed. Unfortunately, this is dependent
on the unit layout and the available space in each unit since the crane may block
deliveries from the hoist if there is not enough space in the unit. The relationship
significance will vary since this method may only be carried out when possible, and
in other situations may have a high impact on the location decision for both the
crane and the hoist.
Shared suites
(A1) to hoist
location (D1).
Formwork
storage (B8) to
crane location
(B1).
There is a variation in the relationship significance for the location of the formwork
for project managers, as formwork engineers are typically responsible for the
operation of the crane, as well as the formwork storage. Due to this, the project
managers may have to modify their decisions based on the formwork engineer’s
requirements.
Road permit
(E4) to delivery
schedule (E5).
Depending on the location of a construction site and the surrounding roads and
traffic, obtaining road permits may range in difficulty from obtaining road permits
with an associated expense to rerouting site traffic and deliveries outside the area or
work times to accommodate local traffic.
Crane type (E3)
to crane speed
(E17).
The major influence that the crane type has on the crane speed is choosing between
a hammerhead and a luffing crane, as luffing cranes require more time to complete
swings due to needing to fold up the jib.
4.8 Conclusion
This paper outlines a general planning process used in construction site logistic planning at the
start of a project and discusses factors that affect planning decisions in detail. It presents an
interaction diagram that shows relationships between decision factors and planning categories and
indicates their significance in a variety of scenarios.
This paper aims to be used as a teaching tool for in-class learning, an introduction to new personnel
in the industry, and a support tool for decision making by experienced professionals by presenting
situations and nuances of the factors included in the interaction diagram. Since there is no existing
site logistics manual due to geological and site-specific differences, this paper presents a
framework for general decisions that can be observed on all sites, with details specific to the City
of Toronto. The proposal for future work in the field consists of developing a phone based
application that can be used to carry out logistic planning decisions seen in section 4, and provide
resources for planners including links to permits, and reminders of application deadlines to aid in
completing the required tasks during the initial phases of site planning.
71
Chapter 5 Conclusion
The entirety of chapter 5 summarizes findings through the research, the contributions to the body
of literature, and paths for future research to follow the development of the interaction diagram
as a decision-making tool and the site logistics interaction diagram to be applied to construction
site planning in Toronto for tall buildings.
Conclusion
The three papers included in this dissertation establish the current procedures used in
construction site logistics planning and use features of existing decision-making tools to create
an interaction diagram for decision-making in construction projects of tall building projects.
In chapter 2, programs for storage on construction sites were reviewed and a proposed
framework for construction planning was introduced. With the framework in mind, it was
necessary to revisit the planning process at an earlier stage. From this, planning processes for the
whole of the construction site were observed on sites and decision-making tools were reviewed
in chapter 3. The interaction diagram was introduced as a tool for decision-making where each
decision had an impact on several domains. An interaction diagram for vertical transportation
equipment for tall buildings in Toronto was developed and applied to a construction site in
Toronto. This interaction diagram and the construction process were described in chapter 4.
5.1 Research Contributions
The interaction diagram was developed as a decision-making tool for multi-domain decisions to
support users in complex planning problems, allow them flexibility in planning and apply their
knowledge for each decision, and encourage communication between trades and stakeholders
early in the planning process by visually showing users all the domains that are impacted by a
decision. This aim of this tool is to be comprehensive and adaptable for users.
The interaction diagram was applied to construction logistics planning with a focus on vertical
transportation for tall buildings in Toronto to summarize the implicit knowledge from interviews
72
with industry professionals. Several interaction diagrams can be made for various domains and
joined together to create a larger decision-making model that encompasses all domains of a
construction site. The four goals of this research were addressed throughout the chapters. These
are listed below:
1. The methods for construction planning and storage were summarized in chapters 2, 3.4
and 4.4. These chapters looked at storage methods, logistic planning models, equipment
management, information exchange models and decision-making tools. A typical
construction planning procedure used in industry was outlined in chapter 4.5. This
information was gathered through interviews with planners and review of the procedure
with experts.
2. Site operations were observed on a variety of construction sites in the GTA and expert
planners in the industry were interviewed. These site visits led to gathering concrete lift
time data for lifts of varying materials and weights, at different sites, during different
weather conditions. The sites were observed from fall throughout winter to include
impacts of wind and cold weather in Toronto.
3. The interaction diagram was developed as a method for decision-making across multiple
domains. The method for creating the interaction diagram was presented in chapter 3.6.
The interaction diagram separates factors for each domain and shows impacts of a
decision on factors within and outside of the domain, thus enabling users to view impacts
of a decision for an entire project at a glance.
4. The interaction diagram was applied to vertical transportation domains on tall
construction buildings in Toronto. The factors were collected through site visits and
surveys with professionals. The vertical transportation interaction diagram is introduced
in chapter 3.6 and applied to a building in Toronto in chapter 3.6.3, where decisions using
the interaction diagram are compared to decisions that were carried out on the actual
construction site. This interaction diagram is explained in detail, where each factor, its
impact and the reason for each decision is described in chapter 4.6.
73
5.2 Limitations of Research
Although the interaction diagram allows users the freedom to make decisions suitable to their
needs, it is a tool that requires updating. This can be in the form of adding sections for new
technologies that would make construction more efficient or gathering additional factors for new
domains of impact. The use of the interaction diagram is dependent on the industry professional
using it and on their understanding of each construction project.
As a way to address these limitations, it is recommended that the interaction diagram is updated
on a set time frame for each company or when a new construction method or technology is
developed. The interaction diagram is built to allow users to make decisions with a glance on the
impacts on the overall project and draw on their own experience, however, creating an automated
program to aid in the use of the interaction diagram would add structure to the decision-making
process. This option is explored in the following section.
5.3 Future Research
Through site visits and interviews with industry experts, areas of further research have been
identified. As previously mentioned, a program should be created to automate parts of the
logistics process for construction logistics planning and add structure to planning process. This is
discussed in section 5.3.1. In this section, the framework for a program for a tower crane and
concrete pump is introduced, as well as databases for tower cranes, concrete buckets and
concrete pumps. A database for construction hoists should be developed by collecting
manufacturer data for construction hoists available in Toronto.
Furthermore, a program for hoist scheduling should be created that allows different trades to
request times for lifting their materials and site managers to review all requests. Currently, the
construction hoist schedules are typically booked on a first-come, first-serve basis. This does not
allow a schedule for the hoist that is always beneficial for the site, and trades are required to use
the hoist within their allotted time or risk losing their spot. In addition to the hoist scheduling
program, a web-based application available to project planners should be developed that can run
through the construction planning process outlined in section 4.5, alerting site planners of any
74
documentation and permits they need to file, and ensuring all procedures are addressed. All of
these developments should draw on the factors outlined in the interaction diagram to ensure the
impacts are accounted for in the programs. Finally, more interaction diagrams covering all
domains of design, planning and construction should be created through interviews with industry
professionals to create an overview of the entire building process in Toronto.
5.3.1 Programming from Tacit Knowledge
Each domain of the interaction diagram introduced in the interaction diagram identifies areas
where programs can be created to work together to aid in construction site logistics planning.
One such area is to expand on existing programs of finding the best location for a crane using
purely mathematical calculations to create a program that finds the best location for the crane,
using building and equipment properties, combinations of pick-up and drop-off points and
adjusted equations from empirical data collection; and the improved site productivity when using
a concrete pump. A flowchart for the process is shown in Figure 17. More details can be found
throughout Table 9 to
Table 13, with references to which factors from the interaction diagram are included in the
program.
75
Figure 17: Crane and Concrete Pump Program Decision Flowchart
76
The first step of the program is to retrieve all relevant information of building characteristics,
equipment and weather data for the project at hand. This gives the program context as to what
problem is being solved so solutions are specific to the building and location. The user is then
asked to provide restrictions for pick-up points, number of pours and areas to avoid for the
placement of the crane. These are factors that the user can choose and is not restricted to the site
plans.
After this, equipment is chosen from crane and concrete pump databases. Combinations of the
pieces of equipment are run through the simulation to calculate the most efficient vertical
transportation time for the site using different types of equipment and locations for the
equipment. In these scenarios, materials to be lifted are assigned to specific pieces of equipment.
The concrete is assigned to the concrete pump if the scenario includes the concrete pump, and all
materials to be lifted are assigned to the tower crane.
The four scenarios for each simulation consist of: interior crane and concrete pump, exterior and
concrete pump, interior crane only, and exterior crane only. For each run, lift times for all
materials to be lifted are calculated and stored. The best 3 total lift times are stored in an array. If
the current run is better than the previous runs, the new time and crane coordinates are replaced.
Once all the points of the building are checked for coordinates of the crane, new combinations of
equipment are run through the program again.
Finally, after all equipment combinations have been checked, the program displays the results of
the best run time, the most efficient equipment combination, the predicted downtime for
equipment forecasted from historical weather data and the recommended dismantling procedure
for the crane based on the location of the crane. Table 9 to
Table 13 break down a pseudocode for a program to minimize the time of lifts for materials with
four scenarios consisting of cranes and concrete pumps on a construction site. Each step from the
flowchart in Figure 17 is represented by one of the following tables.
77
Table 9: Step 1 – Retrieve All Inputs
Factor Code Comments
B13
B16
READ building coordinates and neighboring buildings to avoid
(starting from SW, going clockwise)
READ number of building floors and elevations of each
READ lift object information (type; x,y,z coordinates for pick-up and
drop-off points; weight)
READ crane database (crane radius, capacity, lift time)
READ concrete pump database (flow rate)
READ schedule breakdown procedure (day to day activities)
READ material breakdown based on schedule (day to day)**
READ weather data for temperature and rain/ snow patterns
ASSIGN a = total number of items to be lifted
Input from
database or
building model
**Create activity
(i) dependencies
Table 10: Step 2 - User Inputs
Factor Code Comments
B6
A3, A5
B4
ASK USER FOR:
Number of pours/ floor (pour layout)
3 pick-up point locations
Areas to avoid placing crane*
Acceptable closeness of crane to edge of slab*
Maximum distance of crane from road for removal of crane*
*automate if
possible
Avoid shear walls,
elevator shaft,
stairs and
mechanical room
for crane
placement
Table 11: Step 3 - Choose Equipment Combination
Factor Code Comments
CHOOSE crane from database and acceptable radius depending on
maximum lift weight and surrounding buildings distance
CHOOSE concrete bucket from database
CHOOSE concrete pump from database
Table 12: Step 4 - Calculate Total Lift Times for 4 Scenarios for Each Equipment
Combination
Factor Code Comments
Scenario 1: Interior Crane and Concrete Pump
Set Crane Coordinates: x = 0, y = 0
For y<= north coordinate of building
If x<=east coordinate of building
For (objecti = 1, i<a, i = +1)
Starts crane at SW
corner
78
If obecti type ≠ concrete
CraneTimei = vertical lift time as a
function of object weight + horizontal
movement of boom and tangent movement of
hook time as function of distance from pick-
up point to drop-off point + lowering object as a
function of height of drop-off point + time to return
crane to pick-up point
Else
ConcretePumpTimei = Concrete
Pump flowrate * (zdist + √(xdist2 +
ydist2)) * area covered in pour (m2)
End if
Activity Time Duration Function
If i type = concrete
If day time = day time + activity
duration > 8
Activity start = next day at 0
hour
Activity end = activity
duration / 8
If day time = day time + activity
duration < 8
Activity start = day time
Activity end = day time +
activity duration
Elseif i type ≠ concrete
Activity start = activity end of
activityi-1
Activity end = activity start + activity
duration
End if
Store activity start and activity end in array j
End loop
Total Lift Time Function
If j total time = array k1
If crane location of j closer to the middle of
the building than crane location of k1
Array k3 = array k2
Array k2 = array k1
Array k1 = array j
End if
Else if j total time < array k1
Array k3 = array k2
Array k2 = array k1
Array k1 = array j
Calculates object
lift time for all
objects except
concrete
Calculates
concrete lift time
using concrete
pump
Stores activity
duration, day start
and day end in
array j (temporary
table for each run).
These are based on
8 hour work days.
Repeats loop for
next object
If current run is
better than stored
run, the top 3
results are replaced
so minimum time
and closest crane
location to the
center of the
building is stored.
This stores total
time of all lifts for
the construction of
the building,
schedule of lifts
and crane location
in the arrays.
79
Else if j total time = array k2
If crane location of j closer to the middle of
the building than crane location of k2
Array k3 = array k2
Array k2 = array j
End if
Else if j total time < array k2
Array k3 = array k2
Array k2 = array j
Else if j total time = array k3
If crane location of j closer to the middle of
the building than crane location of k3
Array k3 = array j
End if
Else if j total time < array k3
Array k3 = array j
End if
x = x + ½ crane pad width
Else
x = 0
y = y + ½ crane pad width
End if
End loop
Moves crane x
direction
Moves crane y
direction
Scenario 2: Exterior Crane and Concrete Pump
x = -1/2 crane pad width
y = -1/2 crane pad width
For y <= N coordinate of building + ½ crane pad width
For (objecti = 1, i<a, i = +1)
If objecti type ≠ concrete
CraneTimei
Else
ConcretePumpTimei
Endif
End loop
Activity Time Duration Function
Total Lift Time Function
y = y + ½ crane pad width
End loop
For x <= E coordinate of budilnig + ½ crane pad width
For (objecti = 1, i<a, i = +1)
If objecti type ≠ concrete
CraneTimei
Else
ConcretePumpTimei
Endif
Starts outside
building at SW
corner
Moves coordinate
in positive y
direction
80
End loop
Activity Time Duration Function
Total Lift Time Function
x = x + ½ crane pad width
End loop
For y >= S coordinate of building - ½ crane pad width
For (objecti = 1, i<a, i = +1)
If objecti type ≠ concrete
CraneTimei
Else
ConcretePumpTimei
Endif
End loop
Activity Time Duration Function
Total Lift Time Function
y = y - ½ crane pad width
End loop
For x >= W coordinate of budilnig + ½ crane pad width
For (objecti = 1, i<a, i = +1)
If objecti type ≠ concrete
CraneTimei
Else
ConcretePumpTimei
Endif
End loop
Activity Time Duration Function
Total Lift Time Function
x = x - ½ crane pad width
End loop
Moves coordinate
in positive x
direction
Moves coordinate
in negative y
direction
Moves coordinate
in negative x
direction
Scenario 3: Interior Crane Only
Set Crane Coordinates: x = 0, y = 0
For y<= north coordinate of building
If x<=east coordinate of building
For (objecti = 1, i<a, i = +1)
CraneTimei
End loop
Activity Time Duration Function
Total Lift Time Function
x = x + ½ crane pad width
Else
x = 0
y = y + ½ crane pad width
End if
End loop
Starts crane at SW
corner
Moves crane x
direction
Moves crane y
direction
81
Scenario 4: Exterior Crane Only
x = -1/2 crane pad width
y = -1/2 crane pad width
For y <= N coordinate of building + ½ crane pad width
For objecti
CraneTimei
i = i + 1
End loop
Activity Time Duration Function
Total Lift Time Function
y = y + ½ crane pad width
End loop
For x <= E coordinate of budilnig + ½ crane pad width
For objecti
CraneTimei
i = i + 1
End loop
Activity Time Duration Function
Total Lift Time Function
x = x + ½ crane pad width
End loop
For y >= S coordinate of building - ½ crane pad width
For objecti
CraneTimei
i = i + 1
End loop
Activity Time Duration Function
Total Lift Time Function
y = y - ½ crane pad width
End loop
For x >= W coordinate of budilnig + ½ crane pad width
For objecti
CraneTimei
i = i + 1
End loop
Activity Time Duration Function
Total Lift Time Function
x = x - ½ crane pad width
End loop
Starts outside
building at SW
corner
Moves coordinate
in positive y
direction
Moves coordinate
in positive x
direction
Moves coordinate
in negative y
direction
Moves coordinate
in negative x
direction
REPEAT all scenarios for different combinations of tower crane and
82
concrete pump to determine best lift times
Table 13: Step 5 - Display Results
Factor Code Comments
DISPLAY best time for each scenario, equipment used and location of
tower crane
DISPLAY time hoist and tower crane are estimated to be inoperable
from forecasting from historical weather data
RECOMMEND dismantling procedure applicable based on each crane
location
The program uses equipment database to retrieve information relevant to calculations. A crane
database and concrete pump database were created. The crane database, shown in Figure 18,
summarizes crane type, capacity, height, and other characteristics of cranes available in Toronto.
A crane load chart can be seen in Figure 19, showing that as crane boom length and radius
increases, the capacity of the crane decreases. The information for the crane database is retrieved
from individual crane load charts included in Appendix C. Cranes are owned by various
formwork companies, and therefore the stock may differ between companies. For this reason, a
variety of cranes were included in the database so a company could choose the crane they owned
after the program optimizes the crane for the particular site. Concrete pump and concrete bucket
data are retrieved from manufacturer data for equipment in Toronto. These can be seen in Figure
20 and Figure 21, respectively.
83
Figure 18: Crane Database Summary
Figure 19: KNF 336i-16 Load Chart
84
Figure 20: Concrete Pump Database Summary
Figure 21: Concrete Bucket Data Summary
Adding to this program, the construction hoist operation can be added to determine material
handling and delivery times by the hoist and the improved productivity of the construction site as
the overall payload of the crane is decreased. Finally, interaction diagrams for the planning
phases and other domains of construction or the lifetime of a building can be developed and used
85
with the construction site logistics interaction diagram to increase the scope of decision-making.
In this manner, the interaction diagram can be used to visually view the impacts of factors and
their decisions on multiple domains, and act as an input for the creation of programming for
construction site logistics planning.
86
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Appendices
Appendix A: Crane Cycle Equations
Equations from the literature were applied to the lifts to predict cycle times (Huang et al., 2011).
It was noticed that there were great variations between the actual time to perform a lift and the
estimated time for a lift as calculated from equations from the literature as the equations did not
account for environmental or situational factors, such as wind, operator experience, and repair
time.
Equation 3 to Equation 5 calculate the distances of the crane center (Crk) to the object destination
(Dj) and source (Si), and the distance between the object source and destination coordinate,
respectively. Equation 6 calculates the radial movement of the hook, whereas Equation 7
calculates the tangent movement of the hook.
Finally, Equation 8 and Equation 9 calculate the horizontal and vertical movement of the crane,
respectively. Equation 10 adds the results of Equation 8 and Equation 9 with coefficients relating
to simultaneous vertical and horizontal movement of the hook and operator experience to
calculate the total cycle time for a lift. Diagrams showing the horizontal and vertical movements
of a crane can be seen in Figure 22 and Figure 23.
𝜌(𝐷𝐽𝑥, 𝐶𝑟𝑘
𝑥) = √(𝐷𝑗𝑥 − 𝐶𝑟𝑘
𝑥)2 + (𝐷𝑗𝑦
− 𝐶𝑟𝑘𝑦
)2
Equation 3: Distance between Destination (drop-off) Point and Crane Coordinates
𝜌(𝑆𝑖𝑥, 𝐶𝑟𝑘
𝑥) = √(𝑆𝑖𝑥 − 𝐶𝑟𝑘
𝑥)2 + (𝑆𝑖𝑦
− 𝐶𝑟𝑘𝑦
)2
Equation 4: Distance between Source (pick-up) Point and Crane Coordinates
𝐼𝑖,𝑗 = √(𝐷𝑗𝑥 − 𝑆𝑖
𝑥)2
+ (𝐷𝑗𝑦 − 𝑆𝑖
𝑦)
2
Equation 5: Distance between Destination (drop-off) Point and Source (pick-up) Point
𝑇𝑟(𝑖,𝑗)𝑘 =
|𝜌 (𝐷𝑗𝑥,𝐶𝑟𝑘
𝑥) − 𝜌 (𝑆𝑖
𝑥,𝐶𝑟𝑘𝑥
)
𝑉𝑟
92
Equation 6: Time for Radial Movement of Hook
𝑇𝜔(𝑖,𝑗)𝑘 =
1
𝑉𝜔arccos(
(𝑙𝑖,𝑗)2 − 𝜌(𝐷𝑗𝑥,𝐶𝑟𝑘
𝑥)
2− 𝜌(𝑆𝑖
𝑥,𝐶𝑟𝑘𝑥
)2
2𝜌(𝐷𝑗𝑥,𝐶𝑟𝑘
𝑥)𝜌(𝑆𝑖𝑥,𝐶𝑟𝑘
𝑥)), (0 ≤ arccos(𝜃) ≤ 𝜋)
Equation 7: Time for Tangent Movement of Hook
𝑇ℎ(𝑖,𝑗)𝑘 = max (𝑇𝑟(𝑖,𝑗)
𝑘 , 𝑇𝜔(𝑖,𝑗)𝑘 )+ ∝ min (𝑇𝑟(𝑖,𝑗)
𝑘 , 𝑇𝜔(𝑖,𝑗)𝑘 )
Equation 8: Total Time for Horizontal Movement of Hook
𝑇𝑣(𝑖,𝑗)=
|𝑆𝑗𝑧− 𝐷𝑗
𝑧|𝑉ℎ
Equation 9: Total Time for Vertical Movement of Hook
𝑇𝑖,𝑗𝑘 = 𝛾𝑘 { 𝑚𝑎𝑥 (𝑇ℎ(𝑖,𝑗)
𝑘 , 𝑇𝑣(𝑖,𝑗)) + 𝛽 𝑚𝑖𝑛 (𝑇ℎ(𝑖,𝑗)𝑘 , 𝑇𝑣(𝑖,𝑗)) }
Equation 10: Total Time for Each Lift
Figure 22: Radial and Tangent Movement of Hook
93
Figure 23: Vertical Movement of Hook
Appendix B: Charts Showing Significance Ratings for Relationships
In Figure 24, Figure 25, Figure 26, and Figure 27 below, significance ratings for all factors from
the two experts are shown.
94
Figure 24: All Building Factors Significance Ratings
Figure 25: Crane Factor Significance Ratings
95
Figure 26: Hoist Factor Significance Ratings
96
Figure 27: Traffic Management and Concrete Pump Factors Significance Ratings
Appendix C: Crane Load Charts
The following figures, from Figure 28 to Figure 40, are load charts from manufacturer’s for
cranes included in the database.
97
Figure 28: Crane 1 - KNF 336i-16 Load Chart
Figure 29: Crane 2, 3 and 6 - Pecco PC 2000
98
Figure 30: Crane 4- Peiner SK315Figure 31: Condor FZ 001
Figure 32: Crane 7 - Comedil CTL-250
99
Figure 33: Crane 8 - AVRO LJK 160
Figure 34: Crane 9 - Pecco PC 1400
100
Figure 35: Crane 10 - Pecco PC 1200
Figure 36: Crane 11 - Pecco PC 3600
101
Figure 37: Crane 12 and 16 - Comedil CTT 331
102
Figure 38: Crane 13 - Peiner SK 415
103
Figure 39: Crane 14 - Pecco Sn 406
Figure 40: Crane 15 - Pecco PC 3000