site expert: a prototype knowledge-based expert system

SITE EXPERT: a prototype knowledge-based expert system

EDIZ ALKOC & FUAT ERBATUR*

Department of Civil Engineering, Middle East Technical University, 06531 Ankara, Turkey

INTRODUCTION

The use of artificial intelligence techniques in engi-neering has gained considerable popularity in recentyears. In this respect, expert systems have attractedparticular interest from various engineering disciplines.One of these disciplines is the construction industry.There are a number of reasons why expert systems suitthe construction environment. Firstly, employment inconstruction is at one site for a certain period of time,and there is little repetition and limited opportunity tolearn from earlier mistakes. Secondly, most constructionprojects are unique, organizations are always recon-structed with different designs, teams and equipment.For these two basic reasons, the transfer of constructionexpertise becomes important and achieving this taskthrough an expert system seems to be most appropriate.

In the present paper, a prototype knowledge-basedexpert system, SITE EXPERT, is described. SITEEXPERT is an advisory system intended to provideadvice on productivity improvement on constructionsites. Besides advising on human resources and sitelayout as productivity factors, the system covers pro-ductivity of the three basic operations of construction,i.e. pouring and placing of concrete, erection andremoval of formworks, and fixing reinforcement. It alsoprovides advice based on the simulation results of con-creting models.

Similar to any rule-based system, SITE EXPERTconsists of: (1) a knowledge-base that represents andstores the expert's knowledge and facts about theconstruction domain as rules; (2) an inference enginethat facilitates a reasoning process to solve a specificproblem; (3) a context memory that contains the infor-mation about the problem currently being solved; and(4) a user interface that inputs and outputs information.

In the following sections, all the stages in the devel-opment of SITE EXPERT are described, including theacquisition, organization, representation and imple-mentation of the knowledge, and evaluation of theprototype. The development of the system is shown inFig. 1. SITE EXPERT is composed of seven separateknowledge-bases. These knowledge-bases are alsoexplained in detail.

The results of the prototype system development leadone to believe that artificial intelligence methods providepowerful facilities for capturing the knowledge ofconstruction processes and for advising the practitionersof construction in productivity improvement within acomputer format close to human reasoning.

BACKGROUND

Research into artificial intelligence started in the late1950s, but expert systems did not appear until the mid-1970s. Some of the major applications which were

Abstract The present paper reports on the development

of SITE EXPERT: a prototype knowledge-based expert

system. It is an advisory system. SITE EXPERT is intended

to be used for productivity improvement in construction

and provides advice on: (1) the productivity of three basic

operations of construction, i.e. pouring and placing of

concrete, erection and removal of formwork, and fixing

reinforcement; and (2) human resources and site layout as

productivity factors. The system uses information from

construction experts, text books, data recorded at con-

struction sites and the engineer's own knowledge, as well

as knowledge obtained by running simulation models. In

the present paper, the development, operation and eva-

luation of the prototype system is described. The results of

this prototype system development demonstrate that

artificial intelligence methodologies provide powerful

facilities for capturing information about construction pro-

cesses and advising the practitioners of construction on

productivity improvement within a computer format close

to human reasoning.

Keywords expert system, construction, productivity

improvement, knowledge base, advisory system, con-

creting operations

238

Engineering, Construction and Architectural Management 1998 5 | 3, 238±251

# 1998 Blackwell Science Ltd

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SITE EXPERT: a prototype knowledge-based expert system 239

# 1998 Blackwell Science Ltd, Engineering, Construction and Architectural Management 5 | 3, 238±251

developed during the early years of the expert systemsare summarized below.

DENDRAL was developed in the early- and mid-1970s at Stanford University, Stanford, CA, USA, foridentifying the molecular structure of organic com-pounds (Lindsay et al. 1980). A medical system,MYCIN, by Shortliffe (1976) is often cited as the firstexpert system. It was developed at Stanford University inthe mid-1970s to help physicians in the diagnosis andtreatment of meningitis and bacteria infections. Itsknowledge base contains about 450 rules. Similarly,PROSPECTOR, developed at Stanford ResearchInstitute in the late-1970s (Duda et al. 1979), is a diag-nostic expert system for mineral exploration. It usesproduction rules and plausible reasoning. The knowl-edge-base contains about 1600 rules. CADECUS, for-merly named INTERNIST, is an expert system for thediagnosis of disease of internal medicine (Pople 1982). Itcontains over 15000 rules and covers some 25% of dis-eases of internal medicine. XCON, originally called R1,is a production system programming language devel-oped at Carnegie-Mellon University. It designs theconfiguration of VAX-11/78 computer components forthe Digital Equipment Corporation (Kraft 1984).

During the last decade, knowledge-based expertsystems have been developed to support the decisionmaking and problem solving process in the constructionindustry. There have been numerous research efforts ondeveloping knowledge-based expert systems for con-struction. Some applications of advisory expert systemsare reviewed below.

A set of four advisory expert systems, developed forthe UK Alvey Community Club, offer advice on finan-cial budget, procurement, time and appraisal during thestrategic planning of a building scheme (Brandon et al.1988). These have 1500 rules in the knowledge-base anduse the SAVOIR shell. Claims by or on contractors arehandled by expert systems described by Diekmann &Kruppenbacher (1984). D'Agapeyeff & Hawkins (1987)described a system to offer advice at the design stage ofgas production systems about the corrosion life of the

steel tubing. Reinschmidt & Finn (1986) described asystem which selects the most appropriate weldingprocedure according to, for example, the types ofmaterial being welded and the type of weld required.Levitt & Kunz (1987) described the platform series ofexpert systems which offer advice on constructionplanning. Rules are used to identify common sub-activities in completed activities which are either aheadof or behind schedule. Rules to modify activity timesaccording to when weather-sensitive activities occur inthe year are also used to activate a dynamic Gannt chartdisplay.

DEVELOPMENT OF SITE EXPERT

The main structure of SITE EXPERT is no differentfrom other expert systems. An expert system needsknowledge, some means of using the knowledge and thecapability of communicating with the user.

There are two types of knowledge in SITE EXPERT:Knowledge obtained from standard elicitation methodsand knowledge obtained from simulation modellingoutputs. The initial phase of knowledge elicitation inSITE EXPERT includes a literature review and iterativeprototyping. In the second phase, this knowledge isvalidated and expanded by interviews with site experts,and again, with iterative prototyping. Table 1 sum-marizes the main knowledge acquisition and knowledgerepresentation methods with an indication of thosewhich are actually used in the development of SITEEXPERT. Knowledge gained from related literature wasused to build a prototype model. The comments of fiveexperts on the model were taken with interviews andwritten communication. The domain experts were allexperienced practitioners from different constructionfirms and training institutions. Finally, the refinedknowledge was stored in the seven separate knowledge-bases named as `main', `site layout', `performance oflabour', `formworking', `reinforcement', `concreting'and `simulation prototype'. The organization of theSITE EXPERT knowledge- bases is shown in Fig. 2.

Knowledge acquisition

Knowledge elicitation Knowledge representation

Method SITE EXPERT Method SITE EXPERT

Interviews Yes Predicate calculus and

mathematical logic

No

Observational studies Yes Semantic networks No

Induction Yes Semantic triplets No

Prototyping Yes Rule-based systems Yes

Frames No

Table 1 Knowledge elicitation and

representation

Alkoc, E. & Erbatur, F.240


Because SITE EXPERT has separate knowledge-bases,this enables the application of suitable inferencemechanisms according to the purpose of the knowledge-base. It also enables the user to run specific consulta-tions separately rather than running the whole system.

Knowledge statements in a knowledge-base, such asrules, are not processed in order. These are searched tofind the next best statement to process in order to mostquickly arrive at an answer to a problem. In advisorysystems, as discussed in the present paper, the searchprocess is looking for the best advice to give in a parti-cular situation. The search process starts by nominatingto the shell program a list of goals to be evaluated inorder. Once a rule is executed, the knowledge-base ismodified, if necessary, according to the obtained result.The inference engine then triggers the next rule to befired depending on the present reasoning method. Tworeasoning methods often employed in inferencemechanisms: (1) forward chaining; and (2) backwardchaining.

The selection of a system shell for engineering appli-cations is based on certain factors and is not an easy task.Table 2 lists some of the relevant considerations.Detailed information on existing expert system shellscan be found in Harmon & King (1985), Waterman(1986), Williamson (1986), Wigan (1986) and Adeli(1987). Ludvigsen et al. (1986) reviewed seven com-mercial expert system shells popular in the USA in termsof user-friendliness, documentation and user support. Areview of nine expert system shells popular in the UKwas also reported by Alwood et al. (1985).

For the development of SITE EXPERT, Xi PlusRelease 3, Version 3.5 (Xi Plus Release 3 1988) wasused. The assessment criteria for choosing Xi Plusinclude: rules being defined in English; controlling theinference in a procedural manner; and a searchmechanism including both forward and backwardchaining. In Xi Plus, know-how is expressed in a formsimilar to simple natural language. The basic elementsfor expressing knowledge are identifiers, relations andvalues.

The user interface provides a textual and graphicalinterface between the user and the system. Since mostexpert systems are designed to be used by individualswith little computer literacy, user-friendly facilities suchas on-line help, explanation and error recovery areessential parts of the user interface. The operation ofSITE EXPERT is shown in Fig. 3. It is a totally inter-active procedure where the users communicate with thesystem through a user interface.

KNOWLEDGE-BASES IN SITE EXPERT

SITE EXPERT starts consultation with the `main'knowledge-base and connects to the chosen knowledge-base from the menu. It is possible to return to the previousmenu from every hierarchical level in all knowledge-bases. At any time, the user can examine any or all of theconclusions which have been reached so far. The systemcan be asked to explain its reasoning in reaching a con-clusion and why a question is being asked as part of theconsultation process. The user can change answers to

Figure 2 Organization of SITE EXPERT knowledge-bases.



questions or ask for information during a consultation,and by using the what-if facility, can also explore the effectof alternative answers on the conclusions. At some pointsin consultation, the knowledge-base may need to give theuser some advice, guidance or results. It does this on areport screen. A report can consist of one or more screendisplays. The total number of reports included in SITEEXPERT are 98. The system also asks whether some tipsare required during the process of consultation. The useris free to accept these tips without affecting the branchingof the knowledge. A sample consultation with SITEEXPERT is given in Àppendix 1'.

Main knowledge-base

The system starts with an introduction, and followingthe introduction, values for the identifier àdvicerequired' appear in a menu. If `performance of labour' or`site layout' are selected from the menu, then the systemconnects to the chosen knowledge-base. If `methods andrates of operations' is selected, then a value for theidentifier òperation' is searched for. It is possible to runthe related knowledge-bases for `formworking', `rein-forcement' and `concreting' from the operation menu.The system connects to the `formworking' and `rein-forcement' knowledge-bases once these are selected as avalue for òperation'. Choosing the concreting operationprovides an option of directly connecting to `concreting'knowledge-base or connecting to the `simulationprototype' knowledge-base where the user can get advicefrom the results of concreting simulation models. The`main' knowledge-base consists of 12 rules and adopts aforward-chaining strategy.

`Site layout' knowledge-base

Failure to plan the site layout in advance is a prime causeof operational inefficiency and can increase the overall

cost of a project substantially. In the absence of a precisesite layout plan, neither the site manager nor his sub-ordinates will have a clear indication of where varioussite huts, items of plant and other facilities should belocated. Some of the problems that might occur in sitelayout planning are explained in this knowledge-base.

For the chosen problem, the system asks whether theuser wants to examine the relevant considerations. If theanswer is `yes', then a detailed menu for each problemappears. If the answer is `no', then another type ofproblem is requested. Knowledge representation for the`site layout' knowledge-base is shown in Fig. 4. As withthe other knowledge-bases, there is an option to returnto the previous menu at every level of advice. When theuser is satisfied with the advice provided, the `site layout'knowledge-base connects back to the `main' knowledge-base and enables the user to benefit from the otherknowledge-bases. The `site layout' knowledge-baseconsists of 33 rules and adopts a forward-chainingstrategy.

`Performance of labour' knowledge-base

On any construction site, the contractor's financial gainis dependent, amongst other things, on completion ofthe work on time and at the least cost. Labour pro-ductivity has a direct bearing on this being achieved. Thefactors affecting the performance of labour generally fallinto following categories:. motivation of workers;. human capacity of work;. competence of site management; and. application of working patterns.

This knowledge-base consists of 48 rules and adopts aforward-chaining strategy. The user can stop consulta-tion and go back to the `main' knowledge-base at anylevel. The branching of knowledge in the `performanceof labour' knowledge-base is shown in Fig. 5.

Shell selection consideration

General SITE EXPERT

Type of application Advice giving

Type of machine and operating system PC 486 under DOS Version 3.0 or later

Maximum number of rules allowed 347 existing rules

Response time A few seconds

Type of control strategy and inference

mechanism

Both forward and backward chaining

Availability of complex mathematical routines Required

Ability to interface with other programs Required for future extension

Programming aids Possible

Portability Required

Cost Reasonable

Table 2 Shell selection



`Formworking' knowledge-base

The `formworking' knowledge-base enlightens the userabout methods and rates for the erection and removal offormwork. These include operational statement, mate-rials and tools required, operatives, plant, methodstatement, and basic operation times for columns, stop-ends, suspended floors and beams, and steel panelshutters. The hierarchy of knowledge in the `for-mworking' knowledge-base is shown in Fig. 6. It has 130rules and it also adopts a forward-chaining strategy.

`Fixing reinforcement' knowledge-base

The `fixing reinforcement' knowledge-base has 52 rulesand works in a similar way to the `formworking'knowledge-base. In other words, it adopts a forward-chaining strategy, and provides advice on methods andrates for fixing reinforcement in the form of operationalstatement, method, materials and tools required, andbasic times.

The methods and rates for fixing reinforcementincluded in this section are associated with reinforce-

Figure 3 Operation of SITE EXPERT.



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Figure 6 Hierarchy of knowledge for the `formwork' knowledge base.



ment which is delivered to site ready bent. Allowancesfor additional site bending and cutting have beenincluded. Fixing slab, beam and column reinforcementare examined within this knowledge-base. The knowl-edge hierarchy is shown in Fig. 7.

`Concreting' knowledge-base

The `Concreting' knowledge-base concentrates on themethods and rates of concreting activities for slab, beamand column pours by crane and bucket, and by pump.Most variations in the basic times are caused by theshape of pour, and therefore, the basic times for slabs,beams and columns are treated separately. There aretwo main sections: (1) methods; and (2) rates. In themethods section, detailed descriptions and explanationsare provided for mixing, transportation, raising, placingand finishing activities. In the rates section, basic ele-ment times and total operation times are provided.Firstly, the place and means of concreting, and then thearea and volume of concrete to be placed are asked, sincethe duration of some activities such as `tamp' and `sho-vel' are surface area dependent. Some procedures, suchas `pour' and `vibrate', depend on volume instead, whileothers depend on both. The system reports basic ele-ment times for `clean', `prepare tools', `pour', `shovel',`tamp', `clear', `vibrate', `trowel' and `cover' activities.The total basic time for the complete operation is alsoprovided. This knowledge-base has 23 rules and it alsoadopts a forward-chaining strategy.

`Simulation prototype' knowledge-base

One of the characteristics of SITE EXPERT is itsintegration with simulation models in order to cope withthe inherent randomness of construction operations.During the consultation, SITE EXPERT provides anextra option when advice on methods and rates ofconcreting operations is desired. Although planningtimes for any amount of concreting can be obtained fromthe concreting knowledge-base, a prototype knowledge-base prepared with computer simulation outputs of

concreting models enables the users to realize how thenumber of resources, the interaction of work crewscaused by work space limitations, and the interaction ofwork crews as a result of sharing with other activitiesaffect productivity. Several simulation models have beenprepared with MicroCYCLONE (Halpin 1990) simu-lation software for cyclic operations. All the modelssimulated a 1 m3 volume of concrete to be poured intoslabs, beams and columns. Data analysed with workstudy techniques are used as input to simulation modelswith beta distribution parameters obtained from theVIBES (AbouRizk et al. 1991) and SIDES (AbouRizk &Sawney 1993) statistical softwares. This simulationprocess has been described in detail by Alkoc & Erbatur(1997).

The `simulation prototype' knowledge-base has 49rules and the level of advice required is controlled withyes/no type questions. The information below isprovided from the outputs of simulation modelling.

Durations and details of activities

Reports for the mean durations of activities, percentageof time the activities are busy and average waiting timefor resources are provided in this option. This enablesthe user to compare these values for different methods ineach pour.

Multiple stochastic run outputs

This option provides a mean and a standard deviationfor total duration, hourly productivity and total cost forthe chosen method of concreting. This helps theprogrammer in estimating with PERT (Weist & Ferde-nand 1977) methods. Values are obtained from multiplestochastic simulation runs.

Comparison of different resource combinations

This option provides advice on the optimum combina-tion of resources for the chosen method. It also explainsthe cost and duration effect of every combination.

Figure 7 Knowledge hierarchy for the `reinforcement' knowledge-base.



Comparison of different methods and different

pours

This option gives some general advice such as:. whether it is more productive to use a 1 m3 bucket or a

0.5 m3 bucket in the bucket-cycle for slab, beam andcolumn pours;

. whether it is more productive to pour with crane andbucket, or with pump; and

. which of slab, beam and column pours have longerdurations or more cost.After choosing one of the options explained above

from the main menu, the system asks for the member tobe cast: slab, beam or column. It also asks whether theconcrete is poured by crane and bucket, or by pump.Then, according to the chosen option, the systemreports, describing the methods of pour, and usedresource combinations appear on the screen.

EVALUATION OF SITE EXPERT

The evaluation of a knowledge-base can be described asthe process of assessing the overall quality of a knowl-edge-based system. The evaluation of an expert systemmust be associated with its performance. This is a dif-ficult task. One reason for this difficulty is that, unlikehuman beings, expert systems are not required to passcertain tests to become licensed or certified (Hayes-Roth1984). Generally, there are two methods of evaluatingany computer code: verification and validation.

The verification for SITE EXPERT consisted of anumber of testing procedures adopted throughout thestages of development. This was carried in a veryinformal way by verifying the rules and the whole systemfor consistency. The content of rules were checked andverified for any discrepancies and errors against pub-lished data and human experience. This was achieved bythe submission of the prototype rules content to severalsite engineers for criticism and evaluation. They wereasked to read and comment on the principles developed.Their comments and suggestions were compiled andimplemented wherever this was possible.

A system is said to be consistent if repeated executionswith the same data lead to the same results and con-clusions. The consistency of all parts of the system thatwere subsequently built were checked using sets of inputdata to test the logic. This procedure was carried outuntil the system was compatible and consistently pro-duced the intended output in the right context. Thisprocess was achieved by running the system severaltimes and following every single branching of knowl-edge. In these runs, a mixture of inputs like boundaryconditions, meaningless combinations, valid and invalid

data, and obvious error conditions are used as well asstandard menu options.

Validation consists of checking whether the prototypesystem has reached a reasonable level of quality at theend of the development stage. Informal validation bydomain experts has been used to test the system. Thevalidation focuses mainly on the performance issuesspecific to the application of the system. A number ofqualitative validation criteria were chosen in order toprovide as independent an analysis as possible.

The outputs obtained from simulation models weremanually input into SITE EXPERT instead of trans-ferring this knowledge with subroutine programs(Baldwin 1994). This enables the validation of outputfrom simulation processes before these are used as aninput to the knowledge-base. The knowledge containedin SITE EXPERT has been filtered twice by thismethod.

The outputs of SITE EXPERT have been validatedon two major construction operations with a value ofover US$50 000 000: the Manavgat River Water SupplyProject, Manavgat, Turkey; and the Yapi Kredi BankasiOperations Center Complex, Gebze, Turkey. Both theseprojects used various applications of concreting opera-tions. Qualitative outputs were discussed with the chiefengineers of these projects, and quantitative outputswere compared with daily, monthly and yearly sitereports.

CONCLUSION

The development of a prototype system was undertakenin order to investigate the feasibility of artificial-intelli-gence-based tools for enhancing the existing productiv-ity improvement methods. SITE EXPERT hasdemonstrated that knowledge-based productivityimprovement could be possible by using artificial intel-ligence techniques. SITE EXPERT is a prototype sys-tem. It represents a conceptual model, and for thisreason, the expertise need not be very detailed in thefield, but rather, sufficient to solve the problem. This isthe situation for most of the knowledge-based systemsunder development (Levitt & Kunz 1987).

The results of the present study confirm that artificialintelligence methodologies provide powerful facilitiesfor capturing the knowledge of construction processes.These also show that it is possible to advise practitionerson productivity improvement within a computer formatclose to human reasoning.

Knowledge-based system tools have great potential insolving ill-structured problems commonly encounteredin construction. SITE EXPERT is capable oftransforming ill-defined productivity improvement



knowledge into an operational prototype system. Theadvice provided is not committed to a single project orcase, but considered conceptual in nature. Therefore, itcan be applied to the great majority of constructionprojects. The costs of consultation with experts can alsobe limited with such an expert system and time could besaved in waiting for the expert to arrive on site. Addi-tionally, although text books can provide an importantand valuable source of information, having on-lineadvice from real expertise is more practical and user-friendly.

The knowledge organization used in SITE EXPERTallows the transformation of a knowledge-specificdomain written in English into a computer syntax veryeasily. The primary benefit is that this form of knowledgeorganization allows experts who are not computer pro-grammers to understand and contribute to the devel-opment of construction knowledge-based systems.Furthermore, the knowledge in this form can be trans-lated to any inference engine or representation envir-onment with ease.

The power of an expert system is related to the sizeand completeness of its knowledge-base, and the qualityand completeness of a knowledge-base determines thevalidity and accuracy of a viable operational knowledge-based system. It should be noted that SITE EXPERT isa prototype, and therefore, that it lacks this completenessin its present state. The concept provided by this pro-totype system will be of value during the future devel-opment of a commercially viable knowledge-basedsystem for construction productivity improvement.

ACKNOWLEDGEMENTS

This paper is based on a doctoral thesis entitled Aknowledge-based prototype advisory expert system for pro-ductivity improvement in construction submitted to theMiddle East Technical University, Ankara, Turkey. Thefirst author offers sincere thanks to Dr A. D. Price,Department of Civil Engineering, LoughboroughUniversity of Technology, Loughborough, UK, forproviding the SERC reports which were used to gathersome of the data used in this research. The authors alsowould like to acknowledge the help provided by Dr R. J.Alwood and Dr A. Baldwin of the Department of CivilEngineering during the first author's stay at Loughbor-ough University of Technology.

REFERENCES

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AbouRizk, S. & Sawney, A. (1993) Subjective and interactiveduration estimation. Canadian Journal of Civil Engineering,20, 457±470.

Adeli, H. (1987) Software review: INSIGHT 2+. Micro-computers in Civil Engineering, 2 (2), 173±184.

Alkoc, E. & Erbatur, F. (1997) Productivity improvement inconcreting operations through simulation. Building Researchand Information, 25 (2), 82±91.

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APPENDIX 1: SAMPLE CONSULTATION WITH SITE EXPERT

Hello!!

Welcome to SITE EXPERT!

This expert system is here to give you some advice on:

. methods and rates of(a) concreting(b) formworking(c) fixing reinforcement operations. site layout. performance of labour

Hit ENTER to start Consultation . . .

ENTER

You want some advice on:

Select one of . . .

methods and rates of operationsperformance of labour

site layoutnone

On any construction site the contractor's financial gain isdependent, amongst other things, on completion of thework on time and at the least cost, and the productivity oflabour has a direct bearing on this being achieved. Thefactors affecting the performance of labour generally fallinto following categories.

Hit ENTER to Continue!

ENTER

Which category do you want to examine in detail?

Select one of . . .

human capacity for workcompetence of site managementmotivation of workers

application of working patternsnone

Motivation factor to be examined is:

Select one of . . .

feardisciplinejob satisfactionfinancial incentives

none

Incentive schemes of this nature are widely used in indus-trialized countries, but are often a source of contention anddispute between management and workforce. The schemesenable workers to earn bonuses over and above the normalrate of pay for achieving a rate of output at or above a pre-determined standard. It is not always easy to work out whatthis standard performance should be.


ENTER

Financial incentive scheme is:

Select one of . . .

bonus targetsbasis for setting targets

advantages and disadvantages of financial incentivesnone

Do you want information on any of the following basis forsetting targets?

Select one of . . .

work measurementthe estimatefeedbackback to previous menu

Work measurement is the best method as targets are morelikely to be accurate. Depending on policy, it is usual to offera bonus over and above the basic wage for a standardperformance of 100.

Hit ENTER to go back to previous menu!

ENTER

Do you want information on any of the following basis forsetting targets?

Select one of . . .

work measurementthe estimatefeedbackback to previous menu

Financial incentive scheme is:

Select one of . . .

bonus targetsbasis for setting targetsadvantages and disadvantages of financial incentivesnone



Motivation factor to be examined is:

Select one of . . .

feardisciplinejob satisfactionfinancial incentivesnone

Which category do you want to examine in detail?

Select one of . . .

human capacity for workcompetence of site managementmotivation of workersapplication of working patternsnone

This is the end of the Performance of Labour knowledge-base.

Hit ENTER to go back to main menu!

ENTER


Select one of . . .

methods and rates of operationsperformance of laboursite layoutnone

Which concreting operation do you want to examine in detail?

Select one of . . .

concretingformworking

reinforcementnone

Hi! This is FORMWORKING EXPERT.

You can get information about operational statement,materials and tools required, operatives, plant, methodstatement, and basic operation times of formworkingoperations for:

* columns* stop-ends* suspended floors and beams* steel panel shutters


ENTER

Do you want to learn more on planning times?

Select one of . . .

yesno

What type of formworking do you want to examine?

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columnsstop-endssuspended floors and beams

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Type of floor and beam formwork is:

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traditional decking systemfalsework to external beamscomplex external floor beam

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operational statementmaterials and tools required

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Materials and tools required are:

(i) Joinery trade tools(ii) Release agent(iii) Beam shutters(iv) Timber packs(v) She-bolts(vi) Acrow props


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operational statementmaterials and tools requiredoperativesplantmethod statement

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Method Statement:

(i) Erect lower internal shutter and infill deck(ii) Erect lower outer shutter(iii) Position kicker(iv) Strip outer shutter after concreting(v) Erect upper internal and external shutters(vi) Strip upper inner and outer shutters(vii) Strip lower internal shutter and decking


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operational statementmaterials and tools requiredoperativesplantmethod statementbasic operation times

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operational statementmaterials and tools requiredoperativesplantmethod statementbasic operation timesback to previous menu

Type of floor and beam formwork is:

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traditional decking systemfalsework to external beamscomplex external floor beaminternal beamnone _ go back to previous menu

What type of formworking do you want to examine?

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columnsstop-endssuspended floors and beamsnone _ go back to previous menu

Which concreting operation do you want to examine in detail?

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concretingformworkingreinforcementnone


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methods and rates of operationsperformance of laboursite layoutnone

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The following Basic Element Times cover the three maintasks:lower internal shutter, lower external shutter and uppershutters.

Basic Element Times (min m±1)

Uppershutter

Lowerexternal

Lowerinternal

Clean and oil 2.38 7.69 1.33Make up and repair 3.27 2.21 2.67Position shutters 10.27 17.19 12.00Position she-bolts 6.70 14.84 0.00Position props 4.61 10.94 4.00Make kicker Ð 5.21 ÐLevel shutters 2.98 1.56 0.00Strip shutters 6.40 14.06 14.06

The Basic Times presented below covers the work involvedin the construction of stop-ends and the adjustment ofbeams to suit the columns.

Basic Times for Additional Work (min)

Upper shutter Lower external

Stop-ends 35.0 52.5Column in beam 17.5 48.9

Allowances for Ancillary Work:

Percentage of Total BasicElement Time

Uppershutter

Lowerexternal

Lowerinternal

Prepare 5.9 2.5 6.65General 0.0 1.8 26.65Fetch 1.7 7.6 13.35Instructions 0.7 0.5 0.00Away 2.1 6.8 13.35

Total 10.4 19.2 60.0




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