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Modeling and Development of an Activity based Process Planning Matrix, Its
Optimization using Design Structure Matrix (DSM)
Dr. Riaz Ahmad1, Umer Asgher
2
1,2National University of Sciences and Technology
Islamabad, Pakistan [email protected],
Abstract :- Process planning is a link between engineering drawings and the final part manufacturing. Industrialized
process planning is the represents successive manufacturing processes so that to carry out organizational objectives.
In this paper the automobile manufacturing industry is taken as a case study. Primary basic process plan is developed
for a part and then it is modeled mathematically. This work is a continuation of previous my work on the modeling of
process plan and its optimization. Here in this paper mathematically modeled process plan is then optimized using
Design structure Matrix (DSM) in order to find optimal or sub optimal solutions. Study then explore the capability of
DSM optimization method in handling optimization of manufacturing process plan. Finally the research examines the
convergence of DSM optimization technique to an optimal solution for a reconfigurable manufacturing framework.
Keywords:- Manufacturing processes, Process planning Matrix, Design Structure Matrix, optimization, algorithms.
1 Introduction
Task of process planning embrace the following
two basic stages; Process design is macroscopic
decision making of largely process route to
transform the raw material to a product.
Operation design is microscopic decision-making
of the individual operations contained in the
process route. Process planning in the
reconfigurable manufacturing setup involves a
series of all activates from a raw material to the
final product. A propos two hundred years back,
pioneer of such as Adam Smith & David Richard and john
stuart Mill theory of ‘vendibility: production intended for
the ‘market’. A large set of development in terms of
manufacturing good took place in twenty first century.
Now days the modern research examine the various ways
and means to optimize the production and manufacturing
criteria’s [1][3]. Optimization algorithms in
manufacturing are typically written for either
minimization or maximization production related
problems. In some algorithms, some minor modification
enables to carry out either minimization or maximization,
and requires wide acquaintance of the algorithm. A
mathematically
developed process plan is taken as reference or base
function for further investigation of optimization. DSM is
powerful toll used now a days in various processes to
optimize whether its facility layout and then time. The industry we undertook is presently
manufacturing of security vehicles. Presently
there is no process a plan exists in that factory for the
manufacturing; all the activities involved are performed in
non-conventional manner without any existing process
plan. Only computerized CNC have pro-E codes for
machining process and part drawings are available. This
leads me to firstly develop the process plan, for that matter
I have taken complete side plate of the vehicle and
developed its process plan [2]. The process plan is
modeled mathematically. Then optimization of the process
planning is by considering all the activities in terms of
time. The DSM optimization is performed is order to
reach the optimal point where all the time activities are
optimum.
Section I is the introduction, section II is on the
subject of the Design structure Matrix and its applications
on Process optimization, section III demonstrates the
manufacturing process development and modeling based
on previous work. Section IV is the an Activity based
Process Planning precedence Matrix, section V is Design
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structure Matrix (DSM) optimization of the process plan
followed by optimization results and analysis. Final
section is about the Conclusions and recommendations
about future work
2 Design structure Matrix and Process
optimization Products, processes and organizations are all complex
systems. The most practical and reasonable approach to
complex structures have involved in some way or the
other decomposing the complex unit to smaller
subsystems. Subsystems, being smaller in size and less
complex enhance understanding of the big picture. The
systems behavior can further be analyzed by establishing
relations between the subsystems and studying their input
and output components. Non-trivial projects consists of
numerous processes (subsystems) that are dependent on
one another. These interdependencies keep growing with
the size of the project increasing the level of complexity.
Numerous approaches to solve this problem have been
adopted, PERT, CPM being quite common. However,
these approaches did not scale up as they were only
capable of handling sequential and parallel processes. The
need to handle iterative processes within complex projects
led to the development of a new instrument called as
Design Structure Matrix (DSM). Dependency Structure
Matrix”, “Problem Solving Matrix”. As a project
management tool DSM provides a representation that
allows for feedback and cyclic task dependencies. The
matrix contains a list of all tasks and the corresponding
information exchange patterns. It is otherwise known as
information based matrix [4][5]. All the elements of the
DSM matrix are linked via a relationship and this
relationship helps in understanding the behavior of the
process. This relationship between the elements of DSM
N - square matrix shows the dependency of each element
with each other. This relationship is of three types as
shown in the figure 1. The activities are associated with
each other as parallel or sequential or both means coupled
activities.
Fig. 1 DSM Element Relationships [4]
The partitioning is a process is used to rearrange the
activities in a DSM matrix to minimize gaps and optimize
the activities in such a way to change the facility layout.
The whole process of the partitioning is summarized in the
figure 2. ; Identify tasks that can be executed without
input from the rest of the tasks in the matrix. Observing an
empty row in the DSM can easily identify those tasks.
Place those tasks in the top of the DSM. Once a task is
rearranged, it is removed from the matrix for any further
consideration. Step 1 is repeated on the remaining tasks.
For each individual operation a standard time may be
specified [4][5]. This is the total time in which an
operation should be completed at standard performance
and consists of the time elements as indicated in the figure
2.
.
DSM Partitioning process
(a) A B C D(i/p) E F G
A X X
B X
C (o/p) X X X X(o/p)
D X
E X X
F (i/p)
G X X
Fig. 2 DSM Partitioning
Optimization word is derivative from Latin word
“optimums”, the most excellent and characterize the
number of activity involved to discover the best. All
engineering tasks involve either minimization or
maximization of an objective function. It will be very
difficult to discuss formulation of each type of engineering
optimization problem in one course. However a designer
can learn different types of optimization techniques and
latter choose optimal algorithm for his or her problem.
First we shall learn optimal problem formulation.
Optimization deal by means of function. Function is
basically mapping commencing one space to a-different.
In industrial plan actions, a raw optimal design is achieve
by just comparing only some substitute design solution
formed by means of a priori knowledge [6]. In these
activities, the possibility of every design result is initially
investigated. After that, an approximation of the original
goal (cost, time, profit) of every design result is computed
plus the most excellent design result is adopted. This raw
technique is frequently followed for the reason that of the
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time and resource restrictions. In several cases this
technique is followed merely as be deficient in of
knowledge of the obtainable optimization measures. An
optimization algorithm requires evaluation of a number of
design solutions, and more often than not is time intense
and computationally costly. The optimization method has
to be used in those problems wherever there is a specific
requirement of accomplishing a excellence in the product
or a spirited product. The reason of the formulation
method is to build a mathematical model of the best
possible design problem, which could be solving using an
optimization algorithm [7]. The engineering optimization
problem is summarized in the figure 3 and figure 4.
Fig. 3 Engineering Optimization Problems
Optimization algorithm is gradually more admired
in design engineering activity, mainly as of the
accessibility, affordability of elevated swiftness of
computers. They extensively used in those engineering
design situations wherever the stress is on maximize or
minimize a definite objective. A basis function of process
planning optimization in AST side plate manufacturing is
as shown in the figure 4.
GENERAL AIM OF PROJECT
T1 T2 T n-1 T n
STRATEGIC
<Time
Objectives:PROCESS PLANNINGPARAMETERS
PROCESS PLAN
OPTIMIZATION
FAC 1 FAC 2 FAC 3 FAC 4
TIME OPT TIME OPT TIME OPT
PRACTICAL
T T2 T3
max effectiveness
PROCESS PLAN FORMULATION WITH ACTIVE CONTROL
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Fig. 4 Process Optimization
3 Flow Line & Work Station analysis The next step after process design is operation design. This is concerned with the detailed decisions of production implementation, that is, the types of operations to be performed in the production process (the content of each operation and the cathode of performing it). The content of each operation is determined in connection with process design and may be broken down into several steps, such as loading the work piece into the chuck of a machine tool, starting the machine, and unloading the work piece from the chuck and placing item a conveyer [3][8].
3.1 Operation Analysis and Case Study
The method of operation can be analyzed from the viewpoints of a combination of machine elements and human elements (man-machine system), operative workers, and work simplifications. Man-Machine system analysis is performed to identify and reduce or eliminate idle time for either the worker or the machine constituting the selected workstation. The man-machine combination is essentially chosen to minimize the overall operation cycle time with least idle times , At the very first stage the Aluminum plates are stored at a dedicated place. The whole manufacturing process sequentially from raw material storage till the final assembly stage is completely described in previous work [1][9] as some details are as follow:-
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The stage is Rough cutting is the first stage. The Aluminum plates transported from the storage section to the savage saw for rough cutting. The plates then move to the CNC bench. Then stage come (Quality control) QC-I. There are total ten quality controls. PRO-E design is feed into the CNC machine for design of side plate. First phase of machining process is for outer side of the plate and second phase is for other side as per the PRO-E design. The second step of the quality control is to judge the abnormalities. Then is semiautomatic drilling, tons Hydraulic press, debarring, Surface treatment (chemical processes). The quality control are involved all in between the stages of the side plate. Then stages side door starts, semiautomatic plasma cutting, semiautomatic welding, surface treatment for the side plate. Here the side plate is again a processed through all the stages of the surface treatment. All these stages are linked via quality controls. Twentieth stage is Surface treatment for the side door and firing pots. Twenty first stage is QC-IX .Then is final Assembly stage, the door and the side plate with the help of the clamps and the hinges. Final stage of Painting. Quality assurance department (QA) is to finally inspects and ensure all the things that have already been inspected in all QCs(1-10) are again checked against the standard drawing and dimensions as per user requirements and correct specification.
4 Activity based process planning
precedence matrix
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Fig. 5 DSM Process Modeling stage-I [1][2]
There are two possible relationships between any two operations. A partial order exists between two operations; this order is called a precedence relationship and is represented in Figure 4.Precedence relationship exists between operations and they may be performed concurrently and in parallel. The precedence relationship between two successive operation or activities (operation A proceeds operation B or operation B follows operation A) is represented by (a) flow diagram, (b)arrow, (c) ordering symbol, or (d) precedence matrix. The work flow is a sequence of operations among which specified precedence relationships exist. Since we know that work flow is a sequence of activities among which a specific precedence relationship exists [1][4].
5 DSM Process Modeling and Its
application On Case Study
This is the process whose aim is to remove or at least reduce the number of feedback marks above the diagonal in the matrix by manipulating or reordering the rows and columns of the matrix. After setting up the original matrix with the current information flow and feedbacks, the partitioning process proceeds as follows; categorize the tasks that can be carry out devoid of input from the rest of the tasks in the matrix. Examine an blank row in the matrix that can simply recognize those tasks. Place those tasks in the top of the matrix. As the tasks are rearranged, it is detached from the matrix for any supplementary consideration. Step one is repeated on the remaining tasks.
For each individual operation a standard time may be specified. This is the total time in which an operation should be completed at standard performance and consists of the time elements. The observed time value of the operation, recorded under time study, are modified to the time required to perform the operation at the ‘standard’ or ‘normal’ pace by a technique called performance rating [4]. This time is the basic time, or normal time. To determine the standard time is necessary to add time allowances for personal needs, unavoidable fatigue, and extra delays. Further allowances may be made for other reason.
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Fig. 6 DSM Process Modeling stage-I
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Fig.7 DSM Process modeling stage-II
6 Partitioning
Classify tasks that carry no information to other tasks in
the matrix. As discussed earlier as well; observe any blank
column in the Matrix can simply classify those tasks.
Place those tasks in the bottom of Matrix. Once tasks are
rearranged, it is detached from the matrix and step two is
repeated on the residual tasks [4][5]. After steps one and
two, if there remained no remaining tasks in the Matrix,
then the matrix is totally partitioned; otherwise, the
residual tasks hold at least one information circuit.
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Fig 8. DSM Process Optimization
Determine the circuits or loops of information by the Path Searching Method. Cave in the tasks involved in a single circuit into one representative task and go to step one if there are any more loops. If there are no more tasks, proceed to next step. Expand all the combined loops to obtain your final Matrix and Schedule. Determine the circuits or loops of information by the Path Searching Method.
7 Results and Discussion Since the arrangements or the facility layout in the actual
manufacturing floor is depicted in the figure 1 and the
after the application of DSM we have reached on the final
arrangements in the figure 8 after going through all the
intermediate steps. The initial arrangements of figure 1
will give rise to the total of 7 days in manufacturing a side
plate. When we apply the DSM on the facility layout , the
activates which were away from the diagonal have come
close and below the diagonal and in this way they have
become optimized in terms of time and space. In the
comparison of the figure 1 that is the facility layout before
the application of DSM and the figure 8 that is the facility
layout after the application of DSM Partitioning. Marks
underneath the diagonal symbolize forward flow of
information and marks over the diagonal symbolize
feedback from an afterward downstream task to a previous
or upstream one. Design iterations create rework and
require extra communications and compromise, which
consequence into stretched processes. So we applied the
process called Partitioning to achieve this. We can clearly
make out all the activities that were present above the
diagonal have come below the diagonal it means they
have been optimized in terms of time and three activities
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which were scattered have become clusters. Secondly the
activities x18, x20 and x26 have come closer to form a
cluster, so their times and be combined in a cluster.
The table 1 shows the actual manufacturing timings,
the LP optimized timings in the corresponding work on
process planning [1][2] and the DSM optimized timings
after applying the portioning and clustering. DSM shows
the best optimized timings in terms of total manufacturing
time.
Table 1: optimization timings comparison [1][2]
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Fig 9. Comparison of optimization methods[1]
8 Conclusion & Deductions
When we apply the DSM on the facility layout , we got to
have a layout in figure 8 in which the activities are
rearranged and most of the tasks are performed in
different fashion , the DSM makes process activates
optimized in terms of time and space. The methods used
in comparisons are Linear programming method
considering all the constraints and DSM process modeling
timings method considering all the constraints. It is
obvious from the table 1 and in the figure 9 that there is a
further improvement in the results we obtained from DSM
as compared to actual and even slight better than LP
Optimization. The optimization has dragged down the
actual manufacturing time from 7 days ( 8 working hours /
day) to 5 days, plus further improvement we see in terms
of minutes; in case of DSM process modeling the total
manufacturing time has reduced from 2350 minutes (LP)
to 2290 minutes (DSM). Future work may apply the
proposed method on the entire manufacturing system.
References
[1] Umer Asgher , Dr. Riaz Ahmad, Dr. Aamer Ahmad
Baqai “Modeling Of Multi-Objective Process Plan, Its Optimization using Linear Modeling Technique”, Proceedings of the 2013 International Conference on Systems, Control, Signal Processing and Informatics, pp 110-114.
[2] Umer Asgher, Dr. Riaz Ahmad, Dr. Liaqat Ali “ Devolpment and Modeling Of an Industrial Process Plan, Its Optimization using stochastic search Optimization Technique”, Proceedings of the 2013 International Conference on Systems, Control, Signal Processing and Informatics, pp 115-119.
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[3] K. HITOMI Viva , Manufacturing Systems Engineering, Second Edition
[4] Browning, Tyson R. (1999) "Process Modeling with Design Structure Matrices (DSMs)," INCOSE INSIGHT, 2(3): pp 15-17.
[5] Mengqi Li, Dongying Li, “Modular Decomposition Method Based on Design Structure Matrix and Application ”, TELKOMNIKA, Vol.10, No.8, December 2012, pp. 2169~2175.
[6] Kalyanmoy Deb, “Optimization for engineering design, algorithms and examples”, Prentice Hall (2005).
[7] Rehg, James A. & Kraebber, Henry W. (2005).
Computer-Integrated Manufacturing. (3rd Ed.) Prentice-Hall: Englewood Cliffs, N.J.
[8] H. Lee and S.S. Kim, “Integration of process planning and scheduling using simulation based genetic algorithms”, International Journal of Advanced Manufacturing Technology 18 (2001), pp. 586–590 .
[9] M. Asghar Bhatti, “ Practical Optimization Methods With Mathematics Applications”, Springer-Verlag N.Y, Inc., 2000.
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