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 1riazcae@yahoo.com,

2umer_asgher2000@yahoo.com.

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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