Title page for ETD etd-09132000-14380054


Type of Document Dissertation
Author Mungwattana, Anan
Author's Email Address amungwat@vt.edu
URN etd-09132000-14380054
Title Design of Cellular Manufacturing Systems for Dynamic and Uncertain Production Requirements with Presence of Routing Flexibility
Degree PhD
Department Industrial and Systems Engineering
Advisory Committee
Advisor Name Title
Shewchuk, John P. Committee Chair
de la Garza, Jesus M. Committee Member
Deisenroth, Michael P. Committee Member
Ellis, Kimberly P. Committee Member
Sturges, Robert H. Committee Member
Keywords
  • Routing Flexibility
  • Stochastic Production Requirements
  • Cellular Manufacturing
  • Dynamic Production Requirements
Date of Defense 2000-09-01
Availability unrestricted
Abstract
Shorter product life-cycles, unpredictable demand, and customized

products have forced manufacturing firms to operate more efficiently

and effectively in order to adapt to changing

requirements. Traditional manufacturing systems, such as job shops and

flow lines, cannot handle such environments. Cellular manufacturing,

which incorporates the flexibility of job shops and the high

production rate of flow lines, has been seen as a promising

alternative for such cases. Although cellular manufacturing provides

great benefits, the design of cellular manufacturing systems is

complex for real-life problems. Existing design methods employ

simplifying assumptions which often deteriorate the validity of the

models used for obtaining solutions. Two simplifying assumptions used

in existing design methods are as follows. First, product mix and

demand do not change over the planning horizon. Second, each operation

can be performed by only one machine type, i.e., routing flexibility of

parts is not considered. This research aimed to develop a model and a

solution approach for designing cellular manufacturing systems that

addresses these shortcomings by assuming dynamic and stochastic

production requirements and employing routing

flexibility. A mathematical model and an optimal solution procedure

were developed for the design of cellular manufacturing under dynamic

and stochastic production environment employing routing

flexibility. Optimization techniques for solving such problems usually

require a substantial amount of time and memory space, therefore, a

simulated annealing based heuristic was developed to obtain good

solutions within reasonable amounts of time. The heuristic was

evaluated in two ways. First, different cellular manufacturing design

problems were generated and solved using the heuristic. Then,

solutions obtained from the heuristic were compared with lower bounds

of solutions obtained from the optimal solution procedure. The lower

bounds were used instead of optimal solutions because of the

computational time required to obtain optimal solutions. The results

show that the heuristic performs well under various

circumstances, but routing flexibility has a major impact on the

performance of the heuristic. The heuristic appears

to perform well regardless of problem size. Second, known solutions of two

CM design problems from literature were used to compare with those

from the heuristic. The heuristic slightly outperforms one design

approach, but substantially outperforms the other design approach.

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