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 customizedproducts 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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