Simultaneous part family and machine cell formations in cellular manufacturing systems: An analytical and algorithmic approach.
- Publication Year:
- Usage 51
- Downloads 43
- Bepress 43
- Abstract Views 8
- Bepress 8
- Repository URL:
- https://scholar.uwindsor.ca/etd/3467; https://scholar.uwindsor.ca/cgi/viewcontent.cgi?article=4466&context=etd
- Engineering; Industrial.
thesis / dissertation description
Increased level of global competition and rapid changes in consumers' tastes have forced the companies to reorganize their manufacturing operations, in a way that they can produce large variety of products, in small quantities, at high quality and at a low competitive price. Cellular Manufacturing Systems have been identified as the key in achieving these objectives. In this research, mathematical programming models are developed for single and multi period planning horizons, respectively. The objective of the models is to minimize the total cost function associated with the design of cellular manufacturing systems, while minimizing exceptional part types and obtaining a balanced machining capacity distribution for single and multi period planning horizon. The mathematical models developed for single period planning horizon consider the economic trade-offs among intercellular movement, machine duplication and subcontracting, whereas the mathematical models developed for multi period planning horizon consider the economic cost trade-offs among intercellular movement, machine duplication, subcontracting and machine cell reconfiguration and recognize the fluctuations in part demand in future production periods. In order to reduce the computational time for large size problems, a heuristic technique based on the mathematical models is developed by using the Genetic Algorithms. The mathematical models are tested by using different numerical examples and then the results are analyzed. Then, applicability of a different type of multi period planning strategy is tested and its results are compared with the multi period mathematical models in terms of arising system costs and machine cell utilizations. Finally, efficiency and applicability of genetic algorithms are tested by using a large size example and the results are compared with the mathematical models in terms of the arising cost functions, machine cell utilizations and computational time.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1995 O92. Source: Masters Abstracts International, Volume: 34-02, page: 0846. Adviser: S. M. Taboun. Thesis (M.A.Sc.)--University of Windsor (Canada), 1995.