NDLI: A fuzzy genetic algorithm for high-tech cellular manufacturing system design

Content Provider	IEEE Xplore Digital Library
Author	Sheng-Chai Chi Min-Chuan Yan
Copyright Year	2004
Description	Author affiliation: Dept. of Ind. Manage., Huafan Univ., Taipei, Taiwan (Sheng-Chai Chi; Min-Chuan Yan)
Abstract	With the natural characteristic of multi-process planning, a flexible manufacturing system (FMS) is much more productive than the conventional production approaches because its production processes are flexible so that the bottleneck activities in the production system can be significantly reduced. Therefore, it becomes a high efficient production system due to shorten time of manufacturing lead time, low volume of work-in-process, better performance of line-balancing and high utilization of machinery. The purpose of this research is to propose a design philosophy of part/machine grouping and cellular manufacturing system formulating with the involvement of multi-process-plan based on the techniques of fuzzy theory and genetic algorithm. The multiple objectives of this approach include minimizing the number of movements between the cells, maximizing the production density within the cells and minimizing the production loading variance within the cells. With the needs mentioned above, this research develops a fuzzy genetic clustering analysis model, which integrates fuzzy theory and genetic algorithm. This generalized clustering analysis model uses the input data of machine/part matrix with multi-process-plan, fuzzy production demands and fuzzy technical feasibility of machines under the conditions that the movements between the cells should be minimized, the production density within the cells should be maximized and the production loading variance should be minimized. This proposed prototyped model fuzzifies some essential manufacturing factors and attempts to explore a better result for cellular manufacturing system design in order to make the model with much applicability for high technology industries in the real world.
Sponsorship	IEEE IEEE Syst., Man, and Cybernetics Soc. Univ. of Alberta, Faculty of Eng., Dept. of Elec. & Comput. Eng. Alberta Innovation & Sci. ASERC iCORE Alberta Ingenuity (AI) Fund Nat. Res. Council (NRC) Pearson Educ. Canada J. Wiley McGraw Hill Elsevier BV Inst. of Phys. Res. Studies Press SUN Microsystems Springer-Verlag Login Brothers Canada
Starting Page	907
Ending Page	912
File Size	373478
Page Count	6
File Format	PDF
ISBN	0780383761
DOI	10.1109/NAFIPS.2004.1337425
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy systems Genetic algorithms Cellular manufacturing Production systems Flexible manufacturing systems Algorithm design and analysis Process planning Production planning Machinery Analysis of variance
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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