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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/686
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| DC Field | Value | Language |
|---|
| contributor.author | Ponnambalam, S G | - |
| contributor.author | Sudhakarapandian, R | - |
| contributor.author | Mahapatra, S S | - |
| contributor.author | Saravansankar, S | - |
| date.accessioned | 2008-05-16T03:50:41Z | - |
| date.available | 2008-05-16T03:50:41Z | - |
| date.issued | 2007 | - |
| identifier.citation | IEEE International Conference on Industrial Engineering and Engineering Management, Hotel Furama River Front, 405 Havelock Road, Singapore 169633, 2-5 December 2007. | en |
| identifier.uri | http://hdl.handle.net/2080/686 | - |
| description | Copyright for the paper belongs to proceedings publisher | en |
| description.abstract | Cellular Manufacturing System (CMS) is
regarded as an efficient production strategy for batch type of
production. CMS rests on the principle of grouping the
machines into machine cells and parts into part families
based on suitable similarity criteria. Usually zero-one
machine-part incidence matrix (MPIM) obtained from the
route sheet information is used to form machine cells. In this
paper, an attempt has been made to solve the cell formation
problem considering work load data and a genetic algorithm
(GA) is suggested to form machine cells and part families.
The performance of the proposed algorithm is compared
with existing algorithms such as K-means algorithm and
modified ART1 algorithm found in the literature using a
newly defined performance measure known as modified
grouping efficiency (MGE). The proposed algorithm is
tested with problems from open literature and the results are
compared with the existing algorithms found in the
literature. The results support the better performance of the
proposed algorithm. | en |
| format.extent | 342254 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | - |
| title | Cell formation with workload data in cellular manufacturing system using genetic algorithm | en |
| type | Article | en |
| Appears in Collections: | Conference Papers
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Files in This Item:
| File |
Description |
Size | Format |
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| ssm-2008-conf.pdf | | 334Kb | Adobe PDF | View/Open |
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