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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/736
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| Title: | Manufacturing cell formation with production data using neural networks |
| Authors: | Sudhakarapandian, R
Mahapatra, S S |
| Keywords: | Cell Formation
Group Efficiency
Exceptional elements |
| Issue Date: | 2008 |
| Publisher: | Elsevier |
| Citation: | Computers & Industrial Engineering (Accepted Version) |
| Abstract: | Batch type production strategies need adoption of cellular manufacturing (CM) in
order to improve operational effectiveness by reducing manufacturing lead time
and costs related to inventory and material handling. CM necessitates that parts
are to be grouped into part families based on their similarities in manufacturing
and design attributes. Then, machines are allocated into machine cells to
produce the identified part families so that productivity and flexibility of the
system can be improved. Zero-one part-machine incidence matrix (PMIM)
generated from route sheet information is commonly presented as input for
clustering of parts and machines. An entry of ‘1’ in PMIM indicates that the part is
visiting the machine and zero otherwise. The output is generated in the form of
block diagonal structure where each block represents a machine cell having
more than one machines and a part family. The major limitations of this approach
lies in the fact that important production fa... |
| Description: | Copyright for the published version belongs to Elsevier |
| URI: | http://dx.doi.org/10.1016/j.cie.2008.08.003
http://hdl.handle.net/2080/736 |
| Appears in Collections: | Journal Articles
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Files in This Item:
| File |
Description |
Size | Format |
|---|
| ssm-2008-sudhakar.pdf | | 369Kb | Adobe PDF | View/Open |
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