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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/736

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
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