文章基本信息

标题：Application of principal component analysis in machine-part cell formation ,
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作者：Manojit Chattopadhyaya Sitanath Mazumdar ; Pranab K Dan ; Partha Sarathi Chakraborty 等
期刊名称：Management Science Letters
印刷版ISSN：1923-9335
电子版ISSN：1923-9343
出版年度：2012
卷号：2
期号：4
页码：1175-1188
DOI：10.5267/j.msl.2012.03.003
出版社：Growing Science
摘要：The present paper applies Principal Component Analysis (PCA) for grouping of machines and parts so that the part families could be processed in the cells formed by those associated machines. An incidence matrix with binary entries has been chosen to apply this methodology. After performing the eigenanalysis of the principal component and observing the component loading plot of the principal components, the machine groups and part families are identified and arranged to form machine-part cells. Later, the same methodology is extended and it is applied to nine other machine-part matrices collected from literature for the validation of the proposed methodology. The goodness of cell formation is compared using the grouping efficacy and the potential of eigenanalysis in cell formation is established over the best available results using the various established methodologies. The result shows that in 70% of the problems there is an increase in grouping efficacy and in 30% problem, the performance measure of cell formation is as good as the best result from literature.
关键词：Eigen Analysis; Principal Component Analysis; Group Technology; Machine-Part Cell; grouping efficacy