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In this paper, we consider the problem of forming machine cell in cellularmanufacturing (CM). The major problem in the design of a CM system is toidentify the part families and machine groups and consequently to formmanufacturing cells. The aim of this article is to formulate a multivariateapproach based on a correlation analysis for solving cell formation problem.The proposed approach is carried out in two phases. In the first phase, thecorrelation matrix is used as an original similarity coefficient matrix. In thesecond phase, Principal Component Analysis (PCA) is applied to find theeigenvalues and eigenvectors on the correlation similarity matrix. A scatterplot analysis as a cluster analysis is applied to make machine groups whilemaximizing correlation between elements. A numerical example for the design ofcell structures is provided in order to illustrate the proposed approach. Theresults of a comparative study based on multiple performance criteria show thatthe present approach is very effective, efficient and practical

Principal component analysis model for machine-part cell formation problem in group technology