A correlation analysis approach of cell formation in cellular manufacturing system with incorporated production data

Abstract

The crucial step in the design of a Cellular Manufacturing (CM) system is the Cell Formation (CF) problem. This problem consists of identifying the part families and the machine groups and, consequently, forming manufacturing cells. The aim of this paper is to formulate a new multivariate approach based on a correlation analysis for solving CF problem. The proposed approach is carried out in two phases. In the first phase, the correlation matrix is used as similarity coefficient matrix. In the second phase, Principal Component Analysis (PCA) is applied as a cluster analysis to make simultaneously machine groups and part families. This approach integrates significant production data such as processing time and part type production volume in the early stages of grouping decisions for CM. The objective is to minimise the total processing time outside the cells. Two illustrative examples and numerical results are provided.