Abstract
In this paper, the clarifications regarding the usage of Mahalanobis distance (MD) for the machine-part cell formation (MPCF) are demonstrated. Perhaps, for the first time, part families are created using the correlation matrix derived from the covariance matrix of the given incidence matrix. The proposed MD-based method is compared with the existing popular methods for MPCF using the benchmark data sets from the literature. Also, in the present work, the procedure for calculation of MD for the purpose of machine-part cell formation in the event of high correlations is explained. The comparative performance analysis reveals that the grouping efficacy of the proposed MD-based method is at par or better when compared with the other popular algorithms available in the literature.
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