A nonparametric stochastic procedure for flexible manufacturing systems evaluation

Evaluating alternative manufacturing technologies in the presence of multiple performance measures is often a difficult task for the decision maker. It is for this reason that justification and evaluation of flexible manufacturing systems has been receiving significant attention in the manufacturing circles. This paper proposes an innovative framework, which is based on the combined application of data envelopment analysis and nonparametric statistical procedures, for the selection of flexible manufacturing systems. The strengths of this methodology are that it incorporates variability measures in the performance of alternative systems, provides decision maker with effective alternative choices by identifying homogeneous groups of systems, and presents graphic aids for better interpretation of results. The methodology is illustrated through its application on a previously reported data set.