DEA-based robot selection procedure incorporating fuzzy criteria values

Abstract

Data envelopment analysis (DEA), which avoids the critical assumption that the performance parameters are mutually independent, appears as an effective decision tool for the robot selection problem. However, a robust robot selection procedure necessitates the consideration of both quantitative criteria such as cost and engineering attributes, and qualitative criteria, e.g. vendor-related attributes, in the decision process. Qualitative attributes may be indicated by using linguistic variables or fuzzy numbers. The paper introduces revised DEA formulation incorporating both quantitative and qualitative factors to determine the best robot alternative. When multiple efficient robot alternatives are identified as a result of the analysis, cross efficiency analysis is used to determine the best robot alternative. A comprehensive example is presented to illustrate the decision-making procedure.