Using data envelopment analysis for evaluating flexible manufacturing systems in the presence of imprecise data

Abstract

The aim of this paper is to present a comprehensive methodology for evaluation and selection of advanced manufacturing technologies, incorporating both the economic and strategic aspects and the related imprecise as well as exact data into the decision making process. Initially, a data envelopment analysis (DEA) model that can take into account crisp, ordinal, and fuzzy data is introduced. Then, the developed framework is used for flexible manufacturing system (FMS) selection. The DEA approach is performed by employing capital and operating cost, required floor space and work-in-process (WIP) as the input variables, and using product flexibility, quality improvement and lead time reduction as the output variables. The assessment of FMS alternatives versus product flexibility and quality improvement are represented via ordinal data, while WIP and lead time reduction are stated using triangular fuzzy numbers. The proposed framework is illustrated through an application and comparative results are presented.