Applying linguistic criteria in FMS selection: fuzzy‐set‐AHP approach

This paper presents a computational framework that combines both fuzzy sets and analytical hierarchy process (AHP) for selecting the best‐ranked flexible manufacturing system from a number of feasible alternatives. Fuzzy sets are employed to recognize the selection criteria as linguistic variables rather than numerical ones, which, in turn, makes the framework quite user‐friendly. AHP is used to determine the due weight of the selection criteria, in accordance with their relative importance. In total, 14 criteria are considered, grouping them into flexibility, cost, productivity, and risk. The criteria under the first three groups are independent (i.e. their own fuzzy sets evaluate them) and the criteria under risk are indirectly evaluated by using the fuzzy sets of the criteria under flexibility. The proposed framework is implemented by developing an expert system called FmsExpert, using Borland C++. The performance of this system is also demonstrated by using an example.