A fuzzy digraph method for robot evaluation and selection

Abstract

The selection of a robot for a particular industrial application has been confounded the decision makers for at least four decades. The increment of production demands and the large number of alternative robots, contributed to the complexity of the selection problem. In this article, a fuzzy digraph method is developed for robot evaluation and selection, according to a given industrial application. All the information about the objective and subjective attributes are expressed in linguistic terms, represented by fuzzy numbers. Considering the number of robot selection attributes and their relative importance, a digraph is developed for the optimum representation of interrelations. The digraph model associates the systematical process for attributes combination with the simplicity which characterizes the robot evaluation method, by using a matrix approach. The procedure is discriminated between subjective and objective attributes and the corresponding matrix of relative importances is formed for all the alternative robots. Using the positive determinants of fuzzy matrices, a pair of indexes obtained for each robot. The methodology is concluded by converting the fuzzy output into a crisp value and estimating the selection index. Using the selection index, the evaluation of alternative robots and the selection of the most appropriate is eventually feasible. Two numerical examples are included to illustrate the proposed approach. Moreover, the ‘Fuzzy TOPSIS’ and ‘Digraph’ models are implemented according to the particular example, in order to display the classification per methodology.