Volume 2 Issue 4 pp. 819-830 Fall, 2011


A comparative study on the ranking performance of some multi-criteria decision-making methods for industrial robot selection


Vijay Manikrao Athawale and Shankar Chakraborty
Industrial robots are mainly employed to perform repetitive and hazardous production jobs, multi-shift operations etc. to reduce the delivery time, improve the work environment, lower the production cost and even increase the product range to fulfill the customers’ needs. When a choice is to be made from among several alternative robots for a given industrial application, it is necessary to compare their performance characteristics in a decisive way. As the industrial robot selection problem involves multiple conflicting criteria and a finite set of candidate alternatives, different multi-criteria decision-making (MCDM) methods can be effectively used to solve such type of problem. In this paper, ten most popular MCDM methods are considered and their relative performance are compared with respect to the rankings of the alternative robots as engaged in some industrial pick-n-place operation. It is observed that all these methods give almost the same rankings of the alternative robots, although the performance of WPM, TOPSIS and GRA methods are slightly better than the others. It can be concluded that for a given industrial robot selection problem, more attention is to be paid on the proper selection of the relevant criteria and alternatives, not on choosing the most appropriate MCDM method to be employed.


DOI: 10.5267/j.ijiec.2011.05.002

Keywords: Robot selection, MCDM method, Ranking performance, Spearman’s rank correlation coefficient, Kendall’s coefficient of concordance
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