Decision-making and performance measurement models with applications to robot selection

Many advanced manufacturers use robots extensively to perform repetitious, difficult, and hazardous tasks with precision. Robots improve quality and p roductivity dramatically if deployed properly. The process of selecting the most suitable robot among many alternatives involves robots' performance i n a number of key areas. Various quantitative methods have been proposed as an aid to selection decision on the choice of robots. This paper demonstra tes the use of and compares some of the current multiattribute decision-mak ing (MADM) and performance measurement methods through a robots selection p roblem borrowed from Khouja (Khouja hi. The use of data envelopment analysi s for technology selection. Comput Ind Eng 1995,28:123-132). Particular emp hasis is placed on a performance measurement procedure called operational c ompetitiveness rating (OCRA) and an MADM tool called technique for order pr eference by similarity to ideal solution (TOPSIS). A rank-correlation test shows that the methods considered produce similar rankings for the robots. The final selection is made on the basis of the rankings obtained by averag ing the results of OCRA, TOPSIS, and a utility model. (C) 1999 Elsevier Sci ence Ltd. All rights reserved.