Decision Support System for Evaluation and Ranking of Robots Using Hybrid Approach

Abstract

A hybrid approach namely “fuzzy modified distance based approach (FMDBA)” is proposed and presented for the selection and ranking of industrial robots, which is hitherto not applied in open literature for the purpose. The priority weights of the selection criteria/sub-criteria and performance ratings of the alternative robots for subjective selection criteria/sub-criteria are obtained on ten point and seven-point fuzzy scales using experts’ opinion. Statistical methods are used for ensuring reliability of the data obtained from experts. FMDBA method can incorporate interaction among selection criteria/sub-criteria into the decision analysis, an issue that has been generally overlooked in earlier robot selection studies. The robots are ranked according to the Euclidian distance of alternative robots termed as composite distance from the hypothetically imagined best possible robot. The methodology is illustrated through an example using a previously published data set of 27 robots based on four selection criteria. The results are compared with those of other multicriteria decision aids, which have been also employed in earlier studies addressing robot selection. A decision support system, “ROBORANK,” is developed, which is user friendly and also does not require an extensive technical knowledge of the selection criteria/sub-criteria and or robots for its use.