Track: Artificial Intelligence

Abstract

Industrial Robot selection is an important function for many advanced manufacturing technologies. This paper presents a decision support system to aid the managers in selecting the best combination of robots. The selection model is based on Grey Relational Analysis (GRA) and KOHONEN Algorithm. The proposed approach of this paper first clusters different Robots based on KOHONEN algorithm and then ranks various robots in each cluster according to Grey Relational Analysis (GRA) Concept. Finally, Pareto combination robots are selected in the budget scope of the organization through the application of Multiple Objective Genetic Algorithm. The results obtained from the Grey Based KOHONEN model are compared with those obtained from the TOPSIS model. Solving the two-objective studied model has revealed that the ranks of the Grey Based KOHONEN model have produced a non-dominance solution as compared with the TOPSIS model. The proposed framework is tested in a case study to show its usefulness and applicability in practice.