ABSTRACT
In today’s extremely volatile global market scenario, industrial organizations are facing severe challenges to survive. In this circumstance, the management of industrial organizations is constantly searching for a way of making correct decisions in every aspect. Proper selection of robots for continuous and repetitive jobs in automotive manufacturing organizations is one of the most important and hard tasks for decision-makers. This hard task becomes harder and more complex when a decision is to be made with vague, imprecise, and ambiguous information in a fuzzy environment. This chapter aims to analyze the complexity of decision-making by exploring a new homogeneous group decision-making approach in robot selection, considering both tangible and intangible factors. A numerical example of a robot selection problem is illustrated. Assessment of performance rating of alternatives under subjective criteria as well as estimation of relative weights of selection criteria have been carried out based on the experience, opinion, and perception of the expert/decision-makers involved in the assessment process. The normalization process has been accomplished to restrict the magnitude and regulate the sense of the performance ratings of alternatives. The weights of the criteria and the normalized performance ratings have been 90integrated to calculate performance indices with benefit sense. The alternative having the highest degree of performance index has been selected as the best alternative. The results justify the applicability and validity of the proposed method.
