Fuzzy-TODIM for Industrial Robot Selection

Abstract

Robot selection is a complex decision making process in industrial context due to advanced features and facilities that are continuously being incorporated into the robots by different robot manufacturers. Recently, global marketplace has made absolutely difficult for the manufacturing organizations to withstand without adopting new tools and technologies, due to increased market competitiveness, higher customers’ expectation for quality products, reduced delivery time, lowered production cost and increased product range. With the advent of wide variety of robot types and models with distinct features; it increases complexity and diversity in their application areas offered by different robotic products. Therefore, selecting the most appropriate robot has now become very difficult and complicated job. In order to facilitate accurate decision making for robot selection, in this paper, a fuzzy based Multi-Criteria Decision Making (MCDM) tool has been highlighted. TODIM (Tomada de Decisión Inerativa Multicritero) coupled with Generalized Fuzzy Numbers (GFNs) set theory has been utilized herein to determine the most preferable robot from amongst possible candidate alternatives. The study explores both subjective and objective data in relation to robot selection attributes/criteria. Application potential of fuzzy based TODIM has been highlighted in this pape