Robot selection based on grey‐MULTIMOORA approach

Abstract

Purpose -The purpose of this paper is to report an efficient decision-support system for industrial robot selection. It seeks to analyze potential robot selection attributes with a relatively new MCDM approach which employs grey set theory coupled with MULTIMOORA method. Design/methodology/approach -Use of interval-valued grey numbers (IVGN) adapted from grey theory has been explored to tackle subjective evaluation information collected from an expert group; finally MULTIMOORA (multi-objective optimization by ratio analysis) method has been applied in order to aggregate individual criterion/attribute scores into an equivalent evaluation index towards evaluating feasible ranking order of candidate alternative robots.Findings -An empirical study has also been shown here for better understanding of the said selection-module; effectively applicable to any other decision-making scenarios. Originality/value -This method is computationally very simple, easily comprehensible, and robust which can simultaneously consider numerous subjective attributes. Grey MULTIMOORA ranking is expected to provide a good guidance to the managers of an organization to select the feasible robot. It will also provide a good insight to the robot manufacturer so that it can improve its product or introduce a new product to satisfy customer needs.

An integrated MCDM method for robot selection under interval‐valued Pythagorean uncertain linguistic environment

“…On the basis of a literature review and expert interviews, improved product quality (CR 1 ), reduced cycle time (CR 2 ), increased manufacturing flexibility (CR 3 ), low cost (CR 4 ), and vendor's support (CR 5 ) are identified as five CRs; freedom (C 1 ), work space (C 2 ), velocity (C 3 ), load capacity (C 4 ), accuracy (C 5 ), warranty period (C 6 ), and protection class (C 7 ) are identified as seven evaluation criteria in this study. The linguistic terms sets used to assess the weights of CRs S ( ) 1 , the relationship between CRs and criteria S ( ) 2 , and the performance of the alternative robots S ( ) 3 are presented as follows: The importance degrees of CRs evaluated by the five decision makers are shown in Table 1. The assessments of relationships between CRs and evaluation criteria are derived in the form of IVPULNs.…”

“…Liu et al combined interval 2‐tuple linguistic sets and TOPSIS method to deal with robot evaluation and selection problems. Datta et al addressed robot selection problems on the basis of the grey‐multi‐objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method, where interval‐valued grey numbers were utilized to assess the performance of candidates and the MULTIMOORA approach was adopted to rank the alternative robots. Keshavarz Ghorabaee developed a new model by integrating type 2 fuzzy sets and VIKOR method to manage robot evaluation and selection problems.…”

“…The selection of a suitable robot calls for much attention on their requirements. Inappropriate robot may damage a firm's market competitive advantage in the long run . Consequently, the selection of the optimal robot to satisfy a specific requirement and manufacturing environment among various robots has become a critical and challenging mission for industrial firms …”

“…Inappropriate robot may damage a firm's market competitive advantage in the long run. 3 Consequently, the selection of the optimal robot to satisfy a specific requirement and manufacturing environment among various robots has become a critical and challenging mission for industrial firms. 4,5 In the procedure of robot evaluation, crisp numbers are deficient to reflect the real-life situations due to the inherent uncertainty of human preference.…”

Interval 2‐tuple Pythagorean fuzzy linguistic MULTIMOORA method with CIA and their application to MCGDM

“…Compared with other methods, such as TOPSIS, TODIM, and VIKOR, the most important features of the MULTIMOORA method are simplicity, little mathematical calculations, good stability and low solving time. Datta developed an improved MULTIMOORA method using gray numbers. Souzangarzadeh combined the MULTIMOORA with numeric logic method for determining a conical segmented aluminum tubeąŕs optimum design.…”