The Implementation of MABAC Approach for Arc Welding Robot Selection with Rough Approach Integration

In the current days, several immense applications in the agricultural machineries, automobile components, manufacturing process of steel furniture and some other applications can be found by the automated industries like the arc welding. Actually, the selection of the most suitable robot for a certain welding application may be handled as a critical decision making with multi-criteria, where the optimal alternative needs must be chosen based on a certain conflicting evaluation criteria. In this study, an approach “multi-attributive-border-approximation-area-comparison (MABAC)” has been integrated with rough numbers to solve a certain problem, which is arc welding robot selection. Five certain decision makers gave their opinions that have been aggregated to each other by using the rough numbers in order to mitigate the subjectivity and the personality in the process of decision maker. However, MABAC approach is used to rank the proposed alternatives in addition to select the optimal robot for a certain welding application. Moreover, the criteria weights were calculated based on the rough entropy approach that reveals that both of welding payload and welding performance are considered as the most essential robot-selection criteria in the arc welding application, followed by the robot cost. In this paper, the usage of the rough MABAC approach indicated that robot A6 is the most proper choice, while the worst selection is for A2.