An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

Author:

Sampathkumar Swethaa1ORCID,Augustin Felix1ORCID,Kaabar Mohammed KA2ORCID,Yue Xiao-Guang34

Affiliation:

1. Mathematics Division, School of Advanced Sciences, Vellore Institute of Technology, Chennai, Tamil Nadu, India

2. Jabalia Camp, United Nations Relief and Works Agency (UNRWA) Palestinian Refugee Camp, Gaza Strip Jabalya, Palestine

3. Department of Computer Science and Engineering, European University Cyprus, Nicosia, Cyprus

4. Department of Information and Knowledge Management, School of Consumer Intelligence and Information Systems, University of Johannesburg, Johannesburg, South Africa

Abstract

Manufacturing robots are used for industrial purposes. Robots used for manufacturing purpose have the power to create products from raw materials and are capable of operating endlessly even in lights-out situations for continuous production. Manufacturing robots can be used in applications like arc welding, spot welding, materials handling, machine tending, painting, machine cutting and so on. Selecting a robot for a given application is complex. However, robot selection is used in selecting a suitable robot for the preferred output with specific application ability. In recent years, many authors used multi-criteria decision-making methods to select a robot that meets the need. This study presents a hybrid model by integrating complex proportional assessment (COPRAS) with the weighted aggregates sum product assessment (WASPAS) methods in intuitionistic dense fuzzy set to select a manufacturing robot for a particular application. Intuitionistic dense fuzzy entropy is used in calculating the weights for the criteria and intuitionistic dense fuzzy COPRAS and WASPAS are used in ranking the best alternatives where in the optimum types of robots are obtained. Here, intuitionistic dense fuzzy sets are used as it is capable of dealing with the intangible factors while selecting a robot. On the basis of the manufacturing robot selection, two comparisons are given. First, the results are compared with various [Formula: see text] values between 0 and 1 and second the results are compared with the fuzzy set, intuitionistic fuzzy set and the dense fuzzy set to show the effectiveness of the proposed methodology with the intuitionistic dense fuzzy set.

Publisher

SAGE Publications

Subject

Mechanical Engineering

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