A SWARA-CoCoSo-Based Approach for Spray Painting Robot Selection

Kumar, Vidyapati; Kalita, Kanak; Chatterjee, Prasenjit; Zavadskas, Edmundas Kazimieras; Chakraborty, Shankar

doi:10.15388/21-INFOR466

Informatica

A SWARA-CoCoSo-Based Approach for Spray Painting Robot Selection

Volume 33, Issue 1 (2022), pp. 35–54

Vidyapati Kumar Kanak Kalita Prasenjit Chatterjee Edmundas Kazimieras Zavadskas Shankar Chakraborty

https://doi.org/10.15388/21-INFOR466

Pub. online: 3 December 2021 Type: Research Article

Open Access

Received
1 September 2021

Accepted
1 November 2021

Published
3 December 2021

Abstract

In order to avoid working in a constrained hazardous environment, manual spray painting operation is gradually being replaced by automated robotic systems in many manufacturing industries. Application of spray painting robots ensures defect-free painting of dissimilar components with higher repeatability, flexibility, productivity, reduced cycle time and minimum wastage of paint. Due to availability of a large number of viable options in the market, selection of a spray painting robot suitable for a given application poses a great problem. Thus, this paper proposes the integrated application of step-wise weight assessment ratio analysis (SWARA) and combined compromise solution (CoCoSo) methods to identify the most apposite spray painting robot for an automobile industry based on seven evaluation criteria (payload, mass, speed, repeatability, reach, cost and power consumption). The SWARA method identifies cost as the most significant criterion based on a set preference order, whereas, Fanuc P-350iA/45 is selected as the best spray painting robot by CoCoSo method. The derived ranking results are also contrasted with other popular multi-criteria decision making (MCDM) techniques (TOPSIS, VIKOR, COPRAS, PROMETHEE and MOORA) and subjective criteria weighting methods (AHP, PIPRECIA, BWM and FUCOM). High degrees of similarity in the ranking patterns between the adopted approach and other MCDM techniques prove its effectiveness in solving complex industrial robot selection problems. This integrated approach is proved to be quite robust being almost unaffected by the changing values of the corresponding tuning parameter in low-dimensional MCDM problems.

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Biographies

Kumar Vidyapati

vidyapatikumar.me@kgpian.iitkgp.ac.in

V.Kumar is pursuing his PhD in the Department of Mechanical Engineering of Indian Institute of Technology Kharagpur, India. The research area of V. Kumar includes application of different soft computing tools in solving complex optimization and decision making problems.

Kalita Kanak

drkanakkalita@veltech.edu.in

K. Kalita is currently associated with Vel Tech University, India as Assistant Professor in the Mechanical Engineering department. The research area of K. Kalita includes optimization of composite laminated structures, computational mechanics and soft computing techniques.

Chatterjee Prasenjit

p.chatterjee@mckvie.edu.in

P. Chatterjee is currently the Dean (Research and Consultancy) at MCKV Institute of Engineering, India (NAAC Accredited “A” Grade Autonomous Institute under UGC Act, 1956). P. Chatterjee is mainly interested in development of different MCDM tools and their real-time applications, operations management and quantitative techniques.

Zavadskas Edmundas Kazimieras

edmundas.zavadskas@vgtu.lt

E.K. Zavadskas, prof. chief researcher of Institute of Sustainable Construction, Faculty of Civil Engineering, VilniusTech, Lithuania. A member of the Lithuanian Academie of Sciences; Honorary doctor from Poznan, Saint-Petersburg, and Kyiv universities. Chairman of EURO Working Group ORSDCE. Associate, guest editor or board member for 40 international journals. Founding editor of journals TEDE, JCEM, IJSPM. He is a highly cited researcher in 2014, 2018–2021. Research interests: multi-criteria decision making, civil engineering, sustainable development, fuzzy systems.

Chakraborty Shankar

s_chakraborty00@yahoo.co.in

S. Chakraborty is a professor at the Department of Production Engineering of Jadavpur University, India, and a regular reviewer of several journals of international repute. The research area of S. Chakraborty includes operations research, multi-criteria decision making, statistical quality control and soft computing.

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robot spray painting MCDM SWARA CoCoSo

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