Abstract
Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).
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Recommended by Associate Editor Young Whan Park
Ravipudi Venkata Rao is a Professor in the Department of Mechanical Engineering of S.V. National Institute of Technology, Surat, Gujarat (India). He received his B.Tech. degree from Nagarjuna University, M.Tech. degree from BHU, Varanasi, and Ph.D. degree from BITS, Pilani, India and D.Sc. degree from Poland. He has more than 26 years of teaching and research experience. He has authored more than 300 research papers published in various reputed international journals and conference proceedings. He is also on the editorial boards of various international journals and Associate Editor of few. His research interests include advanced engineering optimization techniques and the applications, advanced manufacturing technology, automation and robotics.
Dhiraj P. Rai is a Research Scholar in the Department of Mechanical Engineering of S.V. National Institute of Technology, Surat, Gujarat (India). His research interests include advanced engineering optimization techniques and their applications in manufacturing.
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Rao, R.V., Rai, D.P. Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm. J Mech Sci Technol 31, 2513–2522 (2017). https://doi.org/10.1007/s12206-017-0449-x
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DOI: https://doi.org/10.1007/s12206-017-0449-x