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Article

A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO

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Department of Industrial & Production Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar 144805, India
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Department of Mechanical Engineering, Maharishi Markandeshwar (Deemed to be University), Mullana 133207, India
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Department of Automobile Engineering, Amity Institute of Technology, Amity University, Noida 201313, India
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Department of Mathematics, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar 144805, India
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Fashion and Lifestyle Accessory Design Department, National Institute of Fashion Technology, Mumbai 410210, India
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Department of Mechanical and Production Engineering, Guru Nanak Dev Engineering College, Ludhiana 141006, India
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Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp.76, 454080 Chelyabinsk, Russia
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School of Mechanical and Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK
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Authors to whom correspondence should be addressed.
Academic Editors: Chao Xu and Jing Zuo
Materials 2022, 15(2), 635; https://doi.org/10.3390/ma15020635
Received: 24 November 2021 / Revised: 4 January 2022 / Accepted: 6 January 2022 / Published: 15 January 2022
(This article belongs to the Special Issue Study on the Development and Applications of Magnesium Alloys)
In the present research, the AZ31 alloy is machined by wire-cut electric discharge machining (WEDM). The experiments were designed according to the Box-Behnken design (BBD) of response surface methodology (RSM). The input process variables, namely servo feed (SF), pulse on-time (Ton), servo voltage (SV), and pulse off-time (Toff), were planned by BBD, and experiments were performed to investigate the cutting rate (CR) and recast layer thickness (RCL). The analysis of variance (ANOVA) was performed to determine the influence of machining variables on response characteristics. The empirical models developed for CR and RCL were solved using Multi-Objective Particle Swarm Optimization (MOPSO). Pareto optimal front is used for the collective optimization of CR and RCL. The optimal solution suggested by the hybrid approach of RSM-MOPSO is further verified using a confirmation test on the random setting indicated by the hybrid algorithm. It is found that the minimum RCL (6.34 µm) is obtained at SF: 1700; SV: 51 V; Toff: 10.5 µs; and Ton: 0.5 µs. However, maximum CR (3.18 m/min) is predicted at SF: 1900; SV: 40 V; Toff: 7 µs; and Ton: 0.9 µs. The error percentage of ±5.3% between the experimental results and predicted solutions confirms the suitability of the proposed hybrid approach for WEDM of AZ31. View Full-Text
Keywords: AZ31 alloy; hybrid approach; Multi-Objective Particle Swarm Optimization (MOPSO); recast layer; response surface methodology (RSM); wire-cut electric discharge machining (WEDM) AZ31 alloy; hybrid approach; Multi-Objective Particle Swarm Optimization (MOPSO); recast layer; response surface methodology (RSM); wire-cut electric discharge machining (WEDM)
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MDPI and ACS Style

Goyal, K.K.; Sharma, N.; Dev Gupta, R.; Singh, G.; Rani, D.; Banga, H.K.; Kumar, R.; Pimenov, D.Y.; Giasin, K. A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO. Materials 2022, 15, 635. https://doi.org/10.3390/ma15020635

AMA Style

Goyal KK, Sharma N, Dev Gupta R, Singh G, Rani D, Banga HK, Kumar R, Pimenov DY, Giasin K. A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO. Materials. 2022; 15(2):635. https://doi.org/10.3390/ma15020635

Chicago/Turabian Style

Goyal, Kapil K., Neeraj Sharma, Rahul Dev Gupta, Gurpreet Singh, Deepika Rani, Harish K. Banga, Raman Kumar, Danil Y. Pimenov, and Khaled Giasin. 2022. "A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO" Materials 15, no. 2: 635. https://doi.org/10.3390/ma15020635

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