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Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Nguyen, T.-T. and Duong, Q.-D. and Mia, M. (2021) Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 235 (13). pp. 2155-2173. ISSN 9544054

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Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality.pdf

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Abstract

Boosting energy efficiency and machining quality are prominent solutions to achieve sustainable production for turning operations. In this work, a machining condition-based optimization has been performed to decrease the total specific energy (SEC), carbon emission (CE), and average roughness (AR) of the actively driven rotary turning (ADRT) process. The processing factors are the tool rotational speed (Tv), depth of cut (a), feed rate (fr), and workpiece speed (Wv). The turning experiments of the mold material labeled SKD11 have been conducted on a CNC lathe. The regression method is employed to develop comprehensive models of the total specific energy, carbon emissions, and average roughness. The entropy approach is then applied to drive out the weight value of each ADRT response. Finally, the non-dominated sorting particle swarm optimization (NSPSO) is utilized to determine the optimal parameters. The findings indicated that the optimal values of the Tv, a, fr, and Wv are 77 m/min, 0.32 mm, 0.25 mm/rev., and 128 m/min, respectively. The SEC, AR, and CE are decreased by 18.07%, 10.46%, and 5.02%, respectively, as compared to the initial approach. Moreover, the developed active rotary turning operation can be considered as an effective technical solution to boost the machining efficiency of hardened steels. © IMechE 2021.

Item Type: Article
Divisions: Faculties > Faculty of Mechanical Engineering
Identification Number: 10.1177/09544054211001014
Uncontrolled Keywords: Carbon; Energy efficiency; Particle swarm optimization (PSO); Regression analysis; Screening; Comprehensive model; Machining conditions; Machining efficiency; Multiresponse optimization; Non-dominated Sorting; Sustainable production; Technical solutions; Turning experiments; Turning
Additional Information: Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/8575

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