Multi-Objective Optimization of the Rotary Turning of Hardened Mold Steel for Energy Saving and Surface Roughness Improvements
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Mechanical Engineering, Le Quy Don Technical University, Viet Nam
Faculty of Engineering and Technology, Nguyen Tat Thanh University, Viet Nam
Submission date: 2023-03-13
Final revision date: 2023-09-23
Acceptance date: 2023-09-24
Online publication date: 2023-09-27
Publication date: 2023-12-14
Corresponding author
Trung Thanh Nguyen   

Mechanical Engineering, Le Quy Don Technical University, 236 Hoang Quoc Viet, 10000, Ha Noi, Viet Nam
Journal of Machine Engineering 2023;23(4):101-121
In this investigation, the specific cutting energy (SCE) and average surface roughness (Ra) were decreased using the hard-rotary turning (HRT) factors, including the inclination angle (I), depth of cut (D), feed rate (f), and spindle speed (S). The Bayesian regularized feed-forward neural network was applied to develop the SCE and Ra models. The entropy method and vibration and communication particle swarm optimization (VCPSO) algorithm were employed to compute the weights and determine optimal factors. The optimizing outcomes presented that the optimal I, D, f, and S were 35 deg., 0.45 mm, 0.50 mm/rev., and 1200 rpm, respectively, while the SCE and Ra were decreased by 37.4% and 6.6%, respectively. The total turning cost was saved by 7.5% at the selected solution. The valuable outcomes could be applied to the practical HRT process to decrease performance measures, while the developed HRT operation could be utilized for machining difficult-to-cut materials.
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