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Multi-response Optimization of GTAW Process Parameters in Terms of Energy Efficiency and Quality

Van, A.-L. and Nguyen, T.-C. and Bui, H.-T. and Dang, X.-B. and Nguyen, T.-T. (2024) Multi-response Optimization of GTAW Process Parameters in Terms of Energy Efficiency and Quality. Strojniski Vestnik/Journal of Mechanical Engineering, 70 (5-6). pp. 259-269. ISSN 00392480

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Abstract

This work optimizes the current (I), voltage (V), flow rate (F), and arc gap (G) of the gas tungsten arc welding (GTAW) of the Ti40A titanium alloy to decrease the heat input (HI) and improve the ultimate tensile strength (TS) and micro-hardness (MH). The radial basis function network (RBFN) was utilized to present performance measures, while weighted principal component analysis (WPCA) and an adaptive non-dominated sorting genetic algorithm II (ANSGA-II) were applied to estimate the weights and generate optimal points. The evaluation via an area-based method of ranking (EAMR) was employed to determine the best solution. The results indicated that the optimal I, V, F, and G are 89 A, 23 V, 20 L/min, and 1.5 mm, respectively. The improvements in the TS and MH were 1.2 and 19.8 , respectively, while the HI was saved by 18.4 . The RBFN models provided acceptable accuracy for prediction purposes. The ANSGA-II provides better optimality than the conventional NSGA-II. The HI, TS, and MH of the practical GTAW Ti40A could be enhanced using optimality. The optimization method could be utilized to deal with optimization problems for not only other GTAW operations but also other machining processes. © 2024 The Authors.

Item Type: Article
Divisions: Offices > Office of International Cooperation
Identification Number: 10.5545/sv-jme.2023.890
Uncontrolled Keywords: Energy efficiency; Gas metal arc welding; Gas welding; Genetic algorithms; Microhardness; Principal component analysis; Tensile strength; Titanium alloys, Gas tungsten arc welding; Gas tungsten arc welding process; Gas tungsten-arc welding; Heat input; Micro-hardness; Multiresponses optimization; Non dominated sorting genetic algorithm ii (NSGA II); Optimality; Ultimate tensile strength; Welding process parameters, Radial basis function networks
URI: http://eprints.lqdtu.edu.vn/id/eprint/11306

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