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<p>To improve the surface performance of 42CrMo steel under high-load and high-friction conditions, specifically, the gradient structure was achieved by gradually adjusting the Inconel 718/WC powder feeding ratio layer by layer, with the WC content increasing from the bottom layer to the top layer using magneto-thermal-assisted laser cladding. A multi-objective optimization model was developed using microhardness, surface flatness, and heat-affected zone depth as performance indicators. Process parameters were screened via central composite design (CCD), and a third-order polynomial regression model was established. A multi-objective whale optimization algorithm (MOWOA) was combined with entropy weight and TOPSIS methods to determine the optimal parameters: 46.11&#xa0;J/mm2 laser energy density, 51.09% overlap ratio, 199.98&#xa0;°C preheating temperature, and 27.04 mT magnetic field strength. Validation experiments confirmed the model's reliability, with prediction errors below 5%. The proposed method effectively improves coating quality and offers guidance for parameter optimization in advanced laser remanufacturing.</p>

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Multi-Objective Optimization Method and Experimental Verification of Magnetic Thermal-Assisted Laser Cladding Process Parameters Based on Multi-Objective Whale Optimization Algorithm

  • 期刊论文

  • 发表日期：

    2026年2月26日

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  • Peiyou Li,
  • Jingpeng Qin,
  • Linsen Shu,
  • Jiahao Shi,
  • Siyu Mao

摘要

To improve the surface performance of 42CrMo steel under high-load and high-friction conditions, specifically, the gradient structure was achieved by gradually adjusting the Inconel 718/WC powder feeding ratio layer by layer, with the WC content increasing from the bottom layer to the top layer using magneto-thermal-assisted laser cladding. A multi-objective optimization model was developed using microhardness, surface flatness, and heat-affected zone depth as performance indicators. Process parameters were screened via central composite design (CCD), and a third-order polynomial regression model was established. A multi-objective whale optimization algorithm (MOWOA) was combined with entropy weight and TOPSIS methods to determine the optimal parameters: 46.11 J/mm2 laser energy density, 51.09% overlap ratio, 199.98 °C preheating temperature, and 27.04 mT magnetic field strength. Validation experiments confirmed the model's reliability, with prediction errors below 5%. The proposed method effectively improves coating quality and offers guidance for parameter optimization in advanced laser remanufacturing.