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<p>To solve the problems of deformation, micro-cracks, and residual tensile stress in laser cladding coatings, the technique of laser cladding with Fe-based memory alloy can be considered. However, the process of in-situ synthesis of Fe-based memory alloy coatings is extremely complex. At present, there is no clear guidance scheme for its preparation process, which limits its promotion and application to some extent. Therefore, in this study, response surface methodology (RSM) was used to model the response surface between the target values and the cladding process parameters. The NSGA-2 algorithm was employed to optimize the process parameters. The results indicate that the composite optimization method consisting of RSM and the NSGA-2 algorithm can establish a more accurate model, with an error of less than 4.5% between the predicted and actual values. Based on this established model, the optimal scheme for process parameters corresponding to different target results can be rapidly obtained. The prepared coating exhibits a uniform structure, with no defects such as pores, cracks, and deformation. The surface roughness and microhardness of the coating are enhanced, the shaping quality of the coating is effectively improved, and the electrochemical corrosion performance of the coating in 3.5% NaCl solution is obviously better than that of the substrate, providing an important guide for engineering applications.</p>

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Optimization of laser cladding FeMnSiCrNi memory alloy coating process based on response surface model and NSGA-2 algorithm

  • 期刊论文

  • 发表日期：

    2025年4月26日

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  • Yu Zhang,
  • Guang-lei Liu,
  • Shu-cong Liu,
  • Wen-chao Xue,
  • Wei-mei Chen,
  • Hai-xia Liu,
  • Jian-zhong Zhou

摘要

To solve the problems of deformation, micro-cracks, and residual tensile stress in laser cladding coatings, the technique of laser cladding with Fe-based memory alloy can be considered. However, the process of in-situ synthesis of Fe-based memory alloy coatings is extremely complex. At present, there is no clear guidance scheme for its preparation process, which limits its promotion and application to some extent. Therefore, in this study, response surface methodology (RSM) was used to model the response surface between the target values and the cladding process parameters. The NSGA-2 algorithm was employed to optimize the process parameters. The results indicate that the composite optimization method consisting of RSM and the NSGA-2 algorithm can establish a more accurate model, with an error of less than 4.5% between the predicted and actual values. Based on this established model, the optimal scheme for process parameters corresponding to different target results can be rapidly obtained. The prepared coating exhibits a uniform structure, with no defects such as pores, cracks, and deformation. The surface roughness and microhardness of the coating are enhanced, the shaping quality of the coating is effectively improved, and the electrochemical corrosion performance of the coating in 3.5% NaCl solution is obviously better than that of the substrate, providing an important guide for engineering applications.