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<p>This study investigates the optimization of laser powder bed fusion (LPBF) processing parameters and aging treatment conditions for maraging steel to enhance its mechanical performance. A series of experiments were conducted to generate robust datasets for artificial intelligence-based tools, enabling advanced optimization strategies. A genetic algorithm (GA) was employed to optimize relative density and microhardness by systematically analyzing the effects of laser power, scanning speed, hatch spacing, aging time, and temperature. The optimized parameters predicted by GA were validated through additional experiments by manufacturing samples using the recommended settings. Within these optimized conditions, tensile behavior was evaluated, accompanied by fractographic and microstructural analyses to gain deeper insights into fracture mechanisms. The findings of this study provide valuable guidance for optimizing manufacturing processes and heat treatments, offering a foundation for industrial applications requiring high-performance maraging steel components.</p>

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Optimization of LPBF Processing and Aging Treatment Parameters for Maraging Steel Using Genetic Algorithms: Experimental Validation and Fracture Behavior Analysis

  • 期刊论文

  • 发表日期：

    2025年5月28日

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  • Ola Jaballah,
  • Narges Omidi,
  • Chaimae Belmarouf,
  • Asim Iltaf,
  • Noureddine Barka,
  • Abderrazak El Ouafi

摘要

This study investigates the optimization of laser powder bed fusion (LPBF) processing parameters and aging treatment conditions for maraging steel to enhance its mechanical performance. A series of experiments were conducted to generate robust datasets for artificial intelligence-based tools, enabling advanced optimization strategies. A genetic algorithm (GA) was employed to optimize relative density and microhardness by systematically analyzing the effects of laser power, scanning speed, hatch spacing, aging time, and temperature. The optimized parameters predicted by GA were validated through additional experiments by manufacturing samples using the recommended settings. Within these optimized conditions, tensile behavior was evaluated, accompanied by fractographic and microstructural analyses to gain deeper insights into fracture mechanisms. The findings of this study provide valuable guidance for optimizing manufacturing processes and heat treatments, offering a foundation for industrial applications requiring high-performance maraging steel components.