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Laser technologies in manufacturing functional materials and applications of machine learning-assisted design and fabrication

  • Xiangning Zhang
  • , Li Zhou
  • , Guodong Feng
  • , Kai Xi
  • , Hassan Algadi
  • , Mengyao Dong
  • Chongqing Industry Polytechnic College
  • Xi'an Jiaotong University
  • Najran University

科研成果: 期刊稿件文献综述同行评审

43 引用 (Scopus)

摘要

The integration of laser technologies and machine learning has marked a transformative era in functional materials manufacturing. This review highlights how AI-driven methods optimize laser-assisted processes, enabling real-time error correction and parameter adjustment. By comparing different laser machining techniques and emphasizing their synergy with machine learning, this paper provides insights into the future of smart manufacturing and new research avenues for improving material performance. Laser-assisted processes, such as laser cutting and laser-induced oxidation, improve precision, reduce thermal damage, and enable the fabrication of complex geometries. Additionally, laser cladding and coating technologies enhance interfacial properties. The incorporation of machine learning algorithms in laser manufacturing processes further optimizes parameters, enhances real-time error correction, and improves quality control. This review uniquely emphasizes the synergistic effects of combining laser technologies with artificial intelligence, presenting a comprehensive comparison of different laser machining techniques and their practical applications. By addressing current limitations and exploring new research avenues, this review highlights the significant advancements and future potential in laser-based manufacturing technologies. Graphic Abstract: (Figure presented.)

源语言英语
期刊论文编号76
期刊Advanced Composites and Hybrid Materials
8
1
DOI
出版状态已出版 - 2月 2025

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 9 - 产业、创新和基础设施
    可持续发展目标 9 产业、创新和基础设施

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