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<p>Over the past two decades, metal additive manufacturing (MAM) has evolved into a transformative technology. Although substantial progress has been made regarding new materials and layer-by-layer construction techniques, fabricating components with complex geometries remains constrained by the flexibility of structural optimization. This paper provides a comprehensive review of topology optimization (TO) methods and their applications within MAM. As our primary innovation, we systematically categorize critical manufacturing constraints into topological algorithms to establish practical engineering guidelines. Subsequently, we evaluate key structural challenges, including multi-material configurations, lattice structures, multi-scale designs, and triply periodic minimal surface (TPMS) architectures. We also thoroughly examine the integration of these optimized structures across the aerospace, automotive, and medical sectors. Ultimately, this review concludes that embedding process constraints into early-stage optimization significantly improves physical printability. Furthermore, transitioning toward advanced multi-scale structures and synergistically integrating artificial intelligence are essential for maximizing manufacturing capabilities, providing comprehensive guidance for future research.</p>

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Topology optimization methods and applications in metal additive manufacturing: a comprehensive review and prospective advances

  • 期刊论文

  • 发表日期：

    2026年6月25日

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  • Bin Ji,
  • Hua Yan,
  • Guoshuo Sui,
  • Peilei Zhang,
  • Qinghua Lu,
  • Haichuan Shi

摘要

Over the past two decades, metal additive manufacturing (MAM) has evolved into a transformative technology. Although substantial progress has been made regarding new materials and layer-by-layer construction techniques, fabricating components with complex geometries remains constrained by the flexibility of structural optimization. This paper provides a comprehensive review of topology optimization (TO) methods and their applications within MAM. As our primary innovation, we systematically categorize critical manufacturing constraints into topological algorithms to establish practical engineering guidelines. Subsequently, we evaluate key structural challenges, including multi-material configurations, lattice structures, multi-scale designs, and triply periodic minimal surface (TPMS) architectures. We also thoroughly examine the integration of these optimized structures across the aerospace, automotive, and medical sectors. Ultimately, this review concludes that embedding process constraints into early-stage optimization significantly improves physical printability. Furthermore, transitioning toward advanced multi-scale structures and synergistically integrating artificial intelligence are essential for maximizing manufacturing capabilities, providing comprehensive guidance for future research.