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<p>Metal additive manufacturing (AM) has emerged as a critical manufacturing route for producing geometrically complex metallic components; however, its structural application is limited by strong process–structure–property coupling and defect-driven reliability concerns. This review provides a rigorous and integrated analysis of metal AM technologies by quantitatively and mechanistically linking fabrication conditions with microstructural evolution, mechanical response, and long-term performance. Primary processing routes including powder bed fusion, directed energy deposition, and binder jetting are evaluated in terms of energy density, melt pool dynamics, and thermal gradients that govern solidification kinetics. The response of key alloy systems (steels, aluminum alloys, titanium alloys, and nickel-based superalloys) is examined with respect to phase transformation pathways, grain morphology (columnar vs. equiaxed), texture development, and defect formation mechanisms such as porosity, lack of fusion, and keyholing. The influence of these microstructural features on anisotropic mechanical behavior, including tensile strength, fatigue life, and fracture resistance, is critically analyzed. Emphasis is placed on the role of thermal history and cyclic reheating in generating residual stresses and microstructural heterogeneity, which directly impact reliability under service conditions. The effectiveness of post-processing techniques such as heat treatment and hot isostatic pressing in modifying defect populations and enhancing structural integrity is also assessed. Current limitations in process repeatability, standardization, and predictive modeling are identified, highlighting the need for integrated in-situ monitoring, physics-informed modeling, and data-driven optimization. This review establishes a mechanistic framework for understanding and improving the reliability of metal additive manufacturing in structural applications.</p>

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Metal additive manufacturing technologies: a review of material response, fabrication approaches, microstructural development, mechanical characteristics, and reliability performance

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月3日

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  • Praveena Bindiganavile Anand,
  • Ali B. M. Ali,
  • Santhosh Nagaraja,
  • Aseel Smerat,
  • Ahmed Shakir Al-Hiti,
  • Wahaj Ahmad Khan

摘要

Metal additive manufacturing (AM) has emerged as a critical manufacturing route for producing geometrically complex metallic components; however, its structural application is limited by strong process–structure–property coupling and defect-driven reliability concerns. This review provides a rigorous and integrated analysis of metal AM technologies by quantitatively and mechanistically linking fabrication conditions with microstructural evolution, mechanical response, and long-term performance. Primary processing routes including powder bed fusion, directed energy deposition, and binder jetting are evaluated in terms of energy density, melt pool dynamics, and thermal gradients that govern solidification kinetics. The response of key alloy systems (steels, aluminum alloys, titanium alloys, and nickel-based superalloys) is examined with respect to phase transformation pathways, grain morphology (columnar vs. equiaxed), texture development, and defect formation mechanisms such as porosity, lack of fusion, and keyholing. The influence of these microstructural features on anisotropic mechanical behavior, including tensile strength, fatigue life, and fracture resistance, is critically analyzed. Emphasis is placed on the role of thermal history and cyclic reheating in generating residual stresses and microstructural heterogeneity, which directly impact reliability under service conditions. The effectiveness of post-processing techniques such as heat treatment and hot isostatic pressing in modifying defect populations and enhancing structural integrity is also assessed. Current limitations in process repeatability, standardization, and predictive modeling are identified, highlighting the need for integrated in-situ monitoring, physics-informed modeling, and data-driven optimization. This review establishes a mechanistic framework for understanding and improving the reliability of metal additive manufacturing in structural applications.