A comprehensive review focuses on powder-based metal additive manufacturing (AM), providing a systematic examination of the formation mechanisms, characterization techniques, control strategies, and performance implications of porosity defects. First, it systematically categorizes the three primary types of porosity defects—lack-of-fusion defects, gas-induced pores, and keyhole defects—elucidating the complex interactions among process parameters, material properties, and environmental factors in their formation. Next, various advanced detection techniques are compared, including metallographic analysis, X-ray computed tomography, in situ monitoring, optical layer-by-layer inspection, and laser ultrasound imaging, evaluating their advantages and limitations in terms of resolution, real-time capability, and quantitative analysis. This analysis provides a theoretical foundation for multi-scale defect characterization. Subsequently, preventive and corrective strategies are summarized across three key stages: pre-processing, in-process optimization, and post-processing. These strategies include thermo-fluid-solid coupled numerical simulations, data-driven machine learning approaches, external field interventions (magnetic, acoustic, thermal, and mechanical), as well as post-processing techniques such as hot isostatic pressing and surface enhancement. Current state of these techniques is discussed, including their effectiveness in enhancing part density and service performance, and their inherent limitations. Finally, key challenges are identified in the field and future research directions are outlined, emphasizing real-time monitoring, multi-scale coupled modeling, and intelligent adaptive process control. This review aims to provide theoretical insights and technical guidance for minimizing defects and improving the overall performance of metal AM components.
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