Design for Metal Additive Manufacturing: A Review of Design Strategies and Process Constraints

Metal additive manufacturing (AM) enables components with high geometric complexity and functional integration; however, these advantages are realized only when topology optimization (TO) aligns with AM-specific constraints. This review examines TO strategies for metal AM, with emphasis on laser powder bed fusion (LPBF) as the most established industrial route. It categorizes and assesses density-based methods, level-set approaches, and lattice or architected-material optimization, focusing on how each captures manufacturability (overhang limits, minimum feature size, surface roughness), physics (residual stress, thermal distortion), and AM-induced anisotropy. It further distinguishes algorithms that embed constraints directly into the TO loop from workflows that rely on post-optimization repair. It discusses implications for robustness and transferability across machines and alloys. Experimental and numerical evidence for titanium alloys, aluminum alloys, nickel-based superalloys, and stainless steels is synthesized to relate design decisions and processing conditions to reported gains in stiffness-to-weight ratio, strength, fatigue performance, and buy-to-fly efficiency. Persistent gaps include validation under realistic load spectra, uncertainty quantification, standardized benchmarks, microstructure-informed objectives, and sustainability metrics. Beyond synthesizing existing TO formulations and constraints, this review contributes a criteria-based decision structure linking TO method selection, constraint strategy, and process-physics coupling and identifies four inherent paradoxes defining the field’s open challenges.