Engineering design perspectives on additive manufacturing path planning: from geometric principles to function-driven optimisation

Path planning plays a crucial role in additive manufacturing (AM), shaping material deposition strategies that influence geometric accuracy, material efficiency, and structural integrity. This paper presents a comprehensive review of AM path planning from an engineering design perspective, systematically analyzing geometry-based and function-driven methodologies. Geometry-based approaches establish structured deposition strategies, while function-driven approaches integrate mechanical, thermal, and AI-driven refinements to optimise part performance. Their interplay is explored, highlighting emerging hybrid strategies that balance computational efficiency with adaptive optimisation. By bridging geometric fundamentals with function-driven adaptability, this review provides a foundation for future research in AI-assisted, multi-physics-aware, and real-time adaptive path planning, advancing the role of digital technologies in engineering design and manufacturing.