The growing demand for complex internal structural components in the aerospace and automotive industries has highlighted significant manufacturing challenges due to tool accessibility constraints. While additive manufacturing (AM) enables the integrated fabrication of complex internal features, its inherent surface quality deficiencies restrict precision and performance. Powder bed (PB)-based additive/subtractive hybrid manufacturing (ASHM) offers a transformative approach for fabricating components with intricate internal features. However, it faces two key challenges: first, the widespread reliance on 3-axis systems limits geometric capability for curved structures, and suboptimal trade-offs between efficiency and surface quality in manual CAM-based process planning. This study presents a novel PB-based 5-axis ASHM system and a comprehensive hybrid manufacturing strategy planning method. This method comprises three key components: global toolpath planning, cutter contact point (CCP) accessibility judgment, and accessibility-driven adaptive layering. This integrated approach enables the adaptive generation of optimal AM/SM alternation strategies and collision-free 5-axis toolpaths specifically tailored for intricate internal features. Departing from conventional approaches, this method prioritizes CCP accessibility as the criterion for model segmentation, ensures global machinability of internal features while effectively reducing AM/SM alternations and generating corresponding 5-axis collision-free toolpaths. Experimental validation using two representative internal structures confirms the method's effectiveness. The proposed hybrid manufacturing strategy demonstrates 50 % fewer AM/SM alternations and over tenfold efficiency improvement compared to conventional manual planning, while achieving 40–60 % greater machinable area than 5-axis CNC. Furthermore, it achieves superior surface quality (Ra 0.5–0.8 μm, significantly better than AM-only 6.2–8.3 μm) and exceptional dimensional accuracy (within ±0.03 mm, representing an 80 % improvement compared to AM). This work establishes a novel solution for efficient and integrated precision manufacturing of intricate internal structures.
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