Development of a modular computer-aided process planning (CAPP) system for additive-subtractive hybrid manufacturing of pockets, holes, and flat surfaces

The International Journal of Advanced Manufacturing Technology(2018)

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摘要
Additive manufacturing (AM) can significantly reduce the development time for small batch parts or parts with complicated geometries. However, the accuracy of most metal AM processes requires parts to be subjected to secondary processing (typically machining) in order to obtain requisite tolerances. Process plan development for hybrid manufacturing, which is defined for the following as additive manufacturing followed by subtractive multi-axis computer numerical control (CNC) machining, typically takes weeks rather than hours or days. This paper outlines a feature-based advanced hybrid manufacturing process planning system (FAH-PS) that uses feature-specific geometric, tolerance, and material data inputs to generate four-automated process plans based on user-specified feature precedence for hybrid manufacturing. FAH-PS currently has the capability to identify manufacturing processes for critical pockets, flat surfaces, and hole features. Additional plans generated by FAH-PS minimize tool changes, orientation changes, etc., to improve process times. FAH-PS is modular and extensible to allow for additional feature types, materials, tool sizes, and/or optimization strategies to be included in future versions. A case study, using a custom patient-specific bone plate, demonstrated system capabilities and processing time reductions as compared to the current manual process planning for hybrid manufacturing methodologies. Using the generated FAH-PS process plan resulted in a 35% reduction in machining time from the current hybrid manufacturing strategy. Imploring a strategy of minimizing tool and orientation changes generated a process plan that demonstrated that even further improvements were possible.
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关键词
Automated process planning,Subtractive machining,Additive manufacturing,Modular programming,Automated operation planning,Hybrid manufacturing process planning
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