Optimal process planning for hybrid additive-subtractive manufacturing using recursive volume decomposition with decision criteria

This paper explores the concept of hybrid manufacturing (HM), which combines two or more manufacturing processes to improve efficiency and productivity. HM can be categorized based on the combination of additive, subtractive, transformative, and assistive processes, and this study specifically focuses on widely-adopted hybrid additive-subtractive manufacturing. The potential of HM to improve productivity and manufacturability is investigated from a process planning perspective. To enable fully automated and optimized process planning, a new set of decision criteria for handling a newly devised recursive volume decomposition of 3D CAD models is introduced along with a cost and time model for optimization. An optimization scheme is developed based on these requirements, and an efficient optimization algorithm using a genetic algorithm is proposed. The experimental results demonstrate that the integration of additive and subtractive processes in HM can overcome the limitations of conventional manufacturing. The optimal solutions reduce 69% and 63% of manufacturing cost and time on average for four test cases, and statistical significance was observed for the decision criteria most of the time.

Automated summary

This paper explores the concept of hybrid manufacturing (HM), specifically focusing on the widely-adopted hybrid additive-subtractive manufacturing. The study investigates the potential of HM to improve productivity and manufacturability from a process planning perspective. A new set of decision criteria and an optimization model are introduced, and an efficient optimization algorithm using genetic algorithm is proposed. Experimental results show that the integration of additive and subtractive processes in HM can overcome the limitations of conventional manufacturing, reducing manufacturing cost and time significantly for multiple test cases.