Process Planning of Multi-axis FDM Additive Manufacturing

This research is conducted around a recently emerged new technology – multi-axis additive manufacturing (AM). The multi-axis aspect of an AM process enables manufacturing complex shapes that are difficult or impossible to fabricate by any traditional 2.5-axis AM processes. Furthermore, many known hurdles that hinder AM’s applications, e.g., the staircase effect, excessive amount of supporting structure and poor surface quality, will be tremendously mitigated owing to the nature of multi-direction printing. However, akin to most emerging manufacturing technologies, the most prominent challenge to popularizing multi-axis AM is its process planning. With the extra degrees of freedom, the process-planning problem becomes much more complex than that of the traditional 2.5-axis AM. In this talk, we present several methodologies that strive to offer practical solutions to this challenging process-planning problem. Various new concepts, models, and mathematical tools are introduced, and ample physical multi-axis AM experiments are conducted on a homebuilt multi-axis AM platform to validate the proposed methodologies.

Dr. Kai Tang received BSE in Mechanical Engineering from his hometown university the Nanjing Institute of Technology (now Southeast University) in 1982 and afterward, as sponsored by the Chinese government, went to University of Michigan (Ann Arbor) where he received PhD in Computer Engineering in 1990. From 1991 to 2001, he worked as a software specialist at Schlumberger CAD/CAM (which in 1994 became Applicon and in 1999 became part of Unigraphics), where he developed multi-axis and mill-turn CAM software. In June 2001, he “went back” to school and joined Hong Kong University of Science and Technology (HKUST), arising from Assistant professor (2001), Associate professor (2006), and Full professor (2011). Since Aug. 2022 he has been with the newly established HKUST (Guangzhou) as the Head of Smart Manufacturing Thrust. Dr. Kai Tang’s research interests are broad but mostly concentrating on developing efficient and practical algorithms in CAD/CAM, while his current focal point is on multi-axis machining and printing of complex models. Since joining HKUST in 2001, as sole PI he has obtained in total of HK$56+ million in research funding from Hong Kong RGC and ITC, China’s NSFC, and other applied funds. In 2023 he was awarded China’s长江讲席教授. He was on the Stanford List of Top 2% Scientists of both career-long and single-year impacts since 2022. For more details about his research, please refer to: http://mektang.people.ust.hk/.