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DTSTAMP:20260114T163648Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T162500
DTEND;TZID=Australia/Melbourne:20231212T164000
UID:siggraphasia_SIGGRAPH Asia 2023_sess161_papers_232@linklings.com
SUMMARY:VASCO: Volume and Surface Co-Decomposition for Hybrid Manufacturin
 g
DESCRIPTION:Fanchao Zhong, Haisen Zhao, Haochen Li, Xin Yan, and Jikai Liu
  (Shandong University); Baoquan Chen (Peking University); and Lin Lu (Shan
 dong University)\n\nAdditive and subtractive hybrid manufacturing (ASHM) i
 nvolves the alternating use of additive and subtractive manufacturing tech
 niques, which provides unique advantages for fabricating complex geometrie
 s with otherwise inaccessible surfaces. However, a significant challenge l
 ies in ensuring tool accessibility during both fabrication procedures, as 
 the object shape may change dramatically, and different parts of the shape
  are interdependent. In this study, we propose a computational framework t
 o optimize the planning of additive and subtractive sequences while ensuri
 ng tool accessibility. Our goal is to minimize the switching between addit
 ive and subtractive processes to achieve efficient fabrication while maint
 aining product quality. We approach the problem by formulating it as a Vol
 ume-And-Surface-CO-Decomposition (VASCO) problem. First, we slice volumes 
 into slabs and build a dynamic-directed graph to encode manufacturing cons
 traints, with each node representing a slab and direction reflecting opera
 tion order. We introduce a novel geometry property called hybrid-fabricabi
 lity for a pair of additive and subtractive procedures. Then, we propose a
  beam-guided top-down block decomposition algorithm to solve the VASCO pro
 blem. We apply our solution to a 5-axis hybrid manufacturing platform and 
 evaluate various 3D shapes. Finally, we assess the performance of our appr
 oach through both physical and simulated manufacturing evaluations.\n\nReg
 istration Category: Full Access\n\nSession Chair: J. Andreas Bærentzen (Te
 chnical University of Denmark)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_232&sess=sess161
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