Journal
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
Volume 57, Issue 6, Pages 2457-2483Publisher
SPRINGER
DOI: 10.1007/s00158-018-1994-3
Keywords
Additive manufacturing; Topology optimization; Support structure; Lattice infill; Material feature; Multi-material; Uncertainty; Post-treatment
Categories
Funding
- National Science Foundation [CMMI-1634261, CMMI 1462270]
- Ford Research & Advanced Engineering
- State University of New York at Stony Brook
- Natural Science Foundation of China (NSFC) [61628211, 61432003]
- Key Laboratory of High Performance Complex Manufacturing at Central South University, China
- National Natural Science Foundation of China (NSFC) [51535012, U1604255]
- Key research and development project of Hunan province [2016JC2001]
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Manufacturing-oriented topology optimization has been extensively studied the past two decades, in particular for the conventional manufacturing methods, for example, machining and injection molding or casting. Both design and manufacturing engineers have benefited from these efforts because of the close-to-optimal and friendly-to-manufacture design solutions. Recently, additive manufacturing (AM) has received significant attention from both academia and industry. AM is characterized by producing geometrically complex components layer-by-layer, and greatly reduces the geometric complexity restrictions imposed on topology optimization by conventional manufacturing. In other words, AM can make near-full use of the freeform structural evolution of topology optimization. Even so, new rules and restrictions emerge due to the diverse and intricate AM processes, which should be carefully addressed when developing the AM-specific topology optimization algorithms. Therefore, the motivation of this perspective paper is to summarize the state-of-art topology optimization methods for a variety of AM topics. At the same time, this paper also expresses the authors' perspectives on the challenges and opportunities in these topics. The hope is to inspire both researchers and engineers to meet these challenges with innovative solutions.
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