Current and future trends in topology optimization for additive manufacturing
Jikai Liu (University of Pittsburgh)
Andrew T. Gaynor (U.S. Army Research Laboratory)
Shikui Chen (State University of New York)
Zhan Kang (Dalian University of Technology)
Krishnan Suresh (University of Wisconsin-Madison)
Akihiro Takezawa (Hiroshima University)
Lei Li (University of Notre Dame)
Junji Kato (Tohoku University)
Jinyuan Tang (Central South University)
Charlie Wang (TU Delft - Materials and Manufacturing)
Lin Cheng (University of Pittsburgh)
Xuan Liang (University of Pittsburgh)
Albert. C. To (University of Pittsburgh)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
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.