Design for Additive Manufacturing: Opportunities and Challenges
Additive Manufacturing (AM) is changing the word from biomedical devices to aerospace parts in the last decades. This revolution requires new design methodologies that can take full advantages of AM. Design for Additive Manufacturing (DFAM) methods and tools include topology optimization, design for multiscale structures (lattice or cellular structures), multi-material design, mass customization, part consolidation, and other design methods which can make use of AM-enabled features. Recently, new AM processes, big data, and Artificial Intelligence (AI) brought even more opportunities to the product design. Meanwhile, the complexities in the materials, structures, and AM processes make it challenging to find the optimal design result. In this seminar, the opportunities and challenges in DFAM will be introduced to give you a better view about AM.
About the speaker
Dr. Guoying Dong is an Assistant Professor in the CU Denver Department of Mechanical Engineering. He received his PhD degree from McGill University in 2019. He worked as a Research Fellow at Singapore University of Technology and Design for two years. Then, he joined CU Denver as an Assistant Professor in Nov. 2021. Dr. Dong’s research interests include design for additive manufacturing (AM), numerical modeling, and artificial intelligence. He developed a simulation platform during his PhD to support the design of lattice structures fabricated by AM. He also worked on the Convolutional Neural Network (CNN) that can predict in-process mechanical properties for AM. His current research is focusing on the intelligent design and manufacturing of advanced materials and structures.