Ph.D. Candidate Weizhi Lin, winner of the Best Poster Award at the Institute for Operations Research and the Management Sciences (INFORMS) Quality Statistics and Reliability competition in Seattle.
Weizhi Lin, a Ph.D. candidate in the Daniel J. Epstein Department of Industrial and Systems Engineering at USC, has been awarded the Best Poster Award at the Institute for Operations Research and the Management Sciences (INFORMS) Quality Statistics and Reliability competition in Seattle. This recognition highlights her innovative work advancing 3D printing through automated surface analysis.
The INFORMS competition featured 26 student participants from 18 universities, including 20 Ph.D. candidates. Lin’s victory highlights USC Viterbi School of Engineering’s continuing leadership in advanced manufacturing research and artificial intelligence applications. Lin’s award-winning research, conducted in the lab of Professor of Industrial and Systems Engineering Qiang Huang, addresses and improves challenges seen with qualification and quality control in 3D printing. Product qualification in 3D printing requires experts to manually inspect the regions of each printed object and compare them to the original design. This is an extremely labor-intensive and challenging task, especially with complicated shapes such as dental models, which often result in infinite varieties of surface patch types.
Lin and Professor Huang developed an innovative automated method that improves and automates this inspection process. The computer program uses advanced mathematical techniques to identify and analyze different surface areas of a 3D-printed object. The program recognizes patterns in how certain surface regions usually deviate from the original design. The program can then use these patterns to predict future projects, significantly streamlining the quality control process.
One of the main areas Lin wants to focus on is what she calls “small-data challenge” in 3D printing. “Traditional machine learning methods often require large, costly datasets and struggle with unseen designs,” Lin explained. “My research focuses on developing data-efficient learning methods to improve qualification and control in 3D printing, reducing reliance on costly trials.”
Upon completing her Ph.D., Lin plans to pursue a faculty position that will allow her to continue her research. Her research is part of ongoing efforts at USC’s Viterbi School of Engineering to make 3D printing more ethical, efficient and sustainable.
Published on November 13th, 2024
Last updated on November 13th, 2024
