Opportunity: Design for Manufacturing using Machine Learning

Recent advances in machine learning (ML) have shown great promise for improving automated mechanical design techniques such as topology optimization, usually by demonstrating improved computational efficiency or superior mechanical performance. However, such research often focuses on design novelty and performance, while treating manufacturability as a secondary rather than coequal consideration. This helps perpetuate the proverbial wall between mechanical designers and manufacturing engineers. The present research opportunity will investigate how ML-guided design optimization can best incorporate manufacturability. Cutting-edge ML approaches including generative modeling will be studied through training, evaluation, and comparison efforts. Experience writing Python code and at least some past exposure to modern ML techniques will facilitate timely onboarding, efficient progress, and demonstrable results by the end of the effort.