Abstract
Generative Design is an artificial intelligence technology that presents thousands of solutions based on a given combination of criteria with the help of cloud computing. We applied the generative design approach to the gear structure of a diesel engine to eliminate the conflict between gear noise reduction and friction reduction. Sensitivity studies were conducted by the gear train CAE model which surrogates characteristic values to verify the validity of the input conditions for generative design. A generative design was performed, and a prototype was selected from a huge number of design results. The engine test results with prototype gears showed that the generative design was effective in reducing noise at the same level as conventional parts without deteriorating friction.
