Transfer learning

A novel machine learning model predicts wear and tear in manufacturing parts with less real-world data for cost savings and improved productivity.

A computational platform designed by A*STAR researchers accurately predicts a machine’s functional lifespan even with limited data.

By giving algorithms the ability to generalize, researchers are expanding the range of problems that can be tackled with artificial intelligence.

Leveraging both artificial intelligence and field knowledge may prove to be a superior strategy for predicting machine health.