Recent NSF Award for Intuitive Predictive Maintenance of Industrial and Agricultural Equipment

The SRSL team recently received an award from the National Science Foundation (NSF) to investigate probabilistic and explainable deep learning for the intuitive predictive maintenance of industrial and agricultural equipment. The approach will not only predict the remaining useful life of a machine component, but it will also quantify the uncertainty of a prediction. As a result, maintenance decisions can be made from a risk-based perspective, eliminating unnecessary maintenance stemming from low-confidence predictions. This STTR Phase I project is in collaboration with a local-to-Iowa industry partner, Percēv (a subsidiary of Grace Technologies) and Grace, and is set to be completed in November 2021.