Industrial production can be complex, with many factors at play, such as machinery breakdowns. However, an improved decision-support system that incorporates multiple information sources can make a difference when costs are totalled. In this project, Bernard Schmidt has studied a model that could lead to reduced maintenance costs.
The research increases knowledge in the field of predictive maintenance, particularly in the classification of the remaining useful life of critical components. It also enhances understanding of the importance of having maintenance data and other contextual data available and in a usable format to enable predictive analyses.