What impact can machinery failure have in an industrial context? Is it possible to predict the best time to perform maintenance interventions?This workshop provides an overview of Machine Learning methodologies for Predictive Maintenance in the context of Industry 4.0 and Internet-of-Things (IoT) with the aim of optimizing the scheduling of maintenance interventions in order to significantly reduce plant downtime and the resulting costs. A real-world case study is also presented where different Machine Learning models are used to predict the remaining useful life time of turbofans from sensor data placed on them.
- Introduction to the Machine Learning
- Classification, regression, model quality
- Prognostics and Health Management
- Case Study: NASA’s Turbofan Engine Degradation Simulation