Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods

Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0. It has improved manufacturing efficiency and helped industries to face economic, social, and environmental challenges successfully. Condition-Based Maintenance (CBM) performs machines and components' maintenance routines based on their needs, and Prognostics and Health Management (PHM) monitors components' wear evolution using indicators. PHM is a proactive way of implementing CBM by predicting the Remaining Useful Life (RUL), one of the most important indicators to detect a component's failure before it effectively occurs. RUL can be predicted…

• ER
  European Regional Development Fund