A part of the course is devoted to lectures on advanced methods for the availability, reliability and maintainability (RAM) analysis of complex systems, and Prognostics and Health Management (PHM) for condition-based and predictive maintenance. Monte Carlo Simulation, nonlinear regression and data analytics are illustrated. Another important part of the course consists of hands-on sessions in which the participants directly apply the methods explained in the lectures to practical case studies. Finally, in the last part of the course, real applications of the advanced methods illustrated in the course are presented. The applications range from Monte Carlo Simulation for system availability analysis to the use of regression and classification techniques for fault detection, to classification and prognostics for condition-based, predictive and prescriptive maintenance management.
The goal of this course is to provide participants with advanced methodological competences, analytical skills and computational tools necessary to effectively operate in the areas of reliability, availability, maintainability, diagnostics and prognostics of modern industrial equipment and systems.