Continuing Education Course:

RAM&PHM 4.0: Advanced Methods for Reliability, Availability, Maintainability, Prognostics and Health Management of industrial equipment

Francesco Di Maio
IEEE Reliability Chapter (Chair) – Italy Section

The 2018 professional one-week training course: “RAM&PHM 4.0: Advanced methods for Reliability, Availability, Maintainability, Prognostics and Health Management of industrial equipment” took place at Politecnico di Milano, Milan (Italy) on December 10-13. The course was the XXI edition of the series. Its goal has been 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 industrial equipment. The course presents advanced analytics to improve safety, increase efficiency, manage equipment aging and obsolescence, set up condition-based and predictive maintenance.

Since the beginning, the course has been officially supported by IEEE Reliability Chapter (Italy) and the European Safety and Reliability Association (ESRA); that, since 2005, has been officially offering scholarships to PhD students for covering the registration fee.

The first part of the course has been devoted to the presentation of advanced methods for the availability, reliability and maintainability analysis of complex systems and for the development of Prognostics and Health Management (PHM) and Condition-Based Maintenance (CBM) approaches. In this respect, the basics of Monte Carlo Simulation, nonlinear regression and filter models (Artificial Neural Networks, Principal Component Analysis, Auto-Associative Kernel Regression, Ensemble Systems, Hilbert Huang and Wavelet transforms) and evolutionary optimization methods (Genetic Algorithms) have been illustrated. In the second part of the course, exercise sessions on Monte Carlo simulation, Artificial Neural Networks and Genetic Algorithms provided the participants with the opportunity for directly applying the methods to practical case studies. Finally, in the last part of the course, real applications of the advanced methods have been illustrated. The applications range from the evaluation of maintenance costs taking into account the reliability and availability of equipment, to the application of Monte Carlo Simulation for system availability analysis and condition-based maintenance management, to the use of regression and classification techniques for fault detection, classification and prognosis in industrial equipment.

The 2019 edition of the course will take place at Politecnico di Milano, Milan (Italy) on November 2019. For any information, please contact francesco.dimaio@polimi.it