Programme
Start
14-01-21
Price: 1400
End
04-02-21
Duration
196 hours
DIPARTIMENTO DI ENERGIA
Course code 06/21
Description
Lectures will be held in English. All participants will receive a complete set of the presentation slides with specific examples and case studies, selected reference lists and resources in electronic format, and a participant certificate.
One part of the course is 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, Monte Carlo Simulation, nonlinear regression and filter models (Artificial Neural Networks, Principal Component Analysis, Auto-Associative Kernel Regression, Ensemble Systems, Deep Learning, Convolutional Neural Networks, Reservoir Computing) are illustrated.
In another part of the course, hands-on sessions provide the participants with the opportunity of directly applying the methods 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 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.
Educational project
In recent years, the volume of data and information collected by the industry has been growing exponentially, and more sophisticated and performing analytics have been developed to exploit their content.
This offers great opportunities for optimized, safe and reliable productions and products, including optimal predictive maintenance for ¿zero-defect¿ production with reduced warehouse costs, and improved system availability, with ¿zero unexpected shutdowns¿.
To grasp these opportunities, new system analysis capabilities and data analytics skills are needed.
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. The course presents advanced techniques and analytics to improve safety, increase efficiency, manage equipment aging and obsolescence, set up condition-based and predictive maintenance.
Requirements
The course is mainly dedicated to control, process, quality and maintenance engineers, data scientists, data miners, researchers and PhD students in the area of Reliability, Availability, Maintainability (RAM) and fault diagnostics and Prognostics and Health Management (PHM).
Location
Il corso si svolgera' online sulla piattaforma di Microsoft Teams
Faculty and staff
Director
ENRICO ZIO
Co-Director
PIERO BARALDI
Department/School/Institution
DIPARTIMENTO DI ENERGIA
Contact person
GIULIA PERNICANO
0223998509
courses-deng@polimi.it
