Advanced methods for reliability, availability, maintainability, diagnostics and prognostics of industrial equipment - XVa Edizione

Staff scientifico ed organizzativo

Destinatari

The course is mainly dedicated to engineers, analysts and researchers in the area of reliability and risk analysis and to developers and users of systems for Diagnostics, Prognostics and Health Management (PHM) and Condition Based Maintenance (CBM), including: Controls/Diagnostic Engineers, Engineering Supervisors, Operator/Maintenance Engineers, and Program Managers.

Struttura didattica

  • Inizio delle lezioni: 17/09/2012
  • Fine delle lezioni: 20/09/2012
  • Totale ore: 32

Finalitā e Contenuti

The first 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, the basics of Monte Carlo Simulation, nonlinear regression and filter models (Artificial Neural Networks, Principal Component Analysis, Auto Associative Kernel Regression, Ensemble Systems) and evolutionary optimization methods (Genetic Algorithms) is illustrated. In the second part of the course, exercise sessions on Monte Carlo simulation, Artificial Neural Networks and Genetic Algorithms 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 are 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 availability analysis and condition-based maintenance management, to the use of regression and classification techniques for fault detection, classification and prognosis in complex industrial plants.

Brochure (Calendario e quote d'iscrizione)

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