第21期“工业设备可靠性、可用性、维修性、故障预测与健康管理”培训-北航中法工程师学院

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第21期“工业设备可靠性、可用性、维修性、故障预测与健康管理”培训

发布者：发布日期：2018-10-30 来源：返回

RISE Lab和CRESCI协助举办第21期“工业设备可靠性、可用性、维修性、故障预测与健康管理”培训。

该培训将于2018年12月10-13日于意大利米兰召开，届时将由知名专家学者为广大学员讲授相关课程，详情如下：

Dear Colleague,

a gentle reminder regarding the XXI edition of the continuing education course:
"RAM&PHM 4.0: Advanced methods for Reliability, Availability, Maintainability, Prognostics and Health Management of industrial equipment"

which will be held on 10-13 December 2018 in Milano, Italy.

The course is organized by the Energy Department of the Politecnico di Milano.

It 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).

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 industrial equipment. The course presents advanced analytics to improve safety, increase efficiency, manage equipment aging and obsolescence, set up condition-based and predictive maintenance.

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, Hilbert Huang and Wavelet transforms) and evolutionary optimization methods (Genetic Algorithms) are 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 illustrated in the course are presented. 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 European Safety and Reliability Association (ESRA, www.esrahomepage.org) supports the course with two scholarships for PhD students covering the registration fee.

Further details on the course can be found on the attached flyer.

Best regards,

Piero Baraldi
Enrico Zio
Course Directors

flier_RAMPHM_DEC18.pdf

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