| Description |
1 online resource (xv, 181 pages) : illustrations |
| Bibliography |
Includes bibliographical references and index. |
| Summary |
"Modeling Remaining Useful Life Dynamics in Reliability Engineering applies traditional reliability engineering methods to Prognostics and Health Management (PHM), looking at Remaining Useful Life (RUL) and predictive maintenance to enable engineers to effectively and safely predict machinery lifespan. One of the key tools used in defining and implementing predictive maintenance policies is the RUL indicator. However, it is essential to account for the uncertainty inherent to the RUL, as otherwise predictive maintenance strategies can be incorrect. This can cause high costs, or alternatively, ineffective predictions. Methods used to estimate RUL are very numerous and diverse, and broadly speaking, fall into three categories: model-based, data-driven, or hybrid, which uses both. The book starts by building on established theory, and applying cutting edge research to it, such as artificial intelligence models and deep learning. It looks at traditional reliability engineering methods through their relation to Prognostics and Health Management (PHM) requirements and presents the concept of RUL loss rate. Following on from this, the book presents a general method for defining a nonlinear transformation enabling the MRL to become a linear function. It also touches on topics such as Weibull distribution, gamma distribution and degradation, along with time-to-failure distributions. Features: Provides both practical and theoretical background of RUL. Describes how the uncertainty of RUL can be related to RUL loss rate. Provides new insights into time-to-failure distributions. Offers tools for predictive maintenance. The book will be of interest to engineers and researchers in reliability engineering, Prognostics and Health Management and industry management"-- Provided by publisher. |
| Biography |
Pierre Dersin graduated from the Massachusetts Institute of Technology (MIT) with a Ph.D. in Electrical Engineering after receiving a Master's degree in Operations Research also from MIT. He also holds math & E.E.degrees from Université Libre de Bruxelles ( Belgium). Since 2019, he has been Adjunct Professor at LuleŪniversity of Technology (Sweden) in the Operations & Maintenance Engineering Division. In January 2022, he founded a small consulting company, Eumetry sas, in Louveciennes, France, in the fields of RAMS, PHM and AI, just after retiring from ALSTOM where he had spent more than 30 years. With Alstom, he was RAM (Reliability-Availability-Maintainability) Director from 2007 to 2021 and founded the "RAM Center of Excellence".In 2015, he launched the predictive maintenance activity and became PHM (Prognostics & Health Management) Director of ALSTOM Digital Mobility, and then ALSTOM Digital & Integrated Systems, St-Ouen, France. Prior to joining Alstom, he worked in the USA on the reliability of large electric power networks, as part of the Large Scale System Effectiveness Analysis Program sponsored by the US Department of Energy, from MIT and Systems Control, Inc, and later, with FABRICOM (Suez Group), on fault detection and diagnostics in industrial systems. He has contributed a number of communications and publications in scientific conferences and journals in the fields of RAMS, PHM, AI, automatic control and electric power systems (including Engineering Applications of AI, IEEE Transactions on Automatic Control, IEEE Transactions on Power Apparatus & Systems, ESREL, RAMS Symposia, French Lambda-Mu Symposia, the 2012 IEEE-PHM Conference, the 2014 European Conference of the PHM Society ( keynote speaker) and WSC 2013). He serves on the IEEE Reliability Society AdCom and the IEE Digital Reality Initiative,and chairs the IEEE Reliability Society Technical Committee on Systems of Systems. He is a contributor of four chapters in the "Handbook of RAMS in Railways: Theory & Practice" (CRC Press, Taylor & Francis),2018, including a chapter on "PHM in Railways '(Ch.6). In January 2020, he was awarded the Alan 0. Plait Award for the best tutorial at the RAMS conference, " Designing for Availability in Systems, and Systems of Systems". His main research interests focus on the confluence between RAMS and PHM, as well as complex systems resilience and asset management. |
| Subject |
Reliability (Engineering) -- Statistical methods.
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Service life (Engineering) -- Mathematical models.
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Durée de vie (Ingénierie) -- Modèles mathématiques. |
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Reliability (Engineering) -- Statistical methods |
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Service life (Engineering) -- Mathematical models |
| Other Form: |
Print version: Dersin, Pierre. Modeling remaining useful life dynamics in reliability engineering First edition. Boca Raton : CRC Press, [2023] 9781032168593 (DLC) 2022056955 |
| ISBN |
9781003250685 electronic book |
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1003250688 electronic book |
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9781000886863 electronic book |
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1000886867 electronic book |
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9781000886900 electronic book |
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1000886905 electronic book |
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hardcover |
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paperback |
| Standard No. |
10.1201/9781003250685 doi |
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