9780367563066-0367563061-Prognostics and Remaining Useful Life (RUL) Estimation

Prognostics and Remaining Useful Life (RUL) Estimation

ISBN-13: 9780367563066
ISBN-10: 0367563061
Edition: 1
Author: Peter Sandborn, Diego Galar, Kai Goebel, Uday Kumar
Publication date: 2021
Publisher: CRC Press
Format: Hardcover 490 pages
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Book details

ISBN-13: 9780367563066
ISBN-10: 0367563061
Edition: 1
Author: Peter Sandborn, Diego Galar, Kai Goebel, Uday Kumar
Publication date: 2021
Publisher: CRC Press
Format: Hardcover 490 pages

Summary

Prognostics and Remaining Useful Life (RUL) Estimation (ISBN-13: 9780367563066 and ISBN-10: 0367563061), written by authors Peter Sandborn, Diego Galar, Kai Goebel, Uday Kumar, was published by CRC Press in 2021. With an overall rating of 4.0 stars, it's a notable title among other books. You can easily purchase or rent Prognostics and Remaining Useful Life (RUL) Estimation (Hardcover) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Maintenance combines various methods, tools, and techniques in a bid to reduce maintenance costs while increasing the reliability, availability, and security of equipment. Condition-based maintenance (CBM) is one such method, and prognostics forms a key element of a CBM program based on mathematical models for predicting remaining useful life (RUL). Prognostics and Remaining Useful Life (RUL) Estimation: Predicting with Confidence compares the techniques and models used to estimate the RUL of different assets, including a review of the relevant literature on prognostic techniques and their use in the industrial field. This book describes different approaches and prognosis methods for different assets backed up by appropriate case studies.

FEATURES

  • Presents a compendium of RUL estimation methods and technologies used in predictive maintenance
  • Describes different approaches and prognosis methods for different assets
  • Includes a comprehensive compilation of methods from model-based and data-driven to hybrid
  • Discusses the benchmarking of RUL estimation methods according to accuracy and uncertainty, depending on the target application, the type of asset, and the forecast performance expected
  • Contains a toolset of methods and a way of deployment aimed at a versatile audience

This book is aimed at professionals, senior undergraduates, and graduate students in all interdisciplinary engineering streams that focus on prognosis and maintenance.

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