Overview
This book introduces the reliability modelling and optimization of warm standby systems. Warm standby is an attractive redundancy technique, as it consumes less energy than hot standby and switches into the active state faster than cold standby. Since a warm standby component experiences different failure rates in the standby state and active state, the reliability evaluation is challenging and the existing works are only restricted to very special cases. By adapting the decision diagrams, this book proposes the methodology to evaluate the reliability of different types of warm standby systems and studies the reliability optimization. Compared with existing works, the proposed methods allow the system to have an arbitrary number of components and allow the failure time distribution of components to observe arbitrary distributions. From this book, the readers can not only learn how to evaluate and optimize the reliability of warm standby systems but also use the methods to study the reliability of other complex systems.
Full Product Details
Author: Rui Peng ,
Qingqing Zhai ,
Jun Yang ,
Rui Peng
Publisher: Springer Verlag, Singapore
Imprint: Springer Verlag, Singapore
Edition: 1st ed. 2021
Weight: 0.285kg
ISBN: 9789811617942
ISBN 10: 9811617945
Pages: 166
Publication Date: 03 May 2022
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Author Information
Rui PENG is a Ph.D supervisor in School of Economics & Management, Beijing University of Technology. His research interests include system reliability, maintenance and defence. He has published more than 90 SCI-indexed journal papers in renowned journals, such as IIE Transactions, IEEE Transactions on Reliability, Reliability Engineering & System Safety. He is an IEEE senior member, an editorial board member of Reliability Engineering & System Safety, a highly cited Chinese Scholar recognized by Elsevier, and selected into the Beijing Nova Program of Science & Technology. Qingqing Zhai is an Assistant Professor in School of Management, Shanghai University. His research interests include system reliability modeling and residual life estimation. He has published more than 20 journal papers in renowned journals such as Risk Analysis, European Journal of Operational Research, etc. Jun Yang is a professor in School of Reliability and System Engineering, Beihang University. His research interests include system reliability, system residual life estimation and system maintenance. He has published more than 60 journal papers and led quite a few NSFC projects.
