Stochastic Models in Reliability Engineering
1st Edition
Published on 30. July 2020
Book
Hardback
464 pages
978-0-367-34585-3 (ISBN)
Description
This book is a collective work by many leading scientists, analysts, mathematicians, and engineers who have been working at the front end of reliability science and engineering. The book covers conventional and contemporary topics in reliability science, all of which have seen extended research activities in recent years.
The methods presented in this book are real-world examples that demonstrate improvements in essential reliability and availability for industrial equipment such as medical magnetic resonance imaging, power systems, traction drives for a search and rescue helicopter, and air conditioning systems.
The book presents real case studies of redundant multi-state air conditioning systems for chemical laboratories and covers assessments of reliability and fault tolerance and availability calculations. Conventional and contemporary topics in reliability engineering are discussed, including degradation, networks, dynamic reliability, resilience, and multi-state systems, all of which are relatively new topics to the field.
The book is aimed at engineers and scientists, as well as postgraduate students involved in reliability design, analysis, experiments, and applied probability and statistics.
The methods presented in this book are real-world examples that demonstrate improvements in essential reliability and availability for industrial equipment such as medical magnetic resonance imaging, power systems, traction drives for a search and rescue helicopter, and air conditioning systems.
The book presents real case studies of redundant multi-state air conditioning systems for chemical laboratories and covers assessments of reliability and fault tolerance and availability calculations. Conventional and contemporary topics in reliability engineering are discussed, including degradation, networks, dynamic reliability, resilience, and multi-state systems, all of which are relatively new topics to the field.
The book is aimed at engineers and scientists, as well as postgraduate students involved in reliability design, analysis, experiments, and applied probability and statistics.
Reviews / Votes
"This book provides a good coverage of topics in the field of stochastic modelling in reliability engineering with pointers to more in-depth material. It is noteworthy that there are future research directions provided in most of the book chapters, which is a useful feature for readers who are looking for research problems in the area of reliability engineering. Academics, engineers and practitioners who are interested in modelling and analysis of data in reliability engineering will appreciate this book for covering a wide range of topics with practical engineering applications."- International Statistical Review (2021)
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Academic and Professional
Illustrations
177 s/w Abbildungen, 81 s/w Tabellen
81 Tables, black and white; 177 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 30 mm
Weight
886 gr
ISBN-13
978-0-367-34585-3 (9780367345853)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Lirong Cui | Ilia Frenkel | Anatoly Lisnianski
Stochastic Models in Reliability Engineering
Book
10/2024
1st Edition
CRC Press
€92.30
Shipment within 15-20 days
Lirong Cui | Ilia Frenkel | Anatoly Lisnianski
Stochastic Models in Reliability Engineering
E-Book
07/2020
1st Edition
CRC Press
€82.99
Available for download
Lirong Cui | Ilia Frenkel | Anatoly Lisnianski
Stochastic Models in Reliability Engineering
E-Book
07/2020
1st Edition
CRC Press
€82.99
Available for download
Persons
Lirong Cui is a professor in the School of Management & Economics at Beijing Institute of Technology. He received his Ph.D. degree in Probability and Statistics from the University of Wales, UK, in 1994. He has worked on quality and reliability-related problems since 1986 and published more than 120 papers and technical reports. He has served as an associate editors for several journals. In 2005, he was awarded the New Century Excellent Talents in China. His recent research interests are in stochastic modeling, Hawkes processes, reliability engineering, optimization, operations research, and applications of probability and statistics in various fields.
Ilia Frenkel, PhD, Researcher in the Center for Reliability and Risk Management, SCE - Shamoon College of Engineering, Beer Sheva, Israel He has obtained M.Sc. degree in Applied Mathematics from Voronezh State University, Russia, and PhD degree in Operational Research and Computer Science from Institute of Economy, Ukrainian Academy of Science, formerly USSR. He has more then 40 years of academic experience and teaching in Universities and Institutions of Russia and Israel. From 1988 till 1991 he worked as Department Chair and Associate Professor in the Applied Mathematics Department and at Computers Department, Volgograd Civil Engineering Institute, Russia .From 2001 he wes served as Senior Lecturer of the Industrial Engineering and Management Department and from 2005 as Chair of the Center for Reliability and Risk Management, SCE-Shamoon College of Engineering, Beer Sheva, Israel. In 2018 he was retired.
He has specialized in applied statistics and reliability with application to preventive maintenance. He published two books and more than 50 scientific articles and book chapters in the fields of reliability, applied statistics and production and operation management. He is an Editor and a member of editorial board of scientific and professional journals .
Anatoly Lisnianski, PhD, Expert-engineer in the Reliability Department of The Israel Electric Corporation Ltd., Israel Anatoly Lisnianski received his M.Sc. degree in Electrical Engineering from the University of Information Technologies, Precision Mechanics and Optics, Sankt-Petersburg, Russia; and Ph.D. degree in Reliability in 1984 from Federal Scientific and Production Center ''Aurora'' in Sankt-Petersburg. From 1975 through 1989, he was a researcher at this center. Starting in 1991 he is working in the Reliability Department of the Israel Electric Corporation as an engineering expert. He is specialized in reliability assessment and optimization for complex technical systems. From 2005 he wes served as Scientific Supervisor of the Center for Reliability and Risk Management, SCE-Shamoon College of Engineering, Beer Sheva, Israel.
He is the author and co-author of more than 120 journal papers, three books, some book chapters, and inventions in the field of reliability and applied statistics. He is a senior member of IEEE and a member of Israel Statistical Association.
Ilia Frenkel, PhD, Researcher in the Center for Reliability and Risk Management, SCE - Shamoon College of Engineering, Beer Sheva, Israel He has obtained M.Sc. degree in Applied Mathematics from Voronezh State University, Russia, and PhD degree in Operational Research and Computer Science from Institute of Economy, Ukrainian Academy of Science, formerly USSR. He has more then 40 years of academic experience and teaching in Universities and Institutions of Russia and Israel. From 1988 till 1991 he worked as Department Chair and Associate Professor in the Applied Mathematics Department and at Computers Department, Volgograd Civil Engineering Institute, Russia .From 2001 he wes served as Senior Lecturer of the Industrial Engineering and Management Department and from 2005 as Chair of the Center for Reliability and Risk Management, SCE-Shamoon College of Engineering, Beer Sheva, Israel. In 2018 he was retired.
He has specialized in applied statistics and reliability with application to preventive maintenance. He published two books and more than 50 scientific articles and book chapters in the fields of reliability, applied statistics and production and operation management. He is an Editor and a member of editorial board of scientific and professional journals .
Anatoly Lisnianski, PhD, Expert-engineer in the Reliability Department of The Israel Electric Corporation Ltd., Israel Anatoly Lisnianski received his M.Sc. degree in Electrical Engineering from the University of Information Technologies, Precision Mechanics and Optics, Sankt-Petersburg, Russia; and Ph.D. degree in Reliability in 1984 from Federal Scientific and Production Center ''Aurora'' in Sankt-Petersburg. From 1975 through 1989, he was a researcher at this center. Starting in 1991 he is working in the Reliability Department of the Israel Electric Corporation as an engineering expert. He is specialized in reliability assessment and optimization for complex technical systems. From 2005 he wes served as Scientific Supervisor of the Center for Reliability and Risk Management, SCE-Shamoon College of Engineering, Beer Sheva, Israel.
He is the author and co-author of more than 120 journal papers, three books, some book chapters, and inventions in the field of reliability and applied statistics. He is a senior member of IEEE and a member of Israel Statistical Association.
Content
Reliability Analysis of A Pseudo Working Markov Repairable System.
System Reliability Assessment with Multivariate Dependence Models.
Reliability Modeling of Multi-Phased Linear Consecutively Connected Systems.
A Method for Complex Multistate Systems Reliability Analysis Based on Compression Inference Algorithm and Bayesian Network.
Reliability Analysis of Demand-Based Warm Standby System with Multi-State Common Bus.
An Upside-Down Bathtub Shaped Failure Rate Model Using DUS Transformation of Lomax Distribution.
Reliability Analysis of Multi-State Systems with Dependent Failures Based on Copula.
Modelling and Inference for Special Types of Semi-Markov Processes.
Weighted Multi-Attribute Acceptance Sampling Plans.
Reliability Assessment for Systems Suffering Common Cause Failure Based on Bayesian Networks and Proportional Hazards Model.
Early Warning Strategy of Sparse Failures for Highly Reliable Products Based on Bayesian Method.
Fault Detection and Prognostics of Aero Engine by Sensor Data Analytics.
Stochastic Modeling of Opportunistic Maintenance for Series Systems with Degrading Components.
On Censored and Truncated Data in Survival Analysis and Reliability Models.
Analysis of Node Resilience Measures for Network Systems.
Reliability Analysis of General Purpose Parts for Special Vehicles Based on Durability Testing Technology.
State of Health Prognostics of Lithium-Ion Batteries.
Life Prediction of Device Based on Material's Microstructure Evolution by Means of Computational Materials Science.
Low-Cycle Fatigue Damage Assessment of Turbine Blades Using A Substructure-Based Reliability Approach.
Phased-Mission Modeling of Physical Layer Reliability for Smart Homes.
Comparative Reliability Analysis of Different Traction Drive Topologies for A Search-and-Rescue Helicopter.
Reliability and Fault Tolerance Assessment of Different Operation Modes of Air Conditioning Systems for Chemical Laboratories.
Dependability Analysis of Ship Propulsion Systems.
Application of Markov Reward Processes to Reliability, Safety, Performance Analysis of Multi-State Systems with Internal and External Testing.
Multi-Objective Maintenance Optimization of Complex System Based on Redundant-Cost Importance.
Which Replacement Maintenance Policy is Better for Multi-State Systems: Policy T or Policy N?
Design of Multi-Stress Accelerated Life Testing Plans Based on D-Optimal Experimental Design.
An Extended Optimal Replacement Policy for a Simple Repairable Modelling.
System Reliability Assessment with Multivariate Dependence Models.
Reliability Modeling of Multi-Phased Linear Consecutively Connected Systems.
A Method for Complex Multistate Systems Reliability Analysis Based on Compression Inference Algorithm and Bayesian Network.
Reliability Analysis of Demand-Based Warm Standby System with Multi-State Common Bus.
An Upside-Down Bathtub Shaped Failure Rate Model Using DUS Transformation of Lomax Distribution.
Reliability Analysis of Multi-State Systems with Dependent Failures Based on Copula.
Modelling and Inference for Special Types of Semi-Markov Processes.
Weighted Multi-Attribute Acceptance Sampling Plans.
Reliability Assessment for Systems Suffering Common Cause Failure Based on Bayesian Networks and Proportional Hazards Model.
Early Warning Strategy of Sparse Failures for Highly Reliable Products Based on Bayesian Method.
Fault Detection and Prognostics of Aero Engine by Sensor Data Analytics.
Stochastic Modeling of Opportunistic Maintenance for Series Systems with Degrading Components.
On Censored and Truncated Data in Survival Analysis and Reliability Models.
Analysis of Node Resilience Measures for Network Systems.
Reliability Analysis of General Purpose Parts for Special Vehicles Based on Durability Testing Technology.
State of Health Prognostics of Lithium-Ion Batteries.
Life Prediction of Device Based on Material's Microstructure Evolution by Means of Computational Materials Science.
Low-Cycle Fatigue Damage Assessment of Turbine Blades Using A Substructure-Based Reliability Approach.
Phased-Mission Modeling of Physical Layer Reliability for Smart Homes.
Comparative Reliability Analysis of Different Traction Drive Topologies for A Search-and-Rescue Helicopter.
Reliability and Fault Tolerance Assessment of Different Operation Modes of Air Conditioning Systems for Chemical Laboratories.
Dependability Analysis of Ship Propulsion Systems.
Application of Markov Reward Processes to Reliability, Safety, Performance Analysis of Multi-State Systems with Internal and External Testing.
Multi-Objective Maintenance Optimization of Complex System Based on Redundant-Cost Importance.
Which Replacement Maintenance Policy is Better for Multi-State Systems: Policy T or Policy N?
Design of Multi-Stress Accelerated Life Testing Plans Based on D-Optimal Experimental Design.
An Extended Optimal Replacement Policy for a Simple Repairable Modelling.