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Stochastic Models in Reliability Engineering de Lirong Cui

Stochastic Models in Reliability Engineering: Advanced Research in Reliability and System Assurance Engineering

Editat de Lirong Cui, Ilia Frenkel, Anatoly Lisnianski
en Limba Engleză Hardback – 30 iul 2020
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.
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Specificații

ISBN-13: 9780367345853
ISBN-10: 0367345854
Pagini: 482
Ilustrații: 177
Dimensiuni: 156 x 234 x 27 mm
Greutate: 0.8 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Advanced Research in Reliability and System Assurance Engineering

Public țintă

Professional

Cuprins

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.

Recenzii

"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)

Descriere

This book is a collective work by many leading scientists, analysts, mathematicians, and engineers who have been working on the front end of reliability science and engineering. The book covers conventional and contemporary topics in reliability science, which have seen extended research activates in the recent years.