Statistical Reliability Engineering: Methods, Models and Applications

This book provides a comprehensive introduction to reliability engineering, covering various methods and models for assessing the reliability of complex systems and applications. It is based on recent research and experience and is suitable for graduate students, data scientists, reliability engineers, and researchers.

Format: Paperback / softback
Length: 497 pages
Publication date: 16 August 2022
Publisher: Springer Nature Switzerland AG

This comprehensive textbook presents the latest methodology and detailed analytical models and methods used in statistical reliability engineering to assess the reliability of complex systems and related applications. Drawing on the authors extensive research and experience spanning over 30 years in the field, the book offers a comprehensive coverage of various reliability methods and models, including:

Statistical Methods and Model Selection for Machine Learning: This chapter explores the use of statistical techniques to develop machine learning models, with a focus on reliability assessment. It discusses model selection algorithms, such as cross-validation and Bayesian inference, and their application to different machine learning tasks, such as classification and regression.

Models for Maintenance and Software Reliability: This chapter discusses the development of models for predicting the reliability of maintenance and software systems. It covers topics such as fault detection and diagnosis, reliability growth modeling, and maintenance optimization.

Statistical Reliability Estimation of Complex Systems: This chapter presents methods for estimating the reliability of complex systems, such as aircraft, power plants, and transportation networks. It discusses techniques for modeling system components, analyzing system failure data, and developing reliability models using statistical methods.

Statistical Reliability Analysis of K Out of N Systems, Standby Systems, and Repairable Systems: This chapter explores the analysis of systems consisting of multiple components or subsystems, such as k out of n systems, standby systems, and repairable systems. It discusses methods for modeling system reliability, analyzing system performance, and developing reliability management strategies.

Throughout the book, numerous examples and solved problems are provided to illustrate the application of the discussed methods and models. This comprehensive text serves as an invaluable resource for reliability engineering graduate students, providing them with a solid foundation in reliability theory and practice. It also serves as a reference for data scientists and reliability engineers, offering practical insights and techniques for reliability assessment and management. Additionally, researchers and instructors in the field will find this text a thorough guide, covering the latest developments and advancements in statistical reliability engineering.

Weight: 789g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030769062
Edition number: 1st ed. 2022