System Reliability Theory Models, Statistical Methods, and Applications

by Rausand, Marvin; Barros, Anne; Hoyland, Arnljot

• ISBN13: 9781119373520
• ISBN10: 1119373522
• Edition: 3rd
• Format: Hardcover
• Copyright: 2020-11-03
• Publisher: Wiley

Summary

Handbook and reference for industrial statisticians and system reliability engineers 

System Reliability Theory: Models, Statistical Methods, and Applications, Third Edition presents an updated and revised look at system reliability theory, modeling, and analytical methods.  The new edition is based on feedback to the second edition from numerous students, professors, researchers, and industries around the world.  New sections and chapters are added together with new real-world industry examples, and standards and problems are revised and updated. 

System Reliability Theory covers a broad and deep array of system reliability topics, including: 

·         In depth discussion of failures and failure modes 

·         The main system reliability assessment methods 

·         Common-cause failure modeling 

·         Deterioration modeling 

·         Maintenance modeling and assessment using Python code 

·         Bayesian probability and methods 

·         Life data analysis using R 

Perfect for undergraduate and graduate students taking courses in reliability engineering, this book also serves as a reference and resource for practicing statisticians and engineers.  

Throughout, the book has a practical focus, incorporating industry feedback and real-world industry problems and examples. 

 

Author Biography

 

MARVIN RAUSAND is Professor Emeritus in the department of Mechanical and Industrial Engineering at the Norwegian University of Science and Technology (NTNU), Norway, and author of Risk Assessment: Theory, Methods, and Applications and Reliability of  Safety-Critical Systems: Theory and Applications, both published by Wiley. 

ANNE BARROS, PhD, is Professor in reliability and maintenance engineering at Ecole CentraleSupélec, University of Paris-Saclay, France. Her research focus is on degradation modeling, prognostics, condition based and predictive maintenance. She got a PHD then a professorship position at University of Technology of Troyes, France and spent five years as a full-time professor at NTNU, Norway. She is currently heading a research group and holds an industrial chair at CentraleSupélec with the ambition to provide reliability assessment and maintenance modeling methods for systems of systems; Bayesian probability and methods; life analysis using R; real world system reliability engineering 

Table of Contents

Preface ix

References xiii

1. Introduction 1

2. The study object and its functions 27

3. Failures and Faults 49

4. Qualitative system reliability analysis 73

5. Probability distributions in reliability analysis 131

6. System reliability analysis 207

7. Reliability importance metrics 281

8. Dependent failures 317

9. Maintenance and maintenance strategies 349

10. Counting processes 377

11. Markov Analysis 445

12. Preventive Maintenance 513

13. Reliablility of safety systems 569

14. Reliability data analysis 617

15. Bayesian reliability analysis 693

16. Reliability data: Sources and quality 721

A Acronyms 743

B Laplace Transforms 747

Author Index 751

Subject Index 755

 

Preface ix

 

References xiii

1. Introduction 1

2. The study object and its functions 27

3. Failures and Faults 49

4. Qualitative system reliability analysis 73

5. Probability distributions in reliability analysis 131

6. System reliability analysis 207

7. Reliability importance metrics 281

8. Dependent failures 317

9. Maintenance and maintenance strategies 349

10. Counting processes 377

11. Markov Analysis 445

12. Preventive Maintenance 513

13. Reliablility of safety systems 569

14. Reliability data analysis 617

15. Bayesian reliability analysis 693

16. Reliability data: Sources and quality 721

A Acronyms 743

B Laplace Transforms 747

Author Index 751

Subject Index 755