Reliability Modeling with Industry 4.0 explores the emerging theoretical and practical developments in reliability engineering in highly digitized industries, including power, computer systems, railway systems, and robotics. Drawing on leading research from around the globe, as well as the latest in industry practice, this book provides cutting edge advice on how to integrate a fully digitized industry 4.0 system for enhanced reliability and reduced maintenance cost. Technologies such as big data, artificial intelligence, and the industrial internet of things are addressed in the context of reliability engineering, providing practical advice on applications.
1. Reliability Modeling in Industry 4.0 - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page i 4. Table of Contents - p. Page iv 5. Copyright - p. Page v 6. Contributors - p. Page v 7. Editors Biography - p. Page viii 8. Preface - p. Page x 9. List of Illustrations - p. Page xi 10. List of Tables - p. Page xii 11. 1 : Reliability analysis and maintenance optimization for the cost-based component maintenance priority with Industry 4.0 - p. Page xii 12. 2 : System reliability in IoT-based data collecting systems using low-cost particulate matter sensors - p. Page 12 13. 3 : Reliability and risk analysis in critical infrastructure protection - p. Page 30 14. 4 : Applied issues of chaotic dynamics in the management of unique evolutionary systems - p. Page 42 15. 5 : Safety-critical railway systems - p. Page 80 16. 6 : Supporting digital transformation in Micro and Small Enterprise (MSE): An operational framework - p. Page 121 17. 7 : Modeling and object recognition skill transfer in industrial intelligent robots - p. Page 141 18. 8 : Systems reliability for industrial multivariate processes: A comparative approach - p. Page 181 19. 9 : Predicting vulnerability discovery processes in an operating system: Stochastic modeling approach - p. Page 206 20. 10 : Efficiency of condensing thermal power plant as a complex system—An algorithm for assessing and improving energy efficiency and reliability during operation and maintenance - p. Page 230 21. 11 : Maintenance and safety of industrial systems: Developed model for assessing the criticality of elements of technical systems - p. Page 322 22. 12 : Risk-informed decision-making: Overview and applications - p. Page 378 23. 13 : Digital Transformation of Engineering Education for Smart Education: A systematic literature review - p. Page 403 24. 14 : MSS principles and application - p. Page 432 25. 15 : On the combined m-consecutive-k-out-of-n: F and consecutive kc-out-of-n: F reliability system: Some advances - p. Page 459 26. 16 : MIRCE Science approach to real-time prediction of fleet reliability with Industry 4.0 - p. Page 471 27. 17 : Reliability assessment of an electrified regional commuter train in greater Munich area - p. Page 497 28. Index - p. Page 515
Reliability Modeling with Industry 4.0 explores the emerging theoretical and practical developments in reliability engineering in highly digitized industries, including power, computer systems, railway systems, and robotics. Drawing on leading research from around the globe, as well as the latest in industry practice, this book provides cutting edge advice on how to integrate a fully digitized industry 4.0 system for enhanced reliability and reduced maintenance cost. Technologies such as big data, artificial intelligence, and the industrial internet of things are addressed in the context of reliability engineering, providing practical advice on applications.
1. Reliability Modeling in Industry 4.0 - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page i 4. Table of Contents - p. Page iv 5. Copyright - p. Page v 6. Contributors - p. Page v 7. Editors Biography - p. Page viii 8. Preface - p. Page x 9. List of Illustrations - p. Page xi 10. List of Tables - p. Page xii 11. 1 : Reliability analysis and maintenance optimization for the cost-based component maintenance priority with Industry 4.0 - p. Page xii 12. 2 : System reliability in IoT-based data collecting systems using low-cost particulate matter sensors - p. Page 12 13. 3 : Reliability and risk analysis in critical infrastructure protection - p. Page 30 14. 4 : Applied issues of chaotic dynamics in the management of unique evolutionary systems - p. Page 42 15. 5 : Safety-critical railway systems - p. Page 80 16. 6 : Supporting digital transformation in Micro and Small Enterprise (MSE): An operational framework - p. Page 121 17. 7 : Modeling and object recognition skill transfer in industrial intelligent robots - p. Page 141 18. 8 : Systems reliability for industrial multivariate processes: A comparative approach - p. Page 181 19. 9 : Predicting vulnerability discovery processes in an operating system: Stochastic modeling approach - p. Page 206 20. 10 : Efficiency of condensing thermal power plant as a complex system—An algorithm for assessing and improving energy efficiency and reliability during operation and maintenance - p. Page 230 21. 11 : Maintenance and safety of industrial systems: Developed model for assessing the criticality of elements of technical systems - p. Page 322 22. 12 : Risk-informed decision-making: Overview and applications - p. Page 378 23. 13 : Digital Transformation of Engineering Education for Smart Education: A systematic literature review - p. Page 403 24. 14 : MSS principles and application - p. Page 432 25. 15 : On the combined m-consecutive-k-out-of-n: F and consecutive kc-out-of-n: F reliability system: Some advances - p. Page 459 26. 16 : MIRCE Science approach to real-time prediction of fleet reliability with Industry 4.0 - p. Page 471 27. 17 : Reliability assessment of an electrified regional commuter train in greater Munich area - p. Page 497 28. Index - p. Page 515
