Modern systems have become increasingly complex to design and build, while the demand for reliability and cost-effective enhancement continues. Robust international competition has further intensified the need for all designers, managers, practitioners, scientists, and engineers to ensure a level of reliability of their products and processes before release at the lowest cost. Developments in Reliability Engineering equips its audience with the necessary information to keep up with the latest original research and state-of-the-art advances in reliability engineering. The volume offers an excursus from historical theories and methods to the present-world practical utility of these concepts with worked-out examples.
1. 9.1: Introduction, basic terms, and definitions - p. 229 2. 9.2: Criteria, indicators, and basic settings of reliability and availability management during the lifetime of the thermal power plant - p. 233 3. 9.3: Characteristics and indicators of energy systems in the Western Balkan countries - p. 262 4. 9.4: Overview of previous research on the reliability of thermal power plants in Western Balkan countries - p. 274 5. 9.5: Theoretical considerations related to the reliability of condensation thermal power plants as component elements of electrical energy systems - p. 299 6. 9.6: Discussion and critical review of previous research on the reliability of thermal power plants in the Western Balkans area - p. 305 7. 9.7: Final considerations - p. 316 8. Chapter 10 Influence of condition diagnostics models on the reliability of industrial production systems: A critical review - p. 327 9. Chapter 11 Multistate-weighted systems and consecutive-type-weighted systems: An overview and some applications - p. 385 10. Chapter 12 Time-varying robust reliability-based design optimization - p. 397 11. Chapter 13 Reliability and availability simulation - p. 421 12. Chapter 14 Availability analysis of non-Markovian models with rejuvenation and checkpointing - p. 445 13. Chapter 15 Replacement models with fixed and random replacement times - p. 475 14. Chapter 16 Machine learning-based cure model in engineering reliability - p. 501 15. Chapter 17 An analysis of one-shot devices with multiple components - p. 523 16. Chapter 18 Reliability and availability evaluation of cloud data center infrastructure - p. 545 17. Chapter 19 Survey of software reliability assessment tools - p. 575 18. Chapter 20 On the quality of maintenance: The forgotten issue - p. 603 19. Chapter 21 G-star-shaped degrading processes: The closure property of multistate systems and the minimum property in the binary-state Weibull case - p. 639 20. Chapter 22 Life testing plan for electronic components based on design of experiments - p. 661 21. Chapter 23 Overview of the algebraic reliability of binary and multistate k-out-of-n and related systems - p. 687 22. 23.1: Introduction - p. 688 23. 23.2: Algebraic reliability of multistate systems - p. 689 24. 23.3: Algebraic reliability of k-out-of-n systems - p. 699 25. 23.3.1: Binary k-out-of-n systems - p. 699 26. 23.3.2: Simple multistate k-out-of-n systems - p. 703 27. 23.3.3: Generalized multistate k-out-of-n systems - p. 707 28. 23.3.4: Binary k-out-of-n systems with multistate components - p. 713 29. 23.3.5: Some variants of multistate k-out-of-n systems - p. 718 30. 23.4: Conclusions - p. 726 31. Chapter 24 Overview and comparison of reliability analysis techniques based on multifidelity Gaussian processes - p. 731 32. 24.1: Introduction - p. 731 33. 24.2: Active learning for reliability analysis based on Gaussian processes in the context of single-fidelity codes - p. 735 34. 24.3: Reliability analysis techniques based on active multifidelity Gaussian processes - p. 742 35. 24.4: Comparison of multifidelity reliability analysis techniques on analytical and simplified-physics application cases - p. 753 36. 24.5: Application of multifidelity reliability analysis on a strut-braced wing aerodynamic problem - p. 772 37. 24.6: Concluding remarks - p. 778 38. Appendix: Benchmark setup - p. 782 39. Chapter 25 Intelligent reliability-based design optimization: Past and future research trends - p. 787 40. Chapter 26 Gray Wolf Optimizer: A powerful, nature-inspired technique for system reliability optimization - p. 827 41. Index - p. 857
Modern systems have become increasingly complex to design and build, while the demand for reliability and cost-effective enhancement continues. Robust international competition has further intensified the need for all designers, managers, practitioners, scientists, and engineers to ensure a level of reliability of their products and processes before release at the lowest cost. Developments in Reliability Engineering equips its audience with the necessary information to keep up with the latest original research and state-of-the-art advances in reliability engineering. The volume offers an excursus from historical theories and methods to the present-world practical utility of these concepts with worked-out examples.
1. 9.1: Introduction, basic terms, and definitions - p. 229 2. 9.2: Criteria, indicators, and basic settings of reliability and availability management during the lifetime of the thermal power plant - p. 233 3. 9.3: Characteristics and indicators of energy systems in the Western Balkan countries - p. 262 4. 9.4: Overview of previous research on the reliability of thermal power plants in Western Balkan countries - p. 274 5. 9.5: Theoretical considerations related to the reliability of condensation thermal power plants as component elements of electrical energy systems - p. 299 6. 9.6: Discussion and critical review of previous research on the reliability of thermal power plants in the Western Balkans area - p. 305 7. 9.7: Final considerations - p. 316 8. Chapter 10 Influence of condition diagnostics models on the reliability of industrial production systems: A critical review - p. 327 9. Chapter 11 Multistate-weighted systems and consecutive-type-weighted systems: An overview and some applications - p. 385 10. Chapter 12 Time-varying robust reliability-based design optimization - p. 397 11. Chapter 13 Reliability and availability simulation - p. 421 12. Chapter 14 Availability analysis of non-Markovian models with rejuvenation and checkpointing - p. 445 13. Chapter 15 Replacement models with fixed and random replacement times - p. 475 14. Chapter 16 Machine learning-based cure model in engineering reliability - p. 501 15. Chapter 17 An analysis of one-shot devices with multiple components - p. 523 16. Chapter 18 Reliability and availability evaluation of cloud data center infrastructure - p. 545 17. Chapter 19 Survey of software reliability assessment tools - p. 575 18. Chapter 20 On the quality of maintenance: The forgotten issue - p. 603 19. Chapter 21 G-star-shaped degrading processes: The closure property of multistate systems and the minimum property in the binary-state Weibull case - p. 639 20. Chapter 22 Life testing plan for electronic components based on design of experiments - p. 661 21. Chapter 23 Overview of the algebraic reliability of binary and multistate k-out-of-n and related systems - p. 687 22. 23.1: Introduction - p. 688 23. 23.2: Algebraic reliability of multistate systems - p. 689 24. 23.3: Algebraic reliability of k-out-of-n systems - p. 699 25. 23.3.1: Binary k-out-of-n systems - p. 699 26. 23.3.2: Simple multistate k-out-of-n systems - p. 703 27. 23.3.3: Generalized multistate k-out-of-n systems - p. 707 28. 23.3.4: Binary k-out-of-n systems with multistate components - p. 713 29. 23.3.5: Some variants of multistate k-out-of-n systems - p. 718 30. 23.4: Conclusions - p. 726 31. Chapter 24 Overview and comparison of reliability analysis techniques based on multifidelity Gaussian processes - p. 731 32. 24.1: Introduction - p. 731 33. 24.2: Active learning for reliability analysis based on Gaussian processes in the context of single-fidelity codes - p. 735 34. 24.3: Reliability analysis techniques based on active multifidelity Gaussian processes - p. 742 35. 24.4: Comparison of multifidelity reliability analysis techniques on analytical and simplified-physics application cases - p. 753 36. 24.5: Application of multifidelity reliability analysis on a strut-braced wing aerodynamic problem - p. 772 37. 24.6: Concluding remarks - p. 778 38. Appendix: Benchmark setup - p. 782 39. Chapter 25 Intelligent reliability-based design optimization: Past and future research trends - p. 787 40. Chapter 26 Gray Wolf Optimizer: A powerful, nature-inspired technique for system reliability optimization - p. 827 41. Index - p. 857
