Computational intelligence in sustainable reliability engineering
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey ; Beverly, Massachusetts :
John Wiley & Sons, Inc
[2023]
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| Colección: | Smart and Sustainable Intelligent Systems
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009752728006719 |
Tabla de Contenidos:
- Cover
- Title Page
- Copyright Page
- Contents
- Preface
- Acknowledgment
- Chapter 1 Reliability Indices of a Computer System with Priority and Server Failure
- 1.1 Introduction
- 1.2 Some Fundamentals
- 1.2.1 Reliability
- 1.2.2 Mean Time to System Failure (MTSF)
- 1.2.3 Steady State Availability
- 1.2.4 Redundancy
- 1.2.5 Semi-Markov Process
- 1.2.6 Regenerative Point Process
- 1.3 Notations and Abbreviations
- 1.4 Assumptions and State Descriptions
- 1.5 Reliability Measures
- 1.5.1 Transition Probabilities
- 1.5.2 MST
- 1.5.3 Reliability and MTCSF
- 1.5.4 Availability
- 1.5.5 Expected Number of Hardware Repairs
- 1.5.6 Expected Number of Software Upgradations
- 1.5.7 Expected Number of Treatments Given to the Server
- 1.5.8 Busy Period of Server Due to H/w Repair
- 1.5.9 Busy Period of Server Due to Software Upgradation
- 1.6 Profit Analysis
- 1.7 Particular Case
- 1.8 Graphical Presentation of Reliability Indices
- 1.9 Real-Life Application
- 1.10 Conclusion
- References
- Chapter 2 Mathematical Modeling and Availability Optimization of Turbine Using Genetic Algorithm
- 2.1 Introduction
- 2.2 System Description, Notations, and Assumptions
- 2.2.1 System Description
- 2.2.2 Notations
- 2.2.3 Assumptions
- 2.3 Mathematical Modeling of the System
- 2.4 Optimization
- 2.4.1 Genetic Algorithm
- 2.5 Results and Discussion
- 2.6 Conclusion
- References
- Chapter 3 Development of Laplacian Artificial Bee Colony Algorithm for Effective Harmonic Estimator Design
- 3.1 Introduction
- 3.2 Problem Formulation of Harmonics
- 3.3 Development of Laplacian Artificial Bee Colony Algorithm
- 3.3.1 Basic Concepts of ABC
- 3.3.2 The Proposed LABC Algorithm
- 3.4 Discussion
- 3.5 Numerical Validation of Proposed Variant
- 3.5.1 Comparative Analysis of LABC with Other Meta-Heuristics.
- 3.5.2 Benchmark Test on CEC-17 Functions
- 3.6 Analytical Validation of Proposed Variant
- 3.6.1 Convergence Rate Test
- 3.6.2 Box Plot Analysis
- 3.6.3 Wilcoxon Rank Sum Test
- 3.6.4 Scalability Test
- 3.7 Design Analysis of Harmonic Estimator
- 3.7.1 Assessment of Harmonic Estimator Design Problem 1
- 3.7.2 Assessment of Harmonic Estimator Design Problem 2
- 3.8 Conclusion
- References
- Chapter 4 Applications of Cuckoo Search Algorithm in Reliability Optimization
- 4.1 Introduction
- 4.2 Cuckoo Search Algorithm
- 4.2.1 Performance of Cuckoo Search Algorithm
- 4.2.2 Levy Flights
- 4.2.3 Software Reliability
- 4.3 Modified Cuckoo Search Algorithm (MCS)
- 4.4 Optimization in Module Design
- 4.5 Optimization at Dynamic Implementation
- 4.6 Comparative Study of Support of Modified Cuckoo Search Algorithm
- 4.7 Results and Discussions
- 4.8 Conclusion
- References
- Chapter 5 Series-Parallel Computer System Performance Evaluation with Human Operator Using Gumbel-Hougaard Family Copula
- 5.1 Introduction
- 5.2 Assumptions, Notations, and Description of the System
- 5.2.1 Notations
- 5.2.2 Assumptions
- 5.2.3 Description of the System
- 5.3 Reliability Formulation of Models
- 5.3.1 Solution of the Model
- 5.4 Some Particular Cases Based on Analytical Analysis of the Model
- 5.4.1 Availability Analysis
- 5.4.2 Reliability Analysis
- 5.4.3 Mean Time to Failure (MTTF)
- 5.4.4 Cost-Benefit Analysis
- 5.5 Conclusions Through Result Discussion
- References
- Chapter 6 Applications of Artificial Intelligence in Sustainable Energy Development and Utilization
- 6.1 Energy and Environment
- 6.2 Sustainable Energy
- 6.3 Artificial Intelligence in Industry 4.0
- 6.4 Introduction to AI and its Working Mechanism
- 6.5 Biodiesel
- 6.6 Transesterification Process
- 6.7 AI in Biodiesel Applications
- 6.8 Conclusion.
- References
- Chapter 7 On New Joint Importance Measures for Multistate Reliability Systems
- 7.1 Introduction
- 7.2 New Joint Importance Measures
- 7.2.1 Multistate Differential Joint Reliability Achievement Worth (MDJRAW)
- 7.2.2 Multistate Differential Joint Reliability Reduction Worth (MDJRRW)
- 7.2.3 Multistate Differential Joint Reliability Fussel-Vesely (MDJRFV) Measure
- 7.3 Discussion
- 7.4 Illustrative Example
- 7.5 Conclusion
- References
- Chapter 8 Inferences for Two Inverse Rayleigh Populations Based on Joint Progressively Type-II Censored Data
- 8.1 Introduction
- 8.2 Model Description
- 8.3 Classical Estimation
- 8.3.1 Maximum Likelihood Estimation
- 8.3.2 Asymptotic Confidence Interval
- 8.4 Bayesian Estimation
- 8.4.1 Tierney-Kadane's Approximation
- 8.4.2 Metropolis-Hastings Algorithm
- 8.4.3 HPD Credible Interval
- 8.5 Simulation Study
- 8.6 Real-Life Application
- 8.7 Conclusions
- References
- Chapter 9 Component Reliability Estimation Through Competing Risk Analysis of Fuzzy Lifetime Data
- 9.1 Introduction
- 9.2 Fuzzy Lifetime Data
- 9.2.1 Fuzzy Set
- 9.2.2 Fuzzy Numbers and Membership Function
- 9.2.3 Fuzzy Event and its Probability
- 9.3 Modeling with Fuzzy Lifetime Data in Presence of Competing Risks
- 9.4 Maximum Likelihood Estimation with Exponential Lifetimes
- 9.4.1 Bootstrap Confidence Interval
- 9.5 Bayes Estimation
- 9.5.1 Highest Posterior Density Confidence Estimates
- 9.6 Numerical Illustration
- 9.6.1 Simulation Study
- 9.6.2 Reliability Analysis Using Simulated Data
- 9.7 Real Data Study
- 9.8 Conclusion
- References
- Chapter 10 Cost-Benefit Analysis of a Redundant System with Refreshment
- 10.1 Introduction
- 10.2 Notations
- 10.3 Average Sojourn Times and Probabilities of Transition States
- 10.4 Mean Time to Failure of the System
- 10.5 Steady-State Availability.
- 10.6 The Period in Which the Server is Busy With Inspection
- 10.7 Expected Number of Visits for Repair
- 10.8 Expected Number of Refreshments
- 10.9 Particular Case
- 10.10 Cost-Benefit Examination
- 10.11 Discussion
- 10.12 Conclusion
- References
- Chapter 11 Fuzzy Information Inequalities, Triangular Discrimination and Applications in Multicriteria Decision Making
- 11.1 Introduction
- 11.2 New f-Divergence Measure on Fuzzy Sets
- 11.3 New Fuzzy Information Inequalities Using Fuzzy New f-Divergence Measure and Fuzzy Triangular Divergence Measure
- 11.4 Applications for Some Fuzzy f-Divergence Measures
- 11.5 Applications in MCDM
- 11.5.1 Case Study
- 11.6 Conclusion
- References
- Chapter 12 Contribution of Refreshment Provided to the Server During His Job in the Repairable Cold Standby System
- 12.1 Introduction
- 12.2 The Assumptions and Notations Used to Solve the System
- 12.3 The Probabilities of States Transitions
- 12.4 Mean Sojourn Time
- 12.5 Mean Time to Failure of the System
- 12.6 Steady-State Availability
- 12.7 Busy Period of the Server Due to Repair of the Failed Unit
- 12.8 Busy Period of the Server Due to Refreshment
- 12.9 Estimated Visits Made by the Server
- 12.10 Particular Cases
- 12.11 Profit Analysis
- 12.12 Discussion
- 12.13 Conclusion
- 12.14 Contribution of Refreshment
- 12.15 Future Scope
- References
- Chapter 13 Stochastic Modeling and Availability Optimization of Heat Recovery Steam Generator Using Genetic Algorithm
- 13.1 Introduction
- 13.2 System Description, Notations, and Assumptions
- 13.2.1 System Description
- 13.2.2 Notations
- 13.2.3 Assumptions
- 13.3 Mathematical Modeling of the System
- 13.4 Availability Optimization of Proposed Model
- 13.5 Results and Discussion
- 13.6 Conclusion
- References.
- Chapter 14 Investigation of Reliability and Maintainability of Piston Manufacturing Plant
- 14.1 Introduction
- 14.2 System Description and Data Collection
- 14.3 Descriptive Analysis
- 14.4 Power Law Process Model
- 14.5 Trend and Serial Correlation Analysis
- 14.6 Reliability and Maintainability Analysis
- 14.7 Conclusion
- References
- Index
- EULA.
