Preface xv Acknowledgment xxi 1 Reliability Indices of a Computer System with Priority and Server Failure 1 S.C. Malik, R.K. Yadav and N. Nandal 1.1 Introduction 2 1.2 Some Fundamentals 4 1.2.1 Reliability 4 1.2.2 Mean Time to System Failure (MTSF) 4 1.2.3 Steady State Availability 4 1.2.4 Redundancy 5 1.2.5 Semi-Markov Process 5 1.2.6 Regenerative Point Process 6 1.3 Notations and Abbreviations 6 1.4 Assumptions and State Descriptions 8 1.5 Reliability Measures 9 1.5.1 Transition Probabilities 9 1.5.2 Mst 10 1.5.3 Reliability and MTCSF 10 1.5.4 Availability 11 1.5.5 Expected Number of Hardware Repairs 12 1.5.6 Expected Number of Software Upgradations 13 1.5.7 Expected Number of Treatments Given to the Server 14 1.5.8 Busy Period of Server Due to H/w Repair 15 1.5.9 Busy Period of Server Due to Software Upgradation 16 1.6 Profit Analysis 17 1.7 Particular Case 18 1.8 Graphical Presentation of Reliability Indices 19 1.9 Real-Life Application 20 1.10 Conclusion 21 References 21 2 Mathematical Modeling and Availability Optimization of Turbine Using Genetic Algorithm 23 Monika Saini, Nivedita Gupta and Ashish Kumar 2.1 Introduction 23 2.2 System Description, Notations, and Assumptions 25 2.2.1 System Description 25 2.2.2 Notations 27 2.2.3 Assumptions 28 2.3 Mathematical Modeling of the System 28 2.4 Optimization 33 2.4.1 Genetic Algorithm 33 2.5 Results and Discussion 34 2.6 Conclusion 36 References 45 3 Development of Laplacian Artificial Bee Colony Algorithm for Effective Harmonic Estimator Design 47 Aishwarya Mehta, Jitesh Jangid, Akash Saxena, Shalini Shekhawat and Rajesh Kumar 3.1 Introduction 48 3.2 Problem Formulation of Harmonics 52 3.3 Development of Laplacian Artificial Bee Colony Algorithm 54 3.3.1 Basic Concepts of ABC 54 3.3.2 The Proposed LABC Algorithm 56 3.4 Discussion 58 3.5 Numerical Validation of Proposed Variant 58 3.5.1 Comparative Analysis of LABC with Other Meta-Heuristics 59 3.5.2 Benchmark Test on CEC-17 Functions 70 3.6 Analytical Validation of Proposed Variant 72 3.6.1 Convergence Rate Test 75 3.6.2 Box Plot Analysis 77 3.6.3 Wilcoxon Rank Sum Test 77 3.6.4 Scalability Test 81 3.7 Design Analysis of Harmonic Estimator 81 3.7.1 Assessment of Harmonic Estimator Design Problem 1 81 3.7.2 Assessment of Harmonic Estimator Design Problem 2 87 3.8 Conclusion 92 References 93 4 Applications of Cuckoo Search Algorithm in Reliability Optimization 97 V. Kaviyarasu and V. Suganthi 4.1 Introduction 98 4.2 Cuckoo Search Algorithm 98 4.2.1 Performance of Cuckoo Search Algorithm 98 4.2.2 Levy Flights 99 4.2.3 Software Reliability 99 4.3 Modified Cuckoo Search Algorithm (MCS) 100 4.4 Optimization in Module Design 102 4.5 Optimization at Dynamic Implementation 103 4.6 Comparative Study of Support of Modified Cuckoo Search Algorithm 104 4.7 Results and Discussions 105 4.8 Conclusion 107 References 108 5 Series-Parallel Computer System Performance Evaluation with Human Operator Using Gumbel-Hougaard Family Copula 109 Muhammad Salihu Isa, Ibrahim Yusuf, Uba Ahmad Ali and Wu Jinbiao 5.1 Introduction 110 5.2 Assumptions, Notations, and Description of the System 112 5.2.1 Notations 112 5.2.2 Assumptions 114 5.2.3 Description of the System 114 5.3 Reliability Formulation of Models 116 5.3.1 Solution of the Model 117 5.4 Some Particular Cases Based on Analytical Analysis of the Model 120 5.4.1 Availability Analysis 120 5.4.2 Reliability Analysis 121 5.4.3 Mean Time to Failure (MTTF) 122 5.4.4 Cost-Benefit Analysis 124 5.5 Conclusions Through Result Discussion 125 References 126 6 Applications of Artificial Intelligence in Sustainable Energy Development and Utilization 129 Aditya Kolakoti, Prasadarao Bobbili, Satyanarayana Katakam, Satish Geeri and Wasim Ghder Soliman 6.1 Energy and Environment 130 6.2 Sustainable Energy 130 6.3 Artificial Intelligence in Industry 4.0 131 6.4 Introduction to AI and its Working Mechanism 132 6.5 Biodiesel 135 6.6 Transesterification Process 136 6.7 AI in Biodiesel Applications 138 6.8 Conclusion 140 References 140 7 On New Joint Importance Measures for Multistate Reliability Systems 145 Chacko V. M. 7.1 Introduction 145 7.2 New Joint Importance Measures 147 7.2.1 Multistate Differential Joint Reliability Achievement Worth (MDJRAW) 148 7.2.2 Multistate Differential Joint Reliability Reduction Worth (MDJRRW) 150 7.2.3 Multistate Differential Joint Reliability Fussel-Vesely (MDJRFV) Measure 152 7.3 Discussion 153 7.4 Illustrative Example 154 7.5 Conclusion 157 References 157 8 Inferences for Two Inverse Rayleigh Populations Based on Joint Progressively Type-II Censored Data 159 Kapil Kumar and Anita Kumari 8.1 Introduction 159 8.2 Model Description 161 8.3 Classical Estimation 163 8.3.1 Maximum Likelihood Estimation 163 8.3.2 Asymptotic Confidence Interval 164 8.4 Bayesian Estimation 166 8.4.1 Tierney-Kadane’s Approximation 167 8.4.2 Metropolis-Hastings Algorithm 169 8.4.3 HPD Credible Interval 170 8.5 Simulation Study 170 8.6 Real-Life Application 176 8.7 Conclusions 177 References 177 9 Component Reliability Estimation Through Competing Risk Analysis of Fuzzy Lifetime Data 181 Rashmi Bundel, M. S. Panwar and Sanjeev K. Tomer 9.1 Introduction 182 9.2 Fuzzy Lifetime Data 183 9.2.1 Fuzzy Set 183 9.2.2 Fuzzy Numbers and Membership Function 184 9.2.3 Fuzzy Event and its Probability 187 9.3 Modeling with Fuzzy Lifetime Data in Presence of Competing Risks 187 9.4 Maximum Likelihood Estimation with Exponential Lifetimes 189 9.4.1 Bootstrap Confidence Interval 192 9.5 Bayes Estimation 192 9.5.1 Highest Posterior Density Confidence Estimates 194 9.6 Numerical Illustration 195 9.6.1 Simulation Study 196 9.6.2 Reliability Analysis Using Simulated Data 210 9.7 Real Data Study 212 9.8 Conclusion 212 References 215 10 Cost-Benefit Analysis of a Redundant System with Refreshment 217 M.S. Barak and Dhiraj Yadav 10.1 Introduction 218 10.2 Notations 219 10.3 Average Sojourn Times and Probabilities of Transition States 220 10.4 Mean Time to Failure of the System 223 10.5 Steady-State Availability 223 10.6 The Period in Which the Server is Busy With Inspection 224 10.7 Expected Number of Visits for Repair 227 10.8 Expected Number of Refreshments 227 10.9 Particular Case 228 10. 10 Cost-Benefit Examination 230 10.11 Discussion 230 10.12 Conclusion 233 References 233 11 Fuzzy Information Inequalities, Triangular Discrimination and Applications in Multicriteria Decision Making 235 Ram Naresh Saraswat and Sapna Gahlot 11.1 Introduction 235 11.2 New f-Divergence Measure on Fuzzy Sets 237 11.3 New Fuzzy Information Inequalities Using Fuzzy New f-Divergence Measure and Fuzzy Triangular Divergence Measure 239 11.4 Applications for Some Fuzzy f-Divergence Measures 241 11.5 Applications in MCDM 244 11.5.1 Case Study 246 11.6 Conclusion 247 References 248 12 Contribution of Refreshment Provided to the Server During His Job in the Repairable Cold Standby System 251 M.S. Barak, Ajay Kumar and Reena Garg 12.1 Introduction 252 12.2 The Assumptions and Notations Used to Solve the System 254 12.3 The Probabilities of States Transitions 256 12.4 Mean Sojourn Time 257 12.5 Mean Time to Failure of the System 257 12.6 Steady-State Availability 258 12.7 Busy Period of the Server Due to Repair of the Failed Unit 259 12.8 Busy Period of the Server Due to Refreshment 259 12.9 Estimated Visits Made by the Server 260 12.10 Particular Cases 261 12.11 Profit Analysis 262 12.12 Discussion 262 12.13 Conclusion 264 12.14 Contribution of Refreshment 265 12.15 Future Scope 265 References 265 13 Stochastic Modeling and Availability Optimization of Heat Recovery Steam Generator Using Genetic Algorithm 269 Monika Saini, Nivedita Gupta and Ashish Kumar 13.1 Introduction 270 13.2 System Description, Notations, and Assumptions 271 13.2.1 System Description 271 13.2.2 Notations 272 13.2.3 Assumptions 273 13.3 Mathematical Modeling of the System 273 13.4 Availability Optimization of Proposed Model 278 13.5 Results and Discussion 280 13.6 Conclusion 285 References 285 14 Investigation of Reliability and Maintainability of Piston Manufacturing Plant 287 Monika Saini, Deepak Sinwar and Ashish Kumar 14.1 Introduction 288 14.2 System Description and Data Collection 290 14.3 Descriptive Analysis 294 14.4 Power Law Process Model 295 14.5 Trend and Serial Correlation Analysis 300 14.6 Reliability and Maintainability Analysis 302 14.7 Conclusion 306 References 307 Index 311

The book is a comprehensive guide on how to apply computational intelligence techniques for the optimization of sustainable materials and reliability engineering. This book focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in reliability engineering, material design, and manufacturing to ensure sustainability. Computational Intelligence in Sustainable Reliability Engineering unveils applications of different models of evolutionary algorithms in the field of optimization and solves the problems to help the manufacturing industries. Some special features of this book include a comprehensive guide for utilizing computational models for reliability engineering, state-of-the-art swarm intelligence methods for solving manufacturing processes and developing sustainable materials, high-quality and innovative research contributions, and a guide for applying computational optimization on reliability and maintainability theory. The book also includes dedicated case studies of real-life applications related to industrial optimizations. Audience Researchers, industry professionals, and post-graduate students in reliability engineering, manufacturing, materials, and design.