Computational Intelligence in Sustainable Reliability Engineering

Herausgegeben:Malik, S. C.; Sinwar, Deepak; Kumar, Ashish; Gadde, S. R.; Chatterjee, Prasenjit; Hung, Bui Thanh

• Gebundenes Buch

Produktbeschreibung

COMPUTATIONAL INTELLIGENCE IN SUBSTAINABLE RELIABILITY ENGINEERING

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.

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Produktdetails

• Smart and Sustainable Intelligent Systems
• Verlag: Wiley & Sons / Wiley-Scrivener
• Artikelnr. des Verlages: 1W119865010
• 1. Auflage
• Seitenzahl: 352
• Erscheinungstermin: 28. März 2023
• Englisch
• Abmessung: 229mm x 152mm x 20mm
• Gewicht: 573g
• ISBN-13: 9781119865018
• ISBN-10: 1119865018
• Artikelnr.: 64103433

Autorenporträt

S. C. Malik, PhD, is a professor of Statistics at Maharshi Dayanand University Rohtak, India. He has published more than 170 research articles in international journals, has participated in about 80 national/international conferences and workshops, as well as authored 3 books. Deepak Sinwar, PhD, is an assistant professor in the Department of Computer and Communication Engineering, School of Computing & Information Technology at Manipal University Jaipur, Jaipur, Rajasthan, India. His research interests include computational intelligence, data mining, machine learning, reliability theory, computer networks, and pattern recognition. Ashish Kumar, PhD, is an assistant professor in the Department of Mathematics & Statistics, Manipal University Jaipur, Jaipur. He has published more than 80 research papers in various national/international journals and participated in more than 50 conferences in India and abroad. His area of interest is reliability modeling and analysis, sampling theory, reliability estimation, and data analysis. Gadde Srinivasa Rao, PhD, is a Professor of Statistics in the Department of Statistics, Dodoma University, Tanzania. He has published more than 140 articles in peer-reviewed journals and participated in more than 70 national and international conferences. His research interests include statistical inference, quality control, and reliability estimation. Prasenjit Chatterjee, PhD, is the Dean (Research and Consultancy) at MCKV Institute of Engineering, West Bengal, India. He has more than 100 research papers in various international journals and peer-reviewed conferences. He has authored and edited more than 20 books and is one of the developers of two multiple-criteria decision-making methods called Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI). Bui Thanh Hung, PhD, is the Director of the Artificial Intelligence Laboratory, Faculty of Information Technology, Ton Duc Thang University, Vietnam, and received his doctorate from Japan Advanced Institute of Science and Technology (JAIST) in 2013. He has published numerous research articles in international journals and conferences as well as 14 book chapters. His main research interests are natural language processing, machine learning, machine translation, text processing, data analytics, computer vision, and artificial intelligence.

Inhaltsangabe

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 Al