Design and Manufacturing Practices for Performability Engineering

Sanjay K. Chaturvedi, PhD is a professor and former head of the Subir Chowdhury School of Quality and Reliability, Indian Institute of Technology, Kharagpur (WB), India with 33 years of teaching and research experience. He’s executed several research and consultancy projects in the QRAMS domain sponsored by private and government organizations. He has published multiple journals articles and three books. His research interests include reliability modeling, analysis, and data, repairable systems, and maintenance. Heeralal Gargama, PhD is an assistant professor at the Subir Chowdhury School of Quality and Reliability, Indian Institute of Technology, Kharagpur (WB), India since 2021. He has worked in the private industry performing Reliability Availability Maintainability and Safety (RAMS) studies and implementing various projects in the railway, defense, commercial aerospace equipment, and automotive industries. His research focuses on railway RAMS, functional safety, physics of failure, and system modeling and analysis. Rajiv N. Rai, PhD is an associate professor at the Subir Chowdhury School of Quality and Reliability, Indian Institute of Technology, Kharagpur (WB), India with over 29 years of experience in the field of reliability, quality, and maintenance engineering. He has 23 years of industrial experience with the Indian Air Force, working at all levels of maintenance, repair, and overhaul of aircraft, aeroengines, and their components. His research interests include repairable systems reliability analysis, quality engineering and management, and reliability and maintenance engineering.

• Foreword xviiPreface xxiAcknowledgment xxix1 Mathematical and Physical Reality of Reliability 1Jezdimir Knezevic1.1 Introduction 21.2 Experiencing Physical Reality of Reliability 21.3 Mathematical Reality of Reliability 91.4 Studying Physical Reality of Reliability 161.5 Closing Remarks Regarding Observed Physical Reality of Reliability 291.6 Closing Questions 301.7 Personal Message from the Author 32References 32Appendix 1.1 332 Models and Solutions for Practical Reliability and Availability Assessment 37K. Trivedi and A. Bobbio2.1 Introduction 372.2 Non-State-Space Methods 412.3 State-Space-Based Methods 502.4 Multi-Level Models 542.5 Conclusions 58References 593 Reliability Prediction of Artificial Hip Joints 61E. A. Elsayed and Danlei Zhang3.1 Introduction 623.2 Archard Law Wear Modeling 643.3 Physics-Based Stochastic Wear Degradation Modeling 733.4 Effect of Hip Implant Materials, Geometry and Patient’s Characteristics on the Wear Volume 79References 914 Principles and Philosophy for an Integrated and Distributed Approach for Reliability and Extensions to Other Qualities 93Kailash [Kal] Kapur, P.E.4.1 What is Quality? 944.1.1 Principle Centered Quality 984.2 Reliability 1024.3 Other Qualities 1034.4 Advances Beyond Binary States (Success/Failure) 1084.5 From Feedback to Prognostics to Feedforward 1154.6 Prognostics and Feedforward Control 117References 1195 An Analytic Toolbox for Optimizing Condition Based Maintenance (CBM) Decisions 121Andrew K. S. Jardine5.1 Condition Monitoring: Then and Now 1225.2 Condition Monitoring: Analogy with Heart Attack 1225.3 Condition Monitoring ‘‘Classical” Approach Vs Proportional Hazards Model (PHM) 1235.4 Another Approach to Overcome these Limitations 1255.5 Early Work with the Proportional-Hazards Model (PHM) 1265.6 Estimated Hazard Rate at Failure 1275.7 EXAKT Optimal Decision – A New “Control Chart” 1285.8 Optimizing CBM Decisions: EXAKT 1305.9 Some Case Studies 1325.10 University/Industry Collaboration 1365.11 Acknowledgement to Companies Who Funded the Research Team Who Developed the CBM Optimization Software 137References 1386 Degradation Modeling with Imperfect Maintenance 139Olivier Gaudoin6.1 Introduction 1396.2 Statistical Inference for a Wiener-Based Degradation Model with Imperfect Maintenance Actions Under Different Observation Schemes 1416.3 Modeling Multivariate Degradation Processes with Time- Variant Covariates and Imperfect Maintenance Effects 1496.4 Conclusion 156References 1567 Asset Maintenance in Railway: Powered by New Technology and Driven by Sustainability 159Uday Kumar7.1 Introduction and Background 1607.2 Rams & Phm 1607.3 New Technology for Railway Maintenance 1617.4 Automation, Robotics and AI in Railway 1667.5 Some Examples of Industrial Projects 1737.6 Maintenance and Sustainability 1807.7 Challenges Associated with Application of Emerging Technologies 1827.8 Concluding Remarks 183References 1848 ISO 14001 History and Applications 185Roderick A. Munro8.1 Need for EMS – Help to Prevent Environmental Disasters 1858.2 India’s Governmental Alignments with the ISO 1868.3 Sustainability Goal 1868.4 History of ISO & Environmental Standards 1878.5 Iso 14000 1888.6 ISO Oversight Process 1898.7 ISO 14001:2015 – Structure 192Bibliography 1948.8 ISO 14001:2015 – Requirements – Shall’s 1948.9 ISO 14001:2015 – Risk & Opportunities 1958.10 ISO 14001:2015 – Aspects & Impacts 1978.11 ISO 14001:2015 – Life Cycle 1998.12 Linkage to Other ISO Management System Standards 2008.13 Potential Environmental Updates Based on Thoughts for ISO 9001:2025 202References 2039 Process Failure Mode and Effects Analysis (PFMEA) with Fuzzy ANP-MARCOS-Based Approach for Manufacturing Process Quality Assessment 209Anwesa Kar and Rajiv Nandan Rai9.1 Introduction 2109.2 Literature Review 2129.3 Methodology 2159.4 Case Study 2239.5 Results and Discussions 2439.6 Summary & Conclusion 247References 24910 Advanced Neural Networks for Estimation of All-Terminal Network Reliability 253Alex Davila-Frias and Om Prakash Yadav10.1 CNN-Based Network Reliability Estimation 25410.2 All-Terminal Estimation of Network Reliability Considering Degradation with Bayesian Methods, Monte Carlo, and Deep Neural Networks 265References 28611 Power Converter Fault Classification Using Multi-Sensor Fusion and 1D-CNN Approach 291Sanjay K. Chaturvedi, Akanksha Chaturvedi and Monalisa Sarma11.1 Introduction 29211.2 Related Work 29511.3 Proposed Fault Diagnosis Approach Based on 1D-CNN 29611.4 Results 30611.5 Conclusion 314References 31412 Assessment of System Reliability Using Quantum Computers: A Primer 317Indranil Hazra, Gabriel San Martín Silva and Enrique López Droguett12.1 Introduction 31712.2 Essentials of Quantum Computing 31912.3 Quantum Circuits for Fault Trees 32212.4 Case Study: Engine Cooling and Control System 32512.5 Summary and Conclusion 337References 33713 Safety Integrity Allocation for Railway Systems 341Heeralal Gargama and Ajeet Kumar13.1 Introduction 34213.2 Risk Assessment and Hazard Control Process 34413.3 Apportionment of Safety Integrity Requirements 34913.4 Conclusion 355References 35514 A New Approach to Economic Development: Implications for India’s Emergence as a Global Manufacturing Hub 359Hwy-Chang Moon, Wenyan Yin and Dilong Huang14.1 Introduction 36014.2 South Korea’s Remarkable Economic Development 36114.3 A New Approach to South Korea’s Economic Growth 36214.4 Implications for India’s Development of Manufacturing Sector 36414.5 Implications for India and Conclusion 371References 37415 Challenges in Applying Reliability Engineering in Product Development 377Dr. Dhananjay Kumar15.1 Introduction 37715.2 Product Lifecycle and Reliability Engineering 37815.3 Main Tasks of a Reliability Professional 38115.4 RAM&T Plan 38215.5 RAM&T Requirements 38315.6 RAM&T Prediction and Uncertainties 38515.7 Components Deratings 38615.8 Analytical Evidence for RAM&T 38715.9 Physical Evidence 38815.10 Manufacturing Reliability 38915.11 In-Life Performance Monitoring 39015.12 End of Life Declaration 39115.13 Conclusion 392References 39216 Challenges and Research Opportunities for Reliability Engineering with Evolving Industry 395Pravin Kadekodi16.1 Introduction 39516.2 Technology Trends 39716.3 Organization’s Expectation from Reliability Engineering Function 40016.4 Combine View of External and Internal Challenges 40216.5 Latest Advancements in Reliability Engineering Methods and the Opportunities for Meeting the Challenges 40316.6 Summary 406References 408Index 409