Reliability and Safety Engineering (eBook)

Ajit K. Verma is a Professor (Technical Safety), ATØM, Stord/Haugesund University College, Haugesund, Norway (since March 2012) and has been a Professor (since Feb 2001) and Senior (HAG) scale Professor (since Jan 2013) with the Department ofElectrical Engineering at IIT Bombay with a research focus in Reliability and Safety Engineering( He has been on leave from IIT Bombay since March 2012). He was the Director of the International Institute of Information Technology Pune, on lien from IIT Bombay, from Aug 2009-Sep 2010. He has supervised/co-supervised 37 PhDs(IIT Bombay and Lulea Technical University, Sweden) and 95 Masters theses(IIT Bombay; LJMU,UK; WMG,Warwick University,UK) in the area of Electronics System reliability, Software Reliability, Reliable Computing, Power Systems Reliability (PSR), Reliability Centred  Maintenance (RCM) and Probabilistic Safety/Risk Assessment (PSA) and Plant Engineering. He is the Springer Book Series Editor of Reliable & Sustainable Electric Power and Energy Systems Management and jointly edited(with Prof.Roy Billinton and Prof.Rajesh Karki) books titled 1.Reliability and Risk Evaluation of Wind Integrated Power Systems 2. Reliability Modeling and Analysis of Smart Power Systems andis also an author of books titled Fuzzy Reliability Engineering-Concepts and Applications (Narosa), Optimal Maintenance of Large Engineering initial initial; background-repeat: initial initial;">Systems(Narosa), Reliability and Safety Engineering (Springer), Dependability of Networked Computer Based Systems (Springer),Risk Management of Non-Renewable Energy Systems(Springer). He has over 250 publications in various journals (125 papers) and conferences. He is a senior member of IEEE and a life fellowof IETE. He has been the Editor-in-Chief of OPSEARCH published by Springer(Jan 2008-Jan 2011) as well as the Founder Editor-in-Chief of International Journal of Systems Assurance Engineering and Management(IJSAEM) published by Springer and an Editor-in-Chief of Journal of Life Cycle Reliability and Safety Engineering. He has been on the editorial board of international journals like Quality Assurance (Associate Editor), International Journal of Automation & Computing(Springer) (Associate Editor), Communications in Dependabilityand Quality Management, International Journal of Performability Engineering, International Journal of Reliability, Quality andSafety Engineering (World Scientific), International Journal of Quality, Statistics, andReliability (Hindawi) and on the advisory board of OPSEARCH(published by Springer) and International Journal of Swarm Intelligence(Inderscience). He has served as a Guest Editor of Special Issueof IETE Technical Review on Quality Management in Electronics, Telecommunication& Information Technology, 2001 and as a Guest Editor of Special Issue of International Journal of Reliability, Quality and Safety Engineering (World Scientific) Dec 2004, June 2006, April 2008, Dec 2009 & June 2010. He hasbeen a Guest Editor of Special Issue of DQM Communications, 2006, 2007 & 2009 and Special Issue on ‘Dependability in computing systems’ of International Journal ofPerformability Engineering, 2006. He was a Guest Editor of Special Issue on ‘Reliable Computing’ of International Journal of Automation and Computing (Oct 2007), May 2010, IJSAEM (June 2010) (with Prof Roy Billintonand Prof RajeshKarki) and IJSAEM (March 2011) ( with Prof Lotfi Zadeh and Prof Ashok Deshpande) and IEEE Transactions on Reliability, March 2011 . He is an Editor of ` Current Trends in Reliability, Availability, Maintainability and Safety- An Industry Perspective` being published by Lecture Notes in Mechanical Engineering, Springer Series.  Prof. A. Srividya is a Professor II at Stord/Haugesund University College(Aug 2014-July 2015). She was a Guest Professor from August 2012 till July 2014 at Stord/Haugesund University College, Haugesund,Norway prior to which she worked with IIT Bombay since 1988 where she is a Professor in Civil Engineering with research focus in the areas of Reliability & Safety Engineering and Quality Management. She has supervised/co-supervised 28 PhD’s and 50 Masters thesis in the area of Structural Reliability, Reliability Based Optimisation, Simulation Studies for Reliability Estimation, Quality Benchmarking Studies for Service Industries, Quality Systems and Accelerated Life Testing. She has executed various research projects to promote industry interface and has been course co-ordinator for industry CEPs like Reliability Engineering and Quality Management and Six Sigma for IT industries. She has jointly authored books titled “Fuzzy Reliability Engineering-Concepts and Applications”(Narosa) and ‘Optimal Maintenance of Large Engineering Systems’(Narosa), ‘Reliability and Safety Engineering’(Springer), ‘Dependability of Networked Computer based Systems’(Springer)and `Risk Management of Non-Renewable Energy Systems’ (Springer). She has 205 publications in various international and national journals and conferences. She has been an Area Editor of OPSEARCH journal published by Springer as well as an Editor of International Journal of Systems Assurance Engineering and Management(IJSAEM) published by Springer and Member in the Editorial Board of International journal of Communications in Dependability and Quality Management. She has been Conference Chairperson of International Conference on Reliability, Safety & Hazard 2005 (Advances in Risk Informed Technology) at Hotel the Leela, Mumbai, Dec 01-03, 2005. She was instrumental in editing and reviewing the proceedings of various International Conferences like International Conference on Quality Reliability and Control 2001, International Conference on Multimedia and Design 2002 and International Conference on Quality Reliability and Information Technology 2003 and International Conference on Reliability, Safety & Hazard 2005 and anEditor of the proceedings (Narosa). She was also the Conference Chair for International Conference on Quality, Reliability and Infocom Technology  held at INSA, New Delhi(Dec’ 2-4),2006. She was a Conference Chair of the International Conference on Reliability, Safety and Quality Engineering, held at NPCIL, Mumbai from Jan 5-7, 2008 and Editor of the proceedings (Macmillan), Conference Chair, 4th International Conference on Quality, Reliability and Infocom Technology 2009 (ICQRIT - 2009), 18 - 20 Dec 2009 New Delhi, India. She is a recipient of “Leadership in Reliability Engineering Education & Research award” by Society of Reliability Engineering, Quality & Operations Management.  Dr. Durga Rao Karanki has been working as a Scientist at Paul Scherrer Institute, Switzerland since 2009. His current research primarily focuses on dynamic risk assessment and uncertainty propagation. He is a visiting faculty at KINGS, Ulsan, South Korea and Indian Institute of Technology Kharagpur. He is on the editorial board of three international journals in the area of reliability and risk analysis. He has actively been involved in probabilistic safety assessment and risk informed decision-making research on nuclear reactors for the last 12 years. His research resulted in more than 50 publications including 2 books, 12 first author journal papers, and several conference papers. One of his works got into the list of most cited Reliability Engineering and System Safety articles (2013 and 2014). He received two awards (2009, 2012) for research Excellency from Society for Reliability Engineering, Quality and Operations Management (SREQOM), New Delhi.  Prior to joining PSI, he worked as a Scientific Officer (2002- 2009) in PSA Section of Bhabha Atomic Research Centre (Mumbai, India), where he conducted research on Dynamic Fault Tree Analysis, Uncertainty Analysis, and Risk Informed Decision Making. He was also a visiting faculty at Department of Atomic Energy (India) training schools. He holds B.Tech in Electrical and Electronics Engineering from the Nagarjuna University (India), M.Tech in Reliability Engineering from the Indian Institute of Technology (IIT) Kharagpur and Ph.D. from the IIT Bombay. 

Foreword 7
Preface 9
Acknowledgments 11
Contents 12
1 Introduction 20
1.1 Need for Reliability and Safety Engineering 20
1.2 Exploring Failures 21
1.3 Improving Reliability and Safety 22
1.4 Definitions and Explanation of Some Relevant Terms 23
1.4.1 Quality 23
1.4.2 Reliability 24
1.4.3 Maintainability 24
1.4.4 Availability 25
1.4.5 Risk and Safety 25
1.4.6 Probabilistic Risk Assessment/Probabilistic Safety Assessment 26
1.5 Resources 26
1.6 History 27
1.7 Present Challenges and Future Needs for the Practice of Reliability and Safety Engineering 31
References 34
2 Basic Reliability Mathematics 37
2.1 Classical Set Theory and Boolean Algebra 37
2.1.1 Operations on Sets 37
2.1.2 Laws of Set Theory 39
2.1.3 Boolean Algebra 39
2.2 Concepts of Probability Theory 40
2.2.1 Axioms of Probability 42
2.2.2 Calculus of Probability Theory 42
2.2.3 Random Variables and Probability Distributions 46
2.3 Reliability and Hazard Functions 49
2.4 Distributions Used in Reliability and Safety Studies 52
2.4.1 Discrete Probability Distributions 52
2.4.1.1 Binomial Distribution 52
2.4.1.2 Poisson Distribution 55
2.4.1.3 Hyper Geometric Distribution 57
2.4.1.4 Geometric Distribution 57
2.4.2 Continuous Probability Distributions 58
2.4.2.1 Exponential Distribution 58
2.4.2.2 Normal Distribution 61
2.4.2.3 Lognormal Distribution 65
2.4.2.4 Weibull Distribution 68
2.4.2.5 Gamma Distribution 71
2.4.2.6 Erlangian Distribution 72
2.4.2.7 Chi-Square Distribution 73
2.4.2.8 F-Distribution 74
2.4.2.9 t-Distribution 76
2.4.3 Summary 77
2.5 Failure Data Analysis 77
2.5.1 Nonparametric Methods 77
2.5.2 Parametric Methods 81
2.5.2.1 Identifying Candidate Distributions 82
2.5.2.2 Estimating the Parameters of Distribution 86
2.5.2.3 Goodness-of-Fit Tests 89
References 90
3 System Reliability Modeling 92
3.1 Reliability Block Diagram (RBD) 92
3.1.1 Procedure for System Reliability Prediction Using RBD 92
3.1.2 Different Types of Models 95
3.1.3 Solving RBD 104
3.1.3.1 Truth Table Method 104
3.1.3.2 Cut-Set and Tie-Set Method 106
3.1.3.3 Bounds Method 109
3.2 Markov Models 109
3.2.1 Elements of Markov Models 109
3.3 Fault Tree Analysis 121
3.3.1 Procedure for Carrying Out Fault Tree Analysis 121
3.3.2 Elements of Fault Tree 124
3.3.3 Evaluations of Fault Tree 126
3.3.4 Case Study 132
References 139
4 Reliability of Complex Systems 140
4.1 Monte Carlo Simulation 140
4.1.1 Analytical versus Simulation Approaches for System Reliability Modeling 140
4.1.2 Elements of Monte Carlo Simulation 142
4.1.3 Repairable Series and Parallel System 144
4.1.4 Simulation Procedure for Complex Systems 149
4.1.4.1 Case Study---AC Power Supply System of Indian NPP 150
4.1.5 Increasing Efficiency of Simulation 156
4.2 Dynamic Fault Tree Analysis 157
4.2.1 Dynamic Fault Tree Gates 158
4.2.2 Modular Solution for Dynamic Fault Trees 160
4.2.3 Numerical Method 161
4.2.4 Monte Carlo Simulation 164
4.2.4.1 Case Study 1---Simplified Electrical (AC) Power Supply System of NPP 168
4.2.4.2 Case Study 2---Reactor Regulation System (RRS) of NPP 173
References 175
5 Electronic System Reliability 177
5.1 Importance of Electronic Industry 177
5.2 Various Components Used and Their Failure Mechanisms 178
5.2.1 Resistors 178
5.2.2 Capacitors 178
5.2.3 Inductors 179
5.2.4 Relays 179
5.2.5 Semiconductor Devices 179
5.2.6 Microcircuits (ICs) 180
5.3 Reliability Prediction of Electronic Systems 181
5.3.1 Parts Count Method 182
5.3.2 Parts Stress Method 182
5.4 PRISM 183
5.5 Sneak Circuit Analysis (SCA) 185
5.5.1 Definition of SCA 185
5.5.2 Network Tree Production 186
5.5.3 Topological Pattern Identification 186
5.6 Case Study 187
5.6.1 Total Failure Rate 188
5.7 Physics of Failure Mechanisms of Electronic Components 190
5.7.1 Physics of Failures 190
5.7.2 Failure Mechanisms for Resistors 190
5.7.2.1 Failure Due to Excessive Heating 190
5.7.2.2 Failure Due to Metal Diffusion and Oxidation 191
5.7.3 Failure Mechanisms for Capacitor 192
5.7.3.1 Dielectric Breakdown 192
5.7.4 MOS Failure Mechanisms 192
5.7.4.1 Electro Migration (EM) 193
5.7.4.2 Time Dependent Dielectric Breakdown 193
AHI (Anode Hole Injection) 194
Thermo-Chemical Model 194
Anode Hydrogen Release (AHR) 194
5.7.4.3 Hot Carrier Injection 195
5.7.4.4 Negative Bias Temperature Instability 195
5.7.5 Field Programmable Gate Array 196
5.7.5.1 Hierarchical Model 196
5.7.5.2 Optimal Model 197
5.7.5.3 Coarse Model 197
5.7.5.4 Tile Based Model 197
References 198
6 Software Reliability 199
6.1 Introduction to Software Reliability 199
6.2 Past Incidences of Software Failures in Safety Critical Systems 200
6.3 The Need for Reliable Software 203
6.4 Difference Between Hardware Reliability and Software Reliability 204
6.5 Software Reliability Modeling 205
6.5.1 Software Reliability Growth Models 207
6.5.2 Black Box Software Reliability Models 207
6.5.3 White Box Software Reliability Models 208
6.6 How to Implement Software Reliability 208
6.7 Emerging Techniques in Software Reliability Modeling---Soft Computing Technique 215
6.7.1 Need for Soft Computing Methods 217
6.7.2 Environmental Parameters 217
6.7.3 Anil-Verma Model 224
6.8 Future Trends of Software Reliability 231
References 232
7 Mechanical Reliability 234
7.1 Reliability Versus Durability 235
7.2 Failure Modes in Mechanical Systems 236
7.2.1 Failures Due to Operating Load 237
7.2.2 Failure Due to Environment 241
7.3 Reliability Circle 241
7.3.1 Specify Reliability 243
7.3.2 Design for Reliability 246
7.3.2.1 Reliability Analysis and Prediction 248
7.3.2.2 Stress-Strength Interference Theory 256
7.3.3 Test for Reliability 260
7.3.3.1 Degradation Data Analysis 264
7.3.4 Maintain the Manufacturing Reliability 265
7.3.5 Operational Reliability 267
References 270
8 Structural Reliability 271
8.1 Deterministic versus Probabilistic Approach in Structural Engineering 271
8.2 The Basic Reliability Problem 272
8.2.1 First Order Second Moment (FOSM) Method 273
8.2.2 Advanced First Order Second Moment Method (AFOSM) 277
8.3 First Order Reliability Method (FORM) 278
8.4 Reliability Analysis for Correlated Variables 282
8.4.1 Reliability Analysis for Correlated Normal Variables 283
8.4.2 Reliability Analysis for Correlated Non-normal Variables 284
8.5 Second Order Reliability Methods (SORM) 285
8.6 System Reliability 296
8.6.1 Classification of Systems 296
8.6.1.1 Series System 296
8.6.1.2 Parallel System 297
8.6.1.3 Combined Series-Parallel Systems 298
8.6.2 Evaluation of System Reliability 298
8.6.2.1 Numerical Integration 299
8.6.2.2 Bounding Techniques 299
8.6.2.3 Approximate Methods 300
References 306
9 Maintenance of Large Engineering Systems 307
9.1 Introduction 307
9.2 Peculiarities of a Large Setup of Machinery 308
9.3 Prioritizing the Machinery for Maintenance Requirements 310
9.3.1 Hierarchical Level of Machinery 313
9.3.2 FMECA (Failure Mode Effect and Criticality Analysis) 315
9.3.2.1 FMEA 316
9.3.2.2 CA (Criticality Analysis) 319
9.3.2.3 Criticality Ranking 321
FMECA Summary 321
9.4 Maintenance Scheduling of a Large Setup of Machinery 323
9.4.1 Introduction 323
9.4.2 Example 325
9.4.3 Example---MOOP of Maintenance Interval Scheduling 328
9.4.4 Use of NSGA II---Elitist Genetic Algorithm Program 330
9.4.5 Assumptions and Result 331
9.5 Decision Regarding Maintenance Before an Operational Mission 335
9.5.1 Introduction 335
9.5.2 The Model 336
9.5.3 Assumptions 337
9.5.4 Result 343
9.6 Summary 345
References 346
10 Probabilistic Safety Assessment 347
10.1 Introduction 347
10.2 Concept of Risk and Safety 347
10.3 An Overview of Probabilistic Safety Assessment Tasks 350
10.4 Identification of Hazards and Initiating Events 353
10.4.1 Preliminary Hazard Analysis 353
10.4.2 Master Logic Diagram (MLD) 353
10.5 Event Tree Analysis 354
10.6 Importance Measures 360
10.7 Common Cause Failure Analysis 363
10.7.1 Treatment of Dependent Failures 364
10.7.2 The Procedural Framework for CCF Analysis 366
10.7.3 Treatment of Common Cause Failures in Fault Tree Models 366
10.7.4 Common Cause Failure Models 371
10.8 Human Reliability Analysis 379
10.8.1 HRA Concepts 379
10.8.2 HRA Process, Methods, and Tools 380
10.8.2.1 HRA Process 380
10.8.2.2 HRA Methods 381
References 384
11 Dynamic PSA 387
11.1 Introduction to Dynamic PSA 387
11.1.1 Need for Dynamic PSA 387
11.1.2 Dynamic Methods for Risk Assessment 388
11.2 Dynamic Event Tree Analysis 390
11.2.1 Event Tree versus Dynamic Event Tree 390
11.2.2 DET Approach---Steps Involved 390
11.2.3 DET Implementation---Comparison Among Tools 393
11.3 Example---Depleting Tank 396
11.3.1 Description on Depleting Tank Problem 396
11.3.2 Analytical Solution 397
11.3.3 Discrete DET Solution 399
11.4 DET Quantification of Risk---Practical Issues and Possible Solutions 402
11.4.1 Challenges in Direct Quantification of Risk with DET 402
11.4.2 Uncertainties and Dynamics in Risk Assessment 403
References 404
12 Applications of PSA 407
12.1 Objectives of PSA 407
12.2 PSA of Nuclear Power Plant 408
12.2.1 Description of PHWR 408
12.2.2 PSA of Indian NPP (PHWR Design) 410
12.2.2.1 Dominating Initiating Events 411
12.2.2.2 Reliability Analysis 415
12.2.2.3 Accident Sequence Identification 417
12.2.2.4 Event Trees 419
12.2.2.5 Dominating Accident Sequences 422
12.2.2.6 Risk Importance Measures 423
12.3 Technical Specification Optimization 424
12.3.1 Traditional Approaches for Technical Specification Optimization 424
12.3.1.1 Measures Applicable for AOT Evaluations 425
12.3.1.2 Measures Applicable for STI Evaluations 427
12.3.2 Advanced Techniques for Technical Specification Optimization 427
12.3.2.1 Mathematical Modeling of Problem 428
12.3.2.2 Genetic Algorithm (GA) as Optimization Method 430
12.3.2.3 Case Studies: Test Interval Optimization for Emergency Core Cooling System of PHWR 431
12.4 Risk Monitor 434
12.4.1 Necessity of Risk Monitor? 435
12.4.2 Different Modules of Risk Monitor 435
12.4.3 Applications of Risk Monitor 437
12.5 Risk Informed In-Service Inspection 439
12.5.1 RI-ISI Models 440
12.5.1.1 ASME/WOG Model 440
12.5.1.2 EPRI Model 443
12.5.1.3 Comparison of RI-ISI Models 446
12.5.2 ISI and Piping Failure Frequency 448
12.5.2.1 In-Service Inspection 448
12.5.2.2 Models for Including ISI Effect on Piping Failure Frequency 450
12.5.2.3 Case Study 457
12.5.2.4 Using Three-State Markov Model 458
12.5.2.5 Using Four-State Markov Model 461
References 468
13 Uncertainty Analysis in Reliability/Safety Assessment 470
13.1 Mathematical Models and Uncertainties 470
13.2 Uncertainty Analysis: An Important Task of PRA/PSA 472
13.3 Methods of Characterising Uncertainties 474
13.3.1 The Probabilistic Approach 474
13.3.2 Interval and Fuzzy Representation 475
13.3.3 Dempster-Shafer Theory Based Representation 476
13.4 Bayesian Approach 478
13.5 Expert Elicitation Methods 483
13.5.1 Definition and Uses of Expert Elicitation 483
13.5.2 Treatment of Expert Elicitation Process 483
13.5.3 Methods of Treatment 484
13.6 Uncertainty Propagation 487
13.6.1 Method of Moments 487
13.6.1.1 Consideration of Correlation Using Method of Moments 489
13.6.2 Monte Carlo Simulation 493
13.6.2.1 Latin Hypercube Sampling 496
13.6.3 Interval Analysis 497
13.6.4 Fuzzy Arithmetic 499
References 504
14 Advanced Methods in Uncertainty Management 505
14.1 Uncertainty Analysis with Correlated Basic Events 505
14.1.1 Dependency: Common Cause Failures versus Correlated Epistemic Parameters 506
14.1.2 Methodology for PSA Based on Monte Carlo Simulation with Nataf Transformation 508
14.1.3 Case Study 511
14.1.3.1 Case A: Effect of Correlation Alone: No CCF Modeled in Fault Tree 512
14.1.3.2 Case B: Effect of Correlation Combined with CCF Modeling 513
14.2 Uncertainty Importance Measures 518
14.2.1 Probabilistic Approach to Ranking Uncertain Parameters in System Reliability Models 519
14.2.1.1 Correlation Coefficient Method 519
14.2.1.2 Variance Based Method 520
14.2.2 Method Based on Fuzzy Set Theory 520
14.2.3 Application to a Practical System 523
14.3 Treatment of Aleatory and Epistemic Uncertainties 526
14.3.1 Epistemic and Aleatory Uncertainty in Reliability Calculations 527
14.3.2 Need to Separate Epistemic and Aleatory Uncertainties 528
14.3.3 Methodology for Uncertainty Analysis in Reliability Assessment Based on Monte Carlo Simulation 529
14.3.3.1 Methodology 530
14.4 Dempster-Shafer Theory 533
14.4.1 Belief and Plausibility Function of Real Numbers 536
14.4.2 Dempster's Rule of Combination 537
14.4.3 Sampling Technique for the Evidence Theory 538
14.5 Probability Bounds Approach 541
14.5.1 Computing with Probability Bounds 542
14.5.2 Two-Phase Monte Carlo Simulation 547
14.5.3 Uncertainty Propagation Considering Correlation Between Variables 552
14.6 Case Study to Compare Uncertainty Analysis Methods 553
14.6.1 Availability Assessment of MCPS Using Fault Tree Analysis 554
14.6.2 Uncertainty Propagation in MCPS with Different Methods 555
14.6.2.1 Interval Analysis 555
14.6.2.2 Fuzzy Arithmetic 555
14.6.2.3 Monte Carlo Simulation 557
14.6.2.4 Dempster-Shafer Theory 558
14.6.2.5 Probability Bounds Analysis 559
14.6.3 Observations from Case Study 561
References 563
Appendix 567
Index 579