handbook of performability engineering

Krishna B. MisraEditor

Handbook ofPerformability Engineering

4y Springer

Contents

1 Performability Engineering: An Essential Concept in the 21st Century 1Krishna B. Misra

1.1 Introduction , 11.1.1 Fast Increasing Population 11.1.2 Limited World Resources 21.1.3 The Carrying Capacity of Earth 31.1.4 Environmental Consequences 3

1.2 Technology Can Help 41.3 Sustainability Principles 51.4 Sustainable Products and Systems 51.5 Economic and Performance Aspects 71.6, Futuristic System Designs 91.7 Performability 101.8 Performability Engineering 111.9 Conclusion 12References '. 12

2 Engineering Design: A Systems Approach 13Krishna B. Misra

2.1 Introduction 132.1.1 Analytic Versus Synthetic Thinking 14

2.2 The Concept of a System 142.2.1 Definition of a System 142.2.2 Classification of Systems 15

2.3 Characterization of a System 152.3.1 System Hierarchy 162.3.2 System Elements 162.3.3 System Inputs and Outputs 16

2.4 Design Characteristics 17

xviii Contents

2.5 Engineering Design 182.5.1 Bottom-up Approach 182.5.2 Top-down Approach 182.5.3 Differences Between Two Approaches. 19

2.6 The System Design Process .T̂ TTTTT. 192.6.1 Main Steps of Design Process 202.6.2 Phases of System Design 212.6.3 Design Evaluation 222.6.4 Testing Designs 222.6.5 Final Design Documentation 23

2.7 User Interaction 232.8 Conclusions 24References 24

3 A Practitioner's View of Quality, Reliability and Safety 25PatrickD.T. O'Connor

3.1 Introduction „ 253.1.1 The Costs of Quality, Reliability and Safety 253.1.2 Achievement Costs: "Optimum Quality" 263.1.3 Statistics and Engineering 283.1.4 Process Variation 29

3.2 Reliability 303.2.1 Quantifying Reliability 31

3.3 Testing 333.4 Safety 353.5 Quality, Reliability and Safety Standards 36

3.5.1 Quality ISO9000 '. 363.5.2 Reliability 383.5.3 Safety : 38

3.6 Managing Quality, Reliability and Safety 393.6.1 Total Quality Management 393.6.2 "Six Sigma" '. 39

3.7 Conclusions 40References 40

4 Product Design Optimization 41Masataka Yoshimura

4.1 Introduction 414.2 Progressive Product Design Circumstances 424.3 Evaluative Criteria for Product Designs 43

4.3.1 Product Quality and Product Performance 434.3.2 Manufacturing Cost 444.3.3 Process Capability , 444.3.4 Reliability and Safety 444.3.5 Natural Environment and Natural Resources 444.3.6 Mental Satisfaction Level 44

4.4 Fundamentals of Product Design Optimization 44

Contents

4.5 Strategies of Advanced Product Design Optimization 464.5.1 Significance of Concurrent Optimization 484.5.2 Fundamental Strategies of Design Optimization 49

4.6 Methodologies and Procedures for Product Design Optimization 504.7 Design Optimization for Creativity and Balance in Product Ma*' acturing 544.8 Conclusions 55References :T:T---^, 55

Constructing a Product Design for the Environmental Process 57Daniel P. Fitzgerald, Jeffrey W. Herrmann, Peter A. Sandborn, Linda C. Schmidtand H. Gogoll Thornton

5.1 Introduction 575.2 A Decision-making View of Product Development Processes 58

5.2.1 Decision Production Systems 585.2.2 Improving Product Development Processes 59

5.3 Environmental Objectives 605.3.1 Practice Environmental Stewardship 605.3.2 Comply with Environmental Regulations 605.3.3 Address Customer Concerns 615.3.4 Mitigate Environmental Risks 615.3.5 Reduce Financial Liability 615.3.6 Reporting Environmental Performance 62

5.4 Product-level Environmental Metrics 625.4.1 Description of the Metrics 625.4.2 Scorecard Model 645.4.3 Guidelines and Checklist Document 64

5.5 The New DfE Process 655.5.1 Product Initiation Document 655.5.2 Conceptual Design Environmental Review 665.5.3 Detailed Design Environmental Review 665.5.4 Final Environmental Review 675.5.5 Post-launch Review 675.5.6 Feedback Loop 67

5.6 Analysis of the DfE Process 675.7 Conclusions 68References 69

Dependability Considerations in the Design of a System 71Krishna B. Misra

6.1 Introduction 716.2 Survivability 716.3 System Effectiveness 736.4 Attributes of System Effectiveness.. 74

6.4.1 Reliability and Mission Reliability... '. 746.4.2 Operational Readiness and Availability 756.4.3 Design Adequacy '. 756.4.4 Reparability 75

Contents

6.4.5 Maintainability 756.4.6 Serviceability 756.4.7 Availability 766.4.8 Intrinsic Availability 766.4.9 Elements of Time 76

6.5 Life-cycle Costs (LCC) 776.6 System Worth 7^>, 786.7 Safety 78

6.7.1 Plant Accidents 786.7.2 Design for Safety 80

References 80

Designing Engineering Systems for Sustainability 81Peter Sandborn and Jessica Myers

7.1 Introduction 817.1.1 Sustainment-dominated Systems 827.1.2 Technology Sustainment Activities 84

7.2 Sparing and Availability 847.2.1 Item-level Sparing Analysis 847.2.2 Availability .". 877.2.3 System-level Sparing Analysis 887.2.4 Warranty Analysis..... 88

7.3 Technology Obsolescence 907.3.1 Electronic Part Obsolescence 917.3.2 Managing Electronic Part Obsolescence 917.3.3 Strategic Planning - Design Refresh Planning 937.3.4 Software Obsolescence 95

7.4 Technology Insertion 967.4.1 Technological Monitoring and Forecasting 967.4.2 Value Metrics and Viability 987.4.3 Roadmapping 100

7.5 Concluding Comments 101References .-. 101

The Management of Engineering 105PatrickD.T. O'Connor

8.1 Introduction 1058.1.1 Engineering is Different 1068.1.2 Engineering in a Changing World 107

8.2 From Science to Engineering 1078.2.1 Determinism 1088.2.2 Variation ; 108

8.3 Engineering in Society : 1098.3.1 Education 1098.3.2 "Green" Engineering 1128.3.3 Safety '. ; '. 1128.3.4 Business Trends 113

Contents xxi

8.4 Conclusions 1138.4.1 In Conclusion: Is Sci^ ^Management Dead? 114

References ^ . .̂ _ ,̂.<'. 115

9 Engineering Versus Marketing: An Appraisal in a Global Economic Environment 117Hwy-Chang Moon

9.1 Introduction 1179.2 Creating Product Values with Low Cost and High Quality 118

9.2.1 "Consumer Tastes Are Becoming Homogenous" 1199.2.2 "Consumers Are Willing to Sacrifice Personal Preference in Returnfor Lower Prices" 1199.2.3 "Economies of Scale Are Significant with Standardization" 120

9.3 Strategic Implications of Global Standardization 1209.4 The Dynamic Nature of the Global Strategy 1219.5 A New Strategy for Dynamic Globalization 1239.6 Conclusions y 125References 125

10 The Performance Economy: Business Models for the Functional Service Economy 127Walter R. Stahel

10.1 Introduction : 12710.2 The Consequences of Traditional Linear Thought 12910.3 Resource-use Policies Are Industrial Policies ..; 12910.4 The Problem of Oversupply 13010.5 , The Genesis of a Sustainable Cycle 13210.6 The Factor Time - Creating Jobs at Home 13310.7 Strategic and Organizational Changes 13410.8 Obstacles, Opportunities, and Trends 13610.9 New Metrics to Measure Success in the Performance Economy 13610.10 Regionalization of the Economy 13710.11 Conclusions 138References 138

11 Cleaner Production and Industrial Ecology:A Dire Need for 21st Century Manufacturing 139Leo Baas

11.1 Introduction 13911.2 Different Levels of the Dissemination of Preventive Concepts 14111.3 Practical Experiences and Types ofEmbeddedness 142

11.3.1 Cognitive Embeddedness 14411.3.2 Cultural Embeddedness : 14511.3.3 Structural Embeddedness 14511.3.4 Political Embeddedness 14611.3.5 Spatial and Temporal Embeddedness 146

11.4 Industrial Ecology Programs in the Rotterdam Harbor Area 14711.4.1 Phase I: The Development of Environmental Management Systems 14711.4.2 Phase II: INES Project (1994-1997) 147

xxii Contents

11.4.3 Phase III: INES " .nport Project (1999-2002) 14811.4.4 Phase IV: I<~ M in the Sustainable Rijnmond Program 149

11.5 Lessons Learned orftrle Introduction and Dissemination of Cleaner Productionand Industrial Ecology 151

11.6 Conclusions and Recommendations 153References 155

12 Quality Engineering and Management 157Krishna B. Misra /

12.1 Introduction 15712.1.1 Definition 15812.1.2 Quality and Reliability 159

12.2 Quality Control : 15912.2.1 Chronological Developments 16012.2.2 Statistical Quality Control : 16112.2.3 Statistical Process Control 16112.2.4 Engineering Process Control 16212.2.5 Total Quality Control 162

12.3 Quality Planning 16212.4 Quality Assurance 16312.5 Quality Improvement 16412.6 Quality Costs 16412.7 Quality Management System 16412.8 Total Quality Management 16512.9 ISO Certification 16612.10 Six Sigma 16612.11 Product Life-cycle Management 16812.12 Other Quality Related Initiatives 168References 170

13 Quality Engineering: Control, Design and Optimization 171Qianmei Feng and Kailash C. Kapur

13.1 Introduction 17113.2 Quality and Quality Engineering 172

13.2.1 Quality 17213.2.2 Quality Engineering 172

13.3 Quality Management Strategies and Programs 17313.3.1 Principle-centred Quality Management 17413.3.2 Quality Function Deployment 17513.3.3 Six Sigma Process Improvement 17613.3.4 Design for Six Sigma (DFSS) 177

13.4 Off-line Quality Engineering 17713.4.1 Engineering Design Activities 17713.4.2 Robust Design and Quality Engineering 178

13.5 On-line Quality Engineering 18013.5.1 Acceptance Sampling and its Limitations 18013.5.2 Inspection and Decisions on Optimum Specifications 181

Contents ,. xxiii

13.5.3 Statistical Process Control 18213.5.4 Process Adjustment with Feedback Control 183


14 Statistical Process Control 187V.N.A. Naikan

14.1 Introduction 18714.2 Control Charts 187

14.2.1 Causes of Process Variation 18814.3 Control Charts for Variables 190

14.3.1 Control Charts for Mean and Range 19014.3.2 Control Charts for Mean and Standard Deviation (X, S) 19114.3.3 Control Charts for Single Units (X chart) 19114.3.4 Cumulative Sum Control Chart (CUSUM) 19214.3.5 Moving Average Control Charts 19214.3.6 EWMA Control Charts 19314.3.7 Trend Charts r. 19314.3.8 Specification Limits on Control Charts 19314.3.9 Multivariate Control Charts 193

14.4 Control Charts for Attributes 19514.4.1 Thep chart 19514.4.2 The np chart 19614.4.3 The c chart..... 19614.4.4 The u chart 19614.4.5 Control Chart for Demerits per Unit (U chart) 196

14.5 Engineering Process Control (EPC) 19814.6 Process Capability Analysis 198

14.6.1 Process Capability Indices 198References 199

15 Engineering Process Control: A Review 203V.K. ButteandL.C. Tang

15.1 Introduction 20315.1.1 Process Control in Product and Process Industries 20315.1.2 The Need for Complementing EPC-SPC 20415.1.3 Early Arguments Against Process Adjustments and Contradictions 205

15.2 Notation ] 20615.3 Stochastic Models 206

15.3.1 Time Series Modeling for Process Disturbances 20615.3.2 Stochastic Model Building 20715.3.3 ARIMA(0 1 1): Integrated Moving Average 208

15.4 Optimal Feedback Controllers.. 20915.4.1 Economic Aspects of EPC 21115.4.2 Bounded Feedback Adjustment 21215.4.3 Bounded Feedback Adjustment Short Production Runs 214

15.5 Setup Adjustment Problem 214

xxiv Contents

15.6 Run-to-run Process Control 21515.6.1 EWMA Controllers 21615.6.2 Double EWMA Controllers 21715.6.3 Run-to-run Control for Short Production Runs 21915.6.4 Related Research 219

15.7 SPC and EPC as Complementary Tools 219References 221

16 Six Sigma: Status and Trends 225U. Dinesh Kumar

16.1 Introduction 22516.2 Management by Metrics 227

16.2.1 Yield : 22716.2.2 Defects per Million Opportunities (DPMO) 22816.2.3 The Sigma Quality Level 228

16.3 Six Sigma Project Selection 22816.4 DMAIC Methodology • 229

16.4.1 DMAIC Case: Engineer Tank 23016.5 Trends in Six Sigma 231

16.5.1 Design for Six Sigma 23116.5.2 Lean Six Sigma '. 232

16.6 Conclusions 232References '. 233

17 Computer Based Robust Engineering 235Rajesh Jugulum and Jagmeet Singh

17.1 Introduction 23517.1.1 Concepts of Robust Engineering 23717.1.2 Simulation Based Experiments 238

17.2 Robust Software Testing 24117.2.1 Introduction 24117.2.2 Robust Engineering Methods for Software Testing 24217.2.3 Case Study 243

References 244

18 Integrating a Continual Improvement Process with the Product Development Process 245Vivek "Vic"Nanda

18.1 Introduction 24518.2 Define a Quality Management System 245

18.2.1 Establish Management Commitment 24518.2.2 Prepare a "Project" Plan 24618.2.3 Define the Quality Policy 24618.2.4 Establish a Process Baseline 24618.2.5 Capture Process Assets 24718.2.6 Establish a Metrics Program 24718.2.7 Define the Continual Improvement Process 247

18.3 Deploy the Quality Management System 249

Contents xxv

18.4 Continual Improvement 25018.5 Conclusions 250References 251

19 Reliability Engineering: A Perspective 253Krishna B. Misra

19.1 Introduction 25319.1.1 Definition 25319.1.2 Some Hard Facts About Reliability 25519.1.3 Strategy in Reliability Engineering 25619.1.4 Failure-related Terminology 25619.1.5 Genesis of Failures 25819.1.6 Classification of Failures 260

19.2 Problems of Concern in Reliability Engineering 26119.2.1 Reliability Is Built During the Design Phase 26219.2.2 Failure Data V 265

19.3 Reliability Prediction Methodology 26619.3.1 Standards for Reliability Prediction 26719.3.2 Prediction Procedures 27119.3.3 Reliability Prediction for Mechanical and Structural Members 273

19.4 System Reliability Evaluation 27419.4.1 Reliability Modeling 27519.4.2 Structures of Modeling 27619.4.3 Obtaining the Reliability Expression 27719.4.4 Special Gadgets and Expert Systems 278

19.5 Alternative Approaches 27919.6 Reliability Design Procedure 28019.7 Reliability Testing 28019.8 Reliability Growth 283References 284

20 Tampered Failure Rate Load-sharing Systems: Status and Perspectives 291Suprasad V. Amari, Krishna B. Misra, andHoang Pham

20.1 Introduction 29120.2 The Basics of Load-sharing Systems 293

20.2.1 The Load Pattern 29320.2.2 The Load-sharing Rule 29320.2.3 Load-Life Relationship 29320.2.4 The Effects of Load History on Life 294

20.3 Load-sharing Models 29520.3.1 Static Models 29520.3.2 Time-dependent Models 29620.3.3 Related Models : 296

20.4 System Description 29920.4.1 Load Distribution 29920.4.2 The TFR Model 30020.4.3 System Configuration 300

xxvi Contents

20.5 A>out-of-« Systems with Identical Components 30020.5.1 Exponential Distribution 30020.5.2 General Distribution 30120.5.3 Examples 302

20.6 A:-out-of-« Systems with Non-identical Components 30320.6.1 Exponential Distributions 30320.6.2 General Distributions 30420.6.3 Further Examples 304

20.7 Conclusions 305 ~References 305

21 O(kn) Algorithms for Analyzing Repairable and Non-repairable k-out-of-n:G Systems 309Suprasad V. Amari, Ming J. Zuo, and Glenn Dill

21.1 Introduction 30921.2 Background 310

21.2.1 General Assumptions 31021.2.2 Availability Measures 31021.2.3 Motivation 311

21.3 Non-repairable &-out-of-« Systems 31121.3.1 Identical Components 31221.3.2 Non-identical Components 312

21.4 Repairable &-out-of-w Systems 31421.4.1 Additional Assumptions 31421.4.2 Identical Components 31421.4.3 Non-identical Components 314

21.5 Some Special Cases 31521.5.1 MTTF 31521.5.2 MTTFF 31621.5.3 Reliability with Repair 31821.5.4 Suspended Animation 318

21.6 Conclusions and Future Work 319References 319

22 Imperfect Coverage Models: Status and Trends 321Suprasad V. Amari, Albert Myers, Antoine Rauzy, andKishor Trivedi

22.1 Introduction 32122.2 A Brief History of Solution Techniques 322

22.2.1 Early Combinatorial Approaches 32322.2.2 State-Space Models 32322.2.3 Behavioral Decomposition '. 32322.2.4 The DDP Algorithm 32322.2.5 Simple and Efficient Algorithm (SAE) 32422.2.6 Multi-fault Models 324

22.3 Fault and Error Handling Models 324,22.4 Single-fault Models 327

22.4.1 PhaseType Discrete Time Models 327- 22.4.2 General Discrete Time Models 327

Contents xxvii

22.4.3 The CAST Recovery Model 32822.4.4 CTMC Models 32822.4.5 The CARE III Basic Model 32822.4.6 The CARE III Transient Fault Model 32922.4.7 ARIES Models 32922.4.8 HARP Models 329

22.5 Multi-fault Models 33022.5.1 HARP Models 33022.5.2 Exclusive Near-coincident Models 33022.5.3 Extended Models 331

22.6 Markov Models for System Reliability 33122.7 Combinatorial Method for System Reliability with Single-fault Models 333

22.7.1 Calculation of Component-state Probabilities 33422.7.2 The DDP Algorithm 33422.7.3 SEA 33622.7.4 Some Generalizations 337

22.8 Combinatorial Method for System Reliability with Multi-fault Models 33922.8.1 k-out-of-n Systems with Identical Components 34022.8.2 k-out-of-n Systems with Non-identical Components 34022.8.3 Modular Systems 34122.8.4 General System Configurations 34222.8.5 Some Generalizations 345

22.9 Optimal System Designs 34522.10 Conclusions and Future Work 346References 346

23 Reliability of Phased-mission Systems 349Liudong Xing and Suprasad V. Amari

23.1 Introduction 34923.2 Types of Phased-mission Systems 35023.3 Analytical Modeling Techniques 351

23.3.1 Combinatorial Approaches 35123.3.2 State Space Based Approaches 35323.3.3 The Phase Modular Approach 355

23.4 BDD Based PMS Analysis 35723.4.1 Traditional Phased-mission Systems 35723.4.2 PMS with Imperfect Coverage 35823.4.3 PMS with Modular Imperfect Coverage 36223.4.4 PMS with Common-cause Failures 363


24 Reliability of Semi-Markov Systems in Discrete Time: Modeling and Estimation 369Vlad Stefan Barbu and Nikolaos Limnios

24.1 Introduction 36924.2 The Semi-Markov Setting ". 37024.3 Reliability Modeling 373

xxviii Contents

24.3.1 State Space Split 37324.3.2 Reliability 37324.3.3 Availability 37424.3.4 The Failure Rate 37424.3.5 Mean Hitting Times 374

24.4 Reliability Estimation 37524.4.1 Semi-Markov Estimation 37524.4.2 Reliability Estimation 37624.4.3 Availability Estimation 377 .24.4.4 Failure Rate Estimation 37724.4.5 Asymptotic Confidence Intervals 378

24.5 A Numerical Example 378References r. 379

25 Binary Decision Diagrams for Reliability Studies 381Antoine B. Rauzy

25.1 Introduction 38125.2 Fault Trees, Event Trees and Binary Decision Diagrams 382

25.2.1 Fault Trees and Event Trees 38225.2.2 Binary Decision Diagrams 38325.2.3 Logical Operations 38425.2.4 Variable Orderings and Complexity Issues 38425.2.5 Zero-suppressed Binary Decision Diagrams 384

25.3 Minimal Cutsets 38425.3.1 Preliminary Definitions 38425.3.2 Prime Implicants 38525.3.3 What Do Minimal Cutsets Characterize? 38725.3.4 Decomposition Theorems 38725.3.5 Cutoffs, p-BDD and Direct Computations 388

25.4 Probabilistic Assessments 38825.4.1 Probability of Top (and Intermediate) Events 38825.4.2 Importance Factors 38925.4.3 Time Dependent Analyses 391

25.5 Assessment of Large Models 39325.5.1 The MCS/ZBDD Approach 39325.5.2 Heuristics and Strategies 394


26 Field Data Analysis for Repairable Systems: Status and Industry Trends 397David Trindade and Swami Nathan

26.1 Introduction 39726.2 Dangers of MTBF 398

26.2.1 The "Failure Rate" Confusion 39926.3 Parametric Methods 40126.4 Mean Cumulative Functions 402

26.4.1 Cumulative Plots 402

Contents xxix

26.4.2 Mean Cumulative Function Versus Age 40326.4.3 Identifying Anomalous Machines 40426.4.4 Recurrence Rate Versus Age 404

26.5 Calendar Time Analysis 40526.6 Failure Cause Plots 40726.7 MCF Comparisons 408

26.7.1 Comparison by Location, Vintage or Application 40826.7.2 Handling Left Censored Data 409

26.8 MCF Extensions 41026.8.1 The Mean Cumulative Downtime Function 41026.8.2 Mean Cumulative Cost Function 411


27 Reliability Degradation of Mechanical Components and Systems 413LiyangXie, and Zheng Wang

27.1 Introduction 41327.2 Reliability Degradation Under Randomly Repeated Loading 414

27.2.1 The Conventional Component Reliability Model 41427.2.2 The Equivalent Load and Its Probability Distribution 41527.2.3 Time-dependent Reliability Model of Components 41627.2.4 The System Reliability Model 42027.2.5 The System Reliability Model Under Randomly Repeated Loads 42027.2.6 The Time-dependent System Reliability Model : 421

27.3 Residual Fatigue Life Distribution and Load Cycle-dependent Reliability Calculations 42227.3.1 Experimental Investigation of Residual Fatigue Life 42227.3.2 The Residual Life Distribution Model 42427.3.3 Fatigue Failure Probability Under Variable Loading 426


28 New Models and Measures for Reliability of Multi-state Systems 431Yung-Wen Liu, andKailash C. Kapur

28.1 Introduction 43128.2 Multi-state Reliability Models 432

28.2.1 Classification of States 43228.2.2 Model Assumptions : 433

28.3 Measures Based on the Cumulative Experience of the Customer 43528.3.1 System Deterioration According to a Markov Process 43628.3.2 System Deterioration According to a Non-homogeneous Markov Process 43728.3.3 Dynamic Customer-center Reliability Measures for Multi-state Systems 439

28.4 Application of Multi-state Models 44028.4.1 Infrastructure Applications - Multi-state Flow Network Reliability 44128.4.2 Potential Application in Healthcare: Measure of Cancer Patient's Quality of Life 441


xxx Contents

29 A Universal Generating Function in the Analysis of Multi-state Systems 447Gregory Levitin

29.1 Introduction 44729.2 The RBD Method for MSS 448

29.2.1 A Generic Model of Multi-state Systems 44829.2.2 Universal Generating Function (w-function) Technique 44929.2.3 Generalized RBD Method for Series-parallel MSS 450

29.3 Combination of Random Processes Methods and the UGF Technique 453 -29.4 Combined Markov-UGF Technique for Analysis of Safety-critical Systems 458

29.4.1 Model of System Element 45929.4.2 State Distribution of the Entire System 461


30 New Approaches for Reliability Design in Multistate Systems 465Jose Emmanuel Ramirez-Marquez

30.1 Introduction 46530.1.1 Binary RAP ; 46530.1.2 Multistate RAP 46630.1.3 Notation 46730.1.4 Acronyms 46830.1.5 Assumptions 468

30.2 General Series-parallel Reliability Computation 46830.3 Algorithm for the Solution of Series-parallel RAP 46830.4 Experimental Results 470

30.4.1 Binary System 47030.4.2 Multistate System with Binary Capacitated Components 47230.4.3 Multistate System with Multistate Components 473

References 475

31 New Approaches to System Analysis and Design: A Review 477Hong-Zhong Huang and Liping He

31.1 Introduction 47731.1.1 Definitions and Classifications of Uncertainty 47831.1.2 Theories and Measures of Uncertainty 47831.1.3 Uncertainty Encountered in Design 480

31.2 General Topics of Applications of Possibility Theory and Evidence Theory 48031.2.1 Basic of Possibility Theory and Evidence Theory 48031.2.2 Introduction to General Applications 481

31.3 Theoretical Developments in the Area of Reliability 48131.3.1 Fuzzy Reliability 48131.3.2 Imprecise Reliability 482

31.4 Computational Developments in the Reliability Area 48431.4.1 Possibility-based Design Optimization (PBDO) 48431.4.2 Evidence-based Design Optimization (EBDO) 48631.4.3 Integration of Various Approaches to Design Optimization 48731.4.4 Data Fusion Technology in Reliability Analysis 488

Contents xxxi

31.5 Performability Improvement on the Use of Possibility Theory and Evidence Theory 48931.5.1 Quality and Reliability.....1 49031.5.2 Safety and Risk 49231.5.3 Maintenance and Warranty 493

31.6 Developing Trends of Possibility and Evidence-based Methods 49431.7 Conclusions 494References 495

32 Optimal Reliability Design of a System 499Bhupesh Lad, M.S. Kulkarni, and Krishna B. Misra

32.1 Introduction 49932.2 Problem Description 50132.3 Problem Formulation 503

32.3.1 Reliability Allocation Formulations 50332.3.2 Redundancy Allocation Formulations 50432.3.3 Reliability and Redundancy Allocation Formulations 50432.3.4 Multi-objective Optimization Formulations 50532.3.5 Problem Formulations for Multi-state Systems 50532.3.6 Formulations for Repairable Systems 505

32.4 Solution Techniques '. :. 50632.4.1 Exact Methods 50732.4.2 Approximate Methods 50932.4.3 Heuristics 51032.4.4 Metaheuristics ; 51132.4.5 Hybrid Heuristics .< 51232.4.6 Multi-objective Optimization Techniques 513

32.5 Optimal Design for Repairable Systems 51332.6 Conclusion 514References 515

33 MIP: A Versatile Tool for Reliability Design of a System 521S.K Chaturvedi and Krishna B. Misra

33.1 Introduction 52133.2 Redundancy Allocation Problem 522

33.2.1 An Overview 52233.2.2 Redundancy Allocation Techniques: A Comparative Study 523

33.3 Algorithmic Steps to Solve Redundancy Allocation Problem 52433.4 Applications of MIP to Various System Design Problems 525

33.4.1 Reliability Maximization Through Active Redundancy 52533.4.2 System with Multiple Choices and Mixed Redundancies 52733.4.3 Parametric Optimization 52833.4.4 Optimal Design of Maintained Systems 52833.4.5 Computer Communication Network Design with Linear/Nonlinear Constraints

and Optimal Global Availability/Reliability 52933.4.6 Multicriteria Redundancy Optimization 530


xxxii Contents

34 Reliability Demonstration in Product Validation Testing 533Andre Kleyner

34.1 Introduction 53334.2 Engineering Specifications Associated with Product Demonstration 53334.3 Reliability Demonstration Techniques 535

34.3.1 Success Run Testing 53534.3.2 Test to Failure 53634.3.3 Chi-Squared Test Design - An Alternative Solution for Success Run Testswith Failures 538

34.4 Reducing the Cost of Reliability Demonstration 53834.4.1 Validation Cost Model 538

- 34.4.2 Extended Life Testing 53934.4.3 Other Validation Cost Reduction Techniques 540

34.5 Assumptions and Complexities of Reliability Demonstration 54134.6 Conclusions 542References ...". 542

35 Quantitative Accelerated Life Testing and Data Analysis 543Pantelis Vassiliou, Adamantios Mettas and Tarik El-Azzouzi

35.1 Introduction 54335.2 Types of Accelerated Tests 543

35.2.1 Qualitative Tests 54435.2.2 ESS and Burn-in 54435.2.3 Quantitative Accelerated Tests .<. 544

35.3 Understanding Accelerated Life Test Analysis 54535.4 Life Distribution and Life-stress Models 546

35.4.1 Overview of the Analysis Steps 54735.5 Parameter Estimation 54835.6 Stress Loading 548

35.6.1 Time-independent (Constant) Stress 54835.6.2 Time-dependent Stress 549

35.7 An Introduction to the Arrhenius Relationship 54935.7.1 Acceleration Factor 55135.7.2 Arrhenius Relationship Combined with a Life Distribution 55135.7.3 Other Single Constant Stress Models 552

35.8 An Introduction to Two-stress Models 55335.8.1 Temperature-Humidity Relationship Introduction 55335.8.2 Temperature-Non-thermal Relationship Introduction 554

35.9 Advanced Concepts 55535.9.1 Confidence Bounds 55535.9.2 Multivariable Relationship and General Log-linear Model 55535.9.3 Time-varying Stress Models 556

References 557

Contents xxxiii

36 HALT and HASS Overview: The New Quality and Reliability Paradigm 559Gregg K. Hobbs

36.1 Introduction 55936.2 The Two Forms of HALT Currently in Use 560

36.2.1 Classical HALT Stress Application Sequence 56036.2.2 Rapid HALT Stress Application Scheme 560

36.3 Why Perform HALT and HASS? 56336.4 An Historical Review of Screening 56636.5 The Phenomenon Involved and Why Things Fail 56836.6 Equipment Required 57036.7 The Bathtub Curve 57136.8 Examples of Successes of HALT 57236.9 Some General Comments on HALT and HASS 57436.10 Conclusions ..; 1 576References 577

37 Modeling Count Data in Risk and Reliability Engineering 579SethD. Guikema and Jeremy P. Coffelt

37.1 Introduction 57937.2 Classical Regression Models for Count Data 580

37.2.1 Ordinary Least Squares Regression (OLS) 58037.2.2 Generalized Linear Models (GLMs) 58137.2.3 Generalized Linear Mixed Models (GLMMs) 58237.2.4 Zero-inflated Models <-. 58237.2.5 Generalized Additive Models (GAMs) 58337.2.6 Multivariate Adaptive Regression Splines (MARS) 58337.2.7 Model Fit Criteria 58437.2.8 Example: Classical Regression for Power System Reliability 584

37.3 Bayesian Models for Count Data 58637.3.1 Formulation of Priors 58737.3.2 Bayesian Generalized Models 591


38 Fault Tree Analysis 595Liudong Xing and Suprasad V. Amari

38.1 Introduction 59538.2 A Comparison with Other Methods 596

38.2.1 Fault Tree Versus RBD 59638.3 Fault Tree Construction..... 597

38.3.1 Important Definitions 59738.3.2 Elements of Fault Trees 59738.3.3 Construction Guidelines 59738.3.4 Common Errors in Construction 598

38.4 Different Forms 59838.4.1 Static Fault Trees 59838.4.2 Dynamic Fault Trees 598

xxxiv Contents

38.4.3 Noncoherent Fault Trees 60038.5 Types of Fault Trees Analysis 601

38.5.1 Qualitative Analysis 60138.5.2 Quantitative Analysis 602

38.6 Static FTA Techniques 60238.6.1 Cutset Based Solutions 60238.6.2 Binary Decision Diagrams 603

38.7 Dynamic FTA Techniques 60738.7.1 Markov Chains 607~38.7.2 The Modular Approach 608

38.8 Noncoherent FTA Techniques 60838.8.1 Prime Implicants 60838.8.2 Importance Measures 60938.8.3 Failure Frequency 610

38.9 Advanced Topics 61138.9.1 Component Importance Analysis 61138.9.2 Common Cause Failures 61238.9.3 Dependent Failure 61338.9.4 Disjoint Events 61438.9.5 Multistate Systems 61538.9.6 Phased-mission Systems 616

38.10 FTA Software Tools 617References 617

39 Common Cause Failure Modeling: Status and Trends 621Per Hokstad and Marvin Rausand

39.1 Introduction 62139.1.1 Common Cause Failures 62239.1.2 Explanation 622

39.2 Causes of CCF 62339.2.1 Root Causes 62339.2.2 Coupling Factors 62439.2.3 The Beta-factor Model and its Generalizations 62639.2.4 Plant Specific Beta-factors 62739.2.5 Multiplicity of Failures 62939.2.6 The Binomial Failure Rate Model and Its Extensions 63039.2.7 The Multiple Greek Letter Model 63139.2.8 The Multiple Beta-factor Model 631

39.3 Data Collection and Analysis 63439.3.1 Some Data Sources 63439.3.2 Parameter Estimation 63539.3.3 Impact Vector and Mapping of Data 636

39.4 Concluding Remarks and Ideas for Further Research 637References 638

Contents xxxv

40 A Methodology for Promoting Reliable Human-System Interaction 641Joseph Sharit

40.1 Introduction 64140.2 Methodology 644

40.2.1 Task Analysis 64440.2.2 Checklist for Identifying Relevant Human Failure Modes 64540.2.3 Human Failure Modes and Effects Analysis (HFMEA) 64840.2.4 Human-failure HAZOP 64840.2.5 Identifying Consequences and Assessing Their Criticality and Likelihood 64940.2.6 Explanations of Human Failures 65040.2.7 Addressing Dependencies 65140.2.8 What-If Analysis 65140.2.9 Design Interventions and Barriers 651

40.3 Summary 652References 665

41 Risk Analysis and Management: An Introduction 667Krishna B. Misra

41.1 Introduction 66741.1.1 Preliminary Definitions 66741.1.2 Technological Progress and Risk 66841.1.3 Risk Perception 67141.1.4 Risk Communication 672

41.2 Quantitative Risk Assessment 67241.3 Probabilistic Risk Assessment 676

41.3.1 Possibilistic Approach to Risk Assessment 67741.4 Risk Management 67741.5 Risk Governance 678References 678

42 Accidents Analysis of Complex Systems Based on System Control for Safety 683Takehisa Kohda

42.1 Introduction 68342.2 Accident Cause Analysis Based on a Safety Control 684

42.2.1 Safety from System Control Viewpoint 68442.2.2 Accident Analysis Procedure 68642.2.3 Illustrative Example 686

42.3 Accident Occurrence Condition Based on Control Functions for Safety 68942.3.1 General Accident Occurrence Conditions 68942.3.2 Occurrence of Disturbances 69042.3.3 Safety Control Function Failure 69042.3.4 Collision Accident Example 691


xxxvi Contents

43 Probabilistic Risk Assessment 699Mohammad Modarres

43.1 Introduction 69943.1.1 Strength of PRA 699

43.2 Steps in Conducting a Probabilistic Risk Assessment 70043.2.1 Objectives and Methodology 70143.2.2 Familiarization and Information Assembly 70143.2.3 Identification of Initiating Events 70143.2.4 Sequences or Scenario Development 70343.2.5 Logic Modeling 70443.2.6 Failure Data Collection, Analysis and Performance Assessment 70443.2.7 Quantification and Integration 70643.2.8 Uncertainty Analysis 70743.2.9 Sensitivity Analysis 70843.2.10 Risk Ranking and Importance Analysis 70843.2.11 Interpretation of Results 709

43.3 Compressed Natural Gas (CNG) Powered Buses: A PRA Case Study 71043.3.1 Primary CNG Fire Hazards 71043.3.2 The Probabilistic Risk Assessment Approach 71043.3.3 System Description 71143.3.4 Gas Release Scenarios 71243.3.5 Fire Scenario Description 71243.3.6 Consequence Determination 71343.3.7 Fire Location 71443.3.8 Risk Value Determination 71443.3.9 Summary of PRA Results 71443.3.10 Overall Risk Results 71443.3.11 Uncertainty Analysis 71543.3.12 Sensitivity and Importance Analysis 71643.3.13 Case Study Conclusions 717

References 717

44 Risk Management 719Terje Aven

44.1 Introduction 71944.1.1 The Basis of Risk Management 72044.1.2 Perspectives on Risk 72244.1.3 Risk Analysis to Support Decisions 72544.1.4 Challenges 725

44.2 Risk Management Principles 72644.2.1 Economic and Decision Analysis Principles 72644.2.2 The Cautionary and Precautionary Principles 72944.2.3 Risk Acceptance and Decision Making 733

44.3 Recommendations 73644.3.1 Research Challenges 739

References 740

Contents xxxvii

45 Risk Governance: An Application of Analytical-deliberative Policy Making 743Ortwin Renn

45.1 Introduction 74345.2 Main Features of the IRGC Framework 74345.3 The Core of the Framework: Risk Governance Phases 74545.4 Stakeholder Involvement and Participation 74945.5 Wider Governance Issues: Organizational Capacity and Regulatory Styles 75045.6 Conclusions 753Reference 754

46 Maintenance Engineering and Maintainability: An Introduction 755Krishna B. Misra

46.1 Introduction 75546.1.1 Maintenance System 75546.1.2 Maintenance Philosophy 75646.1.3 Maintenance Scope Changed with Time 757

46.2 Approaches to Maintenance 75946.2.1 Preventive Maintenance 75946.2.2 Predictive Maintenance 76246.2.3 Failure-finding Maintenance 76546.2.4 Corrective Maintenance 765

46.3 Reliability Centered Maintenance 76846.4 Total Productive Maintenance 76946.5 Computerized Maintenance Management System 771References 772

47 System Maintenance: Trends in Management and Technology 773Uday Kumar

47.1 Introduction 77347.2 Why Does a Component or a System Fail and What Is the Role of Maintenance? 77447.3 Trends in Management of the Maintenance Process 77547.4 TPM Implementation 77547.5 Application of Risk-based Decision Making in Maintenance 77647.6 Outsourcing of Maintenance and Purchasing of the Required Functions 777

47.6.1 Contracting-out of the Maintenance Tasks 77847.6.2 Outsourcing 77847.6.3 Purchasing the Required Function: The Concept of Functional Products 78047.6.4 Maintenance Performance Measurement 780

47.7 Trends in Maintenance Technology and Engineering 78147.7.1 Design out and Design for Maintenance 78147.7.2 Reliability 78147.7.3 Maintainability 781

47.8 Condition Monitoring and Condition-based Maintenance Strategy 78347.8.1 Sensor to Sensor (S2S) 78347.8.2 Sensor to Business (S2B) 783

xxxviii Contents

47.9 ICT Application in Maintenance: e-Maintenance 24-7 78447.9.1 e-Maintenance Framework 785


48 Maintenance Models and Optimization 789Lirong Cui

48.1 Introduction 78948.2 Previous Contributions 79148.3 Maintenance Models 79348.4 Maintenance Policies 79648.5 Maintenance Optimization and Techniques 79948.6 Maintenance Miscellanea 80048.7 Future Developments 802References 803

49 Replacement and Preventive Maintenance Models 807Toshio Nakagawa

49.1 Introduction 80749.2 Replacement Models 808

49.2.1 Simple Replacement Models 80849.2.2 Standard Replacement 80949.2.3 Replacement for a Finite Interval 81049.2.4 The Random Replacement Interval 81049.2.5 Inspection with Replacement 81249.2.6 The Cumulative Damage Model 81349.2.7 The Parallel Redundant System 814

49.3 Preventive Maintenance Models 81549.3.1 The Parallel Redundant System 815

. 49.3.2 The Two-unit System 81649.3.3 The Modified Discrete Policy 81649.3.4 Periodic and Sequential Policies 81749.3.5 Imperfect Policies 818

49.4 Computer Systems 819, 49.4.1 Intermittent Faults 820

49.4.2 Imperfect Maintenance 82049.4.3 Optimum Restart 821

References 822

50 Effective Fault Detection and CBM Based on Oil Data Modeling and DPCA 825Viliam Makis and Jianmou Wu

50.1 Introduction 82550.2 Fault Detection Using MSPC,VAR Modeling and DPCA 827

50.2.1 Hotelling's T2 Chart and PCA-based (TJ,Q) Charts 827

50.2.2 The Oil Data and the Selection of the In-control Portion 82850.2.3 Multivariate Time Series Modeling of the Oil Data in the Healthy State 829

Contents xxxix

50.2.4 Dynamic PCA and the DPCA-based (7^ ,0 , ) Charts for the Oil Data 830

50.2.5 Performance Comparison of Fault Detection and Maintenance Cost 83250.3 CBM Cost Modeling and Failure Prevention 834

50.3.1 The Proportional Hazards Model and the CBM Software EXAKT 83450.3.2 Multivariate Time Series Modeling of the Oil Data 83550.3.3 Application of DCPA to the Oil Data 83650.3.4 CBM Model Building Using DPCA Covariates 83750.3.5 Failure Prevention Performance and the Maintenance Cost Comparison 838


51 Sustainability: Motivation and Pathways for Implementation 843Krishna B. Misra

51.1 Introduction 84351.2 Environmental Risk Assessment 844

51.2.1 Hazard Identification 84451.2.2 Dose-response Assessment 84451.2.3 Exposure Assessment 84551.2.4 Risk Characterization 845

51.3 Ecological Risk Assessment 84551.4 Sustainability 846

51.4.1 Definition 84751.4.2 The Social Dimension to Sustainability 84751.4.3 Sustainability Assessment 84851.4.4 Metrics of Sustainability 84851.4.5 The Economics of Sustainability 85051.4.6 Resistance to Sustainability 851

51.5 Pathways to Sustainability 85251.6 Sustainable Future Technologies 853

51.6.1 Nanotechnology 85351.6.2 Biotechnology 854

References 855

52 Corporate Sustainability: Some Challenges for Implementingand Teaching Organizational Risk Management in a Performability Context 857RodS. Barratt

52.1 Introduction 85752.2 Pressure for Change 85752.3 Internal Control , 86152.4 Risk Assessment and Management 86252.5 Stakeholder Involvement 864

52.5.1 Perceptions of Risk 86552.5.2 Stakeholder Dialog 866

52.6 Meeting Some Educational Challenges 87152.7 Conclusion 874References 874

xl Contents

53 Towards Sustainable Operations Management 875Alison Bettley and Stephen Burnley

53.1 Introduction 87553.2 Sustainability 87653.3 Operations as a System to Deliver Stakeholder Value 87953.4 Integration of Operations and Sustainability Management 883

53.4.1 Operations Strategy 88453.4.2 Operations Design 88953.4.3 Planning and Control 89453.4.4 Improvement 896

53.6 Implications for Operations Management 89853.7 Conclusions 899References 900

54 Indicators for Assessing Sustainability Performance 905P. Zhou and B.W. Ang

54.1 Introduction 90554.2 Non-composite Indicators for Sustainability 90754.3 Composite Indicators for Sustainability 90754.4 Recent Methodological Developments in Constructing CSIs 909

54.4.1 MCDA Methods for Constructing CSIs 90954.4.2 Data Envelopment Analysis Models for Constructing CSIs 91154.4.3 An MCDA-DEA Approach to Constructing CSIs 912

54.5 An Illustrative Example 91454.6 Conclusion 916References 916

55 Sustainable Technology 919Ronald Wennersten

55.1 Introduction 91955.2 What Is Technology for? 92055.3 The Linear Production System 92155.4 Is Globalization a Solution? 921

i 55.5 Technology Lock-in 922y 55.6 From Techno-centric Concerns to Socio-centric Concern 923

55.6.1 Changing the Focus 92355.6.2 Towards a More Holistic View 924

55.7 Technology and Culture 92555.8 Technology and Risk 92655.9 Innovation and Funding of R&D 92755.10 Engineering Education for Sustainable Development 928

/ 55.11 Industrial Ecology-The Science of Sustainability 930/ 55.12 Conclusions 931

References 931

Contents xli

56 Biotechnology: Molecular Design in a Globalizing World 933M.C.E. vanDam-Mieras

56.1 Introduction 93356.2 What is Biotechnology? 93356.3 The Importance of (Bio)Molecular Sciences 934

56.3.1 The "Omics" Research Domains 93456.3.2 Techniques for Analysis and Separation of (Bio)Molecules 93556.3.3 Bio-informatics 93556.3.4 Biotechnology and Nanotechnology 935

56.4 Application of Biotechnology in Different Sectors of the Economy 93556.4.1 Biotechnology and Healthcare 93656.4.2 Biotechnology and Agriculture 93656.4.3 Biotechnology and the Food Industry 93656.4.4 Biotechnology and Industrial Production 937

56.5 Biotechnology and Sustainable Development 93756.5.1 Sustainable Development and Globalization 93756.5.2 Sustainable Development, Policy, and Responsibility 938

56.6 Innovations, Civil Society, and Global Space 93956.6.1 Biotechnology and Governmental Policy 939

56.7 Biotechnology, Agriculture, and Regulations 94056.8 Conclusions 941References 941

57 Nanotechnology: A New Technological Revolution in the 21st Century 943Ronald Wennersten, Jan Fidler and Spitsyna Anna

57.1 Introduction 94357.2 Top-down and Bottom-up Designs 94557.3 Applications of Nanotechnology 94657.4 Applications in the Energy Sector 94657.5 Environmental Applications 94757.6 Other Areas of Applications 94857.7 Market Prospects 94957.8 Nanotechnology for Sustainability 95057.9 Risks to the Environment and Human Health 95157.10 Conclusions 952References 952

58 An Overview of Reliability and Failure Modes Analysis of MicroelectromechanicalSystems (MEMs) 953Zhibin Jiang and Yuanbo Li

58.1 Introduction 95358.2 MEMS and Reliability 95358.3 MEMS Failure Modes and Mechanisms Analysis 954

58.3.1 Stiction 95558.3.2 Wear 95658.3.3 Fracture 95758.3.4 Crystallographic Defects 958

xlii Contents

58.3.5 Creep 95858.3.6 Degradation of Dielectrics 95958.3.7 Environmentally Induced Failure 95958.3.8 Electric-related Failures 96058.3.9 Packaging Reliability 96158.3.10 Other Failure Mechanisms 961

58.4 Conclusions 962References 962_

59 Amorphous Hydrogenated Carbon Nanofilm 967Dechun Ba and Zeng Lin

59.1 Introduction 96759.2 Deposition Methods 968

59.2.1 Ion Beams 96859.2.2 Sputtering 96859.2.3 PECVD 969

59.3 Deposition Mechanism of a-C:H 97059.4 Bulk Properties of a-C:H 97159.5 Electronic Applications 97259.6 Mechanical and Other Properties 973

59.6.1 Elastic Properties 97359.6.2 Hardness 97359.6.3 Adhesion 97459.6.4 Friction 97459.6.5 Wear 97559.6.6 Surface Properties 97559.6.7 Biocompatible Coatings 97559.6.8 Coatings of Magnetic Hard Disks 97559.6.9 Surface Property Modification of Steel 975

References 979

60 Applications of Performability Engineering Concepts 985Krishna B. Misra

60.1 Introduction 98560.2 Areas of Applications 985

60.2.1 Healthcare Sector 98560.2.2 Structural Engineering 98660.2.3 Communications 98660.2.4 Computing Systems 98760.2.5 Fault Tolerant Systems 98760.2.6 Prognostics and Health Monitoring 98860.2.7 Maintenance of Infrastructures 98960.2.8 Restructured Power Systems 99060.2.9 PRA for Nuclear Power Plants 99160.2.10 Problems in Software Engineering 99360.2.11 Concluding Comments 994

References 994

Contents xliii

61 Reliability in the Medical Device Industry 997Vaishali Hegde

61.1 Introduction 99761.2 Government (FDA) Control 99961.3 Medical Device Classification 99961.4 Reliability Programs 1000

61.4.1 The Concept Phase 100061.4.2 The Design Phase 100161.4.3 The Prototype Phase .'. 100361.4.4 The Manufacturing Phase 1004

61.5 Reliability Testing 100561.5.1 The Development/Growth Test 100561.5.2 The Qualification Test 100561.5.3 The Acceptance Test 100561.5.4 The Performance Test 100561.5.5 Screening 100661.5.6 Sequential Testing 1006

61.6 MTBF Calculation Methods in Reliability Testing 100661.6.1 Time Terminated, Failed Items Replaced 100661.6.2 Time Terminated, Failed Items Not Replaced 100661.6.3 Failure Terminated, Failed Items Replaced 100761.6.4 Failure Terminated, Failed Items Not Replaced 100761.6.5 No Failures Observed , 1007

61.7 Reliability Related Standards and Good Practices for Medical Devices 1007References 1009

62 A Task-based Six Sigma Roadmap for Healthcare Services 1011L. C. Tang, Shao- Wei Lam and Thong-Ngee Goh

62.1 Introduction 101162.2 Task Oriented Strategies of Six Sigma 101262.3 Six Sigma Roadmap for Healthcare 1014

62.3.1 The "Define" Phase 101562.3.2 The "Visualize" Phase 101762.3.3 The "Analyze" and "Optimize" Phases 101762.3.4 The "Verify" Phase 1018

62.4 Case Study of the Dispensing Process in a Pharmacy 101962.4.1 Sensitivity Analysis 1021


63 Status and Recent Trends in Reliability for Civil Engineering Problems 1025Achintya Haldar

63.1 Introduction 102563.2 The Need for Reliability-based Design in Civil Engineering 102663.3 Changes in Design Philosophies - Design Requirements 102663.4 Available Analytical Methods - FORM/SORM, Simulation 1027

63.4.1 First-order Reliability Methods 1028

xliv Contents

63.4.2 An Iterative Procedure for FORM 103163.4.3 Example 1033

63.5 Probabilistic Sensitivity Indexes 103563.6 Reliability Evaluation Using Simulation 103663.7 Reliability Evaluation Using FOSM, FORM and Simulation 1037

63.7.1 Example 103763.8 FORM for Implicit Limit State Functions - The Stochastic Finite Element Method 103963.9 Recent Trends in Reliability for Civil Engineering Problems 104063.10 Concluding Remarks 1044References 1044

64 Performability Issues in Wireless Communication Network 1047S. Soh, Suresh Rai, and R.R. Brooks

64.1 Introduction 104764.2 System Models 1048

64.2.1 Reliability Models and Assumptions 104864.2.2 System Communication Models and Reliability Measures 104964.2.3 Component Failure Models 1050

64.3 Performability Analysis and Improvement of WCN 105264.3.1 Example I: Computing Reliability and Expected Hop Count of WCN 105264.3.2 Example II: Mobile Network Analysis Using Probabilistic Connectivity Matrices . 105664.3.3 Example III: Improving End-to-End Performability in Ad Hoc Networks 1063


65 Performability Modeling and Analysis of Grid Computing 1069Yuan-Shun Dai, and Gregory Levitin

65.1 Introduction 106965.2 Grid Service Reliability and Performance 1070

65.2.1 Description of the Grid Computing 107065.2.2 Failure Analysis of Grid Service 107165.2.3 Grid Service Reliability and Performance 107265.2.4 Grid Service Time Distribution and Reliability/Performance Measures 1073

65.3 Star Topology Grid Architecture 107565.3.1 Universal Generating Function 107565.3.2 Illustrative Example 1077

65.4 Tree Topology Grid Architecture 107965.4.1 Algorithms for Determining the pmf of the Task Execution Time 108065.4.2 Illustrative Example 108265.4.3 Parameterization and Monitoring 1084


66 Status and Trends in the Performance Assessment of Fault Tolerant Systems 1087John Kontoleon

66.1 Introduction 108766.2 Hardware Fault Tolerant Architectures and Techniques 1088

Contents xlv

66.2.1 Passive Redundancy 108866.2.2 Dynamic and Hybrid Techniques 108966.2.3 Information Redundancy 1091

66.3 Software FT: Learning from Hardware 109166.3.1 Basic Issues: Diversity and Redundancy 109266.3.2 Space and Time Redundancy 1092

66.4 Global Fault Tolerance Issues 109466.4.1 Fault Tolerant Computer Networks 109566.4.2 Network Protocol-based Fault Tolerance 109566.4.3 Fault Tolerance Management 1098

66.5 Performance Evaluation: A RAM Case Study 110166.6 Conclusions and Future Trends 1103References 1105

67 Prognostics and Health Monitoring of Electronics 1107Nikhil Vichare, Brian Tuchband and Michael Pecht

67.1 Introduction 110767.2 Reliability and Prognostics 110867.3 PHM for Electronics 110867.4 PHM Concepts and Methods 1109

67.4.1 Fuses and Canaries 110967.4.2 Monitoring and Reasoning of Failure Precursors 111167.4.3 Monitoring Environmental and Usage Loads for Damage Modeling 1114

67.5 Implementation of PHM in a System 11:1767.6 Health Monitoring for Product Take-back and End-of-life Decisions 111867.7 Conclusions 1120References 1120

68 RAMS Management of Railway Tracks 1123Narve Lyngby, Per Hokstad, Jorn Vatn

68.1 Introduction 112368.2 Railway Tracks 1123

68.2.1 Railway Track Degradation 112568.2.2 Inspections and Interventions 1126

68.3 Degradation Modeling 112768.3.1 Stochastic Modeling 112768.3.2 Degradation in Local Time 112868.3.3 Degradation of Sections 1129

68.4 Methods for Optimizing Maintenance and Renewal 113168.4.1 Optimizing Point Maintenance 113168.4.2 Optimizing Section Maintenance and Renewal 1133

68.5 Case Studies on RAMS 113468.5.1 Optimizing Ultrasonic Inspection Intervals 113468.5.2 Optimizing Track Maintenance 1141

68.6 Conclusions and Future Challenges 1143References 1143

xlvi Contents

69 Cost-Benefit Optimization Including Maintenance for Structures by a Renewal Model 1147Rudiger Rackwitz and Andreas Joanni

69.1 Introduction 114769.2 Preliminaries 1148

69.2.1 Failure Models for Deteriorating Components 114869.2.2 A Review of Renewal Theory 115069.2.3 Inspection and Repair 1151

69.3 Cost-Benefit Optimization 115269.3.1 General 1152:69.3.2 The Standard Case : 1153

69.4-Preventive Maintenance 115469.4.1 Cost-Benefit Optimization for Systematic Age-dependent Repair 115469.4.2 Cost-Benefit Optimization Including Inspection and Repair 1156

69.5 Example 115869.6 Summary 1160References 1160

70 Reliability and Price Assessment and the Associated Risk Controlfor Restructured Power Systems 1163Y. Ding, Ming Zuo and Peng Wang

70.1 Introduction 116370.2 Reliability and Price Assessment of Restructured Power Systems

with the Poolco Market Model 116770.2.1 Customer Response to Price Changes 116870.2.2 Formulation of the Nodal Price and the Nodal Reliability Problem 116870.2.3 System Studies 1170

70.3 Reliability and Price Assessment of Restructured Power Systemswith the Hybrid Market Model 117070.3.1 Reliability and Cost Models for Market Participants 117070.3.2 A Model of Customer Responses 117270.3.3 Formulations of Reliability and Price Problems 117270.3.4 System Studies 1173

70.4 A Schema for Controlling Price Volatilities Based on Price Decomposition Techniques.... 117470.4.1 Price Decomposition Techniques 117470.4.2 The Proposed Schema 1175

References 1178

71 Probabilistic Risk Assessment for Nuclear Power Plants 1179Peter Kafka

71.1 Introduction 117971.2 Essential Elements of PRA 1181

71.2.1 Identification of Scenarios 118371.2.2 System Reliability 118371.2.3 System Response 118370.2.4 Common Cause Failures 118470.2.5 Human Factors 118470.2.6 Software Reliability 1185

Contents xlvii

70.2.7 Uncertainties 118670.2.8 Probability Aggregation 1186

71.3 Today's Challenges 118771.3.1 The Risk Management Process 118771.3.2 Software Reliability 118971.3.3 Test and Maintenance and Induced Faults 1189

71.4 Outlook 1189References 1190

72 Software Reliability and Fault-tolerant Systems: An Overview and Perspectives 1193Hoang Pham

72.1 Introduction 119372.2 The Software Development Process 119572.3 Software Reliability Modeling 1196

72.3.1 A Generalized NHPP Model 119672.3.2 Application 1: The Real-time Control System 1199

72.4 Generalized Models with Environmental Factors 119972.4.1 Application 2: The Real-time Monitor Systems 1200

72.5 Fault-tolerant Software Systems 120172.5.1 The Recovery Block Scheme 120372.5.2 JV-version Programming 1203

72.6 Cost Modeling 120472.6.1 The Gain Model with Random Field Environments 120472.6.2 Other Cost Models 1205

References 1206

73 Application of the Lognormal Distribution to Software Reliability Engineering 1209Swapna S. Gokhale and Robert E. Mullen

73.1 Introduction 120973.2 Overview of the Lognormal 121073.3 Why Are Software Event Rates Lognormal? 1210

73.3.1 Graphical Operational Profile , 121173.3.2 Multidimensional Operational Profiles 121173.3.3 Program Control Flow 121273.3.4 Sequences of Operations 121273.3.5 Queuing Network Models 121273.3.6 System State Vectors 121373.3.7 Fault Detection Process 1213

73.4 Lognormal Hypotheses 121373.4.1 Failure Rate Model 121373.4.2 Growth Model 121473.4.3 Occurrence Count Model 121473.4.4 Interpretation of Parameters 1215

73.5 Empirical Validation 121673.5.1 Failure Rate Model 121673.5.2 Growth Model 121873.5.3 Occurrence Count Model 1220

73.6 Future Research Directions 1221

xlviii Contents

73.7 Conclusions.... 1223References 1223

74 Early-stage Software Product Quality Prediction Based on Process Measurement Data 1227Shigeru Yamada

74.1 Introduction 122774.2 Quality Prediction Based On Quality Assurance Factors 1228

74.2.1 Data Analysis 122874.2.2 Correlation Analysis 1229-74.2.3 Principal Component Analysis 122974.2.4 Multiple Linear Regression 123074.2.5 The Effect of Quality Assurance Process Factors 1231

74.3 Quality Prediction Based on Management Factors 123174.3.1 Data Analysis 123174.3.2 Correlation Analysis 123274.3.3 Principal Component Analysis 123274.3.4 Multiple Linear Regression 123374.3.5 Effect of Management Process Factors 123474.3.6 Relationship Between Development Cost and Effort 1234

74.4 Relationship Between Product Quality and Development Cost 123574.5 Discriminant Analysis 123674.6 Conclusion 1236References 1237

75 On the Development of Discrete Software Reliability Growth Models 1239P.K. Kapur, P.C. Jha and V.B. Singh

75.1 Introduction 123975.2 Discrete Software Reliability Growth Models 1241

75.2.1 Discrete SRGM in a Perfect Debugging Environment 124275.2.2 Discrete SRGM with Testing Effort 124475.2.3 Modeling Faults of Different Severity 124575.2.4 Discrete Software Reliability Growth Models for Distributed Systems 124975.2.5 Discrete SRGM with Change Points 1251

75.3 Conclusion 1253References 1254

76 Epilogue 1257Krishna B. Misra

76.1 Mere Dependability Is Not Enough 125776.2 Sustainability: A Measure to Save the World from Further Deprivation 125876.3 Design for Performability: A Long-term Measure 125976.4 Parallelism between Biotechnology and Nanotechnology 126576.5 A Peep into the Future 1267References 1268

About the Editor 1271About the Contributors 1273Index 1295

handbook of performability engineering

Documents