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System Reliability Theory: Models, Statistical Methods, and Applications 3rd edition [Hardback]

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(Norwegian University of Science and Technology), ,
  • Formāts: Hardback, 864 pages, height x width x depth: 234x158x38 mm, weight: 1111 g
  • Sērija : Wiley Series in Probability and Statistics
  • Izdošanas datums: 04-Jan-2021
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 1119373522
  • ISBN-13: 9781119373520
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System Reliability Theory: Models, Statistical Methods, and Applications 3rd editionPalielināt
  • Formāts: Hardback, 864 pages, height x width x depth: 234x158x38 mm, weight: 1111 g
  • Sērija : Wiley Series in Probability and Statistics
  • Izdošanas datums: 04-Jan-2021
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 1119373522
  • ISBN-13: 9781119373520
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781119373520.html
Keywords:
"Since the publication of the Second Edition of this popular textbook, new standards have changed the focus of reliability engineering, which introduced new concepts and terminology. Consequently, the Third Edition of System Reliability Theory: Models, Statistical Methods, and Applications has been thoroughly rewritten and updated to meet current standards. With an updated practical focus, incorporation of industry feedback, and many new examples based on real-world industry problems and data, this book begins with an introduction on reliability engineering and is followed by coverage on failures and failure analysis. The authors address failure models and qualitative system analysis and present new coverage on state space models. In addition, a new chapter on component reliability and availability is followed by a chapter on systems of independent components. Component importance is covered followed by a chapter on dependent failures, which now includes a discussion on causes of common cause failures, explicit versus implicit modeling, and the Beta-factor model. The authors also discuss counting processes and Markov Processes. In addition, the authors provide new sections on: maintenance assessment and optimization; advanced models failure rates; human errors; software bugs; CCFs (ICED + method in IEC 61508); generic failure rate databases; FRACAS data; application-specific data; frequency of dangerous failures (PFH); and reliability prediction. The book is supplemented with a companion website, which contains an Instructor Solutions Manual, lecture slides, reliability data sources, sample exam questions, and a terminology review"--

Handbook and reference for industrial statisticians and system reliability engineers 

System Reliability Theory: Models, Statistical Methods, and Applications, Third Edition presents an updated and revised look at system reliability theory, modeling, and analytical methods.  The new edition is based on feedback to the second edition from numerous students, professors, researchers, and industries around the world.  New sections and chapters are added together with new real-world industry examples, and standards and problems are revised and updated. 

System Reliability Theory covers a broad and deep array of system reliability topics, including: 

·         In depth discussion of failures and failure modes 

·         The main system reliability assessment methods 

·         Common-cause failure modeling 

·         Deterioration modeling 

·         Maintenance modeling and assessment using Python code 

·         Bayesian probability and methods 

·         Life data analysis using R 

Perfect for undergraduate and graduate students taking courses in reliability engineering, this book also serves as a reference and resource for practicing statisticians and engineers.  

Throughout, the book has a practical focus, incorporating industry feedback and real-world industry problems and examples. 

 

Preface xxiii
About the Companion Website xxix
1 Introduction
1(30)
1.1 What is Reliability?
1(2)
1.1.1 Service Reliability
2(1)
1.1.2 Past and Future Reliability
3(1)
1.2 The Importance of Reliability
3(3)
1.2.1 Related Applications
4(2)
1.3 Basic Reliability Concepts
6(5)
1.3.1 Reliability
6(2)
1.3.2 Maintainability and Maintenance
8(1)
1.3.3 Availability
8(1)
1.3.4 Quality
9(1)
1.3.5 Dependability
9(1)
1.3.6 Safety and Security
10(1)
1.3.7 RAM and RAMS
10(1)
1.4 Reliability Metrics
11(1)
1.4.1 Reliability Metrics for a Technical Item
11(1)
1.4.2 Reliability Metrics for a Service
12(1)
1.5 Approaches to Reliability Analysis
12(3)
1.5.1 The Physical Approach to Reliability
13(1)
1.5.2 Systems Approach to Reliability
13(2)
1.6 Reliability Engineering
15(2)
1.6.1 Roles of the Reliability Engineer
16(1)
1.6.2 Timing of Reliability Studies
17(1)
1.7 Objectives, Scope, and Delimitations of the Book
17(2)
1.8 Trends and Challenges
19(1)
1.9 Standards and Guidelines
20(1)
1.10 History of System Reliability
20(6)
1.11 Problems
26(1)
References
27(4)
2 The Study Object And Its Functions
31(24)
2.1 Introduction
31(1)
2.2 System and System Elements
31(2)
2.2.1 Item
32(1)
2.2.2 Embedded Item
33(1)
2.3 Boundary Conditions
33(2)
2.3.1 Closed and Open Systems
34(1)
2.4 Operating Context
35(1)
2.5 Functions and Performance Requirements
35(6)
2.5.1 Functions
35(1)
2.5.2 Performance Requirements
36(1)
2.5.3 Classification of Functions
37(1)
2.5.4 Functional Modeling and Analysis
38(1)
2.5.5 Function Trees
38(1)
2.5.6 SADT and IDEF 0
39(2)
2.6 System Analysis
41(1)
2.6.1 Synthesis
41(1)
2.1 Simple, Complicated, and Complex Systems
42(2)
2.8 System Structure Modeling
44(7)
2.8.1 Reliability Block Diagram
44(2)
2.8.2 Series Structure
46(1)
2.8.3 Parallel Structure
46(1)
2.8.4 Redundancy
47(1)
2.8.5 Voted Structure
47(1)
2.8.6 Standby Structure
48(1)
2.8.7 More Complicated Structures
48(1)
2.8.8 Two Different System Functions
49(1)
2.8.9 Practical Construction of RBDs
50(1)
2.9 Problems
51(1)
References
52(3)
3 Failures And Faults
55(24)
3.1 Introduction
55(2)
3.1.1 States and Transitions
56(1)
3.1.2 Operational Modes
56(1)
3.2 Failures
57(3)
3.2.1 Failures in a State
58(1)
3.2.2 Failures During Transition
59(1)
3.3 Faults
60(1)
3.4 Failure Modes
60(2)
3.5 Failure Causes and Effects
62(2)
3.5.1 Failure Causes
62(1)
3.5.2 Proximate Causes and Root Causes
63(1)
3.5.3 Hierarchy of Causes
64(1)
3.6 Classification of Failures and Failure Modes
64(8)
3.6.1 Classification According to Local Consequence
65(1)
3.6.2 Classification According to Cause
65(5)
3.6.3 Failure Mechanisms
70(1)
3.6.4 Software Faults
71(1)
3.6.5 Failure Effects
71(1)
3.7 Failure/Fault Analysis
72(4)
3.7.1 Cause and Effect Analysis
73(1)
3.7.2 Root Cause Analysis
74(2)
3.8 Problems
76(1)
References
77(2)
4 Qualitative System Reliability Analysis
79(62)
4.1 Introduction
79(1)
4.1.1 Deductive Versus Inductive Analysis
80(1)
4.2 FMEA/FMECA
80(8)
4.2.1 Types of FMECA
81(1)
4.2.2 Objectives of FMECA
82(1)
4.2.3 FMECA Procedure
83(4)
4.2.4 Applications
87(1)
4.3 Fault Tree Analysis
88(15)
4.3.1 Fault Tree Symbols and Elements
88(3)
4.3.2 Definition of the Problem and the Boundary Conditions
91(1)
4.3.3 Constructing the Fault Tree
92(3)
4.3.4 Identification of Minimal Cut and Path Sets
95(1)
4.3.5 MOCUS
96(2)
4.3.6 Qualitative Evaluation of the Fault Tree
98(3)
4.3.7 Dynamic Fault Trees
101(2)
4.4 Event Tree Analysis
103(6)
4.4.1 Initiating Event
104(1)
4.4.2 Safety Functions
105(1)
4.4.3 Event Tree Construction
106(1)
4.4.4 Description of Resulting Event Sequences
106(3)
4.5 Fault Trees versus Reliability Block Diagrams
109(2)
4.5.1 Recommendation
111(1)
4.6 Structure Function
111(3)
4.6.1 Series Structure
112(1)
4.6.2 Parallel Structure
112(1)
4.6.3 Koon: G Structure
113(1)
4.6.4 Truth Tables
114(1)
4.7 System Structure Analysis
114(13)
4.7.1 Single Points of Failure
115(1)
4.7.2 Coherent Structures
115(2)
4.7.3 General Properties of Coherent Structures
117(2)
4.7.4 Structures Represented by Paths and Cuts
119(4)
4.7.5 Pivotal Decomposition
123(1)
4.7.6 Modules of Coherent Structures
124(3)
4.8 Bayesian Networks
127(4)
4.8.1 Illustrative Examples
128(3)
4.9 Problems
131(7)
References
138(3)
5 Probability Distributions In Reliability Analysis
141(80)
5.1 Introduction
141(2)
5.1.1 State Variable
142(1)
5.1.2 Time-to-Failure
142(1)
5.2 A Dataset
143(2)
5.2.1 Relative Frequency Distribution
143(1)
5.2.2 Empirical Distribution and Survivor Function
144(1)
5.3 General Characteristics of Time-to-Failure Distributions
145(2)
5.3.1 Survivor Function
147(1)
5.3.2 Failure Rate Function
148(5)
5.3.3 Conditional Survivor Function
153(1)
5.3.4 Mean Time-to-Failure
154(1)
5.3.5 Additional Probability Metrics
155(2)
5.3.6 Mean Residual Lifetime
157(3)
5.3.7 Mixture of Time-to-Failure Distributions
160(1)
5.4 Some Time-to-Failure Distributions
161(1)
5.4.1 The Exponential Distribution
161(7)
5.4.2 The Gamma Distribution
168(5)
5.4.3 The Weibull Distribution
173(7)
5.4.4 The Normal Distribution
180(3)
5.4.5 The Lognormal Distribution
183(5)
5.4.6 Additional Time-to-Failure Distributions
188(1)
5.5 Extreme Value Distributions
188(5)
5.5.1 The Gumbel Distribution of the Smallest Extreme
190(1)
5.5.2 The Gumbel Distribution of the Largest Extreme
191(1)
5.5.3 The Weibull Distribution of the Smallest Extreme
191(2)
5.6 Time-to-Failure Models With Covariates
193(5)
5.6.1 Accelerated Failure Time Models
194(1)
5.6.2 The Arrhenius Model
195(3)
5.6.3 Proportional Hazards Models
198(1)
5.7 Additional Continuous Distributions
198(2)
5.7.1 The Uniform Distribution
198(1)
5.7.2 The Beta Distribution
199(1)
5.8 Discrete Distributions
200(5)
5.8.1 Binomial Situation
200(1)
5.8.2 The Binomial Distribution
201(1)
5.8.3 The Geometric Distribution
201(1)
5.8.4 The Negative Binomial Distribution
202(1)
5.8.5 The Homogeneous Poisson Process
203(2)
5.9 Classes of Time-to-Failure Distributions
205(4)
5.9.1 IFR and DFR Distributions
206(2)
5.9.2 IFRA and DFRA Distributions
208(1)
5.9.3 NBU and NWU Distributions
208(1)
5.9 A NBUE and NWUE Distributions
209(1)
5.9.5 Some Implications
209(1)
5.10 Summary of Time-to-Failure Distributions
210(1)
5.11 Problems
210(8)
References
218(3)
6 System Reliability Analysis
221(78)
6.1 Introduction
221(1)
6.1.1 Assumptions
222(1)
6.2 System Reliability
222(6)
6.2.1 Reliability of Series Structures
223(1)
6.2.2 Reliability of Parallel Structures
224(1)
6.2.3 Reliability of koon Structures
225(1)
6.2.4 Pivotal Decomposition
226(1)
6.2.5 Critical Component
227(1)
6.3 Nonrepayable Systems
228(9)
6.3.1 Nonrepayable Series Structures
228(2)
6.3.2 Nonrepairable Parallel Structures
230(4)
6.3.3 Nonrepairable 2003 Structures
234(1)
6.3.4 A Brief Comparison
235(1)
6.3.5 Nonrepairable koon Structures
236(1)
6.4 Standby Redundancy
237(5)
6.4.1 Passive Redundancy, Perfect Switching, No Repairs
238(2)
6.4.2 Cold Standby, Imperfect Switch, No Repairs
240(1)
6.4.3 Partly Loaded Redundancy, Imperfect Switch, No Repairs
241(1)
6.5 Single Repairable Items
242(10)
6.5.1 Availability
243(1)
6.5.2 Average Availability with Perfect Repair
244(2)
6.5.3 Availability of a Single Item with Constant Failure and Repair Rates
246(1)
6.5.4 Operational Availability
247(1)
6.5.5 Production Availability
248(1)
6.5.6 Punctuality
249(1)
6.5.7 Failure Rate of Repairable Items
249(3)
6.6 Availability of Repairable Systems
252(10)
6.6.1 The MUT and MDT of Repairable Systems
253(5)
6.6.2 Computation Based on Minimal Cut Sets
258(2)
6.6.3 Uptimes and Downtimes for Reparable Systems
260(2)
6.7 Quantitative Fault Tree Analysis
262(13)
6.7.1 Terminology and Symbols
263(1)
6.7.2 Delimitations and Assumptions
263(1)
6.7.3 Fault Trees with a Single AND-Gate
264(1)
6.7.4 Fault Tree with a Single OR-Gate
265(1)
6.7.5 The Upper Bound Approximation Formula for Q0(t)
265(2)
6.7.6 The Inclusion-Exclusion Principle
267(4)
6.7.7 ROCOF of a Minimal Cut Parallel Structure
271(1)
6.7.8 Frequency of the TOP Event
271(2)
6.7.9 Binary Decision Diagrams
273(2)
6.8 Event Tree Analysis
275(2)
6.9 Bayesian Networks
277(7)
6.9.1 Influence and Cause
278(1)
6.9.2 Independence Assumptions
278(1)
6.9.3 Conditional Probability Table
279(1)
6.9.4 Conditional Independence
280(2)
6.9.5 Inference and Learning
282(1)
6.9.6 BN and Fault Tree Analysis
282(2)
6.10 Monte Carlo Simulation
284(7)
6.10.1 Random Number Generation
285(2)
6.10.2 Monte Carlo Next Event Simulation
287(2)
6.10.3 Simulation of Multicomponent Systems
289(2)
6.11 Problems
291(5)
References
296(3)
7 Reliability Importance Metrics
299(38)
7.1 Introduction
299(3)
7.1.1 Objectives of Reliability Importance Metrics
300(1)
7.1.2 Reliability Importance Metrics Considered
300(1)
7.1.3 Assumptions and Notation
301(1)
7.2 Critical Components
302(2)
7.3 Birnbaum's Metric for Structural Importance
304(1)
7.4 Birnbaum's Metric of Reliability Importance
305(8)
7.4.1 Birnbaum's Metric in Fault Tree Analysis
307(1)
7.4.2 A Second Definition of Birnbaum's Metric
308(2)
7.4.3 A Third Definition of Birnbaum's Metric
310(2)
7.4.4 Computation of Birnbaum's Metric for Structural Importance
312(1)
7.4.5 Variants of Birnbaum's Metric
312(1)
7.5 Improvement Potential
313(2)
7.5.1 Relation to Birnbaum's Metric
314(1)
7.5.2 A Variant of the Improvement Potential
314(1)
7.6 Criticality Importance
315(2)
7.7 Fussell--Vesely's Metric
317(6)
7.7.1 Derivation of Formulas for Fussell--Vesely's Metric
317(3)
7.7.2 Relationship to Other Metrics for Importance
320(3)
7.8 Differential Importance Metric
323(3)
7.8.1 Option 1
323(1)
7.8.2 Option 2
324(2)
7.9 Importance Metrics for Safety Features
326(5)
7.9.1 Risk Achievement Worth
327(2)
7.9.2 Risk Reduction Worth
329(1)
7.9.3 Relationship with the Improvement Potential
330(1)
7.10 Barlow--Proschan's Metric
331(2)
7.11 Problems
333(2)
References
335(2)
8 Dependent Failures
337(34)
8.1 Introduction
337(3)
8.1.1 Dependent Events and Variables
337(1)
8.1.2 Correlated Variables
338(2)
8.2 Types of Dependence
340(1)
8.3 Cascading Failures
340(2)
8.3.1 Tight Coupling
342(1)
8.4 Common-Cause Failures
342(4)
8.4.1 Multiple Failures that Are Not a CCF
344(1)
8.4.2 Causes of CCF
344(1)
8.4.3 Defenses Against CCF
345(1)
8.5 CCF Models and Analysis
346(3)
8.5.1 Explicit Modeling
347(1)
8.5.2 Implicit Modeling
348(1)
8.5.3 Modeling Approach
348(1)
8.5.4 Model Assumptions
349(1)
8.6 Basic Parameter Model
349(3)
8.6.1 Probability of a Specific Multiplicity
350(1)
8.6.2 Conditional Probability of a Specific Multiplicity
351(1)
8.7 Beta-Factor Model
352(8)
8.7.1 Relation to the BPM
354(1)
8.7.2 Beta-Factor Model in System Analysis
354(4)
8.7.3 Beta-Factor Model for Nonidentical Components
358(2)
8.7.4 C-Factor Model
360(1)
8.8 Multi-parameter Models
360(6)
8.8.1 Binomial Failure Rate Model
360(2)
8.8.2 Multiple Greek Letter Model
362(2)
8.8.3 Alpha-Factor Model
364(1)
8.8.4 Multiple Beta-Factor Model
365(1)
8.9 Problems
366(2)
References
368(3)
9 Maintenance And Maintenance Strategies
371(30)
9.1 Introduction
371(1)
9.1.1 What is Maintenance?
372(1)
9.2 Maintainability
372(2)
9.3 Maintenance Categories
374(4)
9.3.1 Completeness of a Repair Task
377(1)
9.3.2 Condition Monitoring
377(1)
9.4 Maintenance Downtime
378(4)
9.4.1 Downtime Caused by Failures
379(2)
9.4.2 Downtime of a Series Structure
381(1)
9.4.3 Downtime of a Parallel Structure
381(1)
9.4.4 Downtime of a General Structure
382(1)
9.5 Reliability Centered Maintenance
382(14)
9.5.1 What is RCM?
383(1)
9.5.2 Main Steps of an RCM Analysis
384(12)
9.6 Total Productive Maintenance
396(2)
9.7 Problems
398(1)
References
399(2)
10 Counting Processes
401(72)
10.1 Introduction
401(9)
10.1.1 Counting Processes
401(5)
10.1.2 Basic Concepts
406(2)
10.1.3 Martingale Theory
408(1)
10.1.4 Four Types of Counting Processes
409(1)
10.2 Homogeneous Poisson Processes
410(7)
10.2.1 Main Features of the HPP
411(1)
10.2.2 Asymptotic Properties
412(1)
10.2.3 Estimate and Confidence Interval
412(1)
10.2.4 Sum and Decomposition of HPPs
413(1)
10.2.5 Conditional Distribution of Failure Time
414(1)
10.2.6 Compound HPPs
415(2)
10.3 Renewal Processes
417(1)
10.3.1 Basic Concepts
417(1)
10.3.2 The Distribution of Sn
418(2)
10.3.3 The Distribution of N(t)
420(1)
10.3.4 The Renewal Function
421(2)
10.3.5 The Renewal Density
423(4)
10.3.6 Age and Remaining Lifetime
427(4)
10.3.7 Bounds for the Renewal Function
431(2)
10.3.8 Superimposed Renewal Processes
433(1)
10.3.9 Renewal Reward Processes
434(2)
10.3.10 Delayed Renewal Processes
436(2)
10.3.11 Alternating Renewal Processes
438(9)
10.4 Nonhomogeneous Poisson Processes
447(8)
10.4.1 Introduction and Definitions
447(2)
10.4.2 Some Results
449(3)
10.4.3 Parametric NHPP Models
452(2)
10.4.4 Statistical Tests of Trend
454(1)
10.5 Imperfect Repair Processes
455(9)
10.5.1 Brown and Proschan's model
456(2)
10.5.2 Failure Rate Reduction Models
458(3)
10.5.3 Age Reduction Models
461(1)
10.5.4 Trend Renewal Process
462(2)
10.6 Model Selection
464(2)
10.7 Problems
466(4)
References
470(3)
11 Markov Analysis
473(72)
11.1 Introduction
473(3)
11.1.1 Markov Property
475(1)
11.2 Markov Processes
476(11)
11.2.1 Procedure to Establish the Transition Rate Matrix
479(3)
11.2.2 Chapman--Kolmogorov Equations
482(1)
11.2.3 Kolmogorov Differential Equations
483(1)
11.2.4 State Equations
484(3)
11.3 Asymptotic Solution
487(8)
11.3.1 System Performance Metrics
492(3)
11.4 Parallel and Series Structures
495(6)
11.4.1 Parallel Structures of Independent Components
495(2)
11.4.2 Series Structures of Independent Components
497(2)
11.4.3 Series Structure of Components Where Failure of One Component Prevents Failure of the Other
499(2)
11.5 Mean Time to First System Failure
501(6)
11.5.1 Absorbing States
501(3)
11.5.2 Survivor Function
504(1)
11.5.3 Mean Time to the First System Failure
505(2)
11.6 Systems with Dependent Components
507(5)
11.6.1 Common Cause Failures
508(2)
11.6.2 Load-Sharing Systems
510(2)
11.7 Standby Systems
512(7)
11.7.1 Parallel System with Cold Standby and Perfect Switching
513(2)
11.7.2 Parallel System with Cold Standby and Perfect Switching (Item A is the Main Operating Item)
515(2)
11.7.3 Parallel System with Cold Standby and Imperfect Switching (Item A is the Main Operating Item)
517(1)
11.7.4 Parallel System with Partly Loaded Standby and Perfect Switching (Item A is the Main Operating Item)
518(1)
11.8 Markov Analysis in Fault Tree Analysis
519(2)
11.8.1 Cut Set Information
520(1)
11.8.2 System Information
521(1)
11.9 Time-Dependent Solution
521(3)
11.9.1 Laplace Transforms
522(2)
11.10 Semi-Markov Processes
524(2)
11.11 Multiphase Markov Processes
526(2)
11.11.1 Changing the Transition Rates
526(1)
11.11.2 Changing the Initial State
527(1)
11.12 Piecewise Deterministic Markov Processes
528(4)
11.12.1 Definition of PDMP
529(1)
11.12.2 State Probabilities
529(1)
11.12.3 A Specific Case
530(2)
11.13 Simulation of a Markov Process
532(4)
11.14 Problems
536(7)
References
543(2)
12 Preventive Maintenance
545(60)
12.1 Introduction
545(1)
12.2 Terminology and Cost Function
546(2)
12.3 Time-Based Preventive Maintenance
548(16)
12.3.1 Age Replacement
549(4)
12.3.2 Block Replacement
553(4)
12.3.3 P-F Intervals
557(7)
12.4 Degradation Models
564(10)
12.4.1 Remaining Useful Lifetime
565(2)
12.4.2 Trend Models; Regression-Based Models
567(2)
12.4.3 Models with Increments
569(2)
12.4.4 Shock Models
571(2)
12.4.5 Stochastic Processes with Discrete States
573(1)
12.4.6 Failure Rate Models
574(1)
12.5 Condition-Based Maintenance
574(13)
12.5.1 CBM Strategy
575(1)
12.5.2 Continuous Monitoring and Finite Discrete State Space
576(5)
12.5.3 Continuous Monitoring and Continuous State Space
581(2)
12.5.4 Inspection-Based Monitoring and Finite Discrete State Space
583(3)
12.5.5 Inspection-Based Monitoring and Continuous State Space
586(1)
12.6 Maintenance of Multi-Item Systems
587(8)
12.6.1 System Model
587(2)
12.6.2 Maintenance Models
589(2)
12.6.3 An Illustrative Example
591(4)
12.7 Problems
595(6)
References
601(4)
13 Reliability Of Safety Systems
605(50)
13.1 Introduction
605(1)
13.2 Safety-Instrumented Systems
606(5)
13.2.1 Main SIS Functions
607(1)
13.2.2 Testing of SIS Functions
608(1)
13.2.3 Failure Classification
609(2)
13.3 Probability of Failure on Demand
611(11)
13.3.1 Probability of Failure on Demand
612(5)
13.3.2 Approximation Formulas
617(1)
13.3.3 Mean Downtime in a Test Interval
618(1)
13.3.4 Mean Number of Test Intervals Until First Failure
619(1)
13.3.5 Staggered Testing
620(1)
13.3.6 Nonnegligible Repair Time
621(1)
13.4 Safety Unavailability
622(5)
13.4.1 Probability of Critical Situation
623(1)
13.4.2 Spurious Trips
623(2)
13.4.3 Failures Detected by Diagnostic Self-Testing
625(2)
13.5 Common Cause Failures
627(4)
13.5.1 Diagnostic Self-Testing and CCFs
629(2)
13.6 CCFs Between Groups and Subsystems
631(1)
13.6.1 CCFs Between Voted Groups
632(1)
13.6.2 CCFs Between Subsystems
632(1)
13.7 IEC 61508
632(6)
13.7.1 Safety Lifecycle
633(1)
13.7.2 Safety Integrity Level
634(1)
13.7.3 Compliance with IEC 61508
635(3)
13.8 The PDS Method
638(1)
13.9 Markov Approach
639(5)
13.9.1 All Failures are Repaired After Each Test
643(1)
13.9.2 All Critical Failures Are Repaired after Each Test
644(1)
13.9.3 Imperfect Repair after Each Test
644(1)
13.10 Problems
644(8)
References
652(3)
14 Reliability Data Analysis
655(84)
14.1 Introduction
655(1)
14.1.1 Purpose of the
Chapter
656(1)
14.2 Some Basic Concepts
656(7)
14.2.1 Datasets
657(1)
14.2.2 Survival Times
658(2)
14.2.3 Categories of Censored Datasets
660(2)
14.2.4 Field Data Collection Exercises
662(1)
14.2.5 At-Risk-Set
663(1)
14.3 Exploratory Data Analysis
663(11)
14.3.1 A Complete Dataset
664(1)
14.3.2 Sample Metrics
665(4)
14.3.3 Histogram
669(1)
14.3.4 Density Plot
670(1)
14.3.5 Empirical Survivor Function
671(2)
14.3.6 Q--Q Plot
673(1)
14.4 Parameter Estimation
674(22)
14.4.1 Estimators and Estimates
675(1)
14.4.2 Properties of Estimators
675(2)
14.4.3 Method of Moments Estimation
677(3)
14.4.4 Maximum Likelihood Estimation
680(6)
14.4.5 Exponentially Distributed Lifetimes
686(6)
14.4.6 Weibull Distributed Lifetimes
692(4)
14.5 The Kaplan-Meier Estimate
696(5)
14.5.1 Motivation for the Kaplan-Meier Estimate Based a Complete Dataset
696(1)
14.5.2 The Kaplan-Meier Estimator for a Censored Dataset
697(4)
14.6 Cumulative Failure Rate Plots
701(7)
14.6.1 The Nelson-Aalen Estimate of the Cumulative Failure Rate
703(5)
14.7 Total-Time-on-Test Plotting
708(15)
14.7.1 Total-Time-on-Test Plot for Complete Datasets
708(13)
14.7.2 Total-Time-on-Test Plot for Censored Datasets
721(1)
14.7.3 A Brief Comparison
722(1)
14.8 Survival Analysis with Covariates
723(7)
14.8.1 Proportional Hazards Model
723(3)
14.8.2 Cox Models
726(1)
14.8.3 Estimating the Parameters of the Cox Model
727(3)
14.9 Problems
730(6)
References
736(3)
15 Bayesian Reliability Analysis
739(28)
15.1 Introduction
739(3)
15.1.1 Three Interpretations of Probability
739(2)
15.1.2 Bayes' Formula
741(1)
15.2 Bayesian Data Analysis
742(7)
15.2.1 Frequentist Data Analysis
743(1)
15.2.2 Bayesian Data Analysis
743(2)
15.2.3 Model for Observed Data
745(1)
15.2.4 Prior Distribution
745(1)
15.2.5 Observed Data
746(1)
15.2.6 Likelihood Function
746(1)
15.2.7 Posterior Distribution
747(2)
15.3 Selection of Prior Distribution
749(9)
15.3.1 Binomial Model
749(3)
15.3.2 Exponential Model - Single Observation
752(1)
15.3.3 Exponential Model - Multiple Observations
753(2)
15.3.4 Homogeneous Poisson Process
755(2)
15.3.5 Noninformative Prior Distributions
757(1)
15.4 Bayesian Estimation
758(3)
15.4.1 Bayesian Point Estimation
758(2)
15.4.2 Credible Intervals
760(1)
15.5 Predictive Distribution
761(1)
15.6 Models with Multiple Parameters
762(1)
15.7 Bayesian Analysis with R
762(2)
15.8 Problems
764(2)
References
766(1)
16 Reliability Data: Sources And Quality
767(22)
16.1 Introduction
767(2)
16.1.1 Categories of Input Data
767(1)
16.1.2 Parameters Estimates
768(1)
16.2 Generic Reliability Databases
769(6)
16.2.1 OREDA
770(2)
16.2.2 PDS Data Handbook
772(1)
16.2.3 PERD
773(1)
16.2.4 SERH
773(1)
16.2.5 NPRD, EPRD, and FMD
773(1)
16.2.6 GADS
774(1)
16.2.7 GIDEP
774(1)
16.2.8 FMEDA Approach
775(1)
16.2.9 Failure Event Databases
775(1)
16.3 Reliability Prediction
775(3)
16.3.1 MIL-HDBK-217 Approach
776(2)
16.3.2 Similar Methods
778(1)
16.4 Common Cause Failure Data
778(2)
16.4.1 ICDE
779(1)
16.4.2 IEC 61508 Method
779(1)
16.5 Data Analysis and Data Quality
780(5)
16.5.1 Outdated Technology
780(1)
16.5.2 Inventory Data
781(1)
16.5.3 Constant Failure Rates
781(2)
16.5.4 Multiple Samples
783(2)
16.5.5 Data From Manufacturers
785(1)
16.5.6 Questioning the Data Quality
785(1)
16.6 Data Dossier
785(2)
16.6.1 Final Remarks
785(2)
References
787(2)
Appendix A Acronyms 789(4)
Appendix B Laplace Transforms 793(1)
B.1 Important Properties of Laplace Transforms 794(1)
B.2 Laplace Transforms of Some Selected Functions 794(3)
Author Index 797(6)
Subject Index 803
MARVIN RAUSAND is Professor Emeritus in the department of Mechanical and Industrial Engineering at the Norwegian University of Science and Technology (NTNU), Norway, and author of Risk Assessment: Theory, Methods, and Applications and Reliability of Safety-Critical Systems: Theory and Applications, both published by Wiley.

ANNE BARROS, PHD, is Professor in reliability and maintenance engineering at Ecole CentraleSupélec, University of Paris-Saclay, France. Her research focus is on degradation modeling, prognostics, condition based and predictive maintenance. She got a PHD then a professorship position at University of Technology of Troyes, France (2003 – 2014) and spent five years as a full-time professor at NTNU, Norway (2014 – 2019). She is currently heading a research group and holds an industrial chair at CentraleSupélec with the ambition to provide reliability assessment and maintenance modeling methods for systems of systems.

The late ARNLJOT HŲYLAND, PHD, was a Professor in the Department of Mathematical Sciences at the Norwegian University of Science and Technology.