信頼性工学ハンドブック<br>Handbook of Reliability Engineering (2003. 960 p. w. 134 ill.)

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信頼性工学ハンドブック
Handbook of Reliability Engineering (2003. 960 p. w. 134 ill.)

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  • 製本 Hardcover:ハードカバー版/ページ数 663 p., 134 illus.
  • 商品コード 9781852334536

基本説明

Contents: I. System Reliability and Optimization.- II. Statistical Reliability Theory.- III. Software Reliability.- IV. Maintenance Theory and Testing.- V. Practices and Emerging Applications.

Full Description


An effective reliability programme is an essential component of every product's design, testing and efficient production. From the failure analysis of a microelectronic device to software fault tolerance and from the accelerated life testing of mechanical components to hardware verification, a common underlying philosophy of reliability applies. Defining both fundamental and applied work across the entire systems reliability arena, this state-of-the-art reference presents methodologies for quality, maintainability and dependability. Featuring: Contributions from 60 leading reliability experts in academia and industry giving comprehensive and authoritative coverage. A distinguished international Editorial Board ensuring clarity and precision throughout. Extensive references to the theoretical foundations, recent research and future directions described in each chapter. Comprehensive subject index providing maximum utility to the reader. Applications and examples across all branches of engineering including IT, power, automotive and aerospace sectors. The handbook's cross-disciplinary scope will ensure that it serves as an indispensable tool for researchers in industrial, electrical, electronics, computer, civil, mechanical and systems engineering. It will also aid professional engineers to find creative reliability solutions and management to evaluate systems reliability and to improve processes. For student research projects it will be the ideal starting point whether addressing basic questions in communications and electronics or learning advanced applications in micro-electro-mechanical systems (MEMS), manufacturing and high-assurance engineering systems.

Table of Contents

  PART I. System Reliability and Optimization
Multi-state k-out-of-n Systems 3 (16)
Ming J. Zuo
Jinsheng Huang
Way Kuo
Introduction 3 (1)
Relevant Concepts in Binary Reliability 3 (1)
Theory
Binary k-out-of-n Models 4 (4)
The k-out-of-n:G System with 5 (1)
Independently and Identically
Distributed Components
Reliability Evaluation Using Minimal 5 (1)
Path or Cut Sets
Recursive Algorithms 6 (1)
Equivalence Between a k-out-of-n:G 6 (1)
System and an (n -- k + 1)-out-of-n:F
system
The Dual Relationship Between the 7 (1)
k-out-of-n:G and F Systems
Relevant Concepts in Multi-state 8 (2)
Reliability Theory
A Simple Multi-state k-out-of-n:G Model 10 (1)
A Generalized Multi-state k-out-of-n:G 11 (2)
System Model
Properties of Generalized Multi-state 13 (2)
k-out-of-n:G Systems
Equivalence and Duality in Generalized 15 (4)
Multi-state k-out-of-n Systems
Reliability of Systems with Multiple 19 (18)
Failure Modes
Hoang Pham
Introduction 19 (1)
The Series System 20 (1)
The Parallel System 21 (1)
Cost Optimization 21 (1)
The Parallel-Series System 22 (3)
The Profit Maximization Problem 23 (1)
Optimization Problem 24 (1)
The Series-Parallel System 25 (2)
Maximizing the Average System Profit 26 (1)
Consideration of Type I Design Error 27 (1)
The k-out-of-n Systems 27 (5)
Minimizing the Average System Cost 29 (3)
Fault-tolerant Systems 32 (2)
Reliability Evaluation 33 (1)
Redundancy Optimization 34 (1)
Weighted Systems with Three Failure Modes 34 (3)
Reliabilities of Consecutive-k Systems 37 (24)
Jen-Chun Chang
Frank K. Hwang
Introduction 37 (2)
Background 37 (1)
Notation 38 (1)
Computation of Reliability 39 (2)
The Recursive Equation Approach 39 (1)
The Markov Chain Approach 40 (1)
Asymptotic Analysis 41 (1)
Invariant Consecutive Systems 41 (2)
Invariant Consecutive-2 Systems 41 (1)
Invariant Consecutive-k Systems 42 (1)
Invariant Consecutive-k G System 43 (1)
Component Importance and the Component 43 (4)
Replacement Problem
The Birnbaum Importance 44 (1)
Partial Birnbaum Importance 45 (1)
The Optimal Component Replacement 45 (2)
The Weighted-consecutive-k-out-of-n System 47 (1)
The Linear 47 (1)
Weighted-consecutive-k-out-of-n System
The Circular 47 (1)
Weighted-consecutive-k-out-of-n System
Window Systems 48 (5)
The f-within-consecutive-k-out-of-n 49 (2)
System
The 2-within-consecutive-k-out-of-n 51 (1)
System
The b-fold-window System 52 (1)
Network Systems 53 (4)
The Linear Consecutive-2 Network System 53 (1)
The Linear Consecutive-k Network System 54 (1)
The Linear Consecutive-k Flow Network 55 (2)
System
Conclusion 57 (4)
Multi-state System Reliability Analysis and 61 (30)
Optimization
G. Levitin
A. Lisnianski
Introduction 61 (2)
Notation 63 (1)
Multi-state System Reliability Measures 63 (1)
Multi-state System Reliability Indices 64 (3)
Evaluation Based on the Universal
Generating Function
Determination of u-function of Complex 67 (1)
Multi-state System Using Composition
Operators
Importance and Sensitivity Analysis of 68 (4)
Multi-state Systems
Multi-state System Structure Optimization 72 (19)
Problems
Optimization Technique 73 (1)
Genetic Algorithm 73 (2)
Solution Representation and Decoding 75 (1)
Procedure
Structure Optimization of 75 (1)
Series-Parallel System with
Capacity-based Performance Measure
Problem Formulation 75 (1)
Solution Quality Evaluation 76 (1)
Structure Optimization of Multi-state 77 (1)
System with Two Failure Modes
Problem Formulation 77 (3)
Solution Quality Evaluation 80 (3)
Structure Optimization for Multi-state 83 (1)
System with Fixed Resource Requirements
and Unreliable Sources
Problem Formulation 83 (1)
Solution Quality Evaluation 84 (1)
The Output Performance Distribution of 85 (1)
a System Containing Identical Elements
in the Main Producing Subsystem
The Output Performance Distribution of 85 (2)
a System Containing Different Elements
in the Main Producing Subsystem
Other Problems of Multi-state System 87 (4)
Optimization
Combinatorial Reliability Optimization 91 (26)
C.S. Sung
Y.K. Cho
S. H. Song
Introduction 91 (4)
Combinatorial Reliability Optimization 95 (7)
Problems of Series Structure
Optimal Solution Approaches 95 (1)
Partial Enumeration Method 95 (1)
Branch-and-bound Method 96 (2)
Dynamic Programming 98 (1)
Heuristic Solution Approach 99 (3)
Combinatorial Reliability Optimization 102(5)
Problems of a Non-series Structure
Mixed Series-Parallel System 102(4)
Optimization Problems
General System Optimization Problems 106(1)
Combinatorial Reliability Optimization 107(6)
Problems with Multiple-choice Constraints
One-dimensional Problems 108(3)
Multi-dimensional Problems 111(2)
Summary 113(4)
PART II. Statistical Reliability Theory
Modeling the Observed Failure Rate 117(24)
M. S. Finkelstein
Introduction 117(1)
Survival in the Plane 118(6)
One-dimensional Case 118(1)
Fixed Obstacles 119(2)
Failure Rate Process 121(1)
Moving Obstacles 122(2)
Multiple Availability 124(8)
Statement of the Problem 124(1)
Ordinary Multiple Availability 125(1)
Accuracy of a Fast Repair Approximation 126(1)
Two Non-serviced Demands in a Row 127(2)
Not More than N Non-serviced Demands 129(1)
Time Redundancy 130(2)
Modeling the Mixture Failure Rate 132(9)
Definitions and Conditional 132(1)
Characteristics
Additive Model 133(1)
Multiplicative Model 133(2)
Some Examples 135(1)
Inverse Problem 136(5)
Concepts of Stochastic Dependence in 141(16)
Reliability Analysis
C. D. Lai
M. Xie
Introduction 141(1)
Important Conditions Describing Positive 142(3)
Dependence
Six Basic Conditions 143(1)
The Relative Stringency of the 143(1)
Conditions
Positive Quadrant Dependent in 144(1)
Expectation
Associated Random Variables 144(1)
Positively Correlated Distributions 145(1)
Summary of Interrelationships 145(1)
Positive Quadrant Dependent Concept 145(2)
Constructions of Positive Quadrant 146(1)
Dependent Bivariate Distributions
Applications of Positive Quadrant 146(1)
Dependence Concept to Reliability
Effect of Positive Dependence on the 146(1)
Mean Lifetime of a Parallel System
Inequality Without Any Aging Assumption 147(1)
Families of Bivariate Distributions that 147(5)
are Positive Quadrant Dependent
Positive Quadrant Dependent Bivariate 148(1)
Distributions with Simple Structures
Positive Quadrant Dependent Bivariate 149(1)
Distributions with More Complicated
Structures
Positive Quadrant Dependent Bivariate 150(1)
Uniform Distributions
Generalized Farlie--Gumbel--Morgenstern 151(1)
Family of Copulas
Some Related Issues on Positive Dependence 152(1)
Examples of Bivariate Positive 152(1)
Dependence Stronger than Positive
Quadrant Dependent Condition
Examples of Negative Quadrant Dependence 153(1)
Positive Dependence Orderings 153(1)
Concluding Remarks 154(3)
Statistical Reliability Change-point 157(8)
Estimation Models
Ming Zhao
Introduction 157(1)
Assumptions in Reliability Change-point 158(1)
Models
Some Specific Change-point Models 159(1)
Jelinski--Moranda De-eutrophication 159(1)
Model with a Change Point
Model Review 159(1)
Model with One Change Point 159(1)
Weibull Change-point Model 160(1)
Littlewood Model with One Change Point 160(1)
Maximum Likelihood Estimation 160(1)
Application 161(1)
Summary 162(3)
Concepts and Applications of Stochastic 165(16)
Aging in Reliability
C. D. Lai
M. Xie
Introduction 165(2)
Basic Concepts for Univariate Reliability 167(2)
Classes
Some Acronyms and the Notions of Aging 167(1)
Definitions of Reliability Classes 167(2)
Interrelationships 169(1)
Properties of the Basic Concepts 169(1)
Properties of Increasing and Decreasing 169(1)
Failure Rates
Property of Increasing Failure Rate on 169(1)
Average
Properties of NBU, NBUC, and NBUE 169(1)
Distributions with Bathtub-shaped Failure 169(1)
Rates
Life Classes Characterized by the Mean 170(1)
Residual Lifetime
Some Further Classes of Aging 171(1)
Partial Ordering of Life Distributions 171(2)
Relative Aging 172(1)
Applications of Partial Orderings 172(1)
Bivariate Reliability Classes 173(1)
Tests of Stochastic Aging 173(4)
A General Sketch of Tests 174(3)
Summary of Tests of Aging in Univariate 177(1)
Case
Summary of Tests of Bivariate Aging 177(1)
Concluding Remarks on Aging 177(4)
Class of NBU-t0 Life Distribution 181(20)
Dong Ho Park
Introduction 181(1)
Characterization of NBU-t0 Class 182(4)
Boundary Members of NBU-t0 and NWU-t0 182(2)
Preservation of NBU-t0 and NWU-t0 184(2)
Properties under Reliability Operations
Estimation of NBU-t0 Life Distribution 186(3)
Reneau--Samaniego Estimator 186(2)
Chang--Rao Estimator 188(1)
Positively Biased Estimator 188(1)
Geometric Mean Estimator 188(1)
Tests for NBU-t0 Life Distribution 189(12)
Tests for NBU-t0 Alternatives Using 189(1)
Complete Data
Hollander--Park--Proschan Test 190(2)
Ebrahimi--Habibullah Test 192(1)
Ahmad Test 193(2)
Tests for NBU-t0 Alternatives Using 195(6)
Incomplete Data
PART III. Software Reliability
Software Reliability Models: A Selective 201(12)
Survey and New Directions
Siddhartha R. Dalal
Introduction 201(2)
Static Models 203(2)
Phase-based Model: Gaffney and Davis 203(1)
Predictive Development Life Cycle 203(2)
Model: Dalal and Ho
Dynamic Models: Reliability Growth Models 205(2)
for Testing and Operational Use
A General Class of Models 205(1)
Assumptions Underlying the Reliability 206(1)
Growth Models
Caution in Using Reliability Growth 207(1)
Models
Reliability Growth Modeling with 207(1)
Covariates
When to Stop Testing Software 208(1)
Challenges and Conclusions 209(4)
Software Reliability Modeling 213(22)
James Ledoux
Introduction 213(1)
Basic Concepts of Stochastic Modeling 214(1)
Metrics with Regard to the First Failure 214(1)
Stochastic Process of Times of Failure 215(1)
Black-box Software Reliability Models 215(7)
Self-exciting Point Processes 216(2)
Counting Statistics for a Self-exciting 218(1)
Point Process
Likelihood Function for a Self-exciting 218(1)
Point Process
Reliability and Mean Time to Failure 218(1)
Functions
Classification of Software Reliability 219(1)
Models
0-Memory Self-exciting Point Process 219(1)
Non-homogeneous Poisson Process Model: 220(1)
λ(t; Ht, F0) = f(t; F0) and is
Deterministic
1-Memory Self-exciting Point Process 221(1)
with λ(t; Ht, F0) = f(N(t), t --
TN(t), F0)
m ≥ 2-Memory 221(1)
White-box Modeling 222(1)
Calibration of Model 223(2)
Frequentist Procedures 223(2)
Bayesian Procedure 225(1)
Current Issues 225(10)
Black-box Modeling 225(1)
Imperfect Debugging 225(1)
Early Prediction of Software Reliability 226(1)
Environmental Factors 227(1)
Conclusion 228(1)
White-box Modeling 229(1)
Statistical Issues 230(5)
Software Availability Theory and Its 235(10)
Applications
Koichi Tokuno
Shigeru Yamada
Introduction 235(1)
Basic Model and Software Availability 236(3)
Measures
Modified Models 239(2)
Model with Two Types of Failure 239(1)
Model with Two Types of Restoration 240(1)
Applied Models 241(2)
Model with Computation Performance 241(1)
Model for Hardware-Software System 242(1)
Concluding Remarks 243(2)
Software Rejuvenation: Modeling and 245(20)
Applications
Tadashi Dohi
Katerina Goseva-Popstojanova
Kalyanaraman Vaidyanathan
Kishor S. Trivedi
Shunji Osaki
Introduction 245(1)
Modeling-based Estimation 246(11)
Examples in Telecommunication Billing 247(4)
Applications
Examples in a Transaction-based 251(4)
Software System
Examples in a Cluster System 255(2)
Measurement-based Estimation 257(5)
Time-based Estimation 258(2)
Time and Workload-based Estimation 260(2)
Conclusion and Future Work 262(3)
Software Reliability Management: Techniques 265(20)
and Applications
Mitsuhiro Kimura
Shigeru Yamada
Introduction 265(1)
Death Process Model for Software Testing 266(5)
Management
Model Description 267(1)
Mean Number of Remaining Software 268(1)
Faults/Testing Cases
Mean Time to Extinction 268(1)
Estimation Method of Unknown Parameters 268(1)
Case of 0 < α ≤ 1 268(1)
Case of α = 0 269(1)
Software Testing Progress Evaluation 269(1)
Numerical Illustrations 270(1)
Concluding Remarks 271(1)
Estimation Method of Imperfect Debugging 271(3)
Probability
Hidden-Markov modeling for software 271(1)
reliability growth phenomenon
Estimation Method of Unknown Parameters 272(1)
Numerical Illustrations 273(1)
Concluding Remarks 274(1)
Continuous State Space Model for 274(6)
Large-scale Software
Model Description 275(2)
Nonlinear Characteristics of Software 277(1)
Debugging Speed
Estimation Method of Unknown Parameters 277(2)
Software Reliability Assessment Measures 279(1)
Expected Number of Remaining Faults and 279(1)
Its Variance
Cumulative and Instantaneous Mean Time 279(1)
Between Failures
Concluding Remarks 280(1)
Development of a Software Reliability 280(5)
Management Tool
Definition of the Specification 280(1)
Requirement
Object-oriented Design 281(1)
Examples of Reliability Estimation and 282(3)
Discussion
Recent Studies in Software Reliability 285(20)
Engineering
Hoang Pham
Introduction 285(3)
Software Reliability Concepts 285(3)
Software Life Cycle 288(1)
Software Reliability Modeling 288(1)
A Generalized Non-homogeneous Poisson 289(1)
Process Model
Application 1: The Real-time Control 289(1)
System
Generalized Models with Environmental 289(6)
Factors
Parameters Estimation 292(1)
Application 2: The Real-time Monitor 292(3)
Systems
Cost Modeling 295(1)
Generalized Risk-Cost Models 295(1)
Recent Studies with Considerations of 296(4)
Random Field Environments
A Reliability Model 297(1)
A Cost Model 297(3)
Further Reading 300(5)
PART IV. Maintenance Theory and Testing
Warranty and Maintenance 305(12)
D. N. P. Murthy
N. Jack
Introduction 305(1)
Product Warranties: An Overview 306(2)
Role and Concept 306(1)
Product Categories 306(1)
Warranty Policies 306(1)
Warranties Policies for Standard 306(1)
Products Sold Individually
Warranty Policies for Standard Products 307(1)
Sold in Lots
Warranty Policies for Specialized 307(1)
Products
Extended Warranties 307(1)
Warranties for Used Products 308(1)
Issues in Product Warranty 308(1)
Warranty Cost Analysis 308(1)
Warranty Servicing 309(1)
Review of Warranty Literature 309(1)
Maintenance: An Overview 309(2)
Corrective Maintenance 309(1)
Preventive Maintenance 310(1)
Review of Maintenance Literature 310(1)
Warranty and Corrective Maintenance 311(1)
Warranty and Preventive Maintenance 312(1)
Extended Warranties and Service Contracts 313(1)
Conclusions and Topics for Future Research 314(3)
Mechanical Reliability and Maintenance 317(32)
Models
Gianpaolo Pulcini
Introduction 317(1)
Stochastic Point Processes 318(2)
Perfect Maintenance 320(1)
Minimal Repair 321(9)
No Trend with Operating Time 323(1)
Monotonic Trend with Operating Time 323(1)
The Power Law Process 324(1)
The Log-Linear Process 325(1)
Bounded Intensity Processes 326(1)
Bathtub-type Intensity 327(1)
Numerical Example 328(1)
Non-homogeneous Poisson Process 329(1)
Incorporating Covariate Information
Imperfect or Worse Repair 330(5)
Proportional Age Reduction Models 330(1)
Inhomogeneous Gamma Processes 331(2)
Lawless--Thiagarajah Models 333(1)
Proportional Intensity Variation Model 334(1)
Complex Maintenance Policy 335(8)
Sequence of Perfect and Minimal Repairs 336(2)
Without Preventive Maintenance
Minimal Repairs Interspersed with 338(1)
Perfect Preventive Maintenance
Imperfect Repairs Interspersed with 339(1)
Perfect Preventive Maintenance
Minimal Repairs Interspersed with 340(1)
Imperfect Preventive Maintenance
Numerical Example 341(1)
Corrective Repairs Interspersed with 342(1)
Preventive Maintenance Without
Restrictive Assumptions
Reliability Growth 343(6)
Continuous Models 344(1)
Discrete Models 345(4)
Preventive Maintenance Models: Replacement, 349(18)
Repair, Ordering, and Inspection
Tadashi Dohi
Naoto Kaio
Shunji Osaki
Introduction 349(1)
Block Replacement Models 350(4)
Model I 350(2)
Model II 352(1)
Model III 352(2)
Age Replacement Models 354(2)
Basic Age Replacement Model 354(2)
Ordering Models 356(5)
Continuous-time Model 357(1)
Discrete-time Model 358(1)
Combined Model with Minimal Repairs 359(2)
Inspection Models 361(2)
Nearly Optimal Inspection Policy by 362(1)
Kaio and Osaki (K&O Policy)
Nearly Optimal Inspection Policy by 363(1)
Munford and Shahani (M&S Policy)
Nearly Optimal Inspection Policy by 363(1)
Nakagawa and Yasui (N&Y Policy)
Concluding Remarks 363(4)
Maintenance and Optimum Policy 367(30)
Toshio Nakagawa
Introduction 367(1)
Replacement Policies 368(10)
Age Replacement 368(2)
Block Replacement 370(1)
No Replacement at Failure 370(1)
Replacement with Two Variables 371(1)
Periodic Replacement 371(1)
Modified Models with Two Variables 372(1)
Replacement at N Variables 373(1)
Other Replacement Models 373(1)
Replacements with Discounting 373(1)
Discrete Replacement Models 374(1)
Replacements with Two Types of Unit 375(1)
Replacement of a Shock Model 376(1)
Remarks 377(1)
Preventive Maintenance Policies 378(7)
One-unit System 378(1)
Interval Reliability 379(1)
Two-unit System 380(1)
Imperfect Preventive Maintenance 381(2)
Imperfect with Probability 383(1)
Reduced Age 383(1)
Modified Preventive Maintenance 384(1)
Inspection Policies 385(12)
Standard Inspection 386(1)
Inspection with Preventive Maintenance 387(1)
Inspection of a Storage System 388(9)
Optimal Imperfect Maintenance Models 397(18)
Hongzhou Wang
Hoang Pham
Introduction 397(2)
Treatment Methods for Imperfect 399(5)
Maintenance
Treatment Method 1 399(1)
Treatment Method 2 400(1)
Treatment Method 3 401(1)
Treatment Method 4 402(1)
Treatment Method 5 403(1)
Treatment Method 6 403(1)
Treatment Method 7 403(1)
Other Methods 404(1)
Some Results on Imperfect Maintenance 404(7)
A Quasi-renewal Process and Imperfect 404(1)
Maintenance
Imperfect Maintenance Model A 405(1)
Imperfect Maintenance Model B 405(1)
Imperfect Maintenance Model C 405(2)
Imperfect Maintenance Model D 407(1)
Imperfect Maintenance Model E 408(1)
Optimal Imperfect Maintenance of 409(2)
k-out-of-n Systems
Future Research on Imperfect Maintenance 411(1)
Appendix 412(3)
Acronyms and Definitions 412(1)
Exercises 412(3)
Accelerated Life Testing 415(14)
Elsayed A. Elsayed
Introduction 415(1)
Design of Accelerated Life Testing Plans 416(1)
Stress Loadings 416(1)
Types of Stress 416(1)
Accelerated Life Testing Models 417(9)
Parametric Statistics-based Models 418(1)
Acceleration Model for the Exponential 419(1)
Model
Acceleration Model for the Weibull Model 420(2)
The Arrhenius Model 422(2)
Non-parametric Accelerated Life Testing 424(2)
Models: Cox's Model
Extensions of the Proportional Hazards 426(3)
Model
Accelerated Test Models with the 429(12)
Birnbaum--Saunders Distribution
W. Jason Owen
William J. Padgett
Introduction 429(2)
Accelerated Testing 430(1)
The Birnbaum--Saunders Distribution 431(1)
Accelerated Birnbaum--Saunders Models 431(4)
The Power-law Accelerated 432(1)
Birnbaum--Saunders Model
Cumulative Damage Models 432(1)
Additive Damage Models 433(1)
Multiplicative Damage Models 434(1)
Inference Procedures with Accelerated 435(2)
Life Models
Estimation from Experimental Data 437(4)
Fatigue Failure Data 437(1)
Micro-Composite Strength Data 437(4)
Multiple-steps Step-stress Accelerated Life 441(16)
Test
Loon-Ching Tang
Introduction 441(2)
Cumulative Exposure Models 443(2)
Planning a Step-stress Accelerated Life 445(5)
Test
Planning a Simple Step-stress 446(1)
Accelerated Life Test
The Likelihood Function 446(1)
Setting a Target Accelerating Factor 447(1)
Maximum Likelihood Estimator and 447(1)
Asymptotic Variance
Nonlinear Programming for Joint 447(1)
Optimality in Hold Time and Low Stress
Multiple-steps Step-stress Accelerated 448(2)
Life Test Plans
Data Analysis in the Step-stress 450(3)
Accelerated Life Test
Multiply Censored, Continuously 450(1)
Monitored Step-stress Accelerated Life
Test
Parameter Estimation for Weibull 451(1)
Distribution
Read-out Data 451(2)
Implementation in Microsoft Excel™ 453(1)
Conclusion 454(3)
Step-stress Accelerated Life Testing 457(18)
Chengjie Xiong
Introduction 457(1)
Step-stress Life Testing with Constant 457(6)
Stress-change Times
Cumulative Exposure Model 457(2)
Estimation with Exponential Data 459(3)
Estimation with Other Distributions 462(1)
Optimum Test Plan 463(1)
Step-stress Life Testing with Random 463(5)
Stress-change Times
Marginal Distribution of Lifetime 463(4)
Estimation 467(1)
Optimum Test Plan 467(1)
Bibliographical Notes 468(7)
PART V. Practices and Emerging Applications
Statistical Methods for Reliability Data 475(18)
Analysis
Michael J. Phillips
Introduction 475(1)
Nature of Reliability Data 475(3)
Probability and Random Variables 478(1)
Principles of Statistical Methods 479(1)
Censored Data 480(3)
Weibull Regression Model 483(2)
Accelerated Failure-time Model 485(1)
Proportional Hazards Model 486(3)
Residual Plots for the Proportional 489(1)
Hazards Model
Non-proportional Hazards Models 490(1)
Selecting the Model and the Variables 491(1)
Discussion 491(2)
The Application of Capture--Recapture 493(18)
Methods in Reliability Studies
Paul S. F. Yip
Yan Wang
Anne Chao
Introduction 493(2)
Formulation of the Problem 495(9)
Homogeneous Model with Recapture 496(2)
A Seeded Fault Approach Without 498(1)
Recapture
Heterogeneous Model 499(1)
Non-parametric Case: λi(t) = 499(2)
γiαi
Parametric Case: λi(t) = γi 501(3)
A Sequential Procedure 504(1)
Real Examples 504(1)
Simulation Studies 505(3)
Discussion 508(3)
Reliability of Electric Power Systems: An 511(18)
Overview
Roy Billinton
Ronald N. Allan
Introduction 511(1)
System Reliability Performance 512(3)
System Reliability Prediction 515(6)
System Analysis 515(1)
Predictive Assessment at HLI 516(2)
Predictive Assessment at HLII 518(1)
Distribution System Reliability 519(1)
Assessment
Predictive Assessment at HLIII 520(1)
System Reliability Data 521(4)
Canadian Electricity Association 522(1)
Database
Canadian Electricity Association 523(1)
Equipment Reliability Information
System Database for HLI Evaluation
Canadian Electricity Association 523(1)
Equipment Reliability Information
System Database for HLII Evaluation
Canadian Electricity Association 524(1)
Equipment Reliability Information
System Database for HLIII Evaluation
System Reliability Worth 525(2)
Guide to Further Study 527(2)
Human and Medical Device Reliability 529(14)
B. S. Dhillon
Introduction 529(1)
Human and Medical Device Reliability 529(1)
Terms and Definitions
Human Stress---Performance Effectiveness, 530(1)
Human Error Types, and Causes of Human
Error
Human Reliability Analysis Methods 531(4)
Probability Tree Method 531(1)
Fault Tree Method 532(2)
Markov Method 534(1)
Human Unreliability Data Sources 535(1)
Medical Device Reliability Related Facts 535(1)
and Figures
Medical Device Recalls and Equipment 536(1)
Classification
Human Error in Medical Devices 537(1)
Tools for Medical Device Reliability 537(2)
Assurance
General Method 538(1)
Failure Modes and Effect Analysis 538(1)
Fault Tree Method 538(1)
Markov Method 538(1)
Data Sources for Performing Medical 539(1)
Device Reliability Studies
Guidelines for Reliability Engineers with 539(4)
Respect to Medical Devices
Probabilistic Risk Assessment 543(16)
Robert A. Bari
Introduction 543(1)
Historical Comments 544(2)
Probabilistic Risk Assessment Methodology 546(3)
Engineering Risk Versus Environmental Risk 549(1)
Risk Measures and Public Impact 550(3)
Transition to Risk-informed Regulation 553(1)
Some Successful Probabilistic Risk 553(1)
Assessment Applications
Comments on Uncertainty 554(1)
Deterministic, Probabilistic, 554(1)
Prescriptive, Performance-based
Outlook 555(4)
Total Dependability Management 559(8)
Per Anders Akersten
Bengt Klefsjo
Introduction 559(1)
Background 559(1)
Total Dependability Management 560(1)
Management System Components 561(3)
Conclusions 564(3)
Total Quality for Software Engineering 567(18)
Management
G. Albeanu
Fl. Popentiu Vladicescu
Introduction 567(4)
The Meaning of Software Quality 567(2)
Approaches in Software Quality Assurance 569(2)
The Practice of Software Engineering 571(6)
Software Lifecycle 571(3)
Software Development Process 574(1)
Software Measurements 575(2)
Software Quality Models 577(3)
Measuring Aspects of Quality 577(1)
Software Reliability Engineering 577(2)
Effort and Cost Models 579(1)
Total Quality Management for Software 580(2)
Engineering
Deming's Theory 580(1)
Continuous Improvement 581(1)
Conclusions 582(3)
Software Fault Tolerance 585(28)
Xiaolin Teng
Hoang Pham
Introduction 585(1)
Software Fault-tolerant Methodologies 586(2)
N-version Programming 586(1)
Recovery Block 586(1)
Other Fault-tolerance Techniques 587(1)
N-version Programming Modeling 588(6)
Basic Analysis 588(1)
Data-domain Modeling 588(1)
Time-domain Modeling 589(1)
Reliability in the Presence of Failure 590(1)
Correlation
Reliability Analysis and Modeling 591(3)
Generalized Non-homogeneous Poisson 594(1)
Process Model Formulation
Non-homogeneous Poisson Process 595(7)
Reliability Model for N-version
Programming Systems
Model Assumptions 597(2)
Model Formulations 599(1)
Mean Value Functions 599(1)
Common Failures 600(1)
Concurrent Independent Failures 601(1)
N-version Programming System Reliability 601(1)
Parameter Estimation 602(1)
N-version programming--Software 602(8)
Reliability Growth
Applications of N-version 602(1)
Programming-Software Reliability Growth
Models
Testing Data 602(8)
Conclusion 610(3)
Markovian Dependability/Performability 613(30)
Modeling of Fault-tolerant Systems
Juan A. Carrasco
Introduction 613(2)
Measures 615(7)
Expected Steady-state Reward Rate 617(1)
Expected Cumulative Reward Till Exit of 618(1)
a Subset of States
Expected Cumulative Reward During Stay 618(1)
in a Subset of States
Expected Transient Reward Rate 619(1)
Expected Averaged Reward Rate 619(1)
Cumulative Reward Distribution Till 619(1)
Exit of a Subset of States
Cumulative Reward Distribution During 620(1)
Stay in a Subset of States
Cumulative Reward Distribution 621(1)
Extended Reward Structures 621(1)
Model Specification 622(3)
Model Solution 625(5)
The Largeness Problem 630(2)
A Case Study 632(8)
Conclusions 640(3)
Random-request Availability 643(10)
Kang W. Lee
Introduction 643(1)
System Description and Definition 644(1)
Mathematical Expression for the 645(2)
Random-request Availability
Notation 645(1)
Mathematical Assumptions 645(1)
Mathematical Expressions 645(2)
Numerical Examples 647(1)
Simulation Results 647(4)
Approximation 651(1)
Concluding Remarks 652(1)
Index 653