Introduction to Reliability Engineering, 3rd Edition

Cover
Title Page
Copyright Page
Contents
Chapter 1 Introduction
1.1 Reliability Defined
1.2 Performance, Cost, and Reliability
1.3 Quality, Reliability, and Safety Linkage
1.4 Quality, Reliability, and Safety Engineering Tasks
1.5 Preview
Bibliography
Chapter 2 Probability and Discrete Distributions
2.1 Introduction
2.2 Probability Concepts
Relative Frequency
Classical
Subjective
Sample space (S) = set of all possible outcomes
Outcome (e) = an element of the sample space
Event = A subset of outcomes
Probability Axioms
More Than Two Events
Combinations and Permutations
2.3 Discrete Random Variables
Properties of Discrete Variables
The Binomial Distribution
The Poisson Distribution
Confidence Intervals
Motivation for Confidence Intervals
Introduction to Confidence Intervals
Binomial Confidence Intervals
Cumulative Sums of the Poisson Distribution (Thorndike Chart)
Bibliography
Advanced texts in Probability
Exercises
Chapter 3 The Exponential Distribution and Reliability Basics
3.1 Introduction
3.2 Reliability Characterization
Basic Definitions
The Bathtub Curve
3.3 Constant Failure Rate Model
The Exponential Distribution
Demand Failures
Time Determinations
3.4 Time-Dependent Failure Rates
3.5 Component Failures and Failure Modes
Failure Mode Rates
Component Counts
3.6 Replacements
3.7 Redundancy
Active and Standby Redundancy
Active Parallel
Standby Parallel
Constant Failure Rate Models
3.8 Redundancy Limitations
Common-Mode Failures
Load Sharing
Switching and Standby Failures
Cold, Warm, and Hot Standby
3.9 Multiply Redundant Systems
1/N Active Redundancy
1/N Standby Redundancy
m/N Active Redundancy
3.10 Redundancy Allocation
High- and Low-level Redundancy
Fail Safe and Fail to Danger
Voting Systems
3.11 Redundancy in Complex Configurations
Series–Parallel Configurations
Linked Configurations
Bibliography
Exercises
Redundancy
Chapter 4 Continuous Distributions–Part 1 Normal and Related Continuous Distributions
4.1 Introduction
4.2 Properties of Continuous Random Variables
Probability Distribution Functions
Characteristics of a Probability Distribution
Sample Statistics
Transformations of Variables
4.3 Empirical Cumulative Distribution Function (Empirical CDF)
4.4 Uniform Distribution
4.5 Normal and Related Distributions
The Normal Distribution
Normal Distribution…… Cautions and Warnings!!
Central Limit Theorem
Central Limit Theorem in Practice
The Lognormal Distribution
Log Normal Distribution from a Physics of Failure Perspective
4.6 Confidence Intervals
Point and Interval Estimates
Estimate of the Mean
4.7 Normal and Lognormal Parameters
Bibliography
Chapter 5 Continuous Distributions – Part 2 Weibull and Extreme Value Distributions
5.1 Introduction
The "Weakest Link" Theory from a Physics-of-Failure Point of View
Uses of Weibull and Extreme Value Distributions
Other Considerations
Age Parameters and Sample Sizes
Engineering Changes, Maintenance Plan Evaluation, and Risk Prediction
Weibulls with Cusps or Curves
System Weibulls
No Failure Weibulls
Small Sample Weibulls
Summary
5.2 Statistics of the Weibull Distribution
Weibull "Mathematics´´
The Weibull Probability Plot
Probability Plotting Points – Median Ranks
How to Do a "Weibull Analysis´´
Weibull Plots and Their Estimates of β, η
The Three-Parameter Weibull Did Not Work, What Are My Choices?
The Data has a "Dogleg" Bend or Cusp When Plotted on Weibull Paper
Steep Weibull Slopes (ßs) May Hide Problems
Low-Time Failures and Close Serial numbers – Batch Problems
Maximum-Likelihood Estimates of β and η
Weibayes Analysis
Weibayes Background (You Do Not Necessarily Have Any Failure Times)
Weibull Analysis with Failures Only and Unknown Times on the Unfailed Population
Shifting Weibull Procedure
Confidence Bounds and the Weibull Distribution
Arbitrary Censored Data – Left-Censored, Right-Censored, and Interval Data
The Weibull Distribution in a System of Independent Failure Modes
5.3 Extreme Value Distributions
5.4 Introduction to Risk Analysis
Risk Analysis "Mathematics´´
Bibliography
Exercises
Supplement 1: Weibull Derived from Weakest Link Theory
Chapter 6 Reliability Testing
6.1 Introduction
6.2 Attribute Testing (Binomial Testing)
The Classical Success Run
Zero-Failure Attribute Tests
Non-Zero-Failure Attribute Tests
6.3 Constant Failure Rate Estimates
Censoring on the Right
MTTF Estimates
Confidence Intervals
6.4 Weibull Substantiation and Reliability Testing
Zero-Failure Test Plans for Substantiation Testing
Weibull Zero-Failure Test Plans for Reliability Testing
Reexpression of a Reliability Goal to Determine η
Designing the Test Plan
Test Units with Censored Times (due to Julius Wang, Fiat-Chrysler)
Total Test Time
Why Not Simply Test to Failure?
6.5 How to Reduce Test Time
Run (Simultaneously) More Test Samples Than You Intend to Fail
Sudden Death Testing
Sequential Testing
6.6 Normal and Lognormal Reliability Testing
6.7 Accelerated Life Testing
Compressed-Time Testing
Advanced-Stress Testing–Linear and Acceleration Models
Linear Model Stress Testing
Advanced-Stress Testing–Acceleration Models
The Arrhenius Model
The Inverse Power Law Model
Other Acceleration Models
6.8 Reliability-Enhancement Procedures
Reliability Growth Modeling and Testing
Calculation of Reliability Growth Parameters
Goodness-of-Fit Tests for Reliability Growth Models
For Time-Terminated Testing
For Failure-Terminated Testing
For Grouped Data
Environmental Stress Screening
What "Screens" are used for ESS?
Thermal Cycling
Random Vibration
Other Screens
Highly Accelerated Life Tests10
Highly Accelerated-Stress Screening
Bibliography
Exercises
Supplement 1: Tables for Weibull Zero-failure Substantiation testing
Supplement 2: Tables For Weibull Zer-failure Substantiation testing using (t/Eta)
Supplement 3: Critical Values for Cramer–Von Mises Goodness-of-Fit Test
Supplement 4: Other Reliability Growth Models that have been Proposed and Studied (see AFWAL-TR-84-2024 for details)
(a) Deterministic Models
(b) Poisson Process Models
(c) Markov Processes/Time Series Models
Supplement 5: Chi-Square Table
Chapter 7 Failure Modes and Effects Analysis – Design and Process
7.1 Introduction
7.2 Functional FMEA
7.3 Design FMEA
Design FMEA Procedure
7.4 Process FMEA (PFMEA)
7.5 FMEA Summary
Bibliography
Exercises
Supplement 1: Shortcut Tables for Stalled FMEA Teams
Supplement 2: Future Changes in FMEA Approaches
Supplement 3: DFMEA and PFMEA Forms
Chapter 8 Loads, Capacity, and Reliability
8.1 Introduction
8.2 Reliability with a Single Loading
Load Application
Definitions
8.3 Reliability and Safety Factors
Normal Distributions
Lognormal Distributions
Combined Distributions
8.4 Repetitive Loading
Loading Variability
Variable Capacity1
8.5 The Bathtub Curve–Reconsidered
Single Failure Modes
Combined Failure Modes
Bibliography
Exercises
Supplement 1: The Dirac Delta Distribution
Chapter 9 Maintained Systems
9.1 Introduction
9.2 Preventive Maintenance
Idealized Maintenance
Imperfect Maintenance
Redundant Components
9.3 Corrective Maintenance
Availability
Maintainability
9.4 Repair: Revealed Failures
Constant Repair Rates
Constant Repair Times
9.5 Testing and Repair: Unrevealed Failures
Idealized Periodic Tests
Real Periodic Tests
9.6 System Availability
Revealed Failures
Unrevealed Failures
Simultaneous Testing
Staggered Testing
Bibliography
Exercises
Chapter 10 Failure Interactions
10.1 Introduction
10.2 Markov Analysis
Two Independent Components
Load-Sharing Systems
10.3 Reliability With Standby Systems
Idealized System
Failures in the Standby State
Switching Failures
Primary System Repair
10.4 Multicomponent Systems
Multicomponent Markov Formulations
Combinations of Subsystems
10.5 Availability
Standby Redundancy
Shared Repair Crews
Markov Availability–Advantages and Disadvantages
The Advantages of Markov Availability Analysis
The Disadvantages of Markov Availability Analysis
Bibliography
Exercises
Chapter 11 System Safety Analysis
11.1 Introduction
11.2 Product and Equipment Hazards
11.3 Human Error
Routine Operations
Emergency Operations
11.4 Methods of Analysis
Failure Modes, Effects, and Criticality Analysis (FMECA)
Criticality
Event Trees
11.5 Fault Trees
Fault-Tree Construction
Nomenclature
Fault Classification
Primary, Secondary, and Command Faults
Passive and Active Faults
Fault Tree Examples
Direct Evaluation of Fault Trees
Qualitative Evaluation
Top Down
Bottom Up
Logical Reduction
Quantitative Evaluation
Probability Relationships
Primary-Failure Data
Fault-Tree Evaluation by Cut Sets
Qualitative Analysis
Minimum Cut-Set Formulation
Cut-Set Determination
Cut-Set Interpretations
Quantitative Analysis
Top-Event Probability
Importance
Uncertainty
11.6 Reliability/Safety Risk Analysis
Conclusion: Assuming Worst Case can be Misleading
Another Approach: Monte Carlo Simulation
Bibliography
FMEA/FMECA
Exercises
Appendix A Useful Mathematical Relationships
A.1 Integrals
Definite Integrals
Integration by Parts
Derivative of an Integral
A.2 Expansions
Integer Series
Binomial Expansion
Geometric Progression
Infinite Series
A.3 Solution of First-order Linear Differential Equation
Appendix B Binomial Failure Probability Charts
Appendix C Ф(z): Standard Normal CDF
Appendix D Nonparametric Methods and Probability Plotting
D.1 Introduction
D.2 Nonparametric Methods for Probability Plotting
Boxplots and Histograms
Boxplot
Histogram
Rank Statistics
D.3 Parametric Methods
Weibull Distribution Plotting
Extreme-Value Distribution Plotting
Lognormal Distribution Plotting
D.4 Goodness of Fit
Bibliography
3rd Ed Answers to Odd – Numbered Exercises
Index
EULA