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Reliability Assessments : Concepts, Models, and Case Studies.

"This book provides engineers and scientists with a single source introduction to the concepts, models, and case studies for making credible reliability assessments. It satisfies the need for thorough discussions of several fundamental subjects. Section I contains a comprehensive overview of as...

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Bibliographic Details
Main Author: Nash, Ph. D., Franklin Richard (Author)
Corporate Author: Taylor & Francis
Format: eBook
Language:English
Published: Boca Raton, FL : CRC Press, 2017.
Edition:First edition.
Subjects:
Failure analysis (Engineering)
Analyse des défaillances (Ingénierie)
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Cover
  • Title Page
  • Copyright Page
  • Dedication
  • Table of Contents
  • Preface
  • Acknowledgments
  • Author
  • Section I: Concepts and Models
  • Chapter 1: Overview of Reliability Assessments
  • 1.1 Quality and Reliability
  • 1.1.1 Quality
  • 1.1.2 Reliability (Longevity and Robustness)
  • 1.1.3 Longevity
  • 1.1.4 Robustness
  • 1.1.5 Additional Comments on Robustness Testing
  • 1.1.6 Reliability Is Longevity and Robustness
  • 1.2 Descriptions of Failures
  • 1.2.1 Failure Modes and Mechanisms
  • 1.2.2 Sudden Failures (Event-Dependent)
  • 1.2.3 Sudden Failures (Time-Dependent)
  • 1.2.4 Gradual Degradation Failures (Time-Dependent)
  • 1.2.5 Latent Defect Failures
  • 1.3 Physics of Failure
  • 1.3.1 Stage One: FMA
  • 1.3.2 Stage Two: Eliminate or Mitigate the Root Causes of Failure
  • 1.3.2.1 Short-Term Failures in Semiconductor Lasers
  • 1.3.2.2 Long-Term Failures in Semiconductor Lasers
  • 1.3.3 Stage Three: Quantitative Estimate of Failure Probability
  • 1.3.4 PoF Example: Light Bulbs
  • 1.3.4.1 Stage One
  • 1.3.4.2 Stage Two
  • 1.3.4.3 Stage Three
  • 1.4 Deterministic Modeling of Reliability
  • 1.5 Empirical Modeling of Reliability
  • 1.5.1 One Failure Accelerant: Arrhenius Model
  • 1.5.2 One Failure Accelerant: Coffin-Manson Model
  • 1.5.3 Two Failure Accelerants: Thermal and Nonthermal
  • 1.5.4 Two Failure Accelerants: Thermal, Nonthermal, and Interaction
  • 1.6 Methods for Assessing Reliability
  • 1.6.1 Field Use
  • 1.6.1.1 Example One: IC's, Transistors, and Diode Arrays
  • 1.6.1.2 Example Two: Terrestrial Carrier Laser Modules
  • 1.6.1.3 Example Three: Terrestrial Optical Isolators
  • 1.6.2 Use-Condition Laboratory Aging
  • 1.6.3 Accelerated Laboratory Aging
  • 1.7 Credibility of Reliability Estimates
  • 1.7.1 Suspect Credibility: Estimates versus Field Return FMAs
  • 1.7.2 Suspect Credibility: Laboratory Samples, Aging, and Modeling.
  • 1.7.3 Two Examples
  • 1.7.4 Additional Comments on Reliability Assessments
  • 1.8 Derating and Redundancy
  • 1.8.1 Example: Simultaneous Use of Derating and Redundancy
  • 1.9 Classification of Failures
  • 1.9.1 Bathtub Curve
  • 1.9.2 Normal Failures (Wearout)
  • 1.9.3 Abnormal Failures (Infant Mortality and Freak)
  • 1.10 Stages in a Reliability Assurance Program
  • 1.10.1 Prequalification
  • 1.10.1.1 Identification
  • 1.10.1.2 Reliability by Design
  • 1.10.2 Certification (Reliability by Screening)
  • 1.10.2.1 Burn-In (Semiconductor Lasers)
  • 1.10.2.2 Pedigree Review (Semiconductor Lasers)
  • 1.10.2.3 Burn-In and Robustness Testing (Semiconductor Laser Modules)
  • 1.10.2.4 Pedigree Review (Semiconductor Laser Modules)
  • 1.10.3 Qualification
  • 1.10.4 Surveillance
  • 1.10.5 Requalification
  • Appendix 1A: Example-Photodetector Burn-In
  • References
  • Chapter 2: Concept of Randomness
  • 2.1 Randomness, Determinism, and Chaos
  • 2.1.1 Randomness
  • 2.1.1.1 Narrow Definition of Randomness
  • 2.1.1.2 Broader Definition of Randomness
  • 2.1.1.3 Random Processes with Deterministic Bases
  • 2.1.1.4 Random Processes with Nondeterministic Bases
  • 2.1.2 Randomness and Determinism: Hybrid Case
  • 2.1.3 Determinism
  • 2.1.4 Chaos
  • 2.1.4.1 Three-Body Problem: Poincaré (1890)
  • 2.1.4.2 Weather Prediction: Lorenz (1963)
  • 2.1.4.3 Population Growth: May (1976)
  • 2.1.4.4 Billiards: Sinai (1970) and Bunimovich (1974, 1979)
  • 2.2 Concept of Randomness in Reliability
  • 2.2.1 Example One: Light Bulb Failures
  • 2.2.2 Example Two: Spontaneous Emission from Nuclei and Atoms
  • 2.2.3 Example Three: Coin Tossing ("The Last Man Standing")
  • 2.2.4 Example Four: Hypothetical Resistor Failure
  • 2.2.5 Example Five: Hypothetical Capacitor Failure
  • 2.3 Random and Representative Samples
  • References
  • Chapter 3: Probability and Sampling.
  • 5.5 Derivations of the Exponential Model
  • 5.5.1 Radioactive Decay Observations
  • 5.5.2 Laws of Chance
  • 5.5.3 Homogeneous Poisson Statistics
  • 5.5.4 Quantum Mechanics
  • 5.5.5 System Failure Observations
  • 5.6 Example: Upper Bound Estimates for Zero Failures in Aging
  • 5.6.1 Exponential Model and Laboratory Accelerated Aging with No Failures
  • 5.6.2 Weibull Model and Laboratory Accelerated Aging with No Failures
  • 5.6.3 Exponential Model and Use-Condition Aging with No Failures
  • 5.6.4 Exponential Model and Field-Use Aging with No Failures
  • 5.7 Example: Upper Bound Estimates for a Few Failures in Aging
  • 5.7.1 Zero (n = 0) Failures
  • 5.7.2 One (n = 1) Failure
  • 5.7.3 Several (n> 0) Failures
  • 5.8 Point Estimates for Zero (n = 0) Failures
  • 5.8.1 Approach One
  • 5.8.2 Approach Two
  • 5.9 Lack of Memory Property
  • 5.10 An Appropriate Use of the Exponential Model in Cases of Wearout
  • Appendix 5A: Bounding Thermal Activation Energies
  • References
  • Chapter 6: Reliability Models: Weibull and Lognormal
  • 6.1 Introduction
  • 6.2 Weibull Model
  • 6.2.1 Some Applications of the Weibull Model
  • 6.2.2 Mathematical Origins of the Weibull Model
  • 6.2.2.1 Weibull: Failure Rate Model
  • 6.2.2.2 Weibull: Weakest Link Model
  • 6.2.2.3 Weibull: Smallest Extreme Value Distribution
  • 6.3 Lognormal Model
  • 6.3.1 Some Applications of the Lognormal Model
  • 6.3.2 Mathematical Origins of the Lognormal Model
  • 6.3.2.1 Lognormal: Multiplicative Growth Model
  • 6.3.2.2 Normal: Additive Growth Model
  • 6.3.2.3 Lognormal: Activation Energy Model (1)
  • 6.3.2.4 Lognormal: Activation Energy Model (2)
  • 6.3.2.5 Lognormal: Activation Energy Model (3)
  • 6.3.2.6 Lognormal: Activation Energy Model (4)
  • 6.3.3 Lognormal Wearout: Average Lifetime Improvement
  • References
  • Chapter 7: Bathtub Curves for Humans and Components.
  • 7.1 Human Mortality Bathtub Curve
  • 7.2 Human Mortality Statistics
  • 7.3 Human Mortality Bathtub Curve: Examples
  • 7.4 Contrasting Explanations for Human Mortality Life Spans
  • 7.5 Statistical Life Models for Humans and Other Organisms
  • 7.6 Gompertz Model of Human Mortality: Estimate Example
  • 7.7 Logistic Model of Human Mortality: Estimate Example
  • 7.8 Weibull Model of Human Mortality: Estimate Example
  • 7.9 Logistic Model of Nematode Worm Mortality (1): Estimate Example
  • 7.10 Weibull Model of Nematode Worm Mortality (2): Estimate Example
  • 7.11 Gompertz Model and Late-Life Nonaging: Explain Example
  • 7.12 Logistic Model and Approach to Late-Life Nonaging: Explain Example
  • 7.13 Life Span Heterogeneity and Late-Life Nonaging
  • 7.13.1 Epigenetics: A Possible Origin for Life Span Heterogeneity
  • 7.13.2 Epigenetics: An Experimental Origin for Life Span Heterogeneity
  • 7.14 Component Bathtub Curve
  • 7.15 Modeling the Component Bathtub Curve
  • 7.16 Examples of Empirical (Observed) Component Bathtub Curves
  • 7.16.1 Example 1: Mechanical System
  • 7.16.2 Example 2: Electron Tubes
  • 7.16.3 Example 3: CMOS Integrated Circuit Arrays
  • 7.16.4 Example 4: Non-Hodgkin Lymphoma
  • 7.16.5 Conclusions: Empirical Bathtub Curves
  • 7.17 The Three Regions of the Traditional Bathtub Curve
  • 7.17.1 Early Life Period Premature Failures (Infant-Mortality and Freaks
  • 7.17.1.1 Examples of Empirical Infant-Mortality Failure-Rate Distributions
  • 7.17.1.2 Examples of Empirical Freak Failure Rate Distributions
  • 7.17.2 Useful or Service Life Period: Constant Failure Rate Model
  • 7.17.2.1 Rationale for the Pervasiveness of the Constant Failure Rate Model
  • 7.17.2.2 Examples of Empirical Service Life Periods
  • 7.17.2.3 Conclusions: Empirical Service Life Periods
  • 7.17.3 Wearout Period
  • 7.18 Failure Rates of Humans and Components
  • References.