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Advanced Reliability Analysis

This course builds on the fundamental reliability concepts and methods learned in the Reliability Analysis course. This course goes beyond reliability estimation and reporting by covering methods for improving reliability. This course covers the fundamentals of Quantitative Accelerated Life Testing (ALT). Other advanced topics include the analysis of repairable systems data, and analyzing binary response data. It is assumed that participants have taken the Reliability Analysis course (or equivalent).

Seminar Content (2 or 3 Days)

  1. Regression Modeling of Reliability Data
    • Overview of Simple Linear Regression Models
    • Lognormal and Weibull Accelerated Failure Time (AFT) Models
    • Using Software for Regression of Failure Time Data (Example)
  2. Introduction to Accelerated Life Testing
    • Purpose and Concepts
    • Types of Accelerated Tests
    • Types of Stress Loadings
  3. Accelerated Life Test Models
    • Stochastic Models (Failure time distributions)
    • Structural/Life-Stress Models
    • Acceleration Factor
    • Single Factor Models (Arrhenius, Eyring, Inverse Power Law)
    • Guidelines for ALT Models
    • Example of ALT Data Analysis and Modeling
    • Participant Exercises
  4. Two-Stress and Multiple Stress ALT Models
    • Temperature-Humidity Model
    • Temperature-Non Thermal Model
    • Generalized Eyring Model
    • Proportional Hazards Model
    • General Model Formulation (with Transformations)
    • Participant Exercises
  5. Time-Varying Stress Tests
    • Step Stress Tests
    • Modeling Time-Varying Stresses (Cumulative Damage Models)
    • Time-Varying Use Stress
    • Participant Exercises
  6. Accelerated Degradation Analysis
    • Degradation Models (Linear, Exponential, Power, etc.)
    • Degradation Modeling at Accelerated Conditions
    • Examples and Participant Exercises
  7. Planning Accelerated Life Tests
    • Traditional, Statistically Optimum, and Compromise Plans
    • Test Planning Guidelines
    • Sample Sizes
    • Allocation of Units to Stress Conditions
    • Precision of Estimates
    • Test Plans for one and two Stresses
    • Participant Exercises
  8. Repairable Systems Analysis
    • Mean Cumulative Function
    • Rate of Occurrence of Failure (ROCOF)
    • Parametric Models for Repairable Systems
    • Homogeneous Poisson process and Non-Homogeneous Poisson process
    • Power ROCOF Model
    • Tests for Trends
  9. Analysis of Binary Response Data
    • Probit Model
    • Analysis of Binary Response Data