**Course Overview**

This course teaches participants the fundamental concepts and methods needed to analyze and understand reliability data. The course focuses on the proper application of statistical methods to model failure data, estimate quantities of interest for both components and systems, and make predictions. Knowledge of basic algebra is helpful. Computer software is utilized, although an understanding of underlying concepts and methods is stressed.

**Seminar Content**

- Reliability Concepts and Reliability Data
- Reliability in Product and Process Development
- Unique Characteristics of Reliability Data
- Censored Data
- Probability and Statistics Concepts
- Basic Probability Concepts
- Probability Distributions (e.g. Weibull, Lognormal, etc.)
- Probability Distribution Functions
- Cumulative Distribution Functions
- Hazard Rate
- Mean Time to Failure
- Percentiles
- Conditional Reliability
- Reliability of Systems
- Series Systems
- Parallel Systems
- Complex Systems
- Assessing & Selecting Parametric Models for Failure Time Distributions
- Probability Plotting with and without Censored Data
- Parameter Estimation From Probability Plots
- Using Software to Identify the Best Distribution
- Parametric Estimation of Reliability Characteristics
- Estimation Methods (Maximum Likelihood, Rank Regression)
- Precision of Estimates/Confidence Intervals
- Using Software for Reliability Estimation
- Nonparametric Estimation of Reliability Characteristics
- Estimation with Exact Failures
- Estimation with Censored Data (Kaplan-Meier estimator)
- Using Software for Nonparametric Estimation
- Introduction to Reliability Test Planning
- Test planning regimes
- Using Software for Reliability Estimation Test Plans
- Reliability Demonstration Test Plans