Reliability Engineering and Survival Analysis (1.0 days)

Statistical Methods for Reliability Engineering and Survival Analyses:

This course covers the graphical and quantitative methods used reliability and survival analysis using JMP software. We will explore statistical methods to characterize and predict reliability and probability of survival. Topics include censoring, probability distributions—particularly Weibull and Lognormal, sample size determination, degradation/stability analysis, reliability with covariates/predictor variables, survival analysis, and fitting parametric survival models.

Statistical Methods for Reliability Engineering and Survival Analyses Objectives:

• Understand why and how to censor data from survival studies
• Be able to interpret nonparametric survival plots and models
• Determine the best probability distribution and parameter estimates to characterize reliability
• Be able to model the impact of predictor variables (covariates)
• Calculate sample size estimates for reliability demonstrations
• Model system performance with survival and parametric survival techniques

1. Introduction to Reliability Methods
• Censoring and event plots
• Functions and definitions: reliability, survival, hazard, cumulative
• Nonparametric survival methods
• Probability distributions for reliability analysis

2. Reliability and Survivability Models
• Survival analysis
• Reliability with a single predictor variable
• Reliability with multiple predictor variables using parametric survival models

3. Advanced Approaches
• Degradation and stability analysis
• Sample size determination
• Accelerated life tests