This course is specifically designed to meet the analytical needs of those individuals working within FDA regulated industries. Areas of focus are distribution analysis, area under the curve estimation, hypothesis testing, life and survival estimation, thermal sensitivity, confidence intervals and multiple factor modeling. The course requires 8 hours of instruction.
This course is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
Engineering Statistics and Data Analysis is a recommended course prior to taking LTRA.
- Determine product reliability performance.
- Understand and apply non-parametric reliability analysis.
- Understand and apply parametric reliability analysis.
- Perform multivariate reliability assessment.
- Understand and apply recurrence analysis.
- Use Arrhenius transformations in reliability modeling.
- Select appropriate sample sizes for MTBF studies.
- Model reliability improvement using reliability growth models.
Detailed Course Outline
Introduction to reliability analysis and basic statistics
Nonparametric reliability analysis (Kaplan-Meier)
Parametric reliability analysis (LogNormal, Exponential, Weibull)
Lifetime distribution analysis
Fit Life by X
Multivariate reliability analysis (Parametric Survival)
Reliability growth analysis