8. Assessing Product Reliability

8.1.	Introduction

This section introduces the terminology and models that will be used to describe and quantify product reliability. The terminology, probability distributions and models used for reliability analysis differ in many cases from those used in other statistical applications.

Detailed contents of Section 1

1. Introduction 
1. Why is the assessment and control of product reliability important? 
1. Quality versus reliability 
2. Competitive driving factors
3. Safety and health considerations 
2. What are the basic terms and models used for reliability evaluation? 
1. Repairable systems, non-repairable populations and lifetime distribution models 
2. Reliability or survival function 
3. Failure (or hazard) rate 
4. "Bathtub" curve 
5. Repair rate or ROCOF 
3. What are some common difficulties with reliability data and how are they overcome? 
1. Censoring 
2. Lack of failures 
4. What is "physical acceleration" and how do we model  it? 
5. What are some common acceleration models? 
1. Arrhenius 
2. Eyring 
3. Other models 
6. What are the basic lifetime distribution models used for non-repairable populations? 
1. Exponential 
2. Weibull 
3. Extreme value distributions
4. Lognormal 
5. Gamma 
6. Fatigue life (Birnbaum-Saunders) 
7. Proportional hazards model 
7. What are some basic repair rate models used for repairable systems? 
1. Homogeneous Poisson Process (HPP) 
2. Non-Homogeneous Poisson Process (NHPP) with power law 
3. Exponential law 
8. How can you evaluate reliability from the "bottom-  up" (component failure mode to system failure rates)? 
1. Competing risk model 
2. Series model 
3. Parallel or redundant model 
4. R out of N model 
5. Standby model 
6. Complex systems
9. How can you model reliability growth? 
1. NHPP power law 
2. Duane plots 
3. NHPP exponential law 
10. How can Bayesian methodology be used for reliability evaluation?