Reliability is a statistical approach to describing the dependability and the ability of a system or component to function under stated conditions for a specified period of time in the presence of uncertainty. In this chapter, we provide the statistical definition of reliability, and further introduce the concepts of failure rate, hazard rate, bathtub curve, and their relation with the reliability function. We also present several lifetime metrics that are commonly used in industry, such as mean time between failures, mean time to failure, and mean time to repair. For repairable systems, failure intensity rate, mean time between replacements and system availability are the primary reliability measures. The role of line replaceable unit and consumable items in the repairable system is also elaborated. Finally, we discuss the parametric models commonly used for lifetime prediction and failure analysis, which include Bernoulli, binomial, Poisson, exponential, Weibull, normal, lognormal, and gamma distributions. The chapter is concluded with the reliability inference using Bayesian theory and Markov models.
1.2 Reliability Definition and Hazard Rate
1.2.1 Managing Reliability for Product Lifecycle
Reliability engineering is an interdisciplinary field that studies, evaluates, and manages the lifetime performance of components and systems, such as automobile, wind turbines (WTs), aircraft, Internet, medical devices, power system, ...