2 - Basic reliability concepts and conventions used for determining the losses from failures

Abstract

This chapter discusses the basic reliability concepts and conventions used for determining the losses from failures. This chapter examines the distribution of the time to failure is a key to determining the reliability of components and systems. Differentiating the cumulative distribution of the time to failure yields the probability density of the time to failure. Failures of repairable systems are broadly divided into several basic categories that are given in this chapter. For the purposes of illustrating the basic concepts of this book, only critical and non-critical failures are considered. A popular reliability measure is the mean time to failure (MTTF), which is the average time to the first failure. It can be obtained from the mean of the probability density of the time to failure. Reliability can be interpreted as the probability of surviving a specified minimum failure-free operating period (MFFOP) without a critical failure. If the distribution of the time to failure is the negative exponential distribution a large MTTF means large reliability. The chapter illustrates various models, such as, hazard rate and time to failure distribution; homogeneous Poisson process and its link with the negative exponential distribution; Weibull model; reliability bathtub curve for non-repairable components/systems; and production availability. Redundancy is a technique whereby one or more components in a system are replicated in order to increase reliability. Active and passive redundancy is also discussed. This chapter explains building reliability networks and its type of components. Pseudo-code conventions used in the algorithms for risk-based reliability analysis are given.