Effect Of Reliability Distribution' Parameters Case Study: Gumbel’S Bivariate Exponential

The vast majority of variable exponent distributions retire in the context of reliability in one way. When talking about reliability, consider mainly the time lag between device interference and failure. In a bivariate or multivariate context, it is concerned with dependencies between failures, such as those of two components of the system. The univariate exponential distribution is also important in describing that age for a single component. Bivariate distributions with exponential marginal are also very widely used in describing the lifetime of the two components together. Bivariate exponential distributions often arise from shocks that cause cumulative damage to components that will eventually destroy components or cause cumulative damage. The shock numbers N1 and N2 required to multiply components 1 and 2, respectively, have a bivariate geometric distribution. This research concerns on Stress-Strength Reliability of a Two Component System by using Gumbel’s Bivariate Exponential Distribution, type1. An application of the results is also provided in devices failure data.