SIMULATING ACCELERATED LIFE TESTING MODEL FOR EXPONENTIATED EXPONENTIAL DATA USING GEOMETRIC PROCESS

Accelerated life testing has now become the primary method for rapidly assessing product reliability and designing efficient test plans is a vital step in ensuring that accelerated life tests can properly, quickly and economically assess product reliability. These tests subject the sample to high levels of stress. Then, based on the stress-life relationship, the product's life at a normal stress level can be calculated by extrapolating the life information from a sample at a high-stress level to the normal level. The study describes the Exponentiated Exponential model, which is used to analyze the accelerated life testing plan under the assumption that the lifetimes of items subjected to increasing stress are formed by a geometric process. The maximum likelihood (ML) approach is used to estimate the model parameters. The asymptotic variance of the ML estimators is evolved by the Fisher information matrix. A computer simulation algorithm is conducted to analyze the theoretical results.