AVERAGE RUN LENGTH FOR EXPONENTIATED DISTRIBUTION UNDER TRUNCATED LIFE TEST

Statistical quality control discusses about the screening and preserving the quality of products and services. Control charts are used widely in manufacturing industry. The acceptance sampling plans for truncated life tests are regularly practiced to regulate the sample size from a lot under inspection. Traditional control chart needs more samples for testing the quality of the product. In this paper, failure time of a product follows non-normal distributions like Exponentiated Gamma Distribution, Exponentiated Lomax Distribution and Beta Weibull Distribution. The defectives that are found are put into truncated life test and upper and lower control limits are computed. Control charts using these distributions are designed to monitor the mean shift by detecting the number of unsuccessful products at a definite time. The probability for the in-control process and out of control process are estimated from the sample data. The Average Run Length (ARL) allows an assessment to be considered for various screening policies and based on the various mean shift, the ARL values are computed for various distributions and compared.