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Designing Degradation Experiments Using a Log-Logistic Distribution

Assessing the reliability of a product is very important to improve the product’s quality and to get the trust of customers. Degradation experiments are usually used to assess the reliability of highly reliable products, which are not expected to fail under the traditional life tests. Several decision variables, such as the sample size, the inspection frequency, and the termination time, have a direct influence on the experimental cost and the estimation precision of lifetime information. This paper deals with the optimal design of a degradation experiment where the degradation rate follows a log-logistic distribution. Under the constraint that the total experimental cost does not exceed a predetermined budget, the optimal decision variables are obtained by minimizing the mean squared error of the estimated 100pth percentile of the lifetime distribution of the product. A simulation study and a real example of drug potency data are provided to illustrate the proposed method.