Optimal Design for Step-Stress Accelerated Test with Random Discrete Stress Elevating Times Based on Gamma Degradation Process

• Published in: Quality and reliability engineering international Vol. 32; no. 7; pp. 2391 - 2402
• Main Authors: Amini, Morteza, Shemehsavar, Soudabeh, Pan, Zhengqiang
• Format: Journal Article
• Language: English
• Published: Bognor Regis Blackwell Publishing Ltd 01.11.2016; Wiley Subscription Services, Inc
• Subjects: Accelerated tests; Asymptotic properties; Degradation; discrete times; Economic models; Economics; Fisher information matrix; gamma process; inverse Gaussian distribution; Optimization; Stresses; Thresholds
• ISSN: 0748-8017; 1099-1638
• DOI: 10.1002/qre.1943

Recently, a step‐stress accelerated degradation test plan, in which the stress level is elevated when the degradation value of a product crosses a prespecified value, was proposed. The times of stress level elevating are random and vary from product to product. In this paper, we extend this model to a more economic plan. The proposed extended model has two economical advantages compared with the previous one. The first is that the times of stress level elevating in the new model are identical for all products, which enable us to use only one chamber (oven) for testing all test units. The second is that, the new method does not require continuous inspection and to elevate the stress level, it is not necessary for the experimenter to inspect the value of the degradation continually. The new method decreases the cost of measurement, and also there is no need to use electronic sensors to detect the first passage time of the degradation to the threshold value in the new method. We assume that the degradation path follows a gamma process. The stress level is elevated as soon as the measurement of the degradation of one of the test units, at one of the specified times, exceeds the threshold value. Under the constraint that the total experimental cost does not exceed a prespecified budget, the optimal settings including the optimal threshold value, sample size, measurement frequency, and termination time are obtained by minimizing the asymptotic variance of an estimated quantile of the lifetime distribution of the product. A case study is presented to illustrate the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.