The assessment on the lifetime performance index of products with Gompertz distribution based on the progressive type I interval censored sample

2019 ◽  
Vol 351 ◽  
pp. 66-76 ◽  
Author(s):  
Shu-Fei Wu ◽  
Ya-Ting Hsieh
Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1691
Author(s):  
Shu-Fei Wu ◽  
Yu-Cheng Wu ◽  
Chi-Han Wu ◽  
Wei-Tsung Chang

In this study, the experimental design is developed based on the testing procedure for the lifetime performance index of products following Weibull lifetime distribution under progressive type I interval censoring. This research topic is related to asymmetrical probability distributions and applications across disciplines. The asymptotic distribution of the maximum likelihood estimator of the lifetime performance index is utilized to develop the testing procedure. In order to reach the given power level, the minimum sample size is determined and tabulated. In order to minimize the total cost that occurred under progressive type I interval censoring, the sampling design is investigated to determine the minimum number of inspection intervals and equal interval lengths when the termination time of experiment is fixed or not fixed. For illustrative aims, one practical example is given for the implementation of our proposed sampling design to collect the progressive type I interval censored sample so that the users can use this sample to test if the lifetime performance index exceeds the desired target level.


Author(s):  
Shuo Gao ◽  
Wenhao Gui

Lifetime performance index is a powerful and effective way to analyze whether a product achieves the specified standards. In this paper, we investigate the lifetime performance index for the inverted exponential Rayleigh distribution using progressive type II censored sample data. The censored sample is able to greatly save the cost of the experiment and speed up the experiment. We derive the estimation value of lifetime performance index using the maximum likelihood method, and conduct the hypothesis test. Based on extensive numerical simulation, the power function is utilized to assess effectiveness of hypothesis testing. The simulation results show that lifetime performance index is good for determining whether the lifetime of the product reaches the criterion. Finally, a practical dataset is provided to give a demonstration for the procedures of lifetime performance evaluation.


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