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Inferences on the lifetime performance index for Weibull distribution based on censored observations using the max -value method

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  • Wen-Chuan Lee

Abstract

In the service (or manufacturing) industries, process capability indices (PCIs) are utilised to assess whether product quality meets the required level. And the lifetime performance index (or larger-the-better PCI) CL is frequently used as a means of measuring product performance, where L is the lower specification limit. Hence, this study first uses the max p-value method to select the optimum value of the shape parameter β of the Weibull distribution and β is given. Second, we also construct the maximum likelihood estimator (MLE) of CL based on the type II right‐censored sample from the Weibull distribution. The MLE of CL is then utilised to develop a novel hypothesis testing procedure provided that L is known. Finally, we give one practical example to illustrate the use of the testing procedure under given significance level α.

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  • Wen-Chuan Lee, 2011. "Inferences on the lifetime performance index for Weibull distribution based on censored observations using the max -value method," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(6), pages 931-937.
    • Handle: RePEc:taf:tsysxx:v:42:y:2011:i:6:p:931-937
    DOI: 10.1080/00207720903260168
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    Cited by:

    1. Laumen Benjamin & Cramer Erhard, 2015. "Likelihood Inference for the Lifetime Performance Index under Progressive Type-II Censoring," Stochastics and Quality Control, De Gruyter, vol. 30(2), pages 59-73, December.
    2. Lee, Amy H.I. & Wu, Chien-Wei & Wang, To-Cheng & Kuo, Ming-Han, 2024. "Construction of acceptance sampling schemes for exponential lifetime products with progressive type II right censoring," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Mohammad Vali Ahmadi & Mahdi Doostparast & Jafar Ahmadi, 2015. "Statistical inference for the lifetime performance index based on generalised order statistics from exponential distribution," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(6), pages 1094-1107, April.

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