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Computational testing algorithmic procedure of assessment for lifetime performance index of Pareto products under progressive type I interval censoring

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Abstract

Process capability indices had been widely used to evaluate the process performance to the continuous improvement of quality and productivity. When the lifetime of products possesses a one-parameter Pareto distribution, the larger-the-better lifetime performance index is considered. The maximum likelihood estimator is used to estimate the lifetime performance index based on the progressive type I interval censored sample. The asymptotic distribution of this estimator is also investigated. We use this estimator to develop the new hypothesis testing algorithmic procedure in the condition of known lower specification limit. Finally, two practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.

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Acknowledgements

The author wish to thank an associate editor and referees for their careful reading and valuable suggestions so that the article is more readable and applicable. The author’s research was supported by The National Science Council NSC101-2118-M-032-003- and Ministry of Science and Technology MOST 103-2118-M-032-004-MY2 and MOST 105-2118-M-032-005-MY2 in Taiwan, ROC.

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Authors and Affiliations

  1. Department of Statistics, Tamkang University, Tamsui, Taipei, 25137, Taiwan, ROC

    Shu-Fei Wu

  2. National Taipei University of Business Office of Institutional Research, Taipei, Taiwan, ROC

    Jin-Yang Lu

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  1. Shu-Fei Wu
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  2. Jin-Yang Lu
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Correspondence to Shu-Fei Wu.

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Wu, SF., Lu, JY. Computational testing algorithmic procedure of assessment for lifetime performance index of Pareto products under progressive type I interval censoring. Comput Stat 32, 647–666 (2017). https://doi.org/10.1007/s00180-017-0717-3

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  • DOI: https://doi.org/10.1007/s00180-017-0717-3

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