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Computational testing algorithmic procedure of assessment for lifetime performance index of products with one-parameter exponential distribution under progressive type I interval censoring

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  • Wu, Shu-Fei
  • Lin, Ying-Po

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 exponential 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.

Suggested Citation

  • Wu, Shu-Fei & Lin, Ying-Po, 2016. "Computational testing algorithmic procedure of assessment for lifetime performance index of products with one-parameter exponential distribution under progressive type I interval censoring," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 120(C), pages 79-90.
    • Handle: RePEc:eee:matcom:v:120:y:2016:i:c:p:79-90
    DOI: 10.1016/j.matcom.2015.06.013
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    References listed on IDEAS

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    1. Shuo‐Jye Wu & Ying‐Po Lin & Yi‐Ju Chen, 2006. "Planning step‐stress life test with progressively type I group‐censored exponential data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(1), pages 46-56, February.
    2. Shu-Fei Wu, 2010. "Interval estimation for the two-parameter exponential distribution under progressive censoring," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(1), pages 181-189, January.
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    Cited by:

    1. Jianping Zhu & Hua Xin & Chenlu Zheng & Tzong-Ru Tsai, 2021. "Inference for the Process Performance Index of Products on the Basis of Power-Normal Distribution," Mathematics, MDPI, vol. 10(1), pages 1-14, December.
    2. Mohammad Vali Ahmadi & Jafar Ahmadi & Mousa Abdi, 2019. "Evaluating the lifetime performance index of products based on generalized order statistics from two-parameter exponential model," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 251-275, April.
    3. Shu-Fei Wu, 2023. "Sample Size Determination for Two-Stage Multiple Comparisons for Exponential Location Parameters with the Average," Mathematics, MDPI, vol. 11(2), pages 1-11, January.
    4. Kuen-Suan Chen & Tsang-Chuan Chang, 2022. "Fuzzy testing model for the lifetime performance of products under consideration with exponential distribution," Annals of Operations Research, Springer, vol. 312(1), pages 87-98, May.
    5. Shu-Fei Wu & Yi-Jun Xie & Mao-Feng Liao & Wei-Tsung Chang, 2021. "Reliability Sampling Design for the Lifetime Performance Index of Gompertz Lifetime Distribution under Progressive Type I Interval Censoring," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    6. Tzong-Ru Tsai & Hua Xin & Ya-Yen Fan & Yuhlong Lio, 2022. "Bias-Corrected Maximum Likelihood Estimation and Bayesian Inference for the Process Performance Index Using Inverse Gaussian Distribution," Stats, MDPI, vol. 5(4), pages 1-18, November.
    7. Shu-Fei Wu & Meng-Zong Song, 2023. "Experimental Design for Progressive Type I Interval Censoring on the Lifetime Performance Index of Chen Lifetime Distribution," Mathematics, MDPI, vol. 11(6), pages 1-16, March.

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