A Study on the Experimental Design for the Lifetime Performance Index of Rayleigh Lifetime Distribution under Progressive Type I Interval Censoring
Shu-Fei Wu,
Tzu-Hsuan Liu,
Yu-Hua Lai and
Wei-Tsung Chang
Additional contact information
Shu-Fei Wu: Department of Statistics, Tamkang University, Tamsui, Taipei 251301, Taiwan
Tzu-Hsuan Liu: Department of Statistics, Tamkang University, Tamsui, Taipei 251301, Taiwan
Yu-Hua Lai: Department of Statistics, Tamkang University, Tamsui, Taipei 251301, Taiwan
Wei-Tsung Chang: Department of Computer Science, University of Taipei, Taipei 100234, Taiwan
Mathematics, 2022, vol. 10, issue 3, 1-15
Abstract:
With the rapid development of technology, improving product life performance has become a very important issue in recent decades. The lifetime performance index is used in this research for the assessment of the lifetime performance of products following the Rayleigh distribution. Based on the hypothesis testing procedure with this index, using the maximum likelihood estimator as a testing statistic, the sampling design is determined and the related values are tabulated for practical use to reach the given power level and minimize the total experimental cost under progressive type I interval censoring. When the inspection interval length is fixed and the number of inspection intervals is not fixed, the required number of inspection intervals and sample size with the minimum total cost are determined and tabulated. When the termination time is not fixed, the required number of inspection intervals, sample size and equal interval length reaching the minimum total cost are determined and tabulated. Lastly, a practical example is given to illustrate the use of this sampling design for the testing procedure to determine whether the process is capable.
Keywords: censored sample; Rayleigh distribution; maximum likelihood estimator; lifetime performance indices; testing algorithmic procedure; sampling design (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.mdpi.com/2227-7390/10/3/517/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/3/517/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:3:p:517-:d:742866
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().