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Improved Group Acceptance Sampling Plan for Dagum Distribution under Percentiles Lifetime

  • Received : 20110200
  • Accepted : 20110500
  • Published : 2011.07.31

Abstract

This paper deals with a group acceptance sampling plan for time truncated tests which are based on the total number of failures from the whole group assuming that the life time of an item follows the Dagum (inverse Burr) distribution. This study is developed when a multiple number of items as a group can be tested simultaneously in a tester. The minimum number of groups required for a given group size and acceptance number is determined such that the producer and consumer risks are satisfied simultaneously at the specified quality level, while the termination time and the number of testers are specified. Comparisons are made between the proposed plan and the existing plan on the basis of size of the groups. Two real examples are provided.

Keywords

References

  1. Aslam, M., (2008). Economic reliability acceptance sampling plan for generalized Rayleigh distribution, Journal of Statistics, 15, 26-35.
  2. Aslam, M. and Jun, C.-H. (2009a). A group acceptance sampling plan for truncated life test having Weibull distribution, Journal of Applied Statistics (UK), 39, 1021-1027.
  3. Aslam, M. and Jun, C. H. (2009b). A group acceptance sampling plans for truncated life tests based on the inverse Rayleigh and log-logistic distributions, Pakistan Journal of Statistics, 25, 107-119.
  4. Aslam, M. and Jun, C. H. (2010). A double acceptance sampling plan for generalized log-logistic distributions with known shape parameters, Journal of Applied Statistics, 37, 405-414. https://doi.org/10.1080/02664760802698979
  5. Aslam, M. and Kantam, R. R. L. (2008). Economic reliability acceptance sampling based on truncated life tests in the Birnbaum-Saunders distribution, Pakistan Journal of Statistics, 24, 269-276.
  6. Aslam, M. and Shahbaz, M. Q. (2007).Economic Reliability Tests Plans using the Generalized Exponential Distribution, Journal of Statistics, 14, 52-59.
  7. Baklizi, A. (2003). Acceptance sampling based on truncated life tests in the Pareto distribution of the second kind, Advances and Applications in Statistics, 3, 33-48.
  8. Balakrishnan, N., Leiva, V. and Lopez, J. (2007). Acceptance sampling plans from truncated life tests based on the generalized Birnbaum-Saunders distribution, Communications in Statistics - Simulation and Computation, 36, 643-656. https://doi.org/10.1080/03610910701207819
  9. Dagum, C. (1977). A new model of personal income distribution: specification and estimation, Economic Appliquee, 30, 413-437.
  10. Domma, F. G., Latorre and Zenga, M. (2009). Reliability studies of Dagum distribution, submitted.
  11. Epstein, B. (1954). Truncated life tests in the exponential case, Annals of Mathematical Statistics, 25, 555-564. https://doi.org/10.1214/aoms/1177728723
  12. Fertig, F.W. and Mann, N. R. (1980). Life test sampling plans for two parameterWeibull populations, Technometrics, 22, 165-177. https://doi.org/10.2307/1268455
  13. Goode, H. P. and Kao, J. H. K. (1961). Sampling plans based on the Weibull distribution, In Proceeding of the Seventh National Symposium on Reliability and Quality Control, (24-40). Philadelphia.
  14. Jun, C. H., Balamurali, S. and Lee, S. H. (2006). Variables sampling plans for Weibull distribution lifetimes under sudden death testing, IEEE Transactions on Reliability, 55, 53-58. https://doi.org/10.1109/TR.2005.863802
  15. Kantam, R. R. L. and Rosaiah, K. (1998). Half logistic distribution in acceptance sampling based on life tests, IAPQR Transactions, 23, 117-125.
  16. Kantam, R. R. L., Rosaiah, K. and Rao, G. S. (2001). Acceptance sampling based on life tests: Log-logistic models, Journal of Applied Statistics, 28, 121-128. https://doi.org/10.1080/02664760120011644
  17. Lio, Y. L., Tsai, Tzong-Ru andWu, Shuo-Jye. (2010a). Acceptance sampling plans from truncated life tests based on the Birnbaum-saunders distribution for Percentiles, Communications in Statistics - Simulation and Computation, 39, 119-136.
  18. Lio, Y. L., Tsai, Tzong-Ru and Wu, Shuo-Jye. (2010b). Acceptance sampling plans from truncated life tests based on Burr type XII percentiles, Journal of Chinese institute of Industrial Engineers, 27, 270-280. https://doi.org/10.1080/10170661003791029
  19. Pascual, F. G. and Meeker, W. Q. (1998). The modified sudden death test: Planning life tests with a limited number of test positions, Journal of Testing and Evaluation, 26, 434-443. https://doi.org/10.1520/JTE12692J
  20. Rosaiah, K. and Kantam, R. R. L. (2005). Acceptance sampling based on the inverse Rayleigh distribution, Economic Quality Control, 20, 277-286. https://doi.org/10.1515/EQC.2005.277
  21. Rosaiah, K., Kantam, R. R. L. and Santosh Kumar, Ch. (2006). Reliability of test plans for exponentiated log-logistic distribution, Eco.Quality Control, 21, 165-175.
  22. Rosaiah, K., Kantam, R. R. L. and Santosh Kumar, Ch. (2007). Exponentiated log-logistic distribution-An economic reliability test plan, Pakistan Journal of Statistics, 23, 147-146.
  23. Srinivasa Rao, G., Ghitany, M. E., Kantam, R. R. L. (2009). Acceptance sampling plans for Marshal-Olkin extended Lomax distribution, International Journal of Applied Mathematics, 22, 139-148.
  24. Tsai, T. R. and Wu, S. J. (2006). Acceptance sampling based on truncated life tests for generalized Rayleigh distribution, Journal of Applied Statistics, 33, 595-600. https://doi.org/10.1080/02664760600679700
  25. Vleek, B. L., Hendricks, R. C. and Zaretsky, E. V. (2003). Monto Carlo simulation of Sudden Death Bearing Testing, NASA, Hanover, MD, USA.

Cited by

  1. The Weibull–Dagum distribution: Properties and applications vol.45, pp.24, 2016, https://doi.org/10.1080/03610926.2014.983610