Agric. Econ. - Czech, 2016, 62(12):550-555 | DOI: 10.17221/293/2015-AGRICECON

Economic efficiency of the AOQL single sampling plans for the inspection by variablesOriginal Paper

Jindrich Klufa
Department of Mathematics, Faculty of Informatics and Statistics, University of Economics, Prague, Czech Republic

The paper refers to the AOQL (Average Outgoing Quality Limit) single sampling plans when the remainder of the rejected lots is inspected. These rectifying AOQL plans for inspection by variables were created by the author of this paper and published in the Statistical Papers. These new plans were compared with the corresponding Dodge-Romig AOQL plans for inspection by attributes from the economic point of view. Numerical investigations confirm that under the same protection of consumer, the AOQL plans for inspection by variables are in many situations more economical than the corresponding Dodge-Romig AOQL attribute sampling plans. The dependence of the saving of the inspection cost on the input parameters of acceptance sampling (the average outgoing quality limit, the lot size and the process average proportion defective) is analysed in the paper. Moreover, a criterion for deciding if the inspection by variables should be considered instead of the inspection by attributes is suggested in the paper.

Keywords: acceptance sampling, average outgoing quality limit, economical aspects

Published: December 31, 2016  Show citation

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Klufa J. Economic efficiency of the AOQL single sampling plans for the inspection by variables. Agric. Econ. - Czech. 2016;62(12):550-555. doi: 10.17221/293/2015-AGRICECON.
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    References

    1. Aslam M., Azam M., Jun C.-H. (2015): A new lot inspection procedure based on exponentially weighted moving average. International Journal of Systems Science, 46: 1392-1400.
    2. Balamurali S., Azam M., Aslam M. (2014): Attribute-Variable Inspection Policy for Lots using Resampling Based on EWMA. Communications in Statistics - Simulation and Computation, 45: 3014-3035. Go to original source...
    3. Chen C.H., Chou C.Y. (2001): Economic design of DodgeRomig lot tolerance per cent defective single sampling plans for variables under Taguchi's quality loss function. Total Quality Management, 12: 5-11. Go to original source...
    4. Ho L.L., Quinino R.D., Suyama E., Lourenco R.P. (2012): Monitoring the conforming fraction of high-quality processes using a control chart p under a small sample size and an alternative estimator. Statistical Papers, 53: 507-519. Go to original source...
    5. Dodge H.F., Romig H.G. (1998): Sampling Inspection Tables: Single and Double Sampling. John Wiley, New York.
    6. Hald A. (1981): Statistical Theory of Sampling Inspection by Attributes. Academic Press, London.
    7. Jennett W.J., Welch B.L. (1939): The control of proportion defective as judged by a single quality characteristic varying on a continuous scale. Supplement to the Journal of the Royal Statistical Society, 6: 80-88. Go to original source...
    8. Kaspříková N. (2012): LTPDvar: LTPD plans for sampling inspection by variables. R package version 1.0. Available at http://CRAN.R-project.org/package=LTPDvar
    9. Kasprikova N., Klufa J. (2015): AOQL sampling plans for inspection by variables and attributes versus the plans for inspection by attributes. Quality Technology & Quantitative Management, 12: 133-142. Go to original source...
    10. Klufa J. (1997): Dodge-Romig AOQL single sampling plans for inspection by variables. Statistical Papers, 38: 111-119. Go to original source...
    11. Klufa J. (2008): Dodge-Roming AOQL plans for inspection by variables from numerical point of view. Statistical Papers, 49: 1-13. Go to original source...
    12. Klufa J. (2015): Economic aspects of the LTPD single sampling inspection plans. Agricultural Economics, 61: 326-331. Go to original source...
    13. R Development Core Team (2011): R: A Language and Environment for Statistical Computing. Vienna, Austria: the R Foundation for Statistical Computing. Available online at http://www.R-project.org/
    14. Wang F.K., Lo S.-C. (2015): Single Mixed Sampling Plan Based onYield Index for Linear Profiles. Quality and Reliability Engineering International. First published: 14 September 2015.
    15. Wilrich P.T. (2012): Bayesian sampling plans for inspection by variables. Frontiers in Statistical Quality Control, 10: 227-249. Go to original source...
    16. Yen C.-H., Aslam M., Jun C.-H. (2014): A lot inspection sampling plan based on EWMA yield index. The International Journal of Advanced Manufacturing Technology, 75: 861-868. Go to original source...

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