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DESIGN OF $u$ AND $p$ CONTROL CHARTS FOR IMPRECISE DATA WITH MEDICAL APPLICATION
Keywords:
blood components; attribute charts; classical statistics; uncertainty; monitoring.DOI:
https://doi.org/10.17654/0973514324006Abstract
Background. The prevalent blood components monitoring a control chart by characteristics use classical statistics. This is applicable only in the presence of a determinate fraction of defectives or all observations in the sample. The primary aim of this paper is to present $u$ and $p$ control charts within the framework of neutrosophic statistics. We employ these newly introduced control charts to oversee the monitoring of blood components.
Methods. This paper presents new (neutrosophic) attribute control charts for nursing blood constituents under neutrosophic statistics.
Results. The strategy of the proposed control chart is specified using the neutrosophic interval method. The applications of neutrosophic control charts show that these are relatively effective, informative, flexible, and adequate for monitoring blood constituents in an ambiguous environment.
Received: September 27, 2023
Revised: October 26, 2023
Accepted: November 9, 2023
References
S. Aebtarm and N. Bouguila, An empirical evaluation of attribute control charts for monitoring defects, Expert Systems with Applications 38(6) (2011), 7869-7880.
W. Albers and W. C. Kallenberg, Empirical non-parametric control charts: estimation effects and corrections, J. Appl. Stat. 31(3) (2004), 345-360.
R. W. Amin, M. R. Reynolds Jr. and B. Saad, Non-parametric quality control charts based on the sign statistic, Comm. Statist. Theory Methods 24(6) (1995), 1597-1623.
O.-H. Arif, M. Aslam and C.-H. Jun, EWMA NP control chart for the Weibull distribution, Journal of Testing and Evaluation 45(3) (2017), 1022-1028.
M. Aslam, Design of X-bar control chart for resampling under uncertainty environment, IEEE Access 7 (2019), 60661-60671.
M. Aslam, M. Azam, K.-J. Kim and C.-H. Jun, Designing of an attribute control chart for two-stage process, Measurement and Control 51(7-8) (2018), 285-292.
M. Aslam and N. Khan, A new variable control chart using neutrosophic interval method an application to automobile industry, Journal of Intelligent and Fuzzy Systems 36(3) (2019), 2615-2623.
M. Aslam, R. A. Bantan and N. Khan, Design of a new attribute control chart under neutrosophic statistics, Int. J. Fuzzy Syst. 21(2) (2019), 433-440.
M. Aslam and M. A. Raza, Design of new sampling plans for multiple manufacturing lines under uncertainty, Int. J. Fuzzy Syst. 21(3) (2019), 978-992.
S. T. Bakir, A distribution-free Shewhart quality control chart based on signed-ranks, Quality Engineering 16(4) (2004), 613-623.
S. Chakraborti and S. Eryilmaz, A non-parametric Shewhart type signed-rank control chart based on runs, Comm. Statist. Simulation Comput. 36(2) (2007), 335-356.
S. Chatterjee and P. Qiu, Distribution-free cumulative sum control charts using bootstrap-based control limits, The Annals of Applied Statistics 3(1) (2009), 349-369.
N. Chukhrova and A. Johannssen, Employing fuzzy hypothesis testing to improve modified p charts for monitoring the process fraction nonconforming, Inform. Sci. 633 (2023), 141-157.
A. Duclos and N. Voirin, The p-control chart: a tool for care improvement, International Journal for Quality in Health Care 22(5) (2010), 402-407.
N. Erginel, Fuzzy rule-based and control charts, Journal of Intelligent and Fuzzy Systems 27 (2014), 159-171.
S. Haridy, Z. Wu, K. M. Lee and M. A. Rahim, An attribute chart for monitoring the process mean and variance, International Journal of Production Research 52(11) (2014), 3366-3380.
I. Kaya, A. Karasan, E. Ilbahar and B. Cebeci, Analyzing attribute control charts for defectives based on intuitionistic fuzzy sets, Conference Proceeding of 3rd International Conference on Mathematical Advances and Applications (ICOMAA2020), Conference Proceeding Science and Technology, Vol. 3, 2020, pp. 122-128.
Z. Khan, M. Gulistan, R. Hashim, N. Yaqoob and W. Chammam, Design of S-control chart for neutrosophic data: an application to manufacturing industry, Journal of Intelligent and Fuzzy Systems 38(4) (2020), 4743-4751.
N. Khan, M. Aslam, P. Jeyadurga and S. Balamurali, Monitoring of production of blood components by attribute control chart under indeterminacy, Scientific Reports 11 (2021), Article number 922.
Z. Li, Z. Wang and Z. Wu, Necessary and sufficient conditions for non-interaction of a pair of one-sided EWMA schemes with reflecting boundaries, Statist. Probab. Lett. 79(3) (2009), 368-374.
Z. Li, C. Zou, Z. Gong and Z. Wang, The computation of average run length and average time to signal: an overview, J. Stat. Comput. Simul. 84(8) (2014), 1779-1802.
P. Pereira, J. Seghatchian, B. Caldeira, S. Xavier and G. de Sousa, Statistical control of the production of blood components by control charts of attribute to improve quality characteristics and to comply with current specifications, Transfusion and Apheresis Science 57(2) (2018), 285-290.
P. Qiu, Distribution-free multivariate process control based on log-linear modeling, IIE Transactions 40(7) (2008), 664-677.
P. Qiu and Z. Li, On non-parametric statistical process control of univariate processes, Technometrics 53(4) (2011), 390-405.
R. C. Quinino, L. F. Bessegato and F. R. Cruz, An attribute inspection control chart for process mean monitoring, The International Journal of Advanced Manufacturing Technology 90(9-12) (2017), 2991-2999.
S. Senturk, N. Erginel, I. Kaya and C. Kahraman, Design of fuzzy control charts, Journal of Multiple Valued Logic and Soft Computing 17(5-6) (2011), 459-473.
M. H. Shu and H. C. Wu, Monitoring imprecise fraction of nonconforming items using p control charts, J. Appl. Stat. 37(8) (2010), 1283-1297.
F. Smarandache, Neutrosophic logic - generalization of the intuitionistic fuzzy logic, Proceedings of the Third Conference of the European Society for Fuzzy Logic and Technology, 2003. arXiv preprint math/0303009.
F. Smarandache, Introduction to Neutrosophic Statistics, Sitech and Education Publisher, Craiova, Romania-Educational Publisher, Columbus, Ohio, USA, 2014.
AABB Standards, Standards for Blood Banks and Transfusion Services: The Committee, 1974.
S. F. Yang and B. C. Arnold, Monitoring process variance using an ARL-unbiased EWMA-p control chart, Quality and Reliability Engineering International 32(3) (2016), 1227-1235.
J. Ye, Neutrosophic number linear programming method and its application under neutrosophic number environments, Soft Computing 22(14) (2018), 4639-4646.
L. A. Zadeh, Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A. Zadeh, World Scientific, 1996, pp. 394-432.
H. Zhu, C. Zhang and Y. Deng, Optimisation design of attribute control charts for multi-station manufacturing system subjected to quality shifts, International Journal of Production Research 54(6) (2016), 1804-1821.
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