Volume 26 , Issue 3 , PP: 287-301, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Amer Ibrahim Al-Omari 1 * , Rehab Alsultan 2
Doi: https://doi.org/10.54216/IJNS.260321
This paper introduces new acceptance sampling plans for situations where the life test is terminated at a predetermined time. The minimum sample sizes needed to guarantee a specified average lifetime are determined for different acceptance numbers, confidence levels, and ratios of the fixed test duration to the defined average lifetime. The Shanker distribution is adopted to represent the lifetimes of test units, with its mean serving as the quality indicator. Furthermore, the operating characteristic function values for the proposed sampling plans, along with the associated producer's risk, are provided. Examples are included to demonstrate how to use the tables effectively. An application of a real data set is used to illustrate the usefulness of the suggested acceptance sampling plans.
Shanker distribution , Acceptance sampling plans , Neutrosophic statistical interval method , Operating characteristic function , Producer's risk , Consumer's risk , Truncated life tests
[1] I. Al-Omari, “Time truncated acceptance sampling plans for generalized inverted exponential distribution,” Electron. J. Appl. Stat. Anal., vol. 8, no. 1, pp. 1–12, 2015, doi: 10.1285/I20705948V8N1P1.
[2] G. S. Rao, K. Rosaiah, K. Kalyani, and D. C. U. Sivakumar, “A new acceptance sampling plans based on percentiles for odds exponential log logistic distribution,” Open Stat. Probab. J., vol. 7, no. 1, pp. 45–52, Nov. 2016, doi: 10.2174/1876527001607010045.
[3] W. Gui and M. Aslam, “Acceptance sampling plans based on truncated life tests for weighted exponential distribution,” Commun. Stat. - Simul. Comput., vol. 46, no. 3, pp. 2138–2151, Mar. 2017, doi: 10.1080/03610918.2015.1037593.
[4] Hamurkaroğlu, A. Yiğiter, and N. Danacıoğlu, “Single and double acceptance sampling plans based on the time truncated life tests for the compound Weibull-exponential distribution,” J. Indian Soc. Probab. Stat., vol. 21, no. 2, pp. 387–408, Dec. 2020, doi: 10.1007/s41096-020-00087-7.
[5] T. A. Abushal, A. S. Hassan, A. R. El-Saeed, and S. G. Nassr, “Power inverted Topp-Leone distribution in acceptance sampling plans,” Comput. Mater. Contin., vol. 67, no. 1, pp. 991–1011, 2021, doi: 10.32604/cmc.2021.014620.
[6] S. Yadav, M. Saha, S. Shukla, H. Tripathi, and R. Dey, “Reliability test plan based on logistic-exponential distribution and its application,” J. Reliab. Stat. Stud., vol. 8, no. 1, pp. 1–15, Dec. 2021, doi: 10.13052/jrss0974-8024.14215.
[7] S. Jayalakshmi and S. Vijilamery, “Study on acceptance sampling plan for truncate life tests based on percentiles using Gompertz Fréchet distribution,” vol. 17, no. 1, pp. 1–10, 2022.
[8] Ahmed, M. M. Ali, and H. M. Yousof, “A novel G family for single acceptance sampling plan with application in quality and risk decisions,” Ann. Data Sci., vol. 9, no. 4, pp. 1231–1245, Oct. 2022, doi: 10.1007/s40745-022-00451-3.
[9] R. Vijayaraghavan and A. Pavithra, “Reliability criteria for designing life test sampling inspection plans based on Lomax distribution,” vol. 17, no. 2, pp. 245–258, 2022.
[10] G. Alomani and A. I. Al-Omari, “Single acceptance sampling plans based on truncated lifetime tests for two-parameter Xgamma distribution with real data application,” Math. Biosci. Eng., vol. 19, no. 12, pp. 13321–13336, 2022, doi: 10.3934/mbe.2022624.
[11] D. Al-Nasser and B. Y. Alhroub, “Acceptance sampling plans using hypergeometric theory for finite population under Q-Weibull distribution,” vol. 15, no. 2, pp. 352–366, 2022, doi: 10.1285/I20705948V15N2P352.
[12] O. J. Obulezi, C. P. Igbokwe, and I. C. Anabike, “Single acceptance sampling plan based on truncated life tests for Zubair-exponential distribution,” Earthline J. Math. Sci., pp. 165–181, Jun. 2023, doi: 10.34198/ejms.13123.165181.
[13] H. Tripathi, M. Saha, and S. Halder, “Single acceptance sampling inspection plan based on transmuted Rayleigh distribution,” Life Cycle Reliab. Saf. Eng., vol. 12, no. 2, pp. 111–123, 2023, doi: 10.1007/s41872-023-00221-x.
[14] R. AlSultan and A. Al-Omari, “Zeghdοudi distribution in acceptance sampling plans based on truncated life tests with real data application,” Decis. Mak. Appl. Manag. Eng., vol. 6, no. 1, pp. 432–448, 2023, doi: 10.31181/dmame05012023a.
[15] Z. AL-Husseini, M. Naghizadeh Qomi, and S. M. Taghi MirMostafaee, “Single acceptance sampling plan based on truncated life tests for the exponentiated moment exponential distribution with application in bladder cancer data,” Iran. J. Health Sci., vol. 11, no. 3, pp. 217–228, Jul. 2023, doi: 10.32598/ijhs.11.3.389.1.
[16] M. R. Reddy, B. S. Rao, and K. Rosaiah, “Acceptance sampling plans based on percentiles of exponentiated inverse Kumaraswamy distribution,” Indian J. Sci. Technol., vol. 17, no. 16, pp. 1681–1689, Apr. 2024, doi: 10.17485/IJST/v17i16.222.
[17] F. Y. Eissa, C. D. Sonar, O. A. Alamri, and A. H. Tolba, “Statistical inferences about parameters of the Pseudo Lindley distribution with acceptance sampling plans,” Axioms, vol. 13, no. 7, p. 443, Jun. 2024, doi: 10.3390/axioms13070443.
[18] I. Al-Omari, “Acceptance sampling plan based on truncated life tests for three parameter Kappa distribution,” Econ. Qual. Control, vol. 29, no. 1, pp. 53–62, Jan. 2014, doi: 10.1515/eqc-2014-0006.
[19] D. Al-Nasser and A. I. Al-Omari, “Acceptance sampling plan based on truncated life tests for exponentiated Fréchet distribution,” J. Stat. Manag. Syst., vol. 16, no. 1, pp. 13–24, Jan. 2013, doi: 10.1080/09720510.2013.777571.
[20] Baklizi and A. E. Q. El Masri, “Acceptance sampling based on truncated life tests in the Birnbaum Saunders model,” Risk Anal., vol. 24, no. 6, pp. 1453–1457, Dec. 2004, doi: 10.1111/j.0272-4332.2004.00541.x.
[21] M. Aslam, “Design of sampling plan for exponential distribution under neutrosophic statistical interval method,” IEEE Access, vol. 6, pp. 64153–64158, 2018, doi: 10.1109/ACCESS.2018.2877923.
[22] L. Zhang and J. Wang, “A new approach to acceptance sampling plans using cumulative sum control charts,” J. Quality Technol., vol. 54, no. 1, pp. 1–12, Jan. 2022, doi: 10.1080/00224065.2021.1893145.
[23] S. Kumar and P. Singh, “Multi-criteria decision-making for acceptance sampling plans in quality control,” Int. J. Ind. Eng. Comput., vol. 12, no. 1, pp. 1–15, Jan. 2021, doi: 10.5267/j.ijiec.2020.8.003.
[24] R. Shanker, “Shanker distribution and its applications,” Int. J. Stat. Appl., vol. 5, no. 6, pp. 338–348, 2015, doi: 10.5923/j.statistics.20150506.08.
[25] K. Rosaiah, G. S. Rao, and S. Prasad, “A group acceptance sampling plans based on truncated life tests for Type-II generalized log-logistic distribution,” ProbStat Forum, vol. 9, pp. 88–94, 2016.
[26] J. Smith and A. Johnson, “Statistical methods for quality control in manufacturing,” J. Ind. Eng. Manage., vol. 15, no. 3, pp. 123–134, 2023, doi: 10.3926/jiem.1203.