Applying the Bayesian Technique in Designing a Single Sampling Plan

  • Dler H. Kadir Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region - F.R. Iraq. Also, Department of Business Administration, Cihan University-Erbil, Kurdistan Region, Iraq https://orcid.org/0000-0002-1254-721X
  • Abdul Rahim K. Rahi Department of Business Administration, Dijlah University College, Iraq https://orcid.org/0000-0002-3119-0551
Keywords: Statistical Quality Control, Average Sample Number, Acceptance Quality Level, Operating Characteristic, Bayesian sampling plans

Abstract

 The Bayesian sampling plans for production inspection are considered a technique of sampling inspection techniques for determining the characteristics of the sampling plan based on the assumption that the rate of defectives is a random variable that varies from one production batch to the next, resulting in a probability distribution f(p) that could be determined based on experience and the available quality information available. As part of this study, the parameters of a single Bayesian sampling plan (n,c) were derived by using the Beta-Binomial distribution and compared with those of other single sampling plans. Researchers have identified (ALA company for soft drinks), which handles product quality control. 120 production batches were selected, and the size of the batch and the number of defective items were used to determine the proportion of defective items, given that the variable varies randomly from one production batch to the next. Bayesian and decision-making models can be implemented to create a single sampling inspection process that is close to the actual quality level. The researchers discovered that when the decision-making model was used, the sample size was minimal compared to other inspection plans, leading to a low inspection cost.

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Author Biographies

Dler H. Kadir, Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region - F.R. Iraq. Also, Department of Business Administration, Cihan University-Erbil, Kurdistan Region, Iraq

 Dler Hussien Kadir is a full-time Assistant Professor at the Department of Statistics, College of Administrative and Economics at Salaheddin University-Erbil. He received my Ph.D. degree in the Department of Probability and Statistics at the University of Sheffield in the UK, M.Sc. degree in Statistics from the University of Sulaymaniyah in Iraq, and a B.Sc. Degree in Statistics from Salahaddin University-Erbil. His research interest includes Bayesian inference, MCMC, and Statistical Modeling.

Abdul Rahim K. Rahi, Department of Business Administration, Dijlah University College, Iraq

Abdul Rahim Khalaf Rahi is currently a full-time Professor at the Department of Business Administration, at Dijlah University College. His research interest includes Operation Research, Quality Control, Bayesian inference, and Statistical Modeling.

References

D. H. Kadir and A. R. K. Rahi Al-Harthy. Application of Bayesian Technique for Ala Pepsi Softdrink Company in Sampling Plan Design. University of Sulaimani, Iraq, 2007.

A. M. Q. Muhammad. A Study of Restricted Bayesian Acceptance Sampling Examination Plans for Quality Control with Practical Application. MSc Dissertation, College of Administration and Economics. University of Baghdad, 1999.

B. Ahmed and H. Yousof. A new group acceptance sampling plans based on percentiles for the Weibull Fréchet model. Statistics, Optimization and Information Computing, vol. 11, pp. 409-421, 2023.

D. S. Al-Janibi. Using Decision-Making Methods to Build the Best Model of the Cost Function in Quality Control. Ph.D. Dissertation. College of Administration and Economics. University of Baghdad, Iraq, 1991.

M. Aslam, N. Khan and A. H. Al-Marshadi. Design of variable sampling plan for pareto distribution using neutrosophic statistical interval method. Symmetry, vol. 11, p. 80, 2019.

A. Banihashemi, M. S. F. Nezhad and A. Amiri. A new approach in the economic design of acceptance sampling plans based on process yield index and Taguchi loss function. Computers and Industrial Engineering, vol. 159, p. 107155, 2021.

A. Hald. Bayesian single sampling attribute plans for continuous prior distributions. Technometrics, vol. 10, pp. 667-683, 1968.

A. Hald. Statistical Theory of Sampling Inspection by Attributes. Academic Press Inc., London, 1981.

D. H. Kadir, D. M. Saleh and D. I. Jamil. Comparison between four methods to construction number of defectives control chart. Journal of Arts, Literature, Humanities and Social Science, vol. 39, pp. 538-550, 2019.

D. M. Saleh and D. I. Jamil. Comparison between two estimators by using process capability with application. Journal of Arts, Literature, Humanities and Social Sciences, vol. 39, pp. 551-559, 2019.

N. H. Mahmood, R. O. Yahya and S. J. Aziz. Apply binary logistic regression model to recognize the risk factors of diabetes through measuring glycated hemoglobin levels. Cihan University-Erbil Scientific Journal, vol. 6, pp. 7-11, 2022.

D. M. Saleh, D. H. Kadir and D. I. Jamil. A comparison between some penalized methods for estimating parameters: Simulation study. Qalaai Zanist Journal, vol. 8, pp. 1122-1134, 2023.

K. I. Mawlood and R. O. Yahya. Using dynamic linear models and kalman filter for modeling and forecasting electricity load in Erbil city. Zanco Journal of Humanity Sciences, vol. 22, pp. 347-373, 2018.

Z. A. Omar, R. S. Abduljabar, S. M. Sajadi, S. A. Mahmud and R. O. Yahya. Recent progress in eco-synthesis of essential oil-based nanoparticles and their possible mechanisms. Industrial Crops and Products, vol. 187, p. 115322, 2022.

D. Prajapatin, S. Mitra and D. Kundu. Bayesian sampling plan for the exponential distribution with generalized Type-II hybrid censoring scheme. Communications in Statistics-Simulation and Computation, vol. 52, no. 2, pp. 533-556, 2023.

G. B. Wetherill. Sampling Inspection and Quality Control. 2nd ed. Chapman and Hall, New York, USA, 1977.

D. C. Montgomery. Introduction to Statistical Quality Control. 4th ed. John Wiley Sons Inc., New York, USA, 2001.

D. C. Montgomery. Introduction to Statistical Quality Control. 5th ed. John Wiley Sons Inc., New York, USA, 2005.

A. I. Al-Omari. Acceptance sampling plans based on truncated life tests for Sushila distribution. Journal of Mathematical and Fundamental Sciences, vol. 50, no. 1, pp. 72-83, 2018.

Published
2023-08-05
How to Cite
1.
Kadir D, Rahi AR. Applying the Bayesian Technique in Designing a Single Sampling Plan. cuesj [Internet]. 5Aug.2023 [cited 26Feb.2024];7(2):17-5. Available from: https://journals.cihanuniversity.edu.iq/index.php/cuesj/article/view/984
Section
Research Article