THE OPERATING CHARACTERISTICS CURVE OF THE ACCEPTANCE SAMPLING OF TYPE-A BASED ON OUTGOING PERCENT DEFECTIVE LOT
Abstract
The common type-A of Operating Characteristics (OC) curve measures the consumer’s risk through the incoming quality. However, the proportion of defective can alter after the sampling process; hence, the measure of consumer’s risk is better described by the outgoing quality or lot quality of post sampling inspection. A modified OC curve is developed based on the outgoing quality for two applicable cases; returned samples to the lot and non-returned or destructive samples. This research aims to develop the algorithm and evaluate the alternative acceptance sampling plan for isolated lots by outgoing percent defective. For the returned samples, the acceptance sampling requires less sample than that based on the common OC-curve and is seen as an opportunity for sampling size reduction. The number of reduced samples varies depending on the input parameters: Acceptance Quality Level (AQL), Rejectable Quality Limit (RQL), producer’s risk (α), consumer’s risk (β), and lot size (N). For the non-returned sample, more sample size (n) is required, even more than that of using the Binomial distribution’s sample size, which has been considered conservative.
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Al-Nasser, A. (2022), "Acceptance sampling plans using hyper-geometric theory for finite population under Q-Weibull distribution.", Electronic Journal of Applied Statistical Analysis, pp. 352-366.
Banovac, E., D. Pavlovic, and N. Vistica. (2012), "Analyzing the characteristics of sampling by attributes." Recent Researches in Circuits, Systems, Multimedia and Automatic Control, pp. 158–163.
Brush, G.G., B. Hoadley, and B. Saperstein. (1990), "Estimating Outgoing Quality Using the Quality Measurement Plan.", Technometrics, pp. 31-41.
Brush, G.G., H. Cautin, and B.R. Lewin. (1981), "Outgoing Quality Distribution for MIL-STD-105D Sampling Plans." Journal of Quality Technology, pp. 254-263.
Cavone, Giuseppe, Laura Fabbiano, and Nicola Giaquinto. (2009), "Closed-Form Equations to Design Single Sampling Plans for Isolated Lots." XIX IMEKO World Congress: Fundamental and Applied Metrology. Lisbon.
Chukhrova, N., and A. Johannssen. (2018), "Quality Paper : Improved binomial and Poisson approximations to the Type-A operating characteristic curve." IJQRM, pp. 620-652, DOI 10.1108/IJQRM-10-2017-0203.
Chukhrova, N.,, and A. Johannssen. (2019), "Improved binomial and Poisson approximations to the Type-A operating characteristic function.", International Journal of Quality & Reliabilty Management, pp. 620-652.
Devore, Jay L. (2009), Probability and Statistics for Engineering and The Sciences. 7th. Brooks/Cole Cengage Learning.
ISO28590. (2017), "Sampling Procedure for INspection by Attributes - Introduction to the ISO 2859 Series of Standards for Sampling for Inspection by Attributes."
ISO2859-1. (1999), "Sampling Procedures for Inspection by Attributes - Part 1: Sampling Schemes Indexed by Acceptance Quality Limit (AQL) for Lot-by-Lot Inspection." ISO.
Kreyszig, E. (2009), Advanced Engineering Mathematics, 10th edition, Wiley.
Montgomery, Douglas C. (2009), Statistical Quality Control: A Modern Introduction, John Wiley & Sons (Asia) Pte. Ltd.
Mostofi, A.G., and S. Shirkani. (2019), "Designing a single-sampling plan for attributes in the presence of classification errors." Communications in Statistics-Simulation and Computation, pp. 1-15.
NIST/SEMATECH. 2012. e-Handbook of Statistical Methods. https://doi.org/10.18434/M32189.
Samohyl, Robert Wayne. (2018), "Acceptance Sampling for Attributes via Hypothesis Testing and the Hypergeometric Distribution." J. Ind. Eng. Int.,pp. 395-414. doi:https://doi.org/10.1007/s40092-017-0231-9.
Schilling, Edward G., and Dean V. Neubauer. (2017), Acceptance Sampling in Quality Control. 3rd. Taylor & Francis Group, LLC.
Z1.4, ANSI/ASQ. 2003 (R2013). "Sampling Procedures and Tables for Inspection by Attributes."
DOI: https://doi.org/10.34312/jjps.v3i2.15965
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