2022Jambura Journal of Probability and StatisticsOpen access

THE OPERATING CHARACTERISTICS CURVE OF THE ACCEPTANCE SAMPLING OF TYPE-A BASED ON OUTGOING PERCENT DEFECTIVE LOT

Bahagia Rafika Dewi, Fergyanto E. Gunawan, Firdaus Alamsjah

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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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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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Available 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.

Key concepts: Acceptance sampling, Statistics, Sample (material), Sampling (signal processing), Sample size determination, Quality (philosophy), Mathematics, Econometrics

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