• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.22-38
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• 1997

In a traditional sequential acceptance sampling plan, it is assumed that the sampled items are independent each other. In this paper, stochastically dependent sequential acceptance sampling plans are dealt when there exists dependency between sampled items. Monte-Calro algorithm is used to find the acceptance and rejection probabilities of a lot. The number of defectives for the test to be accepted and rejected in probability ratio sequential test can be found by using these probabilities. The formula for measures of performance of these sampling plans is developed. Type I and II error probabilities are estimated by simulation. This research can be a, pp.ied to sequential sampling procedures in place of control charts where there is a recognized and necessary dependency during the production processes. Also, dependent multiple acceptance sampling plans can be derived by extending this sequential sampling procedure. As a numerical example, a Markov dependent process model is given, and the characteristics of the sampling plans are examined according to the change of the dependency factor.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.8-20
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• 1999

In this paper, a design and estimation procedure for the stochastically dependent nonstationary multiple acceptance sampling plans is developed. At first, the rough-cut acceptance and rejection numbers are given as an initial solution from the corresponding sequential sampling plan. A Monte-Carlo algorithm is used to find the acceptance and rejection probabilities of a lot. The conditional probability formula for a sample path is found. The acceptance and rejection probabilities are found when a decision boundary is given. Several decision criteria and the design procedure to select optimal plans are suggested. The formula for measuring performance of these sampling plans is developed. Type I and II error probabilities are also estimated. As a special case, by setting the stage size as 1 in a dependent sampling plan, a sequential sampling plan satisfying type I and II error probabilities is more accurate and a smaller average sample number can be found. In a numerical example, a Polya dependent process is examined. The sampling performances are shown to compare the selection scheme and the effect of the change of the dependency factor.

• Journal of Industrial Technology
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• v.9
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• pp.51-56
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• 1989

A methodology for determining optimal sampling plans for Bayesian multiattribute curtailed inspection models is proposed, whereby sampling inspection is terminated as soon as the disposition of the inspection lot is determined. An iterative solution procedure is developed for obtaining optimal multiattribute acceptance sampling plans under cuntailed sampling inspection.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.122-129
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• 2018

Purpose: This article develops an optimal reliability acceptance sampling plan for the case where the degradation quantity of the performance characteristic follows Weibull distribution. Method: For developing reliability acceptance sampling plans, the sample size and the acceptance constant are determined based on the accelerated characteristic of the test condition and the product. Results: The sample size and the acceptance constant are provided such that the constraints of the producer and the consumer risks are satisfied. Conclusion: Reliability acceptance sampling plans based on the accelerated degradation test method can be used for the quality control within a resonable amount of cost and time. In this article. an optimal reliability sampling plans are newly developed for this purpose.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.351-359
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• 2002

In this paper, stochastically dependent single and sequential acceptance sampling plans are dealt when the process follows a Polya process model. A Monte-Cairo algorithm is used to find the acceptance and rejection probabilities of a lot. The number of defectives for the test to be accepted and rejected in a probability ratio sequential test can be found by using these probabilities. The formula to measure performance of these sampling plans is developed. Type I and II error probabilities are estimated by simulation. Dependent multiple acceptance sampling plans can be derived by extending the sequential sampling procedure. In numerical examples, single and sequential sampling plans of a Polya dependent process are examined and the characteristics are compared according to the change of the dependency factor.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.11-18
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• 2005

Assume that the life times of the units under test follow the Rayleigh distribution and the test is terminated at a pre assigned time. Acceptance sampling plans are developed for this situation. The minimum sample size necessary to ensure the specified average life are obtained and the operating characteristic values of the sampling plans and producer's risk are given. An example is given to illustrate the methodology.

• Journal of the Korea Safety Management & Science
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• v.9 no.4
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• pp.137-142
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• 2007

This paper is to introduce attribute acceptance sampling plan based on statistical inference of binomial proportions such as PPM or PPB. In addition, this paper presents three variable sampling acceptance sampling plans based on $C_{pm},\;C_{pmk}$, and Taguchi's loss function. Producers are able to consider as not only external vendors but also internal customers.

• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.183-195
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• 2015

In this paper, we propose a two-stage group acceptance sampling plan for generalized inverted exponential distribution under truncated life test. Median life is considered as a quality parameter. Design parameters are obtained to ensure that true median life is longer than a given specified life at certain level of consumer's risk and producer's risk. We also explore situations under which design parameters based on median lifetime can be used for other percentile points. Tables and specific examples are reported to explain the proposed plans. Finally a real data set is analyzed to implement the plans in practical situations and some suggestions are given.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.517-526
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• 2008

This paper introduces fourteen single, double, multiple and sequential acceptance sampling plans based on switching rule. Revised KS standards for acceptance sampling by attribute and by variable such as KSA ISO 2859-0, 1:2001 2859-2:2001, 8422:2001, 3951:2006, 8423:2001, MIL-STD-105E:1989, 414:1968 and ANSI/ASQ Z1.4, Z1.9:2003 are presented.

• Journal of Korean Society for Quality Management
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• v.10 no.2
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• pp.25-33
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• 1982

We discuss a model for acceptance/rejection decision regarding finite populations. The model is based on a beta-binomial prior distribution and additive costs -- relative sampling costs, relative sorting costs and costs of accepted defectives. A substantial part of the paper is devoted to constructing a Bayes sequential sampling acceptance plan (BSSAP) for attributes under the model. It is shown that the Bayes fixed size sampling acceptance plans (BFSAP) are better than the Hald's (1960) single sampling acceptance plans based on a uniform prior. Some tables and examples are provided for comprisons of the minimum Bayes risks of the BSSAP and those of the BFSAP based on a uniform prior and the model.