• Journal of Korean Society for Quality Management
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• v.29 no.1
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• pp.113-127
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• 2001

Skip-lot sampling plans for lot-by-lot inspection are more desirable than the continuous sampling plans for units in modern mass production system under the condition of the submitted product is good. Perry(1973a, 1973b) extended the Dodge(1955)′s skip-lot sampling plans to single and two-level skip-lot sampling plans and Parker & Kessler (1981) modified Perry(1973a)′s plans so that a sample of size one is taken from every lot skipped during the skipping mode. In this paper, Perry(1973b)′s two-level skip-lot sampling plans are modified by applying Parker & Kessler′s plan, designated as MTSkSP1, MTSkSP2, MTSkSP3. Operating characteristic(OC) functions, average sample numbers(ASN) and average outgoing qualities(AOQ) for the proposed plans are derived using Markov chain properties and compared each other and Perry′s plans. The proposed plans not only reduce the ASN but also avoid the danger skipping lots entirely when the lots are produced during sudden "out-of-control".

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.915-927
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• 2003

This paper is the generalization of the modified two-level skip-lot sampling plan(MTSkSP1) to n-level. The general formulas of the operating characteristic(OC) function, average sample number(ASN) and average outgoing quality(AOQ) for the plan are derived using Markov chain properties. The operating characteristic curves, average sample numbers and average outgoing qualities of a reference plan, modified two-level, three-level and five-level skip-lot sampling plans are compared.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1183-1189
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• 2008

The general formulas of the operating characteristic(OC) function, average sample number(ASN) and average outgoing quality(AOQ) for the modified n-level skip-lot sampling plan(MMSkSP2) were derived using Markov chain properties by Cho(2008). In this paper, the OC curve, ASN and AOQ of a reference plan, modified two-level, three-level and five-level skip-lot sampling plans are compared.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.811-818
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• 2008

This paper is the generalization of the modified two-level skip-lot sampling plan(MTSkSP2) to n-level. The general formulas of the operating characteristic(OC) function, average sample number(ASN) and average outgoing quality(AOQ) for the plan are derived using Markov chain properties.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.383-394
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• 2001

This paper is a generalization of single and two-level skip-lot sampling plans to n-level. On every skipping inspection of the n-level skip-lot sampling plan, not only the number of consecutive lots to be accepted but also the fraction of lots to be inspected can be freely choosed. The general formulas of the operating characteristic function, average fraction inspected, average sample number and average outgoing quality in n-level skip-lot sampling plan are derived. The operating characteristic curves, average sample number and average outgoing quality of a reference plan, two-level and five-level skip-lot sampling plans are compared.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.358-365
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• 1995

This paper presents another system of multi-level skip-lot sampling plan, which can directly retum to normal inspection from any skpping inspection level when a sudden shift for the worse in the process mean occurs. All the other properties of the proposed sampling plan are similar to those of the Choi's(1993) plan. The formula of the poerating characteristic function for the proposed n-level skip-lot sampling plan is derived. Sone poerating characteristic properties for the proposed plan are graphically compared with those of the Choi's plan.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.277-287
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• 1993

This paper is a generalization of single- and two-level skip-lot sampling plans to n-level, which can considerably reduce inspection cost when the level of submitted quality is high. In every skipping inspection of the generalized sampling plan, not only skipping parameters but also inspection fractions can be freely choosed. The general formula of the operating characteristic function for the n-level skip-lot sampling plan is derived. Also the operating characteristic curves of a reference plan, two-level and three-level skip-lot sampling plans are compared.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.55-64
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• 1995

Three-level Skip-lot sampling plan split by two stages (Split2-SkSP0 is proposed by modifying multi-level skip-lot sampling plan proposed by Choi(1993), which has normal and terrace inspections on the first and the second stages, respectively. The plan is designed to work more higher level inspections when the quality of the submitted products are good, otherwise, return to the normal or the terrace inspection as fast as possible. Also, the formula of the operating characteristic function for the split skip-lot sampling plan is derived using the Markov chain approach. Also, operating characteristic properties of the proposed plans are studied and graphically compared with those of the multi-level skip-lot sampling plans.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.151-159
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• 1996

The general formulas of average fraction inspected, average sample number and average outgoing quality in n-level skip-lot sampling plan are derived. Average sample number and average outgoing quality of a reference plan, three-level, five-level and ten-level skip-lot sampling plans are compared.

• International Journal of Reliability and Applications
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• v.15 no.2
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• pp.77-84
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• 2014

In this paper, a optimal designing methodology is proposed to determine the parameters for skip-lot sampling plan of type SkSP-2 plan with double sampling plan as reference plan, when the lifetime of the product follows generalized exponential distribution. The two points on the operating characteristic curve approach are used to find the optimal parameters for the proposed plan. The plan parameters are determined so as to minimize the average sample number subject to satisfying simultaneously both producer and consumer risks at the acceptable and limiting quality levels respectively.