• 대한토목학회논문집
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• 제12권4호
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• pp.145-155
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• 1992

아스팔트 포장공사의 판정에 있어 품목집단 특성치의 측정시 공정평균(工程平均)이 규정에 합당해도 표본(標本) 선정이나 측정상의 고유분산치(固有分散値)가 규정한계를 벗어나기도 한다. 그러나 많은 규정들이 이러한 점을 간과(看過)하고 있어 충실한 시공자라도 고유의 불확실성(不確實性)때문에 불이익을 당한다. 따라서 본 연구는 이러한 점에 착안하여 선정된 판정기준에 의하여 시뮬레이션으로 얻은 품목집단의 특성치를 검정하고 이때 재료와 측정상의 불확실성(不確實性)이 지급비율 결정에 미치는 영향을 분석하였다. 각 추정치를 검사특성곡선(檢査特性曲線)으로 도시한 결과 재료 및 측정이 지급비에 영향을 주며 특히 고유측정오차가 그 영향이 가장 큰 것으로 나타났다. 따라서 각 기관의 지급 규정은 측정시 불확실성의 고유치로 인한 시공자의 불이익을 고려하여 제정 및 정비되어야 할 것으로 사료된다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2009년도 추계학술대회
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• pp.3-10
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• 2009

When the measurement method for a performance variable is destructive or expensive, it is profitable to replace the performance variable with a highly correlated surrogate variable. In this paper we propose screening procedures using a surrogate variable with specified producer's and consumer's risks. Blending the basic concepts of acceptance sampling plans and screening procedures, the proposed model can be used effectively by quality professionals. Two models are considered: the normal model with dichotomous performance and continuous surrogate variables, and the bivariate normal model with continuous performance and surrogate variables. It is assumed the surrogate variable given the performance variable is normally distributed in the normal model, and performance and surrogate variables are jointly normally distributed in the bivariate normal model. For the two models, Producer's and consumer's risks are derived, and methods of finding the optimal screening procedures are presented. Numerical examples are also given.

• 품질경영학회지
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• 제37권4호
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• pp.23-30
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• 2009

When the measurement method for a performance variable is destructive or expensive, it is profitable to replace the performance variable with a highly correlated surrogate variable. In this paper we propose screening procedures using a surrogate variable with specified producer's and consumer's risks. Blending the basic concepts of acceptance sampling plans and screening procedures, the proposed model can be used effectively by quality professionals. Two models are considered: the normal model with dichotomous performance and continuous surrogate variables, and the bivariate normal model with continuous performance and surrogate variables. It is assumed the surrogate variable given the performance variable is normally distributed in the normal model, and performance and surrogate variables are jointly normally distributed in the bivariate normal model. For the two models, producer's and consumer's risks are derived, and methods of finding the optimal screening procedures are presented. Numerical examples are also given.