• 산업경영시스템학회지
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• 제34권4호
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• pp.42-48
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• 2011

This paper proposes performance measurement method of quality small-group activity in business. This paper collects and analyzes quality circle activities data respect to tangible and intangible effect in national quality circles competitions festival. This paper proposes QPI (quality-circle performance index) based on Balanced Scorecard for quality small-group activity in quality improvement area. QPI is to measure the performance of quality improvement activities in the business firms. QPI is able to use widely in industries to provide a performance measure of quality small-group activity. In this paper, we propose the application method of QPl.

• 대한토목학회논문집
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• 제37권1호
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• pp.133-141
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• 2017

고속도로의 확충과 산업발전에 따른 물동량 증가로 인하여 도로 구조물의 내구성 저하와 취약구간의 반복적인 하자가 발생하고 있다. 따라서 국외에서 사용하는 품질보증제도 도입방안에 대한 연구가 진행되고 있다. 국내의 경우 한국도로공사는 점검위주의 품질관리에서 목적물의 품질성능 위주의 품질관리 체계로의 전환을 위하여 목적물의 품질 수준 측정이 가능하도록 정량적 평가 지수인 품질성능지수(QPI : Quality Performance Index)를 개발하여 적용하고 있다. 품질성능지수에서 콘크리트포장 평가인자는 포장두께, 압축강도, 평탄성, 기포간격계수로 구성되어 있다. 콘크리트 평가인자의 경우 국외에서 경험적 판단에 의해 자체적으로 선정된 인자를 사용하고 있는 실정이다. 따라서 본 연구에서는 콘크리트 포장 평가인자를 수명예측 시뮬레이션 및 실측 자료를 활용하여 분석하고 평가인자의 적정성을 검토하였다. QPI의 콘크리트포장 평가인자인 포장두께, 압축강도, 평탄성, 기포간격계수는 포장수명, 공용성 및 내구성을 적절하게 판단할 수 있는 인자로 사료된다.

• 품질경영학회지
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• 제46권3호
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• pp.509-522
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• 2018

Purpose: The purpose of this study was to propose more accurate mathematical model which can represent result of government quality assurance activity, especially corrective action and flaw. Methods: The collected data during government quality assurance activity was represented through histogram. To find out which distributions (Poisson distribution, Zero-Inflated Poisson distribution) could represent the histogram better, this study applied Pearson's correlation coefficient. Results: The result of this study is as follows; Histogram of corrective action during past 3 years and Zero-Inflated Poisson distribution had strong relationship that their correlation coefficients was over 0.94. Flaw data could not re-parameterize to Zero-Inflated Poisson distribution because its frequency of flaw occurrence was too small. However, histogram of flaw data during past 3 years and Poisson distribution showed strong relationship that their correlation coefficients was 0.99. Conclusion: Zero-Inflated Poisson distribution represented better than Poisson distribution to demonstrate corrective action histogram. However, in the case of flaw data histogram, Poisson distribution was more accurate than Zero-Inflated Poisson distribution.