• 한국주조공학회지
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• 제24권2호
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• pp.63-70
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• 2004

Foundry techniquews for large steel casting depends on the skills of foundrymen considerably. Especially, the problem of reducing casring surface defects is difficult to clear numerically. Statistical analysis by using wuantification theory for hot tear and sand inclusion, and multiple regression analysis for dimensional defects have been shown to be examples of solving this difficulty. Many causes of surface defects can be evaluated by these analyses. These evaluations serve as the base data of defect reduction and contribute to the constant improvement of casting quality and quality enhancement activity. The system to perform quality enhancement activity was developed and it proved very useful for transfering foundry techniques and skills from the old to young generations.

• 정보기술응용연구
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• 제3권4호
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• pp.119-134
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• 2001

소프트웨어 제품의 품질을 높이는데는 소프트웨어 개발프로세스 중심과 제품 중심의 2가지 접근방법이 있다 CMM, ISO 9000 패밀리나 ISO/IEC 12207, SPICE 등이 프로세스의 인증을 통해서 소프트웨어 품질을 향상시키려는 시도라고 할 수 있다. 그렇지만 ‘좋은’ 프로세스만으로는 ‘좋은’ 제품의 품질을 보장하기가 어렵다. 최근 독립적인 제3자에 의한 소프트웨어 제품의 품질을 평가하기 위한 필요가 점점 증가하고 있다. 본 연구에서는 소프트웨어 제품의 품질을 평가하는데 SQC 기법을 응용하여 평가프로세스의 효율을 기하고 평가결과의 객관성을 확보하는 방안을 다룬다. 랜덤추출법에 의한 테스트 케이스를 선정하는 방법을 소개하고 소프트웨어 제품의 품질에 대한 적합성 기준을 선정하는 방안을 제시한다.

• 한국산학기술학회논문지
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• 제22권1호
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• pp.74-80
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• 2021

본 연구는 최근 전력화가 완료되어 양산이 진행 중인 K5 방독면에 대한 공정품질 수준을 평가하기 위하여 통계적 공정관리 기법을 활용하여 양산 단계 및 로트 별 분석을 수행하였다. 렌즈의 접착강도는 K5방독면의 기술적 요구사항 중 유일하게 생산 공정 간 평가하는 항목으로, 초도 및 2차 양산간 획득된 고무안면부와 렌즈 사이의 접착정도를 측정한 시험결과를 바탕으로 기술통계 및 통계적 공정관리 기법을 적용하여 분석하였다. 기술통계 분석결과에 따르면 초도 양산 대비 2차 양산 공정에 대한 결과가 더 좋음을 나타내고 있었다. 통계적 공정관리 기법인 관리도 분석과 공정능력지수에 대한 양산 단계 별 분석결과, 공정품질 수준 또한 양산이 진행됨에 따라 향상되고 있음을 확인 할 수 있었다. 이는 공정이 점차 안정화 되고 업무 숙련도에 의해 개선이 되고 있음을 보여주고 있었다. 이에 초도 및 2차 양산 간 획득된 성능시험 결과를 바탕으로 향후 3차 양산을 위한 기초자료로서 활용하고자 한다. 더불어 린6시그마의 DMAIC[Define(정의)-Measure(측정)-Analyze(분석)-Improve(개선)-Control(관리)] 방법론을 통해서 K5방독면의 품질향상 등의 목표달성을 수행할 예정이다.

• Journal of the Korean Statistical Society
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• 제33권4호
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• pp.381-399
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• 2004

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC re-duces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This paper considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an IMA(1,1) model with a step shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied according to the predicted deviation from target. For detecting special causes the exponentially weighted moving average control chart is applied to the observed deviations. It was assumed that the adjustment under the presence of a special cause may increase the process variability or change the system gain. Reasonable choices of parameters for the IPC procedure are considered in the context of the mean squared deviation as well as the average run length.

• 대한안전경영과학회지
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• 제15권2호
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• pp.243-253
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• 2013

This research paper introduces the application and implementation of medical decision metrics that classifies medical decision-making into four different metrics using statistical diagnostic tools, such as confusion matrix, normal distribution, Bayesian prediction and Receiver Operating Curve(ROC). In this study, the metrics are developed based on cross-section study, cohort study and case-control study done by systematic literature review and reformulated the structure of type I error, type II error, confidence level and power of detection. The study proposed implementation strategies for 10 quality improvement activities via 14 medical decision metrics which consider specificity and sensitivity in terms of ${\alpha}$ and ${\beta}$. Examples of ROC implication are depicted in this paper with a useful guidelines to implement a continuous quality improvement, not only in a variable acceptance sampling in Quality Control(QC) but also in a supplier grading score chart in Supplier Chain Management(SCM) quality. This research paper is the first to apply and implement medical decision-making tools as quality improvement activities. These proposed models will help quality practitioners to enhance the process and product quality level.

• 품질경영학회지
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• 제32권2호
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• pp.191-200
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• 2004

Using the p chart is not adequate in case that there are lots of data and it is difficult to divide into products conforming or nonconforming because of obscurity of binary classification. So we need to design a new control chart which represents obscure situation efficiently. This study deals with the method to performing arithmetic operation representing fuzzy data into fuzzy set by applying fuzzy set theory and designs a new control chart taking account of a concept of classification on the term set and membership function associated with term set.

• 대한산업공학회지
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• 제7권2호
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• pp.55-59
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• 1981

An Application of Experimental Designs to Improve the quality of Industrial product : optimization Methodology of statistical model. The primary object of this paper is to aid scientists and Engineers, in applying response surface procedures to obtain operating conditions for many technical fields, particularly for industrial manufacturing processes. The problem considered in this paper is to select technically and scientifically some important factors affecting the quality of products through the experimental design and analysis of response surface. Even though the mathematical model is unknown these statistical analysis can be applicable to control the quality of industrial products and to determine optimum operating conditions for many technical fields, particularly, for industrial manufacturing processes. This paper proposes a method to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model.

• 품질경영학회지
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• 제44권2호
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• pp.221-244
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• 2016

Purpose: This research reviews the papers, published in the Journal of the Korean Society for Quality Control (KSQC) and the Journal of the Korean Society for Quality Management (KSQM) since 1965, in the area of statistical methods. The literature review is performed in the four fields of the statistical methods and we categorize the published articles into the several sub-areas in each field. Methods: The reviewed articles are classified into the four main categories: probability model and estimation, Bayesian analysis and non-parametric analysis, regression and time series analysis, and application of data analysis. We examine the contents and relationships of the published articles of the several sub-areas in each category. Results: We summarize the reviewed papers in the chronological road-maps for each sub-area, and outline the relations of the connected papers. Some comments on the contents and the contributions of the reviewed papers are also provided in this paper. Conclusion: Various issues are employed and published on the research of the application statistical methods for past 50 years, and many worthy works are achieved in the theory and application areas of statistical methods for improving quality in the manufacturing and service industries. The future direction of the research in the statistical quality management methods also can be explored by the contents of this research.

• 품질경영학회지
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• 제5권2호
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• pp.3-20
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• 1977

The purpose of this Study is to develope the Role of Statistics in Industrial mass production. The process of mass production will be divided into three steps, that is, Standardization, production and inspection. The Statistics is applied to Specificat-ions, Quality Control and Sampling inspection in these three steps. The applications have developed to Statistical methods based on probability theory. And then, The improved plan is exhibited the point of problems of introducting of spreading of quality control throughout field survey.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2007년도 춘계학술대회
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• pp.302-309
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• 2007

To conduct statistical process control needs the assumption that the process data are independent. However, most of chemical processes, like a semi-conduct processes do not satisfy the assumption because of autocorrelation. It causes abnormal out of control signal in the process control and misleading process capability. In this study, we introduce that Shore's method to solve the problem and to find the optimal subgroup size to estimate variance for AR(l) model. Especially, we focus on finding an actual subgroup size for small samples using simulation. It may be very useful for statistical process control to analyze process capability and to make a Shewhart chart properly.