• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 춘계학술대회
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• pp.509-517
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• 2010

The paper proposes the misuse types of statistical quality tools according to the kind of data and the number of population in DMAIC process of six sigma. The result presented in this paper can be extended to the QC story 15 steps of QC circle. The study also provides the improvement methods about control chart, measurement system analysis, statistical difference, and practical equivalence.

• 산업경영시스템학회지
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• 제20권41호
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• pp.135-145
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• 1997

The statistical approach to quality control aims at alerting its user to any variations in the properties of a manufactured product. Motorola developed and pursued a quality management program called six sigma. The goal of six sigma programs is to improve customer satisfaction through reducing and eliminating defects. six sigma uses several statistical measure to characterize defect levels and process capabilities. The upper and lower specification limits are $\pm6\sigma$(sigma) from nominal, and the process mean is centered at nominal. only 0.002PPM are outside specification limits. Cp=2. this is the design target in a six sigma program. This article presents an important tool available for quality control of a production process at the occurrence of defects in manufactured products at view low levels to improve the efficiency of the manufacturing productivity and to satisfy customer through the reduction of defect rates. To understand the consequences of the level of quality on competitive position, a more technical perspective is needed.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.285-295
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• 2004

Statistical process control(SPC) and engineering process control(EPC) are two complementary strategies for quality improvement. An integrated process control(IPC) can use EPC to reduce the effect of predictable quality variations and SPC to monitor the process for detection of special causes. In this paper we assume an IMA(1,1) model as a disturbance process and an occurrence of a level shift in the process, and we consider the economic performance for applying an EWMA chart to monitor MMSE-controlled processes. The numerical results suggest that the IPC scheme in an IMA(1,1) disturbance model does not give additional advantages in the economic aspect.

• 대한통합의학회지
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• 제9권4호
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• pp.59-69
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• 2021

Purpose: The purpose of this study was to evaluate the effects of client-centered art and craft activities on depression and quality of life in stroke clients. Through this, we aim to find a way to reduce depression and improve the quality of life in stroke clients. Methods: Clients diagnosed with stroke were selected as participants for the study. Participants in the experimental group (n=13) and control group (n=14) received general occupational therapy. Clients in the experimental group participated in client-centered art and craft activities, whereas clients in the control group participated in general art and craft activities for 8 weeks. Beck Depression Inventory(BDI) and Stroke Specific Quality of Life(SS-QOL) were used to evaluate the depression and quality of life of the clients before and after the intervention. Results: The experimental group and control group presented significant statistical difference in depression before and after intervention (p<.01; p<.05). The experimental group showed a greater decrease in depression (p<.05) than the control group. Additionally, the experimental and control group displayed significant statistical difference in quality of life (p<.01) before and after intervention. The experimental group showed a more statistically significant improvement in quality of life (p<.01) than the control group. Conclusion: These results demonstrate the significance of client-centered art and craft activities in reducing depression and improving quality of life in clients with stroke. Therefore, it is expected to be useful in clinical settings. Occupational therapy should be provided based on the decision of the clients.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.65-77
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• 2020

Geometric charts are effective in monitoring the fraction nonconforming in high-quality processes. The in-control fraction nonconforming is unknown in most actual processes; therefore, it should be estimated using the Phase I sample. However, if the Phase I sample size is small the practitioner may not achieve the desired in-control performance because estimation errors can occur when the parameters are estimated. Therefore, in this paper, we adjust the control limits of geometric charts with the bootstrap algorithm to improve the in-control performance of charts with smaller sample sizes. The simulation results show that the adjustment with the bootstrap algorithm improves the in-control performance of geometric charts by controlling the probability that the in-control average run length has a value greater than the desired one. The out-of-control performance of geometric charts with adjusted limits is also discussed.

• 경영과학
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• 제10권2호
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• pp.111-120
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• 1993

The most important factors for a product to survive in the market are cost and quality. In recent years, quality proceeds to cost. There are many techniques of use to improve the quality of a product. One of the techniques is applying statistical methods (especially Taguchi method) to real operational conditions for a continuous manufacturing process in P company. There are 91 factors to control in the process. So, we predetermined 7 main effect factors and 6 interactive effect factors by statistical methods and advices of engineers. With these 13 factors, we determined the optimal level of operations for the process.

• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.589-601
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• 2005

Student evaluation of university teaching is a common tool for measuring the educational contribution of a professor and improving the quality of classes. There, however, exist external factors in the beyond of control of a instructor, which affect the result of Student's rating to prevent practical use of evaluation for administrative purpose. This paper investigates the factors that spoil the validity and the reliability of student evaluation and proposes a method to control the effect by the statistical analysis of evaluation data of Jeonju University for two years.

• 응용통계연구
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• 제11권1호
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• pp.13-28
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• 1998

품질향상을 위한 통계적 공정관리 추진시 데이터의 신뢰성 확보는 무엇보다 중요하다. 그런데 측정치는 계측기 뿐만 아니라 측정자, 측정방법, 측정재료 등 보다 많은 요인들에 의해 영향을 받는다. 본 논문에서는 고전적인 측정시스템 평가에서 주로 관리하는 정확도, 정밀도 및 안정도를 실제 데이터를 이용하여 어떻게 평가하는지 알아보기로 한다.

• 품질경영학회지
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• 제44권3호
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• pp.587-600
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• 2016

Purpose: This paper evaluates the performance of the pre-control(PC), an alternative to statistical process control techniques and compares with a control chart considering the tolerance of process. Methods: The previous studies for PC have drawbacks that PC with two linked stages, qualification and running, are discussed separately and independently. Hence this paper analyzes the performance of PC by integrating two stages. Results: Average outgoing quality limits to grasp the outcome of PC are provided by computational results for two process capability indexes, $C_p$ and $C_{pk}$ and the usefulness of PC from comparative experiments with modified control charts is commented. Conclusion: Helpful guidelines for quality managers to apply PC in practice and areas of process for PC to be more benefit are presented.

• 품질경영학회지
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• 제51권4호
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• pp.663-675
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• 2023

Purpose: Skewness is an indicator used to measure the asymmetry of data distribution. In the past, product quality was judged only by mean and variance, but in modern management and manufacturing environments, various factors and volatility must be considered. Therefore, skewness helps accurately understand the shape of data distribution and identify outliers or problems, and skewness can be utilized from this new perspective. Therefore, we would like to propose a statistical quality control method using skewness. Methods: In order to generate data with the same mean and variance but different skewness, data was generated using normal distribution and gamma distribution. Using Minitab 18, we created 20 sets of 1,000 random data of normal distribution and gamma distribution. Using this data, it was proven that the process state can be sensitively identified by using skewness. Results: As a result of the analysis of this study, if the skewness is within ± 0.2, there is no difference in judgment from management based on the probability of errors that can be made in the management state as discussed in quality control. However, if the skewness exceeds ±0.2, the control chart considering only the standard deviation determines that it is in control, but it can be seen that the data is out of control. Conclusion: By using skewness in process management, the ability to evaluate data quality is improved and the ability to detect abnormal signals is excellent. By using this, process improvement and process non-sub-stitutability issues can be quickly identified and improved.