• Journal of the Korean Data and Information Science Society
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• 제21권6호
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• pp.1051-1060
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• 2010

도금공정에서는 도금두께의 규격한계는 주어지지만 대부분의 경우 목표치는 주어지지 않는다. 목표치가 주어지지 않았을 때 일반적으로 규격의 중심점이 목표치로 사용된다. 하지만 공정능력치가 크다면 규격의 중심을 목표치로 사용하는 것은 총 손실비용면에서 최선의 선택이 아니다. 이 논문에서는 총 손실비용을 생산비용과 손실함수의 합으로 정의하였고 기대 총 손실비용을 최소화 하는 목표치를 제안하였다. 그리고 그때의 공정능력치의 감소가 미미한 것을 보였다.

• 산업경영시스템학회지
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• 제39권3호
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• pp.10-17
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• 2016

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally ${\bar{x}}-R$ control chart or ${\bar{x}}-s$ control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

• 경영과학
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• 제12권1호
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• pp.111-124
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• 1995

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2013-2018
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• 2014

According to the manufacturing process of the laminated stator core for an inserted permanent magnet synchronous motor (IPMSM), the iron loss may be different. It is because the mechanical stress imposed to electrical steel sheet is strongly dependent on the manufacturing process. This paper proposes a new iron loss measurement algorithm which utilizes the induced voltage of a search coil and exciting current. The method is effective even when the distribution of magnetic flux density is not uniform along the magnetic flux path as well as uniform. The developed iron loss measurement system is applied to bonded- and embossed-type segmented stator cores of an IPMSM, and the iron losses are quantitatively compared.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.72-74
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• 2021

다양한 분야에서 현재 활용되고 있는 딥러닝 과정은 데이터 준비, 데이터 전처리, 모델 생성, 모델 학습, 모델 평가로 구성 된다. 이중 모델 학습 과정에서 손실함수는 모델이 학습하면서 출력한 값을 실제 값과 비교하여 그 차이를 출력하게 되고, 출력된 손실값을 기반으로 모델은 역전파 알고리즘을 통해 손실값이 감소하는 방향으로 가중치를 수정해가며 학습을 진행한다. 본 논문에서는 바이오마커 추출을 위한 딥러닝 모델에서 사용될 신경망 출력 값의 손실도를 측정하여 출력해주는 다양한 손실함수를 분석하고 실험을 통해 최적의 손실함수를 찾아내고자 한다.

• 산업경영시스템학회지
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• 제39권1호
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• pp.123-129
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• 2016

In the manufacturing industry fields, thousands of quality characteristics are measured in a day because the systems of process have been automated through the development of computer and improvement of techniques. Also, the process has been monitored in database in real time. Particularly, the data in the design step of the process have contributed to the product that customers have required through getting useful information from the data and reflecting them to the design of product. In this study, first, characteristics and variables affecting to them in the data of the design step of the process were analyzed by decision tree to find out the relation between explanatory and target variables. Second, the tolerance of continuous variables influencing on the target variable primarily was shown by the application of algorithm of decision tree, C4.5. Finally, the target variable, loss, was calculated by a loss function of Taguchi and analyzed. In this paper, the general method that the value of continuous explanatory variables has been used intactly not to be transformed to the discrete value and new method that the value of continuous explanatory variables was divided into 3 categories were compared. As a result, first, the tolerance obtained from the new method was more effective in decreasing the target variable, loss, than general method. In addition, the tolerance levels for the continuous explanatory variables to be chosen of the major variables were calculated. In further research, a systematic method using decision tree of data mining needs to be developed in order to categorize continuous variables under various scenarios of loss function.

• 품질경영학회지
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• 제31권4호
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• pp.164-175
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• 2003

This paper investigates bootstrap confidence intervals of the process capability index(PCI) based on the expected loss derived from the empirical distribution function(EDF). The PCI based on the expected loss is too complex to derive its confidence interval analytically, so the bootstrap method is a good alternative. We propose three types of the bootstrap confidence interval; the standard bootstrap(SB), the percentile bootstrap(PB), and the acceleration biased­corrected percentile bootstrap(ABC). We also perform a comprehensive simulation study under various process distributions, in order to compare the accuracy of the coverage probability of the bootstrap confidence intervals. In most cases, the coverage probabilities of the bootstrap confidence intervals from the EDF PCI turned out to be more accurate than those from the PCI based on the normal distribution. It is expected that the bootstrap confidence intervals from the EDF PCI can be utilized in real processes where the true distribution family may not be known.

• 품질경영학회지
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• 제20권1호
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• pp.80-90
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• 1992

In industries, the capability indices $C_p$ and $C_{pk}$ can be used to provide measures of process potential capability and performance, respectively. The new approach advocated by Taguchi in quality control overcomes some problems in other approaches preventive management activities. Taguchi introduces the emphasis on loss function to improve quality of products on the side of customer. The proceeding concept of capability indices is not rational for the measurement of quality if the process mean is not equal to target value. The Taguchi approach is said to be more reasonable than the others in quality evaluation because of his loss function. However, the capability indices $C_{pm}{^+}$ and $C_{pn}$ using Taguchi's loss function only consider, acceptance cost for deviation from target value within specification limits. In other words, they do not include rejection cost for nonconformings that are failed to fall on the specification limits.

• 대한기계학회논문집
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• 제18권12호
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• pp.3404-3412
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• 1994

The present study was undertaken to investigate the dry wear process and wear mechanism of the alumina ceramics in the purity variation which are used for the mechanical seal, roll, liner and dies. The wear test was carried out under different experimental condition using the wear testing device and in which the annular surface rubbed on dry sliding condition various sliding speed, contact pressure and sliding distance. In case of alumina purity 95%, there was speed range which wear loss increased rapidly owing to enlargement of heat impact force and temperature rise of wear surface. According as the alumina purity increased, wear loss decreased but alumina purity 85% with much void and defect had the most wear loss than any other alumina purity. The friction coefficient of sliding initial stage of wear curves has a large value but according to increase of sliding distance, it decreased owing to drop of the shear strength of wear surfaces.

• 대한산업공학회지
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• 제31권2호
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• pp.164-172
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• 2005

A loss function approach to a multiresponse problem is considered, when process parameters are regarded as random variables. The variation of each response may be amplified through so called propagation of error (POE), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. The forms of POE for each response and for a pair of responses are proposed and they are reflected in our loss function approach to determine the optimal condition. The proposed method is illustrated using a polymer case. The result is compared with the case where parameter fluctuation is not considered.