• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.43-49
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• 2008

This study is about an influence of harmful factors of welding fumes such as Fe, Mn, Cu, Zn to workers who inhales them in welding sites. The influence can be measured with the density of heavy metals in blood after welding. The main factors of the measurement are TWA, a density of welding fume, and a level of heavy metals. The results indicate that there is a positive effect of moving fans as a way of improving the condition in welding workplaces. While welding was done, TWA exceeded the level of Fe 40% and Zn 10% and the level of heavy metals in blood was below the standard for the workers who were under the experiment. Also when the wind was applied on the front side by a fan, the welding fume significantly reduced. It can be concluded that wearing protection gears with safety devices is one of important factors.

• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.70-88
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• 2000

Short runs where it is neither possible nor practical to obtain sufficient subgroups to estimate accurately the control limit are common in modem business environments. In this study, the standardized control chart, Hillier's exact method, Q chart, EWMA(Exponentially Weighted Moving Average) chart for Q statistics and EWMA chart for mean and absolute deviation among many SPC(Statistical Process Control) techniques for short runs have been reviewed and advantages and disadvantages of these techniques are discussed. The simulation experiments to compare performances of these variable charts for process mean and variations are conducted for combination of subgroup size, scale and timing of shifts of process mean an/or standard deviation. Based upon simulation results, some guidelines for practitioners to choose short run SPC techniques are recommended.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.525-533
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• 2015

Modern production process is a very complex structure combined observations which are correlated with several factors. When the error signal occurs in the process, it is very difficult to know the root causes of an out-of-control signal because of insufficient information. However, if we know the time of the change, the system can be controlled more easily. To know it, we derive a maximum likelihood estimator (MLE) of the change point in a process when observations are from a multivariate IMA(1,1) process by monitoring residual vectors of the model. In this paper, numerical results show that the MLE of change point is effective in detecting changes in a process.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.22-28
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• 2009

In order to optimize the polishing process, Run to Run control scheme has been applied to the micro mold polishing in this study. Also, to fully understand the effect of parameters on the surface roughness a design of experiment is performed. By linear approximation of main factors such as gap and rotational speed of micro quill, EWMA (Exponential Weighted Moving Average) gradual mode controller is adopted as a optimizing tool. Consequently, the process converged quickly at a target value of surface roughness Ra 10nm and Rmax 50nm, and was hardly affected by unwanted process noises like initial surface quality and wear of magnetic abrasives.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.337-345
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• 1999

The long-tailed, positively skewed exponential distribution can be made into an almost symmetric distribution by taking the exponent of the data. In these situations, to use the traditional shewhart control limits on an individuals chart would be impractical and inconvenient. The transformed data, approximately bell-shaped, can be plotted conveniently on the individuals chart and exponentially weighted moving average chart. In this paper, using modifying statistics with transformed exponential of the data, we give a method for constructing control charts. Selecting method of exponent for individual chart is evaluated. And consider that smaller weight being assigned to the older data as time process and properties and taking method of exponent($\theta$), weighting factor($\alpha$) are suggested. Our recommendation, on the basis result of simulation, is practical method for EWMA chart.

• IE interfaces
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• v.20 no.2
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• pp.94-102
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• 2007

Portfolio management deals with decision making on 'when' and 'how' to revise an existing portfolio. In this paper, we show that a classical statistical process control (SPC) chart for normal data, a wellestablished tool in quality engineering, can effectively be used for signaling times for revising a portfolio. Noting that the day-to-day performance of a portfolio may be auto-correlated, we use the exponentially weighted moving average center-line chart to develop an automatic portfolio management procedure. The portfolio management procedure is extensively tested on historical data of equities traded in the Korea Exchange (KRX), the American Stock Exchange (AMEX), and the New York Stock Exchange (NYSE). In comparison with the performances of the KOSPI, XAX, and NYA indices during the same time periods, results from these experiments show that SPC chart-based portfolio revision presents itself a convenient and reliable method for optimally managing portfolios.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.320-322
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• 2013

무선센서네트워크에서 MAC 프로토콜은 듀티사이클을 이용하여 센서노드의 에너지 소비를 줄임으로써 배터리의 수명을 연장한다. 기존에 제안된 TA (Traffic-Adaptive)-MAC 프로토콜은 비동기 방식 기반으로 듀티사이클을 조절하여 센서노드의 에너지 소비를 줄인다. 본 기법은 네트워크의 트래픽 상태를 고려하여 동적으로 센서노드의 듀티사이클을 조정한다. 이러한 방법으로 센서노드의 대기시간을 줄이고 센서노드의 에너지를 효과적으로 사용한다. 하지만 이 기법은 네트워크의 트래픽 변화가 잦은 환경에서는 좋지 못한 효율을 보인다. 따라서 본 논문에서는 기존의 TA-MAC 기법에 가중이동평균 방법을 적용하여 합리적인 듀티사이클 선정을 위한 트래픽 계산 방법을 제안한다. 이는 최근 트래픽 값과 현재 감지한 트래픽의 평균을 계산하고 다음 트래픽을 예측하여 네트워크 트래픽이 급격히 변화하는 불안정한 환경에서 더 합리적인 듀티사이클 선정을 돕는다.

• Journal of Integrative Natural Science
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• v.15 no.1
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• pp.1-8
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• 2022

In a multivariate normal production process N_p(µ,Σ), a chart combining three EWMA charts with accumulate-combine method for µ, variance components of Σ, and off-diagonal elements of Σ, into a EWMA (exponentially weighted moving average) chart is considered, which is called a combined EWMA chart. Through simulation work, the proposed combined EWMA chart's numerical performance and properties are examined. The simulation results show that the proposed combined EWMA chart, which is simultaneously monitoring all the process parameters of multivariate normal production process, works effectively in the perspective of means, variances and correlation coefficients. In addition, the combined EWMA chart is extended to VSI chart.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.129-142
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• 2024

In various industries, especially manufacturing and chemical industries, it is often observed that the distribution of a specific process, initially having followed a normal distribution, becomes skewed as a result of unexpected causes. That is, a process deviates from a normal distribution and becomes a skewed distribution. The skew-normal (SN) distribution is one of the most employed models to characterize such processes. The shape of this distribution is determined by the asymmetry parameter. When this parameter is set to zero, the distribution is equal to the normal distribution. Moreover, when there is a shift in the asymmetry parameter, the mean and variance of a SN distribution shift accordingly. In this paper, we propose procedures for monitoring the asymmetry parameter, based on the statistic derived from the noncentral t-distribution. After applying the statistic to Shewhart and the exponentially weighted moving average (EWMA) charts, we evaluate the performance of the proposed procedures and compare it with previously studied procedures based on other skewness statistics.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.206-211
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• 2009

This paper presents a methodology to 1-day-forecast stock index using the automatic feature extraction method based on the neural network with weighted fuzzy membership functions (NEWFM). The distributed non-overlap area measurement method selects the minimized number of input features by automatically removing the worst input features one by one. CPP$_{n,m}$(Current Price Position of the day n: a percentage of the difference between the price of the day n and the moving average from the day n-1 to the day n-m) and the 2 wavelet transformed coefficients from the recent 32 days of CPP$_{n,m}$ are selected as minimized features using bounded sum of weighted fuzzy membership functions (BSWFMs). For the data sets, from 1989 to 1998, the proposed method shows that the forecast rate is 60.93%.