• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.93-101
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• 1993

In this paper, two adaptive exponentially weighted moving avenge control chart schemes which available for real-time are proposed. The weighting coefficient is estimated using a recursive kalman filter algorithm. Simulated average run lengths indicate the proposed schemes are sensitive to process shifts And their performance is comparable to CUSUM control chart and customary EWMA control chart.

• Journal of Radiation Protection and Research
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• v.44 no.2
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• pp.64-71
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• 2019

Background: It is very difficult to distinguish between a radioactive contamination source and background radiation from natural radionuclides in the marine environment by means of online monitoring system. The objective of this study was to investigate a statistical process for triggering abnormal level of count rate data measured from our on-line seawater radioactivity monitoring. Materials and Methods: Count rate data sets in time series were collected from 9 monitoring posts. All of the count rate data were measured every 15 minutes from the region of interest (ROI) for $^{137}Cs$ ($E_{\gamma}=661.6keV$) on the gamma-ray energy spectrum. The Shewhart ($3{\sigma}$), CUSUM, and Bayesian S-R control chart methods were evaluated and the comparative analysis of determination methods for count rate data was carried out in terms of the false positive incidence rate. All statistical algorithms were developed using R Programming by the authors. Results and Discussion: The $3{\sigma}$, CUSUM, and S-R analyses resulted in the average false positive incidence rate of $0.164{\pm}0.047%$, $0.064{\pm}0.0367%$, and $0.030{\pm}0.018%$, respectively. The S-R method has a lower value than that of the $3{\sigma}$ and CUSUM method, because the Bayesian S-R method use the information to evaluate a posterior distribution, even though the CUSUM control chart accumulate information from recent data points. As the result of comparison between net count rate and gross count rate measured in time series all the year at a monitoring post using the $3{\sigma}$ control charts, the two methods resulted in the false positive incidence rate of 0.142% and 0.219%, respectively. Conclusion: Bayesian S-R and CUSUM control charts are better suited for on-line seawater radioactivity monitoring with an count rate data in time series than $3{\sigma}$ control chart. However, it requires a continuous increasing trend to differentiate between a false positive and actual radioactive contamination. For the determination of count rate, the net count method is better than the gross count method because of relatively a small variation in the data points.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.52-61
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• 2012

The design method for cumulative sum (CUSUM) control charts, which can be robust to autoregressive moving average (ARMA) modeling errors, has not been frequently proposed so far. This is because the CUSUM statistic involves a maximum function, which is intractable in mathematical derivations, and thus any modification on the statistic can not be favorably made. We propose residual-based robust CUSUM control charts for monitoring autocorrelated processes. In order to incorporate the effects of ARMA modeling errors into the design method, we modify parameters (reference value and decision interval) of CUSUM control charts using the approximate expected variance of residuals generated in model uncertainty, rather than directly modify the form of the CUSUM statistic. The expected variance of residuals is derived using a second-order Taylor approximation and the general form is represented using the order of ARMA models with the sample size for ARMA modeling. Based on the Monte carlo simulation, we demonstrate that the proposed method can be effectively used for statistical process control (SPC) charts, which are robust to ARMA modeling errors.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.735-744
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• 2021

Maintaining the lifetime of a product is one of the objectives of quality control. In real processes, most samples are constructed with censored data because, in many situations, we cannot measure the lifetime of all samples due to time or cost problems. In this paper, we propose two cumulative sum (CUSUM) control charting procedures to monitor the mean of type I right-censored lognormal lifetime data. One of them is based on the likelihood ratio, and the other is based on the binomial distribution. Through simulations, we evaluate the performance of the two proposed procedures by comparing the average run length (ARL). The overall performance of the likelihood ratio CUSUM chart is better, especially this chart performs better when the censoring rate is low and the shape parameter value is small. Conversely, the binomial CUSUM chart is shown to perform better when the censoring rate is high, the shape parameter value is large, and the change in the mean is small.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.187-194
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• 2020

In today's process-oriented industries, such as semiconductor and petrochemical processes, autocorrelation exists between observed data. As a management method for the process where autocorrelation exists, a method of using the observations is to construct a batch so that the batch mean approaches to independence, or to apply the EWMA (Exponentially Weighted Moving Average) statistic of the observed value to the EWMA control chart. In this paper, we propose a method to determine the batch size of UBM (Unweighted Batch Mean), which is commonly used as a management method for observations, and a method to determine the optimal batch size based on ARL (Average Run Length) We propose a method to estimate the standard deviation of the process. We propose an improved control chart for processes in which autocorrelation exists.

• The Journal of Engineering Geology
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• v.19 no.3
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• pp.261-268
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• 2009

Tunnel measurements provide crucial information on the ground stability during the excavation, visualizing the ground behavioral characteristics with quantitative dada. Generally, the frequency of the measurements is greater during the early stage of the tunnelling process and reduced with time. However, there are no quantitative criteria established for either the activities, such as the time, location and frequency of the measurement or the management guidance, especially for the site of subtle and unexpected displacement during the excavation. It is, however, still challenging to assess behavioral characteristics of subtle and unexpected displacement after stabilization. In this study, we propose a new method to assess stability and to analysis the behavioral characteristics of subtle and unexpected displacement after stabilization using statistic control charts of displacements. We also present a test result on the applicability of control chart and CUSUM control chart to measured displacements.

• Journal of Integrative Natural Science
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• v.9 no.3
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• pp.215-222
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• 2016

When the linear correlation of the quality variables are considerably high, multivariate control charts may be a more effective way than univariate charts which operate quality variables and process parameters individually. Performances and efficiencies of the multivariate control charts under multivariate normal process has been considered. Some numerical results are presented under small scale of the shifts in the process to see the improvement of the efficiency of EWMA chart and CUSUM chart, which use past quality information, comparing to Shewart chart, which do not use quality information. We can know that the decision of the optimum value of the smoothing constant in EWMA structure or the reference value in CUSUM structure are very important whether we adopt combine-accumulate technique or accumulate-combine technique under the given condition of process.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2009.10a
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• pp.231-232
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• 2009

공정의 질 (Quality)과 장비생산성을 향상시키기 위해서는 플라즈마를 엄격히 감시해야 하며, 본 연구에서는 플라즈마 색 정보와 신경망을 결합한 감시 기법을 보고한다. 본 기법은 인-시추 색 정보 수집, 시계열 신경망 모델링, 그리고 CUSUM 제어로 구성된다. 제안한 기법을 소스전력을 변화시켜 발생한 색 정보에 적용하였으며, 신경망 모델은 비정상 플라즈마를 정확하게 탐지할 수 있음을 확인하였다.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.169-183
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• 2004

The synthetic control chart (SCC) proposed by Wu and Spedding (2000) is to detect shifts in the process mean. The performance was re-evaluated by Davis and Woodall (2002), and the steady-state average run length (ARL) performance was shown to be inferior to cumulative sum (CUSUM) or exponentially weighted moving average (EWMA) chart This paper proposes a simple adaptive scheme to improve the performance of the synthetic control chart. That is, once a non-conforming (NC) sample occurs, we investigate the next L-consecutive samples with larger sample sizes and shorter sampling intervals. We employ a Markov chain model to derive the ARL and the average time to s19na1 (ATS). We also propose a statistical design procedure for determining decision variables. Comprehensive comparative study shows that the proposed control chart is uniformly superior to the original SCC or double sampling (DS) Χ chart and comparable to the EWMA chart in ATS performance.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.139-140
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• 2007

본 연구에서는 반도체 플라즈마 장비 감시를 위한 CUSUM 제어 차트 설계기법에 관해 연구하였다. CUSUM 제어 차트에 관여하는 설계변수의 다양한 조합에 대하여 플라즈마 장비의 감시 성능을 평가하였다. 평가를 위해 RF 정합망 감시시스템을 이용하여 플라즈마 임피이던스 정합에 관여하는 정합변수에 대한 실시간 데이터를 수집하였으며, 여기에는 임피이던스와 상위치에 대한 전기적 정보, 그리고 반사전력에 대한 정보가 포함된다. 평가결과, 설계변수의 조합에 대하여 감시 성능이 크게 달랐지만, 각 센서 정보의 감시 성능을 증진시키는 설계변수의 조합이 있었음을 확인하였으며, 이는 각 종 다양한 센서정보 별 CUSUM 제어 차트의 설계가 필요함을 의미한다. 연구에서는 Raw 데이터 대비 성능 분석을 위해 CUSUM 제어 차트의 설계 변수를 변수인 d와 $\Theta$값의 변화를 주어 다수의 (0, $\Theta$)의 조합에 따른 감시 성능을 평가하였으며, 평가에 이용된 데이터는 소스전력이 750 W, 압력이 15 mTorr, $O_2$ 유량이 50 sccm일 때 수집 하였다.