• Title/Summary/Keyword: CUSUM monitoring

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Comparison of accumulate-combine and combine-accumulate methods in multivariate CUSUM charts for mean vector

  • Chang, Duk-Joon;Heo, Sunyeong
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.919-929
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    • 2013
  • We compared two basic methods, combine-accumulate method and accumulate-combine method, using the past quality information in multivariate quality control procedure for monitoring mean vector of multivariate normal process. When small or moderate shifts have occurred, accumulate-combine method yields smaller average run length (ARL) and average time to signal (ATS) than combine-accumulate method. On the other hand, we have found from our numerical results that combine-accumulate method has better performances in terms of switching behavior than accumulate-combine method. In industry, a quality engineer could select one of the two method under the comprehensive consideration about the required time to signal, switching behavior, and other physical factors in the production process.

Numerical Switching Performances of Cumulative Sum Chart for Dispersion Matrix

  • Chang, Duk-Joon
    • Journal of Integrative Natural Science
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    • v.12 no.3
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    • pp.78-84
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    • 2019
  • In many cases, the quality of a product is determined by several correlated quality variables. Control charts have been used for a long time widely to control the production process and to quickly detect the assignable causes that may produce any deterioration in the quality of a product. Numerical switching performances of multivariate cumulative sum control chart for simultaneous monitoring all components in the dispersion matrix ${\Sigma}$ under multivariate normal process $N_p({\underline{\mu}},{\Sigma})$ are considered. Numerical performances were evaluated for various shifts of the values of variances and/or correlation coefficients in ${\Sigma}$. Our computational results show that if one wants to quick detect the small shifts in a process, CUSUM control chart with small reference value k is more efficient than large k in terms of average run length (ARL), average time to signal (ATS), average number of switches (ANSW).

Applicability of Statistical Evaluation to Power Quality Analysis (통계적 방법을 이용한 전력품질 관리방안)

  • Cho, Soo-Hwan;Jang, Gil-Soo;Kwon, Sae-Hyuk;Park, Sang-Ho;Jeon, Young-Soo;Kwak, No-Hong
    • Proceedings of the KIEE Conference
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    • 2006.07a
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    • pp.22-24
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    • 2006
  • The installations of power quality monitoring system have increased drastically over the past several decades. These systems have been effectively used to monitor, analyze and diagnose the conditions of power system, and furthermore can be used to improve the present asset maintenance policy, scheduled (time-based) method, into the advanced, cost-effective and labor-effective maintenance methods, such as condition-based maintenance, predictive maintenance and reliability centered maintenance. As an approach to this, this paper introduces the statistical methods, three kinds of control charts (Shewhart chart, CUSUM chart and EWMA chart), and discusses the applicability of these methods to recognize the changing trends of power quality indices and to estimate the system's condition, using Matlab.

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Change points detection for nonstationary multivariate time series

  • Yeonjoo Park;Hyeongjun Im;Yaeji Lim
    • Communications for Statistical Applications and Methods
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    • v.30 no.4
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    • pp.369-388
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    • 2023
  • In this paper, we develop the two-step procedure that detects and estimates the position of structural changes for multivariate nonstationary time series, either on mean parameters or second-order structures. We first investigate the presence of mean structural change by monitoring data through the aggregated cumulative sum (CUSUM) type statistic, a sequential procedure identifying the likely position of the change point on its trend. If no mean change point is detected, the proposed method proceeds to scan the second-order structural change by modeling the multivariate nonstationary time series with a multivariate locally stationary Wavelet process, allowing the time-localized auto-correlation and cross-dependence. Under this framework, the estimated dynamic spectral matrices derived from the local wavelet periodogram capture the time-evolving scale-specific auto- and cross-dependence features of data. We then monitor the change point from the lower-dimensional approximated space of the spectral matrices over time by applying the dynamic principal component analysis. Different from existing methods requiring prior information on the type of changes between mean and covariance structures as an input for the implementation, the proposed algorithm provides the output indicating the type of change and the estimated location of its occurrence. The performance of the proposed method is demonstrated in simulations and the analysis of two real finance datasets.

Estimating the Elasticity of Crude Oil Demand in Korea (한국 원유수요의 탄력성 추정)

  • Lee, Kyung-Hee;Kim, Kyung-Soo
    • Management & Information Systems Review
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    • v.37 no.3
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    • pp.65-81
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    • 2018
  • This study estimated the long-run and the short-run price and income elasticity of crude oil demand by using the ARDL model in Korea. First, the long-run cointegration relationship existed between crude oil demand and price or income in the ARDL-bounds tests. Second, the long-run own price, the cross price elasticity and the income elasticity were both statistically significant elastic and sensitive in the ARDL. Third, there was autocorrelation of the residuals, but no misspecification errors and heteroscedasticity, and then the residuals showed a normal distribution. And the CUSUM & CUSUMSQ tests showed that the coefficients were stable. Fourth, the short-run own price, the cross price elasticity and the income elasticity were both statistically significant elastic and sensitive in the ARDL-RECM. The ECM with the short-run dynamics showed rapid adjustments in the long-run equilibrium of oil demand after the economic crisis. In the short-run, the sensitivity of crude oil demand to price and income changes has moved in the same direction as the long-run case. Korea, depending too much on foreign crude oil, is vulnerable to the shocks of oil prices, so rising oil prices can certainly have a negative impact on Korea's trade balance. And the elasticity of long-run oil prices may help to control and manage Korea's oil demand. The government needs to strengthen monitoring of the country's policies and market trends related to crude oil, establish strategies to customize national policies and market conditions, and strengthen active market dominance efforts through pioneering new market and diversification.

Real-Time Spacer Etch-End Point Detection (SE-EPD) for Self-aligned Double Patterning (SADP) Process

  • Han, Ah-Reum;Lee, Ho-Jae;Lee, Jun-Yong;Hong, Sang-Jeen
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.436-437
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    • 2012
  • Double patterning technology (DPT) has been suggested as a promising candidates of the next generation lithography technology in FLASH and DRAM manufacturing in sub-40nm technology node. DPT enables to overcome the physical limitation of optical lithography, and it is expected to be continued as long as e-beam lithography takes place in manufacturing. Several different processes for DPT are currently available in practice, and they are litho-litho-etch (LLE), litho-etch-litho-etch (LELE), litho-freeze-litho-etch (LFLE), and self-aligned double patterning (SADP) [1]. The self-aligned approach is regarded as more suitable for mass production, but it requires precise control of sidewall space etch profile for the exact definition of hard mask layer. In this paper, we propose etch end point detection (EPD) in spacer etching to precisely control sidewall profile in SADP. Conventional etch EPD notify the end point after or on-set of a layer being etched is removed, but the EPD in spacer etch should land-off exactly after surface removal while the spacer is still remained. Precise control of real-time in-situ EPD may help to control the size of spacer to realize desired pattern geometry. To demonstrate the capability of spacer-etch EPD, we fabricated metal line structure on silicon dioxide layer and spacer deposition layer with silicon nitride. While blanket etch of the spacer layer takes place in inductively coupled plasma-reactive ion etching (ICP-RIE), in-situ monitoring of plasma chemistry is performed using optical emission spectroscopy (OES), and the acquired data is stored in a local computer. Through offline analysis of the acquired OES data with respect to etch gas and by-product chemistry, a representative EPD time traces signal is derived. We found that the SE-EPD is useful for precise control of spacer etching in DPT, and we are continuously developing real-time SE-EPD methodology employing cumulative sum (CUSUM) control chart [2].

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Comparisons of the Performance with Bayes Estimator and MLE for Control Charts Based on Geometric Distribution (기하분포에 기초한 관리도에서 베이즈추정량과 최대우도추정량 사용의 성능 비교)

  • Hong, Hwiju;Lee, Jaeheon
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.907-920
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    • 2015
  • Charts based on geometric distribution are effective to monitor the proportion of nonconforming items in high-quality processes where the in-control proportion nonconforming is low. The implementation of this chart is often based on the assumption that in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice for high-quality process where the proportion of nonconforming items is very small. An inaccurate estimate of the parameter can result in estimated control limits that cause unreliability in the monitoring process. The maximum likelihood estimator (MLE) is often used to estimate in-control proportion nonconforming. In this paper, we recommend a Bayes estimator for the in-control proportion nonconforming to incorporate practitioner knowledge and avoid estimation issues when no nonconforming items are observed in the Phase I sample. The effects of parameter estimation on the geometric chart and the geometric CUSUM chart are considered when the MLE and the Bayes estimator are used. The results show that chart performance with estimated control limits based on the Bayes estimator is generally better than that based on the MLE.