• Title, Summary, Keyword: statistical process control

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Statistical Efficiency of VSSI $\bar{X}$ Control Charts for the Process with Two Assignable Causes (두 개의 이상원인이 존재하는 공정에 대한 VSSI $\bar{X}$ 관리도의 통계적 효율성)

  • Lee Ho-Jung;Lim Tae-Jin
    • Journal of the Korean Society for Quality Management
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    • v.32 no.4
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    • pp.156-168
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    • 2004
  • This research investigates the statistical efficiency of variable sampling size & sampling interval(VSSI) $\bar{X}$ charts under two assignable causes. Algorithms for calculating the average run length(ARL) and average time to signal(ATS) of the VSSI $\bar{X}$ chart are proposed by employing Markov chain method. States of the process are defined according to the process characteristics after the occurrence of an assignable cause. Transition probabilities are carefully derived from the state definition. Statistical properties of the proposed chart are also investigated. A simple procedure for designing the proposed chart is presented based on the properties. Extensive sensitivity analyses show that the VSSI $\bar{X}$ chart is superior to the VSS or VSI $\bar{X}$ chart as well as to the Shewhart $\bar{X}$ chart in statistical sense, even tinder two assignable causes.

Development of Integrated Variable Sampling Interval EngineeringProcess Control & Statistical Process Control System (가변 샘플링간격 EPC/SPC 결합시스템의 개발)

  • Lee, Sung-Jae;Seo, Sun-Keun
    • Journal of Korean Institute of Industrial Engineers
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    • v.32 no.3
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    • pp.210-218
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    • 2006
  • Traditional statistical process control (SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control (EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted by variable sampling interval (VSI) to change sampling intervals in a predetermined fashion on the predicted process levels under integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA (1,1) disturbance model and zero-order (responsive) dynamic system. Properties of twelve control rules under three patterns of process change (sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

To study of optimal subgroup size for estimating variance on autocorrelated small samples (소표본 자기상관 자료의 분산 추정을 위한 최적 부분군 크기에 대한 연구)

  • Lee, Jong-Seon;Lee, Jae-Jun;Bae, Soon-Hee
    • Proceedings of the Korean Society for Quality Management Conference
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    • pp.302-309
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    • 2007
  • To conduct statistical process control needs the assumption that the process data are independent. However, most of chemical processes, like a semi-conduct processes do not satisfy the assumption because of autocorrelation. It causes abnormal out of control signal in the process control and misleading process capability. In this study, we introduce that Shore's method to solve the problem and to find the optimal subgroup size to estimate variance for AR(l) model. Especially, we focus on finding an actual subgroup size for small samples using simulation. It may be very useful for statistical process control to analyze process capability and to make a Shewhart chart properly.

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Development of VSI Synthetic Control Chart (가변샘플링기법을 이용한 합성관리도의 개발)

  • Song, Suh-Ill;Park, Hyun-Kyu
    • Journal of the Korean Society for Quality Management
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    • v.33 no.1
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    • pp.1-10
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    • 2005
  • This paper develops a new VSI $\={X}-CRL$ synthetic control chart that considers convenience of use in the field, and perception of change of process applying VSI techniques to synthetic control chart, simultaneously. We found the optimal sampling interval and various control limit factor of the suggested chart using markov chain. Comparison and analysis is carried out between synthetic VSI $\={X}-CRL$ chart and other chart in the statistical aspect; $\={X}$ control chart, VSI $\={X}$ chart, another synthetic chart. In case that the process follows normal distribution, the proposed VSI $\={X}-CRL$ synthetic control chart in detecting process mean shift showed the best performance in aspect of statistical performance, regardless of control limit L of CRL/S control chart.

Local T2 Control Charts for Process Control in Local Structure and Abnormal Distribution Data (지역적이고 비정규분포를 갖는 데이터의 공정관리를 위한 지역기반 T2관리도)

  • Kim, Jeong-Hun;Kim, Seoung-Bum
    • Journal of the Korean Society for Quality Management
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    • v.40 no.3
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    • pp.337-346
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    • 2012
  • Purpose: A Control chart is one of the important statistical process control tools that can improve processes by reducing variability and defects. Methods: In the present study, we propose the local $T^2$ multivariate control chart that can efficiently detect abnormal observations by considering the local pattern of the in-control observations. Results: A simulation study has been conducted to examine the property of the proposed control chart and compare it with existing multivariate control charts. Conclusion: The results demonstrate the usefulness and effectiveness of the proposed control chart.

Process operation improvement methodology based on statistical data analysis (통계적 분석기법을 이용한 공정 운전 향상의 방법)

  • Hwang, Dae-Hee;Ahn, Tae-Jin;Han, Chonghun
    • 제어로봇시스템학회:학술대회논문집
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    • pp.1516-1519
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    • 1997
  • With disseminationof Distributed Control Systems(DCS), the huge amounts of process operation data could have been available and led to figure out process behaviors better on the statistical basis. Until now, the statistical modeling technology has been susally applied to process monitoring and fault diagnosis. however, it has been also thought that these process information, extracted from statistical analysis, might serve a great opportunity for process operation improvements and process improvements. This paper proposed a general methodolgy for process operation improvements including data analysis, backing up the result of analysis based on the methodology, and the mapping physical physical phenomena to the Principal Components(PC) which is the most distinguished feature in the methodology form traditional statistical analyses. The application of the proposed methodology to the Balst Furnace(BF) process has been presented for details. The BF process is one of the complicated processes, due to the highly nonlinear and correlated behaviors, and so the analysis for the process based on the mathematical modeling has been very difficult. So the statisitical analysis has come forward as a alternative way for the useful analysis. Using the proposed methodology, we could interpret the complicated process, the BF, better than any other mathematical methods and find the direction for process operation improvement. The direction of process operationimprovement, in the BF case, is to increase the fludization and the permeability, while decreasing the effect of tapping operation. These guide directions, with those physical meanings, could save fuel cost and process operator's pressure for proper actions, the better set point changes, in addition to the assistance with the better knowledge of the process. Open to set point change, the BF has a variety of steady state modes. In usual almost chemical processes are under the same situation with the BF in the point of multimode steady states. The proposed methodology focused on the application to the multimode steady state process such as the BF, consequently can be applied to any chemical processes set point changing whether operator intervened or not.

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Update Cycle Detection Method of Control Limits using Control Chart Performance Evaluation Model (관리도 성능평가모형을 통한 관리한계선 갱신주기 탐지기법)

  • Kim, Jongwoo;Park, Cheong-Sool;Kim, Jun Seok;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.1
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    • pp.43-51
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    • 2014
  • Statistical process control (SPC) is an important technique for monitoring and managing the manufacturing process. In spite of its easiness and effectiveness, some problematic sides of application exist such that the SPC techniques are hardly reflect the changes of the process conditions. Especially, update of control limits at the right time plays an important role in acquiring a reasonable performance of control charts. Therefore, we propose the control chart performance evaluation index (CPEI) based on count data model to monitor and manage the performance of control charts. The CPEI could indicate the degree of control chart performance and be helpful to detect the proper update cycle of control limits in real time. Experiments using real manufacturing data show that the proper update intervals are made by proposed method.

Real-time malfunction detection of plasma etching process using EPD signal traces (EPD 신호궤적을 이용한 플라즈마 식각공정의 실시간 이상검출)

  • Cha, Sang-Yeob;Yi, Seok-Ju;Koh, Taek-Beom;Woo, Kwang-Bang
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.2
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    • pp.246-255
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    • 1998
  • This paper presents a novel method for real-time malfunction detection of plasma etching process using EPD signal traces. First, many reference EPD signal traces are collected using monochromator and data acquisition system in normal etching processes. Critical points are defined by applying differentiation and zero-crossing method to the collected reference signal traces. Critical parameters such as intensity, slope, time, peak, overshoot, etc., determined by critical points, and frame attributes transformed signal-to symbol of reference signal traces are saved. Also, UCL(Upper Control Limit) and LCL(Lower Control Limit) are obtained by mean and standard deviation of critical parameters. Then, test EPD signal traces are collected in the actual processes, and frame attributes and critical parameters are obtained using the above mentioned method. Process malfunctions are detected in real-time by applying SPC(Statistical Process Control) method to critical parameters. the Real-time malfunction detection method presented in this paper was applied to actual processes and the results indicated that it was proved to be able to supplement disadvantages of existing quality control check inspecting or testing random-selected devices and detect process malfunctions correctly in real-time.

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Statistical Analysis on Critical Dimension Variation for a Semiconductor Fabrication Process (반도체 제조공정의 Critical Dimension 변동에 대한 통계적 분석)

  • Park, Sung-Min;Lee, Jeong-In;Kim, Byeong-Yun;Oh, Young-Sun
    • IE interfaces
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    • v.16 no.3
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    • pp.344-351
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    • 2003
  • Critical dimension is one of the most important characteristics of up-to-date integrated circuit devices. Hence, critical dimension control in a semiconductor wafer fabrication process is inevitable in order to achieve optimum device yield as well as electrically specified functions. Currently, in complex semiconductor wafer fabrication processes, statistical methodologies such as Shewhart-type control charts become crucial tools for practitioners. Meanwhile, given a critical dimension sampling plan, the analysis of variance technique can be more effective to investigating critical dimension variation, especially for on-chip and on-wafer variation. In this paper, relating to a typical sampling plan, linear statistical models are presented for the analysis of critical dimension variation. A case study is illustrated regarding a semiconductor wafer fabrication process.

Portfolio Management Using Statistical Process Control Chart (SPC 차트를 이용한 포트폴리오 관리)

  • Kim, Dong-Sup;Ryoo, Hong-Seo
    • 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.