A Study on UBM Method Detecting Mean Shift in Autocorrelated Process Control

Chun, Sang Pyo

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2020, 25(12), pp.187-194
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Chun, Sang Pyo ¹

¹남서울대학교

ABSTRACT

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.
KEYWORDS

Autocorrelation, CUSUM control chart, EWMA control chart, Unweighted Batch Mean, Average Run Length
REFERENCES (13)

[journal] Layth C. Alwan / 1988 / Time-Series Modeling for Statistical Process Control / Journal of Business & Economic Statistics 6 : 87~95

[journal] George C. Runger / 1996 / Batch Mean Control Charts for Autocorrelated Data / IIE Transactions 28(6) : 483~487

[journal] Chung. Chen / 1993 / Joint Estimation of Model Parameters and Outlier Effects in Time Series / Journal of the American Statistical Association 88 : 284~297

[journal] O. O. Atienza / 1998 / A SPC Procedure for Detecting Level Shifts of Autocorrelated Processes / Journal of Quality Technology 30(4) : 340~351

[journal] Runger, George C / 1995 / Average Run Length for CUSUM Control Charts Applied to Residuals / Communications Statistics - Theory and Method 24(1) : 273~282

[journal] Chao-Wen. Lu / 1999 / EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes / Journal of Quality Technology 31(2) : 166~188

[book] Montgomery, Douglas C. / 2013 / Statistical quality control: A modern introduction / John Wiley & Sons, Inc

[journal] Sven Knoth / 2004 / Accurate ARL computation for EWMA-S2 control charts / Statistics and computing 15 : 341~352

[journal] Sven Knoth / 2007 / Accurate ARL computation for EWMA control charts monitoring simultaneously normal mean and variance / Sequential Analysis 26(3) : 251~264

[journal] Haim Shore / 1997 / Process Capability Analysis When Data are Autocorrelated / Quality Engineering 4(4) : 615~626

[journal] S. Jack. Hu / 1996 / Change Patterns of Time SeriesBased Control Charts / Journal of Quality Technology 28(3) : 302~312

[journal] Min. Zhang / 2013 / Geometric charts with estimated control limits / Qualaity and Reliability Engineering International 29 : 209~223

[journal] Min. Zhang / 2014 / Exponential CUSUM charts with estimated control limits / Qualaity and Reliability Engineering International 30 : 275~286
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