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

Chun, Sang Pyo

doi:https://doi.org/10.9708/jksci.2020.25.12.187

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2020, 25(12), pp.187-194
DOI :https://doi.org/10.9708/jksci.2020.25.12.187
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Chun, Sang Pyo ¹

¹ 남서울대학교

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
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KCI Citation (0)

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