MAX-EWMA CHART FOR AUTOCORRELATED PROCESSES (MEWMAP CHART)

Authors

  • K. Thaga Department of Statistics, University of Botswana
  • V.S.S. Yadavalli Department of Industrial and Systems Engineering, University of Pretoria

DOI:

https://doi.org/10.7166/18-2-123

Abstract

ENGLISH ABSTRACT: This paper proposes an exponentially weighted moving average (EWMA) control chart that is capable of detecting changes in both process mean and standard deviation for autocorrelated data (referred to as the Maximum Exponentially Weighted Moving Average Chart for Autocorrelated Process, or MEWMAP chart). This chart is based on fitting a time series model to the data, and then calculating the residuals. The observations are represented as a first-order autoregressive process plus a random error term. The Average Run Lengths (ARLs) for fixed decision intervals and reference values (h, k) are calculated. The proposed chart is compared with the Max-CUSUM chart for autocorrelated data proposed by Thaga (2003). Comparisons are based on the out-of-control ARLs. The MEWMAP chart detects moderate to large shifts in the mean and/or standard deviation at both low and high levels of autocorrelations more quickly than the Max-CUSUM chart for autocorrelated processes.

AFRIKAANSE OPSOMMING: Die navorsing stel voor dat 'n eksponensiaal geweegde bewegende gemiddelde kontrolekaart gebruik word om verandering van prosesgemiddelde en

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Published

2011-11-05

How to Cite

Thaga, K., & Yadavalli, V. (2011). MAX-EWMA CHART FOR AUTOCORRELATED PROCESSES (MEWMAP CHART). The South African Journal of Industrial Engineering, 18(2). https://doi.org/10.7166/18-2-123

Issue

Vol. 18 No. 2 (2007)

Section

General Articles

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