EWMA control charts for autoregressive processes

A B Koehler (), N B Marks and R T O'connell
Additional contact information
A B Koehler: Miami University
N B Marks: Miami University
R T O'connell: Miami University

Journal of the Operational Research Society, 2001, vol. 52, issue 6, 699-707

Abstract: Abstract Many processes must be monitored by using observations that are correlated. An approach called algorithmic statistical process control can be employed in such situations. This involves fitting an autoregressive/moving average time series model to the data. Forecasts obtained from the model are used for active control, while the forecast errors are monitored by using a control chart. In this paper we consider using an exponentially weighted moving average (EWMA) chart for monitoring the residuals from an autoregressive model. We present a computational method for finding the out-of-control average run length (ARL) for such a control chart when the process mean shifts. As an application, we suggest a procedure and provide an example for finding the control limits of an EWMA chart for monitoring residuals from an autoregressive model that will provide an acceptable out-of-control ARL. A computer program for the needed calculations is provided via the World Wide Web.

Keywords: statistical process control; autoregressive model; EWMA control chart; algorithmic control charts (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1057/palgrave.jors.2601140

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