A NUMERICAL METHOD FOR MODELLING THE PARAMETERS Λ AND Δ OF AN EWMA CHART

Abstract

The exponentially weighted moving average chart (EWMA) is widely employed in quality control to monitor a process or to evaluate historic data. EWMA charts are designed to exhibit acceptable average run lengths both when the process is in and out of control. This paper introduces a functional technique for generating the parameters λ and Δ for such a chart that will have specified average run lengths. The parameters are estimated using regression plus an artificial neural network.

Keywords

• ARL
• average run length
• EWMA chart
• Exponentially Weighted Moving Average chart
• neural network
• parameter estimation
• SPC
• statistical process control