Economic-statistical Design of a Logarithmic Transformed S2 EWMA Chart

Abstract

Exponentially weighted moving average (EWMA) control charts are an efficient means in detecting small process shifts, both in position and dispersion of the collected data. Implementing an EWMA chart to control a manufacturing process requires the computation and plotting of a random variable which is a function of the current sample statistic and of the past samples collected from the process. This allows the EWMA to prevail over the traditional Shewhart chart in terms of statistical sensitivity when small shifts in the process position and/or dispersion are expected. The aim of this chapter is to present the economic-statistical design of a S2 EWMA control chart for the on-line control of the process dispersion. The investigated chart operates through a control statistic based on a logarithmic transformation of the sample variance to make possible working on an approximately standard normally distributed random variable. Since the implementation of control charts to monitor process stability has become normal practice within an industrial manufacturing environment, designing economically the control chart is an important managerial aspect of SPC that should be carefully taken into account by practitioners.