A forecast-based monitoring methodology for process transitions

Nonconforming pails are often produced when a process moves from one level to another due to transition events. Control charting, when applied to a st able state process, is an effective monitoring tool to continuously check f or process shifts or upsets. However, the presence of transition events can impede the normal performance of traditional control chart with increased false alarms. The presence of autocorrelation also requires modification to the control charting procedure. We present a methodology for characterizin g the process transition which involves a tracking signal statistic, based on the forecast-based exponentially weighted moving average (EWMA). This te st will supplement the forecast-based EWMA control charting as a means of d etecting when the transition event is complete. Such a procedure facilitate s smooth application of the appropriate control chart by knowing when the t ransition is over. The transition characterization methodology also carries benefits in cost and material savings. We use a color transition process i n plastic extrusion to illustrate a transition event and demonstrate our pr oposed methodology. Simulation is employed to evaluate the performance of t he methodology. Copyright (C) 2001 John Wiley & Sons, Ltd.