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The impracticality of homogeneously weighted moving average and progressive mean control chart approaches
Authors:Sven Knoth  Víctor G. Tercero-Gómez  Marzieh Khakifirooz  William H. Woodall
Affiliation:1. Department of Mathematics and Statistics, Helmut Schmidt University Hamburg, Hamburg, Germany;2. Tecnologico de Monterrey, Monterrey, Nuevo Leon, Mexico;3. Department of Statistics, Virginia Tech, Blacksburg, Virginia, USA
Abstract:There is growing literature on new versions of “memory-type” control charts, where deceptively good zero-state average run-length (ARL) performance is misleading. Using steady-state run-length analysis in combination with the conditional expected delay (CED) metric, we show that the increasingly discussed progressive mean (PM) and homogeneously weighted moving average (HWMA) control charts should not be used in practice. Previously reported performance of methods based on these two approaches is misleading, as we found that performance is good only when a process change occurs at the very start of monitoring. Traditional alternatives, such as exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts, not only have more consistent detection behavior over a range of different change points, they can also lead to better out-of-control zero-state ARL performance when properly designed.
Keywords:average run length  control chart  statistical process monitoring  steady-state average run length
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