Grouped Data Exponentially Weighted Moving Average Control Charts
نویسنده
چکیده
In the manufacture of metal fasteners in a progressive die operation, and other industrial situations, important quality dimensions cannot be measured on a continuous scale, and parts are classified into groups using a step gauge. This article proposes a version of exponentially weighted moving average (EWMA) control charts applicable to monitoring the grouped data for process shifts. The run length properties of this new grouped data EWMA chart are compared with similar results previously obtained for EWMA charts for variables data and with those for Cumulative Sum (CUSUM) schemes based on grouped data. Grouped data EWMA charts are shown to be nearly as efficient as variables based EWMA charts, and are thus an attractive alternative when collection of variables data is not feasible. In addition, grouped data EWMA charts are less affected by the discreteness inherent in grouped data than are grouped data CUSUM charts. In the metal fasteners application, grouped data EWMA charts were simple to implement and allowed the rapid detection of undesirable process shifts.
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