Control charts are widely used in manufacturing to distinguish between variation that is inherent to the process and variation that signals a special event or problem. Several control charts have recently been proposed for the detection of a periodic component, but their analysis is limited to a moving span of recent observations. This article develops tests for periodicity that make use of independent information about the variability of the time series. These tests are then used to construct control charts that search for periodicity in a span of recent observations but estimate the variability of the process from a longer span of earlier observations. By employing more of the available information, the new charts are able to detect cyclic disturbances more quickly than the existing charts.