What is a time-weighted control chart?

Time-weighted control charts are powerful and simple visual tools for determining whether a process is in or out of control.

·    An in-control process exhibits only random variation within the control limits.

·    An out-of-control process demonstrates unusual variation due to the presence of special causes.

In other words, control charts can help you determine whether the process average (center) and process variability (spread) are operating at constant levels. Control charts help you focus problem-solving efforts by distinguishing between common and special-cause variation.

Time-weighted control charts are a special case of variables control charts. With the exception of Moving Average, Minitab's time-weighted control charts are weighted either by previous subgroup means or a target value. The advantage of using time-weighted control charts is the ability to detect small shifts from the target value.

A time-weighted control chart consists of:

·    Plotted points, each of which represents a rational subgroup of data sampled from the process, such as a subgroup mean, individual observation, or weighted statistic. Minitab plots this statistic versus a sample number or time, and displays the results in time order.

·    A center line, which represents the expected value of the quality characteristics for all subgroups.

·    Upper and lower control limits (UCL and LCL), which are set at a distance of 3 s above and below the center line. These control limits provide a visual display for the expected amount of variation. Control limits predict how the process should behave. The control limits are based on the actual behavior of the process, not the desired behavior - they are not specification limits. A process can be in control and yet not be capable of meeting requirements.

Control charts evaluate the pattern of variation for stability through the use of tests for special causes. If you detect special cause variation, you should seek out the factors that contribute to this variation so that you can implement corrective measures.