Quality and Process Methods > Weighted Moving Average Control Charts > Weighted Moving Average Chart Reports
Publication date: 08/13/2020

Weighted Moving Average Chart Reports

The UWMA and EWMA platforms produce charts that can be used to determine whether a process is in a state of statistical control. The report varies depending on the type of chart that you select. Weighted moving average charts update dynamically as data is added or changed in the data table.

Weighted moving average charts have the following characteristics:

Each point plotted on the chart represents an individual process measurement or summary statistic.

Subgroups should be chosen rationally, that is, they should be chosen to maximize the probability of seeing a true process change between subgroups.

The vertical axis of the chart is scaled in the same units as the summary statistic.

The horizontal axis of the chart identifies the subgroup samples and is time ordered. Observing the process over time is important in assessing if the process is changing.

The green line is the center line, or the average of the data. The center line indicates the average (expected) value of the summary statistic when the process is in statistical control. Measurements should appear equally on both sides of the center line. If not, this is possible evidence that the process average is changing.

The two red lines are the upper and lower control limits, labeled UCL and LCL. These limits give the range of variation to be expected in the summary statistic when the process is in statistical control. If the process is exhibiting only routine variation, then all the points should fall randomly in that range.

A point outside the control limits signals the presence of a special cause of variation.

Options within each platform create charts that can be updated dynamically as samples are received and recorded or added to the data table.

When a weighted moving average chart signals abnormal variation, action should be taken to return the process to a state of statistical control if the process degraded. If the abnormal variation indicates an improvement in the process, the causes of the variation should be studied and implemented.

When you double-click the horizontal or vertical axis, the corresponding Axis Specification window appears for you to specify the format, axis values, number of ticks, grid line, reference lines, and other options to display on the axis.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).
.