Control charts are graphs that plot your process data in time-ordered sequence. Most control charts include a center line, an upper control limit, and a lower control limit. The center line …

Multivariate control charts are a type of variables control chart that shows how correlated, or dependent, variables jointly affect a process or outcome. For example, you can use a …

Minitab offers several attribute control charts that plot defects or defectives. A defect refers to a quality characteristic and a defective unit refers to the overall product. A unit may have many …

How do I specify tests and parameters for a control chart? How do I change the default tests and test parameters? Which tests for special causes are included in Minitab?

A good starting point in investigating special-cause variation is to gather several process experts together. Using the control chart, encourage the process operators, the process engineers, …

Before you interpret the Xbar chart, examine the R chart to determine whether the process variation is in control. If the R chart is not in control, then the control limits on the Xbar chart …

Before you interpret the Individual chart (I chart), examine the Moving Range chart (MR chart) to determine whether the process variation is in control. If the MR chart is not in control, then the …

Use this control chart to monitor process stability over time so that you can identify and correct instabilities in a process. For example, a delivery service manager uses a P chart to monitor …

Choose Stat > Control Charts > Attributes Charts > C. In Variables, enter Defects. Click C Chart Options. On the Tests tab, select 1 point > K standard deviations from center line (Test 1) and …

Use stages to create a historical control chart that shows how a process changes over specific periods of time. By default, Minitab recalculates the center line and control limits for each …