Editing Statistical process control (section)

===Control charts===
The data from measurements of variations at points on the process map is monitored using [[control charts]]. Control charts attempt to differentiate "assignable" ("special") sources of variation from "common" sources. "Common" sources, because they are an expected part of the process, are of much less concern to the manufacturer than "assignable" sources. Using control charts is a continuous activity, ongoing over time.

====Stable process====
When the process does not trigger any of the control chart "detection rules" for the control chart, it is said to be "stable". A [[process capability]] analysis may be performed on a stable process to predict the ability of the process to produce "conforming product" in the future.

A stable process can be demonstrated by a process signature that is free of variances outside of the capability index. A process signature is the plotted points compared with the capability index.

====Excessive variations====

When the process triggers any of the control chart "detection rules", (or alternatively, the process capability is low), other activities may be performed to identify the source of the excessive variation.
The tools used in these extra activities include: [[Ishikawa diagram]], [[designed experiment]]s, and [[Pareto chart]]s. Designed experiments are a means of objectively quantifying the relative importance (strength) of sources of variation. Once the sources of (special cause) variation are identified, they can be minimized or eliminated.  Steps to eliminating a source of variation might include: development of standards, staff training, error-proofing, and changes to the process itself or its inputs.

====Process stability metrics====

When monitoring many processes with control charts, it is sometimes useful to calculate quantitative measures of the stability of the processes. These metrics can then be used to identify/prioritize the processes that are most in need of corrective actions. These metrics can also be viewed as supplementing the traditional [[process capability]] metrics. Several metrics have been proposed, as described in Ramirez and Runger.<ref name="Ramarez2006">{{cite journal
| last1 = Ramirez |first1=B.
| last2 = Runger |first2=G.
|title= Quantitative Techniques to Evaluate Process Stability
|journal= Quality Engineering
|volume=18
|issue=1
|pages=53–68
|year=2006 | doi = 10.1080/08982110500403581
|s2cid=109601393
}}</ref>
They are (1) a Stability Ratio which compares the long-term variability to the short-term variability, (2) an ANOVA Test which compares the within-subgroup variation to the between-subgroup variation, and (3) an Instability Ratio which compares the number of subgroups that have one or more violations of the [[Western Electric rules]] to the total number of subgroups.