Editing Control chart (section)

== Overview ==
If analysis of the control chart indicates that the process is currently under control (i.e., is stable, with variation only coming from sources common to the process), then no corrections or changes to process control parameters are needed or desired. In addition, data from the process can be used to [[Predictive analytics|predict]] the future performance of the process. If the chart indicates that the monitored process is not in control, analysis of the chart can help determine the sources of [[Statistical dispersion|variation]], as this will result in degraded process performance.<ref>{{cite web | url=http://www.spcforexcel.com/overcontrolling-process-funnel-experiment | last = McNeese | first = William | title = Over-controlling a Process: The Funnel Experiment | publisher = BPI Consulting, LLC | date=July 2006| access-date = 2010-03-17}}</ref> A process that is stable but operating outside desired (specification) limits (e.g., scrap rates may be in statistical control but above desired limits) needs to be improved through a deliberate effort to understand the causes of current performance and fundamentally improve the process.<ref name="WheelerUV">{{cite book | title=Understanding Variation | publisher=SPC Press | author=Wheeler, Donald J. | year=2000 | location=Knoxville, Tennessee | isbn=978-0-945320-53-1 | url=https://archive.org/details/understandingvar00dona }}</ref>

The control chart is one of the [[Seven basic tools of quality|seven basic tools]] of [[quality control]].<ref>{{cite web | url = http://www.asq.org/learn-about-quality/seven-basic-quality-tools/overview/overview.html | author = Nancy R. Tague | title = Seven Basic Quality Tools | year = 2004 | work = The Quality Toolbox | publisher = [[American Society for Quality]] | location = [[Milwaukee, Wisconsin]] | page = 15 | access-date = 2010-02-05}}</ref> Typically control charts are used for [[Time series|time-series]] data, also known as [[Continuous or discrete variable|continuous]] data or variable data. Although they can also be used for data that has logical comparability (i.e. you want to compare samples that were taken all at the same time, or the performance of different individuals); however the type of chart used to do this requires consideration.<ref>{{cite journal | author = A Poots, T Woodcock | title = Statistical process control for data without inherent order | year = 2012 | journal = BMC Medical Informatics and Decision Making | volume = 12 | page = 86 | doi = 10.1186/1472-6947-12-86 |pmid = 22867269| pmc = 3464151 | doi-access = free }}</ref>