Editing Control chart (section)

{{Short description|Process control tool to determine if a manufacturing process is in a state of control}}
{{more footnotes|date=December 2013}}
{{Infobox quality tool
| image =     Xbar chart for a paired xbar and R chart.svg
| category =  One of the '''[[Seven basic tools of quality]]'''
| describer = [[Walter A. Shewhart]]
| purpose =   To determine whether a process should undergo a formal examination for quality-related problems
}}
'''Control charts''' are [[Plot (graphics)|graphical plots]] used in production control to determine whether quality and [[manufacturing]] processes are being [[Statistical Process Control|controlled]] under stable conditions. (ISO 7870-1)<ref name="ISO7870-1">{{cite web |title=Control charts — Part 1: General guidelines |url=https://www.iso.org/standard/69639.html |publisher=iso.org |accessdate=2022-12-11}}</ref> 
The hourly status is arranged on the graph, and the occurrence of abnormalities is judged based on the presence of data that differs from the conventional trend or deviates from the control limit line.
Control charts are classified into [[Shewhart individuals control chart]] (ISO 7870-2)<ref name="ISO7870-2">{{cite web |title=Control charts — Part 2: Shewhart control charts |url=https://www.iso.org/standard/40174.html |publisher=iso.org |accessdate=2022-12-11}}</ref> and [[CUSUM]](CUsUM)(or cumulative sum control chart)(ISO 7870-4).<ref name="ISO7870-4">{{cite web |title=Control charts — Part 4: Cumulative sum charts |url=https://www.iso.org/standard/74101.html |publisher=iso.org |accessdate=2022-12-11}}</ref>

Control charts, also known as '''Shewhart charts''' (after [[Walter A. Shewhart]]) or '''process-behavior charts''', are a [[statistical process control]] tool used to determine if a [[Manufacturing process management|manufacturing]] or [[business process]] is in a state of [[statistical control|control]].  It is more appropriate to say that the control charts are the graphical device for statistical process monitoring (SPM). Traditional control charts are mostly designed to monitor process parameters when the underlying form of the process distributions are known. However, more advanced techniques are available in the 21st century where incoming data streaming can-be monitored even without any knowledge of the underlying process distributions. [[Distribution-free control chart]]s are becoming increasingly popular.{{citation needed|date=August 2023}}