Sammenlign metoder

	Attribut-kontrolkort (p, np, c, u)	CUSUM-kontrolkort	Shewhart-regulativkort (X-streg / R)
Fagområde	Statistik	Statistik	Statistik
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Oprindelsesår	1931	1954	1931
Ophavsperson	Walter A. Shewhart	E. S. Page	Walter A. Shewhart
Type	Statistical process control charts for count/proportion data	Statistical process control chart for small shifts	Statistical process control chart for variables
Oprindelig kilde	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company. ISBN: 978-0-87389-076-2	Page, E. S. (1954). Continuous inspection schemes. Biometrika, 41(1/2), 100–115.	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company. ISBN: 978-0-87389-076-2
Aliasser	p-chart, np-chart, c-chart, u-chart	cumulative sum chart, CUSUM control chart, Page's CUSUM, kümülatif toplam kontrol kartı	X-bar and R chart, Shewhart chart, variables control chart, process control chart
Relaterede	4	4	4
Resumé	Attributes control charts extend Shewhart's framework to count and proportion data — quality characteristics that are classified rather than measured. The p- and np-charts monitor the proportion or number of defective items using the binomial distribution, while the c- and u-charts monitor the number of defects per unit using the Poisson distribution. They are the standard statistical-process-control tools when inspection yields pass/fail or defect counts rather than continuous measurements.	The cumulative sum (CUSUM) control chart, introduced by E. S. Page in 1954, monitors a process by accumulating the deviations of observations from a target value rather than judging each point in isolation. Because small persistent shifts add up over time, the running sum makes them visible far sooner than a Shewhart chart, making CUSUM the tool of choice for detecting small, sustained changes in the process mean.	The Shewhart control chart, invented by Walter Shewhart at Bell Labs in the 1920s and set out in his 1931 book, is the foundational tool of statistical process control. It plots a process statistic — typically the subgroup mean (X-bar) and range (R) — over time against a center line and three-sigma control limits, distinguishing the natural common-cause variation inherent in a stable process from special-cause variation that signals something has changed and warrants investigation.