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EWMA kontroles karte×Kontrolkartes atribūtiem (p, np, c, u)×KUMULATĪVĀS SUMMAS (CUSUM) KONTROLKARTE×
NozareStatistikaStatistikaStatistika
SaimeProcess / pipelineProcess / pipelineProcess / pipeline
Izcelsmes gads195919311954
AutorsS. W. RobertsWalter A. ShewhartE. S. Page
TipsStatistical process control chart for small shiftsStatistical process control charts for count/proportion dataStatistical process control chart for small shifts
PirmavotsRoberts, S. W. (1959). Control chart tests based on geometric moving averages. Technometrics, 1(3), 239–250. DOI ↗Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company. ISBN: 978-0-87389-076-2Page, E. S. (1954). Continuous inspection schemes. Biometrika, 41(1/2), 100–115. DOI ↗
Citi nosaukumiexponentially weighted moving average chart, EWMA control chart, geometric moving average chart, EWMA kontrol kartıp-chart, np-chart, c-chart, u-chartcumulative sum chart, CUSUM control chart, Page's CUSUM, kümülatif toplam kontrol kartı
Saistītās344
KopsavilkumsThe exponentially weighted moving average (EWMA) control chart, introduced by S. W. Roberts in 1959, monitors a process using a weighted average that gives the most recent observation the greatest weight while letting older observations fade geometrically. Like CUSUM, this memory makes it highly effective at detecting small, sustained shifts in the process mean, with a single smoothing parameter λ controlling how much past information the chart retains.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.
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ScholarGateSalīdzināt metodes: EWMA Chart · Attributes Control Chart · CUSUM Chart. Izgūts 2026-06-18 no https://scholargate.app/lv/compare