ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Контрольная карта EWMA×Контрольные карты для атрибутивных данных (p, np, c, u)×Контрольная карта сумм нарастания (CUSUM)×Контрольная карта Шухарта для переменных (X-среднее / R)×
ОбластьСтатистикаСтатистикаСтатистикаСтатистика
СемействоProcess / pipelineProcess / pipelineProcess / pipelineProcess / pipeline
Год появления1959193119541931
Автор методаS. W. RobertsWalter A. ShewhartE. S. PageWalter A. Shewhart
ТипStatistical process control chart for small shiftsStatistical process control charts for count/proportion dataStatistical process control chart for small shiftsStatistical process control chart for variables
Основополагающий источникRoberts, 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 ↗Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company. ISBN: 978-0-87389-076-2
Другие названияexponentially 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 kartıX-bar and R chart, Shewhart chart, variables control chart, process control chart
Связанные3444
СводкаThe 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.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.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: EWMA Chart · Attributes Control Chart · CUSUM Chart · Shewhart Control Chart. Получено 2026-06-18 из https://scholargate.app/ru/compare