Сравнение методов

	Гибридный статистический контроль процессов	Контрольная карта сумм нарастания (CUSUM)
Область	Планирование эксперимента	Статистика
Семейство	Process / pipeline	Process / pipeline
Год появления	1990s–2000s	1954
Автор метода	Evolved from classical SPC (Shewhart, 1920s); hybrid extensions developed broadly from the 1990s onward by researchers including Montgomery, Woodall, and various neural-network SPC authors	E. S. Page
Тип	Process monitoring and control methodology	Statistical process control chart for small shifts
Основополагающий источник	Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0-470-16992-6	Page, E. S. (1954). Continuous inspection schemes. Biometrika, 41(1/2), 100–115.
Другие названия	Hybrid SPC, combined SPC, integrated SPC, hybrid process monitoring	cumulative sum chart, CUSUM control chart, Page's CUSUM, kümülatif toplam kontrol kartı
Связанные	2	4
Сводка	Hybrid Statistical Process Control integrates classical control-chart methods (Shewhart, CUSUM, EWMA) with complementary techniques — such as neural networks, fuzzy logic, economic design, or multivariate statistics — to monitor and control manufacturing or service processes more effectively than any single approach alone. The hybrid architecture addresses known weaknesses of conventional SPC, including slow detection of small shifts, pattern-recognition limitations, and inability to handle non-normal or autocorrelated data.	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.