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Статистически контрол на процесите с помощта на симулация×Анализ на възможностите на процеса (Cp, Cpk)×
ОбластПланиране на експериментаСтатистика
СемействоProcess / pipelineProcess / pipeline
Година на възникване1980s–present1986
СъздателWalter A. Shewhart (SPC foundations); simulation integration developed through industrial engineering literature from the 1980s onwardVictor Kane
ТипHybrid quantitative methodQuantitative process evaluation index
Основополагащ източникMontgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52. DOI ↗
Други названияSimulation-based SPC, Monte Carlo SPC, SA-SPC, Simulation-integrated SPCProcess Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
Свързани62
РезюмеSimulation-assisted statistical process control (SA-SPC) combines computer simulation — typically Monte Carlo or discrete-event simulation — with classical SPC methods to design, test, and calibrate control charts and monitoring schemes before or alongside deployment on a real production process. Rather than relying solely on closed-form analytical assumptions, SA-SPC uses simulated data to evaluate chart performance under realistic, often non-normal process conditions.Process Capability Analysis quantifies how well a manufacturing or business process produces output within specified tolerance limits. Introduced formally by Victor Kane in 1986, it summarises process spread and centering into dimensionless indices — most notably Cp and Cpk — allowing engineers and quality managers to judge whether a stable process is inherently capable of meeting customer or design specifications consistently.
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ScholarGateСравнение на методи: Simulation-assisted statistical process control · Process Capability Analysis. Извлечено на 2026-06-15 от https://scholargate.app/bg/compare