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حوزهطراحی آزمایشطراحی آزمایش
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش1980s–present1924–1931
پدیدآورWalter A. Shewhart (SPC foundations); simulation integration developed through industrial engineering literature from the 1980s onwardWalter A. Shewhart
نوعHybrid quantitative methodProcess monitoring and quality control method
منبع بنیادینMontgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
نام‌های دیگرSimulation-based SPC, Monte Carlo SPC, SA-SPC, Simulation-integrated SPCSPC, statistical quality control, process control charting, Shewhart control
مرتبط66
خلاصهSimulation-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.Statistical Process Control (SPC) is a data-driven quality method that uses statistical techniques — primarily control charts — to monitor a manufacturing or service process over time. By distinguishing natural process variation (common cause) from unusual, actionable variation (special cause), SPC enables practitioners to maintain processes in a stable, predictable state and to detect problems early, before defective output reaches customers.
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ScholarGateمقایسهٔ روش‌ها: Simulation-assisted statistical process control · Statistical Process Control. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare