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Simulation-Assisted Statistical Process Control×过程能力分析 (Cp, Cpk)×
领域实验设计统计学
方法族Process / pipelineProcess / pipeline
起源年份1980s–present1986
提出者Walter A. Shewhart (SPC foundations); simulation integration developed through industrial engineering literature from the 1980s onwardVictor Kane
类型Hybrid quantitative methodQuantitative process evaluation index
开创性文献Montgomery, 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 ↗
别名Simulation-based SPC, Monte Carlo SPC, SA-SPC, Simulation-integrated SPCProcess Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
相关62
摘要Simulation-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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ScholarGate方法对比: Simulation-assisted statistical process control · Process Capability Analysis. 于 2026-06-15 检索自 https://scholargate.app/zh/compare