方法对比

	贝叶斯过程能力分析	控制图
领域	实验设计	实验设计
方法族	Process / pipeline	Process / pipeline
起源年份	Classical PCA: 1986; Bayesian extensions: 1990s–2000s	1924 (first use); 1931 (seminal book)
提出者	Bayesian extensions developed by multiple authors including Bernardo, Smith, and Vannman; classical PCA by Juran and Kane (1986)	Walter A. Shewhart (Bell Labs)
类型	Bayesian statistical quality method	Statistical monitoring and control technique
开创性文献	Kotz, S., & Johnson, N. L. (2002). Process Capability Indices — A Review, 1992–2000. Journal of Quality Technology, 34(1), 2–19.	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand.
别名	Bayesian PCA, Bayesian capability indices, Bayesian Cp/Cpk estimation, Bayesian process performance analysis	Shewhart chart, process-behavior chart, SPC chart, quality control chart
相关	5	6
摘要	Bayesian Process Capability Analysis integrates Bayesian inference with classical capability indices (Cp, Cpk, Cpm) to estimate how well a production process meets specification limits. Rather than relying solely on observed sample data, it incorporates prior knowledge about process parameters — yielding more stable and credible estimates of process capability, especially under small sample sizes common in manufacturing and quality engineering.	A control chart is a time-series graph with statistically derived upper and lower control limits that separates the natural, random variation of a process (common cause) from unusual, assignable variation (special cause). Invented by Walter Shewhart at Bell Labs in 1924, control charts remain the foundational tool of Statistical Process Control and are used across manufacturing, healthcare, software, and service industries to monitor whether a process remains stable and predictable over time.