方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 基于风险的过程能力分析× | 统计过程控制× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s (formal integration with risk analysis) | 1924–1931 |
| 提出者≠ | Evolved from classical capability indices (Juran, Kane) integrated with risk frameworks (FMEA, ISO 9001) | Walter A. Shewhart |
| 类型≠ | Quantitative quality engineering method | Process monitoring and quality control method |
| 开创性文献≠ | Montgomery, D. C. (2020). Introduction to Statistical Quality Control (8th ed.). Wiley. ISBN: 978-1119399308 | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 |
| 别名 | RBPCA, risk-adjusted capability analysis, capability-risk integration, risk-informed SPC | SPC, statistical quality control, process control charting, Shewhart control |
| 相关≠ | 4 | 6 |
| 摘要≠ | Risk-based Process Capability Analysis (RBPCA) combines classical process capability indices (Cp, Cpk, Pp, Ppk) with structured risk assessment tools — such as FMEA risk priority numbers — to prioritise improvement actions not merely by how capable a process is, but by the potential harm its failures can cause. The approach is widely used in automotive, aerospace, medical device, and pharmaceutical manufacturing to align quality engineering decisions with risk management requirements. | 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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