השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח יכולת תהליך מבוסס-סיכון× | בקרת תהליכים סטטיסטית× | |
|---|---|---|
| תחום | תכנון ניסויים | תכנון ניסויים |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 1990s–2000s (formal integration with risk analysis) | 1924–1931 |
| הוגה השיטה≠ | Evolved from classical capability indices (Juran, Kane) integrated with risk frameworks (FMEA, ISO 9001) | Walter A. Shewhart |
| סוג≠ | Quantitative quality engineering method | Process monitoring and quality control method |
| מקור מכונן≠ | 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 |
| כינויים | RBPCA, risk-adjusted capability analysis, capability-risk integration, risk-informed SPC | SPC, statistical quality control, process control charting, Shewhart control |
| קשורות≠ | 4 | 6 |
| תקציר≠ | 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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