방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 다중 응답 고장 모드 및 영향 분석 (MR-FMEA)× | 통계적 공정 관리× | |
|---|---|---|
| 분야 | 실험설계 | 실험설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1990s–2000s | 1924–1931 |
| 창시자≠ | Extended from classical FMEA (MIL-P-1629, 1949; Ford Motor Company, 1970s); multi-response integration developed in quality engineering literature from the 1990s onward | Walter A. Shewhart |
| 유형≠ | Risk analysis and quality engineering method | Process monitoring and quality control method |
| 원전≠ | Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989 | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 |
| 별칭 | MR-FMEA, multi-response FMEA, multi-criteria FMEA, multi-objective FMEA | SPC, statistical quality control, process control charting, Shewhart control |
| 관련 | 6 | 6 |
| 요약≠ | Multi-response FMEA extends classical Failure Mode and Effects Analysis to systems or processes where each failure mode produces effects across multiple quality characteristics or response variables simultaneously. Rather than assigning a single Risk Priority Number (RPN), it evaluates severity, occurrence, and detectability for each response dimension, then integrates these ratings — often via multi-criteria scoring or weighted aggregation — to obtain a holistic risk ranking that captures the full consequence profile of each failure mode. | 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. |
| ScholarGate데이터셋 ↗ |
|
|