방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 고장 모드 및 영향 분석 (FMEA)× | 통계적 공정 관리× | |
|---|---|---|
| 분야 | 실험설계 | 실험설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1949 (military); widespread industrial adoption 1970s–1980s | 1924–1931 |
| 창시자≠ | U.S. Military / NASA (formalized by MIL-P-1629, 1949) | Walter A. Shewhart |
| 유형≠ | Proactive risk analysis technique | 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 | FMEA, Failure Modes and Effects Analysis, FMECA, Failure Mode Effects and Criticality Analysis | SPC, statistical quality control, process control charting, Shewhart control |
| 관련 | 6 | 6 |
| 요약≠ | Failure Mode and Effects Analysis (FMEA) is a structured, proactive risk management technique used to identify potential failure modes in a system, process, or product design, evaluate their consequences, and prioritize corrective actions before failures occur. Originally developed for the U.S. military in 1949 and later adopted by NASA, automotive, and manufacturing industries, FMEA is now a cornerstone quality-engineering tool embedded in standards such as AIAG-VDA and ISO 9001-aligned processes. | 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 ↗ |
|
|