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| Multi-Response Failure Mode and Effects Analysis (MR-FMEA)× | 統計的プロセス管理× | |
|---|---|---|
| 分野 | 実験計画法 | 実験計画法 |
| 系統 | Process / pipeline | Process / pipeline |
| 提唱年≠ | 1990s–2000s | 1924–1931 |
| 提唱者≠ | 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 |
| 種類≠ | Risk analysis and quality engineering method | Process monitoring and quality control method |
| 原典≠ | 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 |
| 別名 | MR-FMEA, multi-response FMEA, multi-criteria FMEA, multi-objective FMEA | SPC, statistical quality control, process control charting, Shewhart control |
| 関連 | 6 | 6 |
| 概要≠ | 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. |
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