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| Πολυκριτηριακή Μεθοδολογία Six Sigma DMAIC× | Σχεδιασμός Πειραμάτων× | |
|---|---|---|
| Πεδίο | Πειραματικός Σχεδιασμός | Πειραματικός Σχεδιασμός |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 2000s–2010s (applied integration era) | 1935 |
| Δημιουργός≠ | Extension of Six Sigma DMAIC (Motorola/Mikel Harry); multi-response adaptation developed by quality engineering community | Ronald A. Fisher |
| Τύπος≠ | Process improvement methodology with multi-objective optimization | Experimental planning framework |
| Θεμελιώδης πηγή≠ | Harry, M., & Schroeder, R. (2000). Six Sigma: The Breakthrough Management Strategy Revolutionizing the World's Top Corporations. Doubleday. ISBN: 978-0385494090 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Εναλλακτικές ονομασίες | MR-DMAIC, multi-response DMAIC, multi-criteria Six Sigma, multi-objective DMAIC | DOE, experimental design, factorial experimentation, planned experimentation |
| Συναφείς≠ | 5 | 3 |
| Σύνοψη≠ | Multi-response Six Sigma DMAIC extends the classic Define-Measure-Analyze-Improve-Control framework to situations where a process must satisfy several quality characteristics simultaneously. Rather than optimizing a single output, the methodology integrates multi-response optimization techniques — such as desirability functions, TOPSIS, or weighted signal-to-noise ratios — within the Analyze and Improve phases to identify factor settings that jointly meet all quality targets. | Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences. |
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