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| Symulacja wspomagająca Six Sigma DMAIC× | Six Sigma DMAIC× | |
|---|---|---|
| Dziedzina≠ | Planowanie eksperymentów | Zarządzanie jakością |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 2000s–present (systematic integration of simulation with DMAIC) | 2014 |
| Twórca≠ | Integration practice emerged from industrial engineering and operations research communities; DMAIC framework originates with Motorola/GE Six Sigma (1980s–1990s) | Motorola; Pyzdek & Keller |
| Typ≠ | Hybrid process-improvement methodology | Structured process improvement methodology |
| Źródło pierwotne≠ | Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). John Wiley & Sons. ISBN: 978-0470169926 | Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9 |
| Inne nazwy | Sim-DMAIC, Simulation-integrated DMAIC, Six Sigma with simulation, DMAIC simulation modeling | DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC |
| Pokrewne≠ | 6 | 3 |
| Podsumowanie≠ | Simulation-assisted Six Sigma DMAIC embeds discrete-event or Monte Carlo simulation models inside the classic DMAIC cycle (Define, Measure, Analyze, Improve, Control) to test process changes virtually before committing to physical implementation. By running thousands of simulated scenarios, teams quantify variation, identify bottlenecks, and verify improvement hypotheses at low cost and with minimal disruption to live operations. | Six Sigma DMAIC is a data-driven, five-phase process improvement methodology — Define, Measure, Analyze, Improve, and Control — used to reduce defects and process variation to fewer than 3.4 defects per million opportunities. Originating at Motorola in the 1980s and systematized by practitioners including Pyzdek and Keller, it is widely adopted in manufacturing, healthcare, finance, and service industries seeking sustained quality gains. |
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