Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Six Sigma DMAIC× | Gráfico de Control de Variables de Shewhart (X-barra / R)× | |
|---|---|---|
| Campo≠ | Gestión de la calidad | Estadística |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 2014 | 1931 |
| Autor original≠ | Motorola; Pyzdek & Keller | Walter A. Shewhart |
| Tipo≠ | Structured process improvement methodology | Statistical process control chart for variables |
| Fuente seminal≠ | Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9 | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company. ISBN: 978-0-87389-076-2 |
| Alias≠ | DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC | X-bar and R chart, Shewhart chart, variables control chart, process control chart |
| Relacionados≠ | 3 | 4 |
| Resumen≠ | 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. | The Shewhart control chart, invented by Walter Shewhart at Bell Labs in the 1920s and set out in his 1931 book, is the foundational tool of statistical process control. It plots a process statistic — typically the subgroup mean (X-bar) and range (R) — over time against a center line and three-sigma control limits, distinguishing the natural common-cause variation inherent in a stable process from special-cause variation that signals something has changed and warrants investigation. |
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