Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Control Estadístico de Procesos× | Six Sigma DMAIC× | |
|---|---|---|
| Campo≠ | Diseño experimental | Gestión de la calidad |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1924–1931 | 2014 |
| Autor original≠ | Walter A. Shewhart | Motorola; Pyzdek & Keller |
| Tipo≠ | Process monitoring and quality control method | Structured process improvement methodology |
| Fuente seminal≠ | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 | Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9 |
| Alias | SPC, statistical quality control, process control charting, Shewhart control | DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC |
| Relacionados≠ | 6 | 3 |
| Resumen≠ | 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. | 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. |
| ScholarGateConjunto de datos ↗ |
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