Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Статистическое управление процессами× | Шесть сигм DMAIC× | |
|---|---|---|
| Область≠ | Планирование эксперимента | Управление качеством |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1924–1931 | 2014 |
| Автор метода≠ | Walter A. Shewhart | Motorola; Pyzdek & Keller |
| Тип≠ | Process monitoring and quality control method | Structured process improvement methodology |
| Основополагающий источник≠ | 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 |
| Другие названия | SPC, statistical quality control, process control charting, Shewhart control | DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC |
| Связанные≠ | 6 | 3 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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