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Statistické řízení procesů×Six Sigma DMAIC×
OborPlánování experimentůManagement kvality
RodinaProcess / pipelineProcess / pipeline
Rok vzniku1924–19312014
TvůrceWalter A. ShewhartMotorola; Pyzdek & Keller
TypProcess monitoring and quality control methodStructured process improvement methodology
Původní zdrojShewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Další názvySPC, statistical quality control, process control charting, Shewhart controlDMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Příbuzné63
ShrnutíStatistical 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.
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ScholarGatePorovnat metody: Statistical Process Control · Six Sigma DMAIC. Získáno 2026-06-17 z https://scholargate.app/cs/compare