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Controle Estatístico de Processo×Six Sigma DMAIC×
ÁreaDelineamento experimentalGestão da qualidade
FamíliaProcess / pipelineProcess / pipeline
Ano de origem1924–19312014
Autor originalWalter A. ShewhartMotorola; Pyzdek & Keller
TipoProcess monitoring and quality control methodStructured process improvement methodology
Fonte seminalShewhart, 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
Outros nomesSPC, statistical quality control, process control charting, Shewhart controlDMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Relacionados63
ResumoStatistical 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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ScholarGateComparar métodos: Statistical Process Control · Six Sigma DMAIC. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare