Methoden vergelijken

	Optimalisatie-ondersteunde Six Sigma DMAIC	Six Sigma DMAIC
Vakgebied	Experimenteel ontwerp	Kwaliteitsmanagement
Familie	Process / pipeline	Process / pipeline
Jaar van ontstaan	1990s–2000s (integration period)	2014
Grondlegger	Six Sigma: Motorola (Bill Smith, Mikel Harry, 1986); optimization integration formalized in engineering literature through the 1990s–2000s	Motorola; Pyzdek & Keller
Type	Process improvement framework with embedded optimization	Structured process improvement methodology
Oorspronkelijke bron	Antony, J., & Banuelas, R. (2002). Key ingredients for the effective implementation of Six Sigma program. Measuring Business Excellence, 6(4), 20-27.	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Aliassen	Optimization-integrated DMAIC, DMAIC with optimization, Six Sigma optimization framework, Opt-DMAIC	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Verwant	5	3
Samenvatting	Optimization-assisted Six Sigma DMAIC embeds formal mathematical optimization — response surface methods, metaheuristics, or multi-objective solvers — into the Improve phase of the DMAIC cycle. Rather than relying solely on engineering judgment or one-factor-at-a-time trials, the approach uses designed experiments to build a predictive model of the process and then applies an optimization algorithm to locate factor settings that best satisfy quality, cost, or multiple competing performance targets simultaneously.	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.