Salīdzināt metodes

	Robusta procesu spēju analīze	Six Sigma DMAIC
Nozare	Eksperimentu plānošana	Kvalitātes vadība
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1990s–2000s	2014
Autors	Extended from classical PCA (Kane, 1986; Juran, 1974) via robust statistics (Huber, 1981); formalized for capability indices by Tong & Chen (1998) and Pearn & Kotz (1994)	Motorola; Pyzdek & Keller
Tips	Quantitative quality engineering method	Structured process improvement methodology
Pirmavots	Maravelakis, P. E., Bersimis, S., Panaretos, J., & Psarakis, S. (2004). Identifying the out of control variable in a multivariate control chart. Communications in Statistics - Theory and Methods, 33(10), 2499–2510.	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Citi nosaukumi	Robust PCA, Robust Capability Indices, Outlier-Resistant Capability Analysis, Robust Cpk Analysis	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Saistītās	6	3
Kopsavilkums	Robust process capability analysis extends classical capability indices (Cp, Cpk, Ppk) by replacing the sample mean and standard deviation with robust location and scale estimators — such as the median, trimmed mean, MAD, or IQR-based spread — so that outliers and non-normal process distributions do not inflate or distort the capability estimate. The result is a more reliable assessment of whether a manufacturing or service process can consistently meet specification limits.	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.