Comparar métodos

	Análisis de Capacidad de Proceso Robusto	Gráfico de Control
Campo	Diseño experimental	Diseño experimental
Familia	Process / pipeline	Process / pipeline
Año de origen	1990s–2000s	1924 (first use); 1931 (seminal book)
Autor original	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)	Walter A. Shewhart (Bell Labs)
Tipo	Quantitative quality engineering method	Statistical monitoring and control technique
Fuente seminal	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.	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand.
Alias	Robust PCA, Robust Capability Indices, Outlier-Resistant Capability Analysis, Robust Cpk Analysis	Shewhart chart, process-behavior chart, SPC chart, quality control chart
Relacionados	6	6
Resumen	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.	A control chart is a time-series graph with statistically derived upper and lower control limits that separates the natural, random variation of a process (common cause) from unusual, assignable variation (special cause). Invented by Walter Shewhart at Bell Labs in 1924, control charts remain the foundational tool of Statistical Process Control and are used across manufacturing, healthcare, software, and service industries to monitor whether a process remains stable and predictable over time.