Comparer des méthodes

	Analyse de Capabilité Assistée par Optimisation	Maîtrise Statistique des Procédés
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1986–2000s	1924–1931
Auteur d'origine	V. E. Kane (capability indices, 1986); integrated with optimization frameworks by quality engineering researchers in the 1990s–2000s	Walter A. Shewhart
Type	Quantitative engineering method	Process monitoring and quality control method
Source fondatrice	Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52.	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
Alias	OA-PCA, optimization-integrated capability analysis, capability-constrained process optimization, process capability with optimization	SPC, statistical quality control, process control charting, Shewhart control
Apparentées	5	6
Résumé	Optimization-assisted process capability analysis combines classical capability indices (Cp, Cpk, Cpm) with mathematical optimization to identify process parameter settings that simultaneously satisfy engineering specifications and maximize process capability. Rather than simply measuring whether a process is capable, it prescribes the control factor levels — mean, variance, tolerances — that push capability above a target threshold. It is widely applied in manufacturing, chemical processing, and quality engineering contexts where multiple process variables must be tuned jointly.	Statistical 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.