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Dear Editor, This letter presents a novel process monitoring model based on ensemble structure analysis (ESA). The ESA model takes advantage of principal component analysis (PCA), locality preserving projections (LPP), and multi-manifold projections (MMP) models, and then combines the multiple solutions within an ensemble result through Bayesian inference. In the developed ESA model, different structure features of the given dataset are taken into account simultaneously, the suitability and reliability of the ESA-based monitoring model are then illustrated through comparison.

Statistical Process Monitoring Based on Ensemble Structure Analysis