Orthonormal subspace analysis (OSA) is proposed for handling the decomposition issue and principal component selection in traditional key performance indicator (KPI)-related process monitoring methods such as partial least squares (PLS) canonical correlation (CCA). However, it not appropriate to apply static OSA algorithm a dynamic since pays no attention auto-correlation relationships variable...
