State-specific key variables for monitoring multi-state processes

Abstract

The large-scale and complexity of modern chemical plants makes it difficult for the operator to constantly monitor all process variables. Numerous methods exist for monitoring processes however most of them suffer from computational complexity and scale-up problems when applied to large-scale processes. Further, their accuracy also degrades when inessential variables are included in the analysis. In this paper, we describe a systematic method for identifying key variables for process monitoring. The proposed method is especially suited for multi-state processes that operate in different regimes at different times; in such cases different sets of key variables would be needed in different states. A classification of key variables into state-indication, state-differentiation, state-progression, active, external-effect and important-balance variables is proposed. This provides a systematic basis for defining state-specific key variables that reflect the unique and essential features of a state. Methods for identifying the different key variables using process flowsheet, operating procedure, and historical operations data have also been developed. The proposed methodology is illustrated on the startup transition of a simulated fluidized catalytic cracking unit. The benefits of key variable based process monitoring are reduction in monitoring load and improvement in sensitivity. © 2007 Institution of Chemical Engineers.