Risk-based warning system design methodology for multimode processes

Abstract

Complex chemical processes usually operate at multiple operating modes, resulting from various factors, such as changes in market demand, set point modifications, and feedstock changes. It is difficult to monitor a multimode process without generating significant number of false alarms. In this paper, a risk-based alarm system design methodology is proposed to monitor multimode processes. The methodology comprises of three main steps: i) analysis of operating data using Gaussian mixture model, ii) identification of independent operating modes (e.g. set points, virtual transient state), and iii) probabilistic model to assess risk and activation of appropriate warning. A continuous stirred tank reactor with model predictive control system is used to demonstrate the effectiveness of the proposed method.