ANALYSIS OF PLANT-WIDE DISTURBANCES THROUGH DATA-DRIVEN TECHNIQUES AND PROCESS UNDERSTANDING

Abstract

Plant-wide disturbances can have an impact on product quality and running costs. Thus there is a motivation for automated detection of a plant-wide disturbance and for diagnosis of the root cause. In this article, data-driven techniques are used to analyze plant-wide disturbances caused, for instance, by limit cycle oscillation in a control loop. The control loops participating in the disturbance are detected and displayed on a process schematic. Other numerical signatures derived from the data trends are utilized for the diagnosis of the root cause. The outcome is a visual display that integrates process understanding and data-driven analysis.