Enhancing Control Room Operator Decision Making: An Application of Dynamic Influence Diagrams in Formaldehyde Manufacturing

In today’s rapidly evolving industrial landscape, control room operators must grapple with an ever-growing array of tasks and responsibilities. One major challenge facing these operators is the potential for task overload, which can lead to decision fatigue and increased reliance on cognitive biases. To address this issue, we propose the use of dynamic influence diagrams (DID) as the core of our decision support system. By monitoring the process over time and identifying anomalies, DIDs can recommend the most effective course of action based on a probabilistic assessment of future outcomes. Instead of letting the operator choose or search for the right procedure, we display automatically the optimal procedure according to the model. The procedure is streamlined compared to the traditional approach, focusing on essential steps and adapting to the system’s current state. Our research tests the effectiveness of this approach using a simulated formaldehyde production environment. Preliminary results demonstrate the ability of DIDs to effectively support control room operators in making informed decisions during times of high stress or uncertainty. This work represents an important step forward in the development of intelligent decision support systems for the process industries.