Author ORCID Identifier

Document Type

Conference Paper


1.1 MATHEMATICS, Applied mathematics, Probability, 2. ENGINEERING AND TECHNOLOGY, 2.3 MECHANICAL ENGINEERING, Chemical engineering (plants, products), Chemical process engineering

Publication Details

33rd European Safety and Reliability Conference (ESREL 2023)


In today’s complex industrial environment, operators are often faced with challenging situations that require quick and accurate decision-making. The human-machine interface (HMI) can display too much information, leading to information overload and potentially compromising the operator’s ability to respond effectively. To address this challenge, decision support models are needed to assist operators in identifying and responding to potential safety incidents. In this paper, we present an experiment to evaluate the effectiveness of a recommendation system in addressing the challenge of information overload. The case study focuses on a formaldehyde production simulator and examines the performance of an improved Human-Machine Interface (HMI) with the use of an AI-based recommendation system utilizing a dynamic influence diagram in conjunction with reinforcement learning. The preliminary results indicate the potential of these methods to aid operators in decision-making during challenging situations and enhance process safety in the industry



European Union

Creative Commons License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.