HSE management in the Artificial Intelligence era

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Chemelot has set itself the target of becoming the safest, most competitive and most sustainable site in Western Europe by 2025. Brightsite is helping Chemelot achieve this by means of various projects. One of the things we are focusing on as part of program line 4 ‘Securing integral process safety and societal acceptance’ is the development of a predictive model for process safety. An initial version has already shown that modeling that is assisted by Artificial Intelligence and Machine Learning provides opportunities that will enable significant safety improvements in the chemical industry.

Major challenges for HSE management

The chemical industry is investing heavily in robust HSE (Health, Safety and Environment) management systems, as well as in initiatives that will bring about a continuous increase in process safety. In the years to come, HSE management will be faced with major challenges due to the increasing complexity resulting from digitalization and the emergence of new technologies. This changing situation means that conventional HSE management systems may no longer be suitable as a means of identifying and assessing risks. Esta de Goede, Program Manager of Brightsite’s program line 4: “At the same time, production facilities are generating large amounts of data, but at the moment, we are utilizing only a fraction of that data and that’s a shame. We are looking to see whether we can make use of that data in order to optimize process safety and if so, how we can achieve that.” A promising, predictive model for process safety is under development.

“We are convinced that predictive modeling, using Artificial Intelligence (AI) and Machine Learning (ML), will provide additional opportunities to further enhance safety in the chemical industry.”

Join us!

The first steps toward the development of our predictive model have already been made and the time has now come to train and further develop the model, in collaboration with partners from the chemical industry.

Would you like to know more about predictive modeling and/or work with us to develop and apply the model on a practical level? If so, please get in touch with us.