Keynote Talk: Machine Learning and AI Applications in the Chemical Industry

Industrial chemical processes usually come with abundant data and thus provide huge opportunity to leverage machine learning and AI techniques for process improvement. Over the past decade as computational resources have become readily available at much lower costs, together with rapidly growing availability of cloud services, sensor and analytical technology, the number of AI applications adopted for process monitoring, control and optimization have also increased exponentially. Aside from traditional multivariate analysis that is often used for monitoring and fault diagnosis, other analytics fields such as (but not limited to) image analysis, deep learning, sensor fusion, text mining, reinforcement learning, hybrid and physics informed surrogate modeling are also being actively applied to increase reliability, reduce safety events, predict the onset of potential equipment failures and enable real time optimal decision making. This talk will provide examples of AI applications using industrial case studies and also address current challenges as well as outlook.