Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
This is a survey paper, providing an overview for researchers and practitioners in the process industry, but it is incremental as it summarizes existing work without new contributions.
The paper surveys recent applications of modern machine learning tools for monitoring and control in industrial processes, leveraging increased data, computational power, and theoretical advances to address large-scale nonlinear problems.
Over the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning tools on large-scale nonlinear monitoring and control problems. This article provides a survey of recent results with applications in the process industry.