The aim of TAPI (Towards Autonomy in Process Industries) is to move Norwegian land-based process industries towards more autonomous operations by exploring the intersection between machine learning (ML) and more traditional model-based control methods. Industry 4.0 marks a new era in industrial markets and digitalization is an international research topic aiming to increase productivity and competitiveness. This can be achieved through increased energy and resource efficiency and improved process autonomy, stability and control system flexibility. The industry partners (Hydro, Elkem, Borregaard and Yara) face similar challenges related to complex, nonlinear processes in harsh environments with largely varying time constants, where only sparse, often manual measurements are available. These issues cannot be fully solved through traditional control methods, and new competence is needed to address them. The intersection between control theory and ML is an emerging research field with large potential. TAPI will explore, extend and develop new ML methods for control systems that are able to handle the particular challenges of the process industries. To safely apply these control methods in industrial use-cases, this project seeks to significantly advance the understanding and formal analysis of what can be guaranteed with respect to stability, robustness and convergence when using ML methods in control systems, and what is required related to system observability and training data. The project results are expected to increase the competence level, productivity and competitiveness for Norwegian process industry as well as improve safety for process operators and reduce emissions, use of chemicals and waste production. TAPI will be a step towards increased autonomy and digitalization, and towards green competitiveness and zero emissions for land-based process industries.
Project leader: Anne Marthine Rustad
Category: Teknisk-industrielle institutter
Institution: SINTEF DIGITAL