This project is aiming to strengthen Chinese-Norwegian research and industrial collaborations towards digitalizing the offshore oil and gas production especially in subsea. The scientific objective is to develop cognitive subsea process systems that operate autonomously over several years. A special focus is placed on harnessing the power of machine learning and digitalization to improve the effectiveness and efficiency of system prognosis and diagnosis methods, and to use the developed digital twins in combination with the methods for fully autonomous process operations. In addition, we will study the cultural and societal impacts of digitalization on stake holders. In the Norwegian part of this project, we will focus on building and maintaing digital twin models for degrading systems, such that they give an adequate representation of the physical production system. We will further use these digital twin models for developing novel condition-based maintenance approaches that schedule maintenance when the system has reached a sufficiently degraded state. Finally, we will develop algorithms for integrating production decisions with maintennce decisions, such that the overall system is operated optimally. The methods will be tested in collaboration with the industry and with our Partners in China, who will contribute to this project with expertise in degradation modelling and Big Data algorithms. This project will also enhance the exchange of personell. 3 PhD students from NTNU will spend 4 months each in China, and 3 PhD students from China will spend 6 months each at NTNU. In addition, we will organize annual workshops in China and Norway to discuss and share research ideas. The research will be performed in close collaboration with the industrial partners in Norway and China, and we plan industrial placements in which the students can test their results in an industry setting.
Project leader: Johannes Jäschke
Institution: Institutt for kjemisk prosessteknologi