Sustainable digital frameworks to support deployment of autonomous analytics in knowledge intensive manufacturing environments" and its in partnership

The key competitive driver for the PhD is to study Industry 4.0 total connectivity concepts within a specific, knowledge intense industrial background. Industry 4.0 is the fourth industrial revolution that strives for smart manufacturing and autonomy. As with all new innovations, there are a lot of underlying unanswered questions to this shift in paradigm which this research aims to examine and address. On the technological side this will include Cyber Physical Systems, Industrial Internet of Things, Big Data & Monitoring, Machine Learning and others. This research will provide scientific underpinnings for Industry 4.0 approaches to knowledge intense industrial applications.

This PhD is in partnership with Tata Steel. The underlying research will focus on developing a system model for the Cold Rolling Mills in their Port Talbot plant to support the Industry 4.0 standard. The Cold Rolling Mills is the process of condensing steel into thin, ductile coils. Currently, there is heavy automation, but decisions are made from human interaction instead of any form of autonomy. The key objective will be researching into the creation of a digital framework to model the total connectivity concepts that Industry 4.0 requires to enable such autonomy. To achieve our goals, we will use a model-driven approach to create such a digital framework. Model-driven approaches are known to be essential in achieving a level of abstraction that allows to deal with the complexity of the tasks ahead in an efficient way.

Our work will include exploring the use of digital twins and digital threads to create realistic simulations that will use real time data to accurately replicate the Cold Rolling Mill system digitally. This will allow us to commit changes to the digital form without any impact on the physical form. For example, we may simulate the increase pressure levels on the rolls to see the impact it has without any risks of the actual physical assets being damaged. Additionally, the rolls in the Cold Rolling Mills suffer massively from wear and must be refurbished often. Using the data collected from Tata Steel and our modelling techniques, this research also aims to optimize and increase efficiency of Tata's roll stock.