Joel Hogg

Using Causal Inference for Sustainable Digital Twin-based Testing of Smart Manufacturing Processes

Supervised by: Dr José Miguel Rojas, Dr Neil Walkinshaw, Dr Pete Crawforth 

I discovered my passion for research during my undergrad at Sheffield, working on Causal Inference for my dissertation. However, there were no relevant PhDs in the area at the time, so when I saw this posting advertised last year, and at Sheffield too, I felt it was meant to be. I'm hoping this PhD will help me to develop a number of soft skills alongside researching, including communication, and project management / organization.

I'll be looking at the cross-section between Digital Twins and Causal Inference, and as the project develops, I'll hone in on area when I can bring the biggest benefit. Given the broad nature of a PhD, there are many avenues the project could take at this early stage.

In the past few years, Causal Inference has slowly started gaining public traction, and businesses are increasingly using it to gain a better understanding of their data. However, the field has seen little adoption thus far within manufacturing. We feel there is an opportunity to bring some big performance gains to help companies machine more efficiently; both cost and materials-wise.

Smarter manufacturing processes will better utilize existing data to understand the root-cause of any issues, and plan machining with more certainty, helping industry manufacture with less waste, decreasing the environmental impact of manufacturing, and the cost per component. Increasing manufacturing efficiency is key to the Government's Modern Industrial Strategy, and I'm very happy to play a part.