Manufacturing processes potentially generate a lot of data during the manufacture of a product. In most plants, data is either not collected or if collected, there is lack of knowledge on how to derive insights from the data collected.
This PhD will investigate how Machine learning algorithms can be interfaced with manufacturing systems and then applied to derive insights from various manufacturing data. Existing machine learning libraries could be used or novel smart algorithms developed. The aim of applying machine learning will be to improve manufacturing efficiency, reduce defects, reduce downtime of machines, increase productivity among other criteria.
This work will be carried out in collaboration with the renowned University of Sheffield Advanced Manufacturing Research Centre (AMRC) including the AMRC’s £43 million state-of-the-art ‘Factory 2050’ - the UK’s first fully reconfigurable assembly and component manufacturing research facility.
This is a self-funded research project. We require applicants to have either an undergraduate honours degree (2:1) or MSc (Merit or Distinction) in a relevant science or engineering subject from a reputable institution. Prospective candidates for this project should have a background in robotics, programming and embedded systems. Full details of how to apply can be found at the following link: https://www.sheffield.ac.uk/acse/research-degrees/applyphd
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