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PhD Studentship: Digital twins of the manufacturing of structural hollow sections

University of Warwick

Qualification Type: PhD
Location: Coventry
Funding for: UK Students, EU Students
Funding amount: £18,009 per annum stipend for 4 years
Hours: Full Time
Placed On: 18th October 2021
Closes: 7th February 2022

Funding: EPSRC ICASE and Tata Steel funded for UK/EU students

Supervisors: Dr. Sumit Hazra and Dr. Michael Auinger

Start Date: Sept/Oct 2021

This fully funded PhD studentship is an exciting opportunity to radically change the sustainability and efficiency of manufacturing processes. The successful candidate will work at WMG, University of Warwick to apply Data science principles to manufacturing, in close partnership with Tata Steel UK (https://www.tatasteeleurope.com).

You will develop intelligent systems or digital twins for processes such as high-speed induction seam welding of pipes and rectangular hollow sections at Tata Steel’s Pipe Mill in Hartlepool. The mill has an advanced digital infrastructure to control the manufacturing of these products which are critical to the UK’s construction, energy and power sectors.

 This research will address the digitisation of the manufacturing process to bring about new levels of efficiency and sustainability. The challenge will be to harness the data generated from sensors on the manufacturing lines (such as temperature and geometry) to reliably infer process performance such as weld strength. The research will consider but is not constrained by:

  1. The design of experimental programmes to correlate and model sensor data to system performance
  2. The development of novel ‘intelligent’ architectures that fuse sensor data to enable real-time models / digital twins of the process that predict process performance
  3. The development of the architecture into a prototype process for validation

 Entry Requirements

Candidates should have a minimum of an upper second (2.1) honours degree (or equivalent) in Manufacturing Science, Materials Sciences (including Metallurgy), Mechanical Engineering, Data Science or related disciplines. A good command of English is essential for the position. Apply at: https://warwick.ac.uk/fac/sci/wmg/education/researchdegrees/vacancies/phdinintelligentcyberphysicalconnectorsfordigitaltwins

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