PhD Studentship in Intelligent Cyber-Physical Connectors for Digital Twins of Steel Pipes and Structural Hollow Sections

Job Overview

Coventry, England
Job Type
Full Time
Date Posted
1 month ago

Additional Details

Job ID
Job Views

Job Description

University of Warwick

Qualification Type:PhD
Funding for:UK Students, EU Students
Funding amount:£18,009
Hours:Full Time
Placed On:23rd November 2020
Expires:23rd February 2021

Supervisor: Dr. Sumit Hazra

Second/Third Supervisor's: Professor Claire Davis

Funding Source/Stipend: EPSRC iCase - £18,009 for 4 years

Sponsor Company: Tata Steel

Start Date: We would ideally like someone to start as soon as possible, but we can offer some flexibility on this - please contact us to discuss

About the project

This fully funded PhD studentship represents an exciting opportunity to undertake research at the interface of Data and Manufacturing science in close partnership with Tata Steel UK ( The successful candidate will work in WMG, a multidisciplinary department within the University of Warwick, particularly across its Materials and Manufacturing and Data Science groups.

The project will study the manufacturing of pipes and rectangular hollow sections made in the Hartlepool Pipe Mill in Tata Steel and develop a virtual process. The mill manufactures tube products for the construction, engineering, and energy and power markets. The approach will be developed into a generalised framework that will be tested in other manufacturing lines within the business.

This research will address the digitisation of the manufacturing process lines to bring about new levels of efficiency, quality and scrap reduction. The research challenge will be to explore the opportunities to harness the data generated from online sensors that currently monitor discrete aspects of the manufacturing lines (such as temperature and forces) to reliably infer overall process performance such as product geometry.

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 digital twins of the process that predict process performance
  3. The development of the framework into a prototype process for proof-of-concept validation

Essential and desirable criteria

Candidates should have a minimum of an upper second (2.1) honours degree (or equivalent) in Materials Sciences (including Metallurgy, Ceramics), Mechanical Engineering, Data Science or related disciplines. A good command of English is essential for the position.

The ideal candidate will have a strong academic background in one or more of the following areas: experimental design, data processing, mathematical modelling and manufacturing engineering.

Funding and Eligibility

Funding of £18,009 per annum is available for UK/EU applicants for 4 years.

To be eligible for this project the successful applicant should have indefinite leave to remain in the UK and have been ordinarily resident here for 3 years prior to the project start-date, apart from occasional or temporary absences. Additional details of these criteria are available on the EPSRC website.

To apply

Please visit the WMG website directly to apply for this studentship:

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