Postgraduate research opportunities In-process Material Evaluation of Welding & Additive Manufacturing
ApplyKey facts
- Opens: Tuesday 21 June 2022
- Number of places: 1
- Duration: 3 years
- Funding: Home fee, Equipment costs, Travel costs, Stipend
Overview
This project aligns directly with one key deliverable in the 5-year plan “Towards Industry 4.0: In-process Repair of Welding and Wire Additive Manufacturing” associated with the Strathclyde Chancellor’s Fellowship for the primary supervisor (Dr Javadi). The core of this ambitious plan is fully automated Non-Destructive Evaluation in robotic welding and Wire Arc Additive Manufacturing.Eligibility
This is a Strathclyde’s Student Excellence Award and then funding is provided for students with a good Honours degree at a first or upper second-class level, awarded within a relevant cognate discipline. Faculties may stipulate a first-class Honours degree.
Project Details
This project aligns directly with one key deliverable in the 5-year plan entitled “Towards Industry 4.0: In-process Repair of Welding and Wire Additive Manufacturing (IRWWAM)” associated with the Strathclyde Chancellor’s Fellowship for the primary supervisor (Dr Javadi). The core of this ambitious plan is fully automated Non-Destructive Evaluation (NDE) in robotic welding and Wire Arc Additive Manufacturing (WAAM), where the three main research themes are: (I) in-process defect detection, (II) in-process residual stress measurement and (III) in-process material evaluation. When these three core research themes are coupled with process modelling and simulation, the project will deliver an Industry 4.0 adopted system in which the sample can be fully inspected and importantly, repaired during the manufacturing process, if deemed necessary by the system. The in-situ measurement systems will be also linked to the manufacturing system for improving the quality control and creation of a closed-loop feedback system. Manufacturing within the IRWWAM framework will save time and energy (which is usually wasted in backward transmissions between the manufacturing and inspection stations) and hence will be better for the environment. The main plan is then in line with the national UK government's post-COVID recovery plan.
This PhD will focus on the in-process monitoring of the material evolution during welding and additive manufacturing. The necessity of “in-process” evaluation has been justified by the Center for Ultrasonic Engineering (CUE) when the in-process inspection was established for the multi-pass welding [Javadi et al, Materials & Design, Volume 191, 2020]. However, this was not extended to the material evaluation (with the focus on the residual stress) and there is currently no NDT method to monitor the residual stress during the welding and additive manufacturing. The in-process material evaluation will be considered in this project and it is then desired that the candidate is familiar with (or enthusiastic to learn) the following research and technical activities: NDE material evaluation, residual stress, process modelling and verification, in-process inspection, and Industry 4.0.
The project will be based in the new Faculty of Engineering facility “Sensor Enabled Automation Robotics & Control Hub (SEARCH)” laboratory and will link directly with the NDE research team operating within the CUE. There is an excellent opportunity to enhance the capabilities of the world’s first automated robotic AM facility with integrated NDE (RoboWAAM cell currently being installed at the Advanced Forming Research Centre) through the output of this project. Hence, there is an obvious route into the Advanced Forming Research Centre, Lightweight Manufacturing Centre and National Manufacturing Institute Scotland (NMIS) activities and industrial network.
Through CUE, the project will complement Strathclyde’s current The UK Research Centre in NDE (RCNDE) research, which will offer opportunities to collaborate within the RCNDE academic and industrial membership. There will also be both training and collaboration opportunities within the CDTs hosted with FUSE, FIND and Advanced Photonics.
Funding details
The programme is a three-year PhD supported by the Engineering and Physical Sciences Research Council (EPSRC) and all students who are awarded EPSRC DTP-funded studentships have access to a Research Training Support Grant (RTSG) of £1,500 per annum plus a generous stipend and paid tuition fees. However, the students recruited for EPSRC DTP awards must meet the UKRI eligibility criteria regarding residency and academic qualification.
Supervisors
The supervisory team are uniquely placed to provide this PhD student with direct access to a broad range of technical expertise and highly specialised facilities discussed above.
Professor Jorn Mehnen, who is leading Advanced Digital Manufacturing at Strathclyde, will supervise the whole research activities to be aligned with the idea of digital manufacturing and Industry 4.0.
Dr Javadi holds a joint appointment between the Department of Electronic and Electrical Engineering and the Department of Design Manufacturing & Engineering Management which are directly contributing to this PhD proposal.
Exceptional support and access to the strategic facilities in both departments will be available for the successful candidate.
Apply
Please email Dr Yashar Javadi (yashar.javadi@strath.ac.uk) in the first instance, before applying.
The project is due to start as soon as possible and no later than 1 Oct 2022, preferably. We then accept the applications now and if we find a suitable candidate (following the interview), the vacancy will be closed for further applications.
Candidates are encouraged to apply as soon as possible.
Number of places: 1
There are currently a few more PhD places available under the supervision of Dr Javadi and other colleagues in the Electronic & Electrical Engineering and Design, Manufacturing & Engineering Management departments in areas similar to this project. Therefore, if more than one candidate is selected in the interview, a follow-on arrangement will be discussed with the successful candidates.
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