HDR Scholarship - Machine learning supported process control in roll forming

Applications now open. A PhD scholarship is available to initiate and conduct research on the topic 'Machine learning supported process control in roll forming'.

Project Supervisor

Additional Supervision


Geelong Technology Precinct (GTP), Waurn Ponds Campus

Research topic

A new approach and senor technology to facilitate AI supported process monitoring and control over multiple manufacturing process lines. Australia has a need for low cost, modular and flexible building construction and requires new solutions for bushfire proof housing. Deakin`s industry partner, Speedpanel addresses this need by producing roll formed hollow steel sheet profiles that are filled with concrete to provide building wall components. The wall panels can be disassembled, re-configured and reused depending on the customers’ needs while the concrete filler material provides a high fire rating.

The Need:
There is a lack in manufacturing process control which prevents the implementation of solutions for process automation that are required to enable scalable and cost-competitive production and achieve widespread implementation of Speedpanel`s solutions. This is due to a complex roll forming manufacturing process for the outer steel skin that depends on material and process conditions and operator actions. Even though incoming coil material is straightened with a roller leveller the residual stresses in the sheet lead to forming issues in the subsequent roll forming process. At the same time the pour of the concrete is mostly manual and has no means of process control. The Deakin team has developed the “Bench Tester” which enables the monitoring of material parameters on the shop floor while a separate Deakin led project with industry partners FormFlow has developed and commercialised the “SmartScan2D” which is a process specific scanning solution for quality monitoring.

This project is part of a multi-Million dollar Cooperative Research Centres Projects (CRC-P)-research activity between Speedpanel, Formflow and Deakin University including research leaders in the field of advanced (sheet) metal manufacturing, concrete development, and civil engineering. The PhD student will be part of a large team of more than 15 industry, senior/early career research and PhD student participants.

Project aim

This project aims to answer the following fundamental questions:

  • How to implement solutions for continuous material property monitoring and establish a pro-active quality control in the metal shell roll forming process.
  • How to develop process-oriented sensors for concrete pouring that enable the continuous collection of process and quality data and how to combine this into solutions for process automation and quality control.
  • How to establish an AI supported process and quality control system that overarches the full panel manufacturing chain of outer metal shell forming and concrete pouring and enables continuous machine learning.

Important dates

Applications close 5pm, Sunday 1 December 2024


This scholarship is available over 3 years.

  • Stipend of $34,400 per annum tax exempt (2024 rate)
  • Relocation allowance of $500-1500 (for single to family) for students moving from interstate
  • International students only:  Tuition fees offset for the duration of 4 years. Single Overseas Student Health Cover policy for the duration of the student visa.

Eligibility criteria

To be eligible you must:

  • be a domestic or international candidate. Domestic includes candidates with Australian Citizenship, Australian Permanent Residency or New Zealand Citizenship.
  • meet Deakin's PhD entry requirements
  • be enrolling full time and hold an honours degree (first class) or an equivalent standard master's degree with a substantial research component.

Please refer to the research degree entry pathways page for further information.

Additional desirable criteria include:

  • Experienced user of Finite Element Analysis packages (Abaqus, LS Dyna, MSC Marc, etc….) and/or
  • Background in (sheet) metal forming/roll forming and/or
  • Experienced in programming with MATLAB, Python, or equivalent.

How to apply

Please apply using the Find a Research Supervisor tool


Contact us

For more information about this scholarship, please contact:

A/Prof Matthias Weiss 
Email A/Prof Matthias Weiss
+61 3 5227 3368

Prof Bernard Rolfe
Email Prof Bernard Rolfe