About the Project
This project offers an opportunity to develop an automated geometric characterisation framework for wire-based directed energy deposition additive manufacturing (w-DEDAM). You, as a MSc by Research student, will work at the intersection of 3D scanning, point cloud processing, and industrial metrology to quantify as-built geometry, a task traditionally reliant on manual measurement and expert interpretation. By integrating multi-view acquisition, automated registration, and data-driven surface…
analysis, the research aims to separate localised deposition error from thermal distortion and enable in-process geometric monitoring. This is ideal for candidates interested in digital manufacturing, computer vision, and solving complex, real-world engineering challenges.
Wire-arc Directed Energy Deposition (wire-arc DED-AM, also termed WAAM) is a near-net-shape metal additive manufacturing process capable of producing large-scale components at high deposition rates, with growing adoption across the aerospace, energy, and defence sectors. A persistent barrier to its industrial qualification is dimensional and geometric assurance: the as-built geometry deviates from the nominal design as a result of both localised deposition variability and cumulative, residual-stress-induced distortion. Reliable characterisation of build geometry is therefore central to process qualification, and increasingly to the development of closed-loop process control.
The project aims to develop and validate a methodology for the automated geometric characterisation of WAAM-deposited walls from point cloud data, and to establish data-analysis techniques capable of discriminating process-induced geometric error from residual-stress-induced distortion.
The student will be based at the Welding and Additive Manufacturing Centre (WAMC), a renowned hub for impactful research into advanced fusion-based processing and manufacturing methods. The Centre's contributions to industry are demonstrated through its extensive MSc and PhD research initiatives and its ongoing technology development programs in large-scale additive manufacturing. The student will become part of a diverse and dynamic research community at WAMC, fostering collaboration and innovation. Additionally, there will be opportunities to work with WAMC’s industrial partners.
The project will deliver a validated methodology and software pipeline for the automated geometric characterisation of w-DEDAM structures, capable of merging multi-view scans into a single dimensionally consistent representation without manual intervention. It will establish quantitative descriptors that distinguish process-induced deposition error from residual-stress-induced distortion, allowing as-built geometry to be interpreted correctly rather than attributed to a single cause. Demonstrating inter-layer measurement under process conditions will provide the geometric feedback needed for future closed-loop control. The outcomes will support industrial qualification of large-scale metal additive manufacturing and are expected to generate peer-reviewed publications and tools transferable to the Centre's industrial partners.
The student is expected to acquire the following (including but not limited to) knowledge and skills from the research in this project:
- 3D metrology and optical scanning: hands-on experience designing acquisition strategies and operating structured-light or laser scanning equipment on real industrial hardware.
- Point cloud and geometric data processing: registration, coordinate transformation, surface reconstruction and feature extraction.
- Software engineering for research: building an automated, reusable pipeline rather than one-off scripts, with version control and documentation that others can pick up.
- Experimental design and data interpretation: planning deposition trials, isolating confounded effects, and defending conclusions drawn from noisy measurement data.
- Applied additive manufacturing knowledge: practical understanding of a production-scale metal AM process and the qualification requirements that govern its industrial adoption.
- Industrial engagement: working alongside a research centre's industry partners, and translating research output into something an engineering team can actually use.
- Technical communication: peer-reviewed publication, conference presentation, and reporting to non-specialist and industrial audiences.
- Independent project management: scoping, prioritising and delivering a multi-stage research programme to deadline.
Entry requirements
Applicants should hold the equivalent of a first or second-class UK honours degree in a related discipline, such as mechanical, manufacturing, or general engineering. International candidates must also meet the English language requirements set by Cranfield University. The successful candidate should demonstrate self-motivation, proactivity, and good communication and teamwork skills.
How to apply
Start date: 27 Sep 2027
For further information please contact:
Name: Dr Jian Qin
Email: J.Qin@cranfield.ac.uk
Phone: +44 (0)1234 758214
If you are eligible to apply for this studentship, please complete the online application form.
This vacancy may be filled before the closing date so early application is strongly encouraged.
Note, your application will not be considered unless all relevant documents have been uploaded. For more information please visit Applying for a research degree.
Funding Notes
Self-funded opportunity.