PhD opportunity to support the development of a multi-sensor measurement system for in-process defect detection of metal additive manufacturing.
Additive manufacturing (AM), also known as ‘3D printing’, is revolutionising the way we manufacture parts; permitting almost limitless design freedom and allowing more organic, more lightweight and more bespoke solutions. However production of metal parts by AM is a highly energetic and challenging process and the current state of the technology cannot produce parts with the consistency or geometric tolerances that are required for many applications. Through process monitoring we can improve part quality. Key parameters such as melt pool temperature, powder bed temperature and part form and part texture can be difficult to observe; requiring novel solutions.
This PhD studentship offers the opportunity to work alongside leading researchers who are developing novel multi-sensor methods of measurement for AM surfaces. The multi-sensor measurement approach aims to fuse data collected by multiple measurement systems, allowing sources of noise to be rejected, and clearer insights to be made.
The successful applicant will work alongside experienced researchers in developing a prototype multi-sensor measurement system, with responsibility for the development of the data capture and data fusion methods.
Excellent degree in engineering, computer science, science, or equivalent, qualifying the candidate for obtaining a doctoral degree
- Strong skill in computational methods or programming
- Good communication skills
- Ability to present scientific work in oral and written format
- General engineering experience
- Experience with data fusion methods highly desirable
- Experience with fringe projection, photogrammetry or thermography highly desirable.
Ability to work independently and also efficiently in a team
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Last updated July 31, 2017