Additive manufacturing (3D printing) is one of the most affordable and wide spread manufacturing techniques for the production of customised consumer parts supported by modern industry 4.0. Product quality and dimensional stability is important when it comes to intricate medical devices. The processing of polymers in additive manufacturing is complex which involves rapid heating and cooling of polymer material.
Current research shows improvement of bioactivity with additives and bioactive fillers in additive manufactured polymer samples for medical devices . Shrinkage and warpage are common problems in polymer parts, especially in the case of additives , . The complex processing involved in additive manufacturing makes it challenging to attain high quality products .
Cost and quality are important factors in a production process. The required processing time and the production method decide the cost of a product. Specific moulds are required in the case of conventional processing methods such as injection moulding, which increase the cost of customised products. The demand for customised intricate consumer parts in medical sector makes the requirement of mould in conventional methods even more challenging. Additive manufacturing is a solution to this problem.
This research project will look into optimisation of the key attributes of 3D printed samples such as thermal conditions, nozzle diameter, print orientation, and percentage of the additives both experimentally and computationally. The project will further work on improving product quality with various additives for bone implants. Another aspect of the project would be correlation of shrinkage and warpage in 3D printed polymers parts with the process parameters.
The researcher will have an opportunity to work on state of the art 3D printers and other high end thermal, morphological, and mechanical equipment based at our new Belfast campus and NIACE.
The characterisation of 3D printed parts will be carried out using thermal, morphological, biological, and mechanical methods. Furthermore, optimised simulation model will be developed using simple FEA techniques. Candidates with a background of Biomedical, Materials, Mechanical, and Mechatronics are welcome to apply.