Dimensional precision and robustness of Fused Deposition Modelling (FDM) additive manufacturing processes

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Additive Manufacturing (AM) presents designers with a unique set of new possibilities, to design new components with new shapes. Fused Deposition Modelling has become one of the most ubiquitous of AM processes, due to the comparatively low cost of these machines. However, the utility of FDM to designers is limited by the performance capabilities of these machines, especially with complex or small structures. As a result, much of the use is by 'hobbyists' and many parts require several iterations of production due to inaccuracies in manufacture. Whilst most machine brochures cite 'resolution' and axis speed as an indicator of performance, dimensional precision is extremely often not indicated.This project aims to explore the dimensional capability of 3D printing technologies, more specifically that of FDM machines. The first output will be a greater understanding of the current capability of different machines, which is essential data if these technologies are to be used be designers. This data will be used to deliver the second output, the re-design of an FDM machine using the principles of robust machine tool design. Experiments will be conducted on as wide a set of FDM machines as is possible. This will include a baseline study of machine repeatability as well as the characterisation of dimensional accuracy over the full build volume. These experiments will also establish the interdependencies and impact of different process settings on print quality.It is expected that analysis of the outputs from the experimental phase in relation to the underlying machine design principles adopted, will determine how the machine design might influence the variations seen. Outputs from this phase will be used to design a new FDM machine, with the objective of producing parts with a high level of dimensional accuracy and repeatability.The project covers the EPSRC research areas of Engineering Design and Manufacturing Technologies.