Additive manufacturing (AM) techniques provide engineering design flexibility not available when manufacturing is constrained by the tool-path restrictions of conventional subtractive techniques such as turning, milling and grinding. AM techniques allow the manufacture of complex form, light weight components with optimised geometries and topographies, including internal and re-entrant features. These features may greatly enhance the components functional capability. The design flexibility may allow a reduction in assembly part count, with a corresponding reduction in assembly time. Additionally, the ability to use high performance engineering metals in the AM process, such as 316 stainless steel, titanium Ti6Al4V and cobalt chrome provide the aerospace, medical and automotive industries with a new manufacturing toolbox using familiar raw materials. These quality-driven industries are fully aware of the potential of AM and are actively engaged and invested with the AM industry and research community. The complex features and design freedom providing great potential for these industries also presents challenges for surface measurement and characterisation. Surface measurement is vital to assure compliance with designed sealing, bearing, flow and adhesion properties of the component. Parts manufactured using AM are not exempt from the stringent quality requirements applicable to other manufacturing processes and so surface texture requirements will be incorporated into drawings and design specifications, imposed by customers onto suppliers. There will need to be a common language and approved standards. Compliance verification will be mandatory. If a feature is specified on a drawing then these industries will require verification that the component complies with design requirements. Traditionally, line-of-sight measuring devices were able to follow the tool pathways to access and measure these surfaces. With the advent of additive processes, new techniques will need to be developed. X-ray computed tomography (CT) has been used successfully for dimensional and defect detection as it allows the measurement of internal and re-entrant features. Thus far, there has been little research on the application of CT for the measurement of surface texture. This thesis reports on the development of a novel technique, detailing the first extraction of areal surface texture parameters per a recognised standard (ISO 25178-2) from CT scans of AM components. Industry will require reproducibility of measurements and so an interlaboratory comparison was performed to compare CT measurement results using this technique from four laboratories. The repeatability and accuracy of surface measurements is also vital for industrial applications and so the influence on extracted surface texture parameter values of selected CT measurement and reconstruction factors has been investigated. Extraction of true 3D data from CT requires the generation of new surface characterisation parameters to take full advantage of the technique and a new parameter has been developed to enable the true surface of re-entrant surfaces to be characterised. The additive process itself is complex and verification of consistent additive machine performance is vital for production. A series of small, inexpensive, surfacespecific measurement artefacts has been developed and built to characterise the build chamber and provide production process verification. This series of inter-related experimental investigations were chosen to be industrially relevant, to be linked closely to component function and be used as practical measurement and surface characterisation techniques. This work is intended, as far as possible, to not be machine-specific, but to be applicable to all CT machines and all metal powder bed fusion (PBF) AM machines. As AM and CT machine capability improves, as it inevitably will, the techniques and applications presented here are designed to evolve with these changes.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:745173 |
| Date | January 2018 |
| Creators | Townsend, Andrew |
| Contributors | Blunt, Liam |
| Publisher | University of Huddersfield |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.hud.ac.uk/id/eprint/34575/ |
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