Thompson, Adam
(2019)
Surface texture measurement of metal additively manufactured parts by X-ray computed tomography.
PhD thesis, University of Nottingham.
Abstract
Additive manufacturing (AM) is beginning to come of age. With the freedom of design that is offered by AM, new functionality is now available that has not previously been possible because of tool access limits in machining processes. However, as with any emerging technology, a long list of unsolved problems exist. Particularly, in order for AM to become an established method of high value part manufacture, rigorous verification protocols must be followed, and the processes that produce these parts must be well understood in order for them to be well controlled. In verification, surface characterisation is a well-accepted tool in ensuring that a surface has a set of desired functional properties. Surface characterisation is also commonly used in process development, where it is used to improve process understanding. However, verification of AM parts represents a great challenge, as the tools and processes that exist in current standards fall down when the demands of ultra-complex AM components are considered, and the processes themselves are also not yet well understood. In this Thesis, I present the use of X-ray computed tomography (XCT) for surface measurement, for the purpose of verification and process improvement in an AM context. In particular, I focus on the surfaces of metal powder bed fusion parts. In the first portion of this Thesis, I examine metal AM surfaces in detail, using established methods of surface measurement and visualisation to build up a deep understanding of the features present on these surfaces. Particularly, I find that when compared, discrepancies between measurements of surface features made on data acquired using different measurement instruments can be of similar magnitudes to the sizes of the features in question. Following this work, I detail new methods for the measurement of surfaces using XCT, describing a pipeline for extracting and characterising surface information from raw XCT data. Later, I examine some of the factors that affect XCT surface measurements, particularly investigating how varying scan magnification and volumetric reconstruction grid resolution affects measurements. In this work, I find that increasing magnification improves precision, while accuracy and bias do not always improve. Altering resolution, I find that decreasing sampling resolution worsens metrological performance, while increasing it may lead to slight improvements. Finally, I bring together the various aspect of the Thesis by applying the techniques developed throughout to an industrial case involving the measurement of internal channel surfaces. In this study, I discuss the outcomes of the Thesis as a whole, showing that XCT is capable of surface measurement in cases where the surfaces of interest are relatively rough (i.e. with an arithmetic mean height of the scale limited surface, Sa > 1 μm) and are located on or inside parts that are generally penetrable by X-rays produced using state-of-the-art systems (e.g. a cube of Ti6Al4V < 20 mm × 20 mm × 20 mm in size). In the future work, further characterisation of the factors influencing the measurement, overcoming issues relating to ‘black-box’ commercial systems and the development of existing methods of data comparison are identified as core research avenues, and a need for developing metrological traceability in XCT measurement is noted.
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