X-ray computed tomography for predictive quality assessment, 3D visualisation of micro-injection mouldings and soft-tool deformation

Autor: Mert Gülçür, Paul Wilson, Michael Donnelly, Kevin Couling, Vannessa Goodship, Jérôme Charmet, Mark A. Williams, Gregory Gibbons
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Materials & Design, Vol 227, Iss , Pp 111741- (2023)
Druh dokumentu: article
ISSN: 0264-1275
DOI: 10.1016/j.matdes.2023.111741
Popis: This work presents X-ray computed tomography (XCT) as a dimensional quality assurance technique for micro-injection moulded polymeric test objects for the establishment of predictive quality models and quantifying soft-tool deformation. The results are compared against an industry standard laser-scanning-confocal microscope (LSCM) for the evaluation of XCT’s capability. The work demonstrates; (i) the exploitation of a XCT equipment for dimensional characterisation of micro-injection moulded products made out of polymers with adequate acquisition times, (ii) that acquired XCT data from the 3D visualisation of the micromouldings perform on par with a laser-scanning-confocal microscope in a quality prediction model, (iii) that the deformation occurring in an additively manufactured soft-tool can be quantified using XCT. The technique was particularly superior in volumetric data acquisition compared to LSCM in the filling prediction of the micromouldings. Better accuracy and repeatability in predicting the quality of the mouldings up to 92% achieved with XCT, in conjunction with an in-line collected soft-tool surface temperature data as an indirect quality assurance method. Given the capability of the XCT for the 3D data acquisition of polymeric miniature components, the approach described here has great potential in high-value micro-manufacturing process quality modelling for in-line quality assessment of miniature and added value products in data-rich contexts.Rendered 3D animation of the X-ray CT data: https://youtu.be/KwZty_yoDfs.
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