Analysis of the applicability and state monitoring of material extrusion–printed acrylonitrile butadiene styrene injection mould inserts with different infill levels

Abstract

The widespread appearance of additive manufacturing (AM) proved to be a game changer for many traditional plastic processing technologies in the last few years. The application of AM for injection mould making has become a new and promising direction of rapid tooling (RT), especially with the emerging demand for more customizable products. A possible solution to satisfy the desire for mass customization is the application of additively manufactured low-volume moulds and inserts. These prototype moulds also give an excellent opportunity to check and validate designs in a real-life operational environment, before the expensive large-volume steel mould is made. Material extrusion printing was used to produce injection mould inserts from acrylonitrile butadiene styrene (ABS). These inserts proved to be suitable for low-volume injection moulding. The inserts were printed with different infill levels: 80 %, 50 % and 25 %. In previous articles, an earlier unknown complex state monitoring method was created to analyse and quantify in-mould operational behaviour of additively manufactured injection mould inserts. In the present article, this measurement system was applied to material extrusion–printed prototype moulds. This system measures strains (at two locations) and the temperature distribution of the inserts (both volumetric temperature and cavity surface temperature). 3D scanning and conventional thickness and mass measurements were also applied to characterize the dimensional accuracy of the injection moulded products and the inserts as well. The correlation between the definite integral of measured operational strains (occurring during the injection moulding cycles, from the start of holding to the end of the holding phase) and the resulting product properties (mass and thicknesses) was also analysed. An excellent linear correlation was found between them (mostly R2 > 0.9). This finding can pave the way for a more automated quality control system because of its practical applicability and relative ease of use.