Generative design of conformal cooling channels for hybrid-manufactured injection moulding tools

Abstract

Abstract Effective cooling systems for injection moulding (IM) tools are critical to reducing manufacturing costs & cycle time for the polymer parts that they produce. This work presents a novel automated methodology for designing conformal cooling channels (CCCs) for injection moulding (IM) tools. This is done through existing commercial moulding simulation tools interlinked with custom scripts that adjust CCC design in response to the spatial variability in global andlocal temperature at the mould tool-part interface (MTPI). Four mould tool designs for a hollow cylinder were developed and analysed via both numerical simulation and experiments. These include (i) conventional IM tool with straight-drilled cooling channels made of tool steel, (ii) a manually designed CCC system with stainless steel, (iii) copper-aluminium bronze ‘core’ andstainless steel ‘shell’ with CCCs identical to (ii), and (iv) stainless steel with a CCC system automatically designed using generative design (GD) driven by a genetic algorithm. Tool (ii) cooled the part faster than conventional tool with a manually designed CCC system (i) (3-5% predicted vs. 40% measured), as did tool (iii) with the bronze core (9-12% predicted vs. 40% measured). The GD-optimised CCC tool (iv) cooled fastest in both the predicted results (15-30%, 11-25% & 1.5-25% faster than (i), (ii) & (iii)) andmeasured results (70%, 50% & 50% for (i), (ii) & (iii)). The predicted MTPI temperatures were also lower for the GD-optimised tool (65%, 75% & 34% below (i), (ii) & (iii)). Therefore, the novel methodology proposed here for automatically designing IM tool CCCs achieves reduced (a) maximum andspatial variability in MTPI temperatures, (b) cooling time, and (c) warpage.