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

Abstract

Effective cooling systems for injection moulding (IM) tools are critical to reducing manufacturing costs and cycle time for the polymer parts produced. This work presents a novel automated methodology for designing conformal cooling channels (CCCs) for IM tools via interlinking commercial moulding simulation tools with custom scripts. These scripts adjust CCC design in response to the spatial variability in global and local temperatures at the mould tool-part interface (MTPI) via generative design (GD). Four tool designs for manufacturing a simplified part were analysed numerically simulation and experimentally, including tools with either straight-drilled (non-conformal) cooling channels (tool steel), a manually designed CCC system (stainless steel or bronze alloy), or an automatically designed CCC system (stainless steel). While both manually designed CCC tools cool the part faster than the non-conformal tool (3–5% predicted vs. 40% measured for stainless steel and 9–12% predicted vs. 40% measured for bronze alloy), the GD-optimised CCC tool outperformed both (15–30% predicted faster cooling vs. 70% measured). The predicted MTPI temperature feature achieves reductions to both maximum and spatial variability in MTPI temperatures, which lead directly to significant reductions in manufacturing cycle time and polymer part warpage. These findings could have a major impact on the IM industry by reducing tool design costs and raw material waste via improving moulded part quality.