Data-efficient prediction of wax pattern cooling time using a simplified thermal approach for rapid tooling applications

Numerical simulations enhance injection molding by predicting cooling time, reducing costs, and improving quality. However, mesh resolution and modeling assumptions affect accuracy. This study implements a thickness-based correction mechanism to speed up the simulation of cooling time in low-pressure wax injection molding. The method aims to create a prediction model that balances fast computation with accurate results. A corrected simulation-based model for accurate and sustainable prediction of wax pattern cooling time in low-pressure injection molding using rapid tooling is presented. The corrected cooling time can be calculated from the heat content using the proposed equation with a coefficient of determination of about 0.99601. The proposed method achieved prediction accuracies of 91.19% and 93.16% for the cooling time of wax patterns. It also improved the efficiency of obtaining cooling times for golf club heads and piston components to 94.34% and 94.49%, respectively. Compared to the traditional method, the proposed prediction method in this study can reduce the power consumption and carbon emissions of the golf club head and piston components by approximately 94% and 94.5%, respectively. This demonstrates the sustainable potential of high-efficiency simulation and green manufacturing. These results confirm that the proposed method provides a good balance between accuracy and efficiency. In addition, it helps reduce carbon emissions and improve energy use. This demonstrates its strong potential for practical and sustainable applications.