Process parameters affecting quality of high-pressure die-cast Al-Si alloy

In the last years, aluminium alloys have become more and more relevant because of their low density, coupled with good mechanical and corrosion properties. Different processes are available for the production of aluminium alloy components, but a very significant role is played by foundry processes. However, defects and imperfections are physiologically generated by foundry techniques, as a result of the process itself, of the alloy properties and of the die design. Particularly, high-pressure die-casting (HPDC) is considered a “defect generating process”, since an average of 5 - 10 % scrap is typically generated by this process. Several process parameters need to be controlled in order to obtain sound and reliable castings. Among the different process variables, the determination and control of the injection parameters remain a key requirement throughout the HPDC process. In this work, a statistically significant sample of castings in AlSi9Cu3(Fe) alloy has been manufactured through different injection parameters in order to identify the most relevant process parameters and estimate their correlations with the quality of the casting. In particular, the plunger I and II phase velocities (v1 and v2), the switch point between two phases (SW) and the intensification pressure (IP) have been varied randomly in accordance to the Design of Experiment methodology. The static mechanical properties of the castings have been measured using the bending test. Furthermore, the castings have been analysed by X-rays and their percentage of porosity has been estimated by means of image analysis software. Some novel aggregate parameters, representing a measure of the mechanical energy related to the plunger motion and the thermal energy exchanged with the die have been extracted from the plunger displacement curves and from thermocouple signals. The application of statistical concepts, methods and models demonstrates that these novel parameters allow explaining and forecasting both the mechanical properties and the porosity, and therefore the overall quality of the castings.