A study of an industrial counter pressure casting process for automotive parts

Abstract

Counter pressure casting (CPC) is emerging in the automotive manufacturing industry as an alternative to low-pressure die casting (LPDC) due to its reported superior capabilities in aluminum parts production. This study presents the first comprehensive investigation of how CPC's characteristic feature (applied chamber pressure) influences the fluid flow and heat transport occurring in the process and its effect on casting quality. A large amount of high-quality data was acquired from a commercial CPC process for the production of automotive suspension control arms with two process conditions (standard production and low back-pressure condition). Analysis of the data shows that there are no significant differences between the two process pressure conditions with respect to heat transfer during solidification, as-cast microstructure nor mechanical properties. Generally, in-die measured temperatures exhibited a difference within 10 °C for the two process conditions examined and the ultimate tensile strengths (UTSs) of the samples obtained from castings were within 7% for the two process conditions. Furthermore, there was no measurable difference observed in the Secondary Dendrite Arm Spacings (SDASs) obtained under the two process conditions. However, the implementation of chamber back pressure noticeably reduces the venting rate during the filling stage, leading to 12 s delay in the filling time relative to the low back-pressure condition. A computational modelling methodology, originally developed for LPDC, was applied to simulate the CPC process. The model required only an adjustment to pressure curve to account for the delay of filling owing to the reduced venting rate observed for the higher back-pressure condition. The predicted results were found to correlate well with the measured data, demonstrating that the modelling methodology is broadly applicable to permanent die casting processes.

Keywords

• CPC process
• Plant trial
• Data acquisition
• Model development
• ProCAST