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Metal Casting Technologies : March 2006
Figure 2 Thus, the qualified user needs a tool that helps him to implement his knowledge in the areas of error diagnostics and optimization. This 'second generation' of simulation tools (G. Hartmann, R. Seefeldt, 2004) aims to use the knowledge of the user to formulate the purpose of optimization and assessment criteria for the simulation process. The above mentioned steps of a single simula- tion project (change of CAD-geometries, process parameters, start of a simulation, and evaluation of the results) can indeed be carried out by a computer according to appropriate pre-settings. The rapid development of computer proces- sors and memory generates increasingly powerful hardware. Today, it should be possible to simulate hundreds of variations of a casting process overnight. However, the definition of these varia- tions would take some time and the amount of generated information could hardly be evaluated within days. The advantage of the very short computing times can only be used if the evalu- ation and the new definition of the calculated variations would be carried out automatically by the computer. Basically, there are two different approaches. On the one hand, there are knowledge-based systems that perform modifications or optimiza- tions of the casting process based on stored regulations. However, a very high number of clear and unambiguous correlations between cause and effect need to be known for that purpose, which is not the case in high pressure die casting. On the other hand, there is the possibility to use the survival of strong individual's genetic components as it is practiced in nature. Ge- netic algorithms accept variations more or less at random where reasonable variations survive from generation to generation. (Fig. 1) The integration of such optimization algo- rithm into casting simulation software results in a system that is able to perform computerized and fully automated optimizations of the casting process. Basically, this system is suitable for the solution of the following problems in high pres- sure die casting: Gas pores in the casting Due to turbulences and dead areas, gas is en- trapped in the melt before the actual die filling. Purpose of optimization is the minimization of peak gas pressure during filling. The variables are the parameters of the CAD-design of the runner. Die lifetime High temperature gradients that develop during the casting cycle in the die reduce the lifetime of the die. Purpose of optimization is the minimiza- tion of temperature gradients at certain locations of the die and at certain times of the casting cycle. The variables are the parameters of the CAD-de- sign of the cooling/heating lines. Use of dry die agents Dry die agents in a closed die need to evaporate in the shot chamber and to re-condense at the wall of the cavity. Purpose of optimization is to keep the temperature of the die surface on the Figure 3 Figure 4 ADVERTORIAL METAL Casting Technologies March 2006