Autonomous Optimization of Die Casting Processes
For the past two decades die casters have integrated casting process simulation into the development process for new casting programs. The limiting factor was casting process simulation only used fixed process parameters to provide results for each calculated simulation. By using simulation iterations and avoiding real life trials die casters were able to get a step closer to achieving a good tooling and process design in combination with the lowest cost involved. A classic conflict exists in the die casting industry as delivery times demanded by the customer are limiting the options of finding the best tooling and process setup for the required casting quality along with the lowest cost. The latest development in casting process optimization technology now takes the industry a step closer to obtaining an optimized tooling design and process.
This paper provides examples of developing the optimal die design and process quality along with the least amount of time and cost using the optimization tools which are integrated into the casting process simulation software MAGMASOFT® (hereafter referenced as Software A). New statistical tools are used to analyze much more tooling design and process variations leading to an understanding of how they lead to the optimal tooling and process setup much faster.