Autonomous Optimization: A New Approach to Increased Efficiencies

A classic conflict exists in the foundry industry as time constraints dictated by customers’ delivery demands are limiting the options for finding the best rigging and process setup for the required casting quality, in combination with producing castings at the lowest cost. This conflict becomes even more challenging considering the lack of available engineering resources foundries are facing. The few engineers available to a foundry operation need to spend their time fulfilling their most important task of finding the optimal process setup at the lowest possible cost. With limited resources, the foundry can no longer afford to have its engineers spending their time on tedious, repetitive tasks, which don’t require their expertise.

The latest development in casting process optimization technology provides foundry engineers with the tools to obtaining an optimized casting design and process layout at the lowest cost, while requiring less of their valuable time spent in front of the computer. Autonomous optimization software performs the tedious and repetitive tasks without any interaction needed by the engineers. The engineers will be responsible only for the initial simulation setup tasks, steps they are familiar with from using traditional casting process simulation tools.

The optimization tools, which are integrated into MagmaSoft^® casting process simulation software, also include new statistical tools that analyze multiple process layouts in one view, leading to a faster understanding of how the available process and tooling design variables lead to the optimal process setup at the lowest cost.

Traditional casting process simulation tools are used to optimize the process layout in a step-by-step sequence. Design and process modifications are entered manually into the

simulation tool, simulations are run, and then each of them are reviewed by the engineers through evaluating multiple result files. This process of running individual simulations is usually very tedious and time consuming. In fact, it is often the main reason why foundries don’t use casting process simulations at all, as their engineers don’t have time to perform them.

Another limitation of traditional single simulation runs is that each one considers only one set of process parameters, and do not provide any information on the effect of process variations on the finished casting quality in one comprehensive view. Each one must be evaluated against the others manually by selecting a small number of result files and comparing them on the computer screen.

Process variations, however, have a significant influence on casting quality and costs. It is essential to find the optimal rigging and process layout to understand each process parameter’s impact on casting quality and cost.

Identifying the Optimal Layout

With traditional simulation tools (i.e., a design of experiments [DOE] can be performed manually to understand the process window’s effect on casting quality. However, this requires an enormous amount of an engineer’s time to create the geometries, set up the simulations, and finally, evaluate all the results. Many times these essential DOEs are then not conducted due to the lack of time engineers have.