Better results in less time - Improving quality through optimization

Success in the foundry market today not only depends on a good gating and risering design and a resulting good quality part. Moreover, the project design has to guarantee robust quality despite the process variations typical on the shop floor. To keep the business profitable, the solution also has to be a suitable compromise between quality and cost.

In order to achieve these goals, Schulz in Brazil started using the MAGMASOFT® capabilities for Autonomous Engineering and compared it with its traditional way of using the simulation tool. The outcome was more than convincing: it is possible to get better results in less time.

Most ductile iron parts have tight quality requirements. Achieving the specifications for internal soundness is crucial to avoid the component failing in the field. A suspension part with critical safety requirements was used to virtually evaluate the robustness of the process design and compare the outcome with the sequential step-by-step simulation approach used until then.

With an initial feeding system design selected manually, the cast part showed a significant level of porosity defects. A redesign of the feeding system was necessary to solve the porosity problems and improve the quality. Different layouts and feeder sizes were tested in the traditional approach: changes were decided upon by the experts up front. Each version was prepared, simulated and analyzed. Based on the results, the experts decided on the next changes, and this process was repeated.

After running 25 different versions manually and investing two weeks of work, the simulation results showed a decrease of the porosity level. Still, the remaining porosity indication in MAGMASOFT® was critical enough to reject the cast part in some cases of application (Fig. 1).

Fig. 1: Project optimized using simulation in the traditional way - some porosity still remained

Fig. 1: Project optimized using simulation in the traditional way - some porosity still remained

Schulz decided to invest in an additional study using the MAGMASOFT® autonomous engineering tools to eliminate the porosity. Defining the objectives to search for a minimized porosity and a maximized yield, the feeder and gate geometries were designed with MAGMASOFT® parametrically in order to evaluate changes systematically. In addition, the alloy chemistry was varied within the borders of the alloy specification for carbon and silicon, and changes in the pouring temperature were explored, to determine if the feeding system was robust enough to absorb the variations common in foundry processes.

120 designs were simulated and assessed automatically, with the focus on quality and cost requirements. The optimal conditions were achieved for a feeder diameter of 85 mm using a composition of 3.3% C and 2.3% Si. The pouring temperature had less impact on the porosity results, and the chosen best practice was around 1380°C (Fig. 2).

Fig. 2: Parallel coordinate charts to identify the best feeder and gating design and process conditions

Fig. 2: Parallel coordinate charts to identify the best feeder and gating design and process conditions

The best design was sent to the tool shop in order to change the model and perform real casting trials on the shop floor.Fig. 3 illustrates the soundness of the sectioned part. No porosity was found!

Fig. 3: Sectioned part after optimization. No porosity was found.

Fig. 3: Sectioned part after optimization. No porosity was found.

A comparison between the traditional way of simulating and the use of optimization with MAGMASOFT® showed clear advantages. The systematic application of Design of Experiments resulted in better quality in less time. The traditional way took Schulz about two weeks, whereas with the use of MAGMASOFT® autonomous engineering an optimized design was found in only 4 days (Fig. 4).

Fig. 4: Time comparison between feeder and gate optimization using the traditional simulation approach and optimization using a virtual design of experiments

Fig. 4: Time comparison between feeder and gate optimization using the traditional simulation approach and optimization using a virtual design of experiments

Running MAGMASOFT® sequentially consumed 33.5 man-hours of direct human effort, while applying the methodology of Autonomous Engineering only required 5.75 man hours. This sums up to a reduction of 83% of valuable time – now available to be used more profitably in other projects to increase general productivity.

With business in more than 70 countries, Schulz is a dynamic company acting in two segments: automotive parts and air compressors. Schulz is one of the biggest iron foundries in Brazil, with a production capacity of 150 000 t/year. Using MAGMASOFT® since 2006, Schulz applies foundry process simulation in early stages of product development, which leads to robust and reliable results in foundry projects. Due to outstanding quality, Schulz has won many supply chain awards over the years.