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Autonomous optimization reduces particle segregation in MIM

Autonomous optimization reduces particle segregation in MIM

News 26.08.2016

At the World PM2016 Congress & Exhibition, taking place in Hamburg, Germany, from October 9th to 13th, SIGMA Engineering GmbH will introduce a new approach to minimize particle segregation in Metal Injection Molding (MIM).


Three different particle concentrations on the part surface at different filling times and gating positions.

Simulation is a well-established tool in MIM, as it accurately predicts flow- and thermal-related effects in the green part molding. In recent years, SIGMASOFT® Virtual Molding has developed a number of new features to predict particle segregation, one of the most common problems associated to MIM. Particle segregation causes surface defects, and once the green part is sintered, the differences in density lead to inhomogeneous shrinkage and therefore to warpage. Particle segregation is mainly a process-driven effect, caused by shear. Therefore, process parameters and part gating are critical.

At this years’ WorldPM, Timo Gebauer, SIGMA’s Chief Technical Officer, will show how autonomous optimization can be used to reduce the appearance of particle segregation.

The figure shows particle concentration for a very simple part. Three scenarios are considered: on the left, the part is filled with a short filling time. The part in the center was simulated with a long filling time, and the right part shows the particle concentration for the short time but with a different gate position. For each variation the segregation pattern is quite different.
“To understand the problem it makes sense to run various simulations in a Design of Experiments (DOE). This can help figuring out the correlations of the different boundary conditions and the influence on the observed result”, explains Gebauer. In the optimization, an even particle distribution is the main goal, and both filling time and gate geometry are varied in a first study. The difference in particle concentration diminishes with increasing filling time, and there is a miminum achieved with a given offset to the middle plane of the part for the gate position.

To make the simulation feasible for an industrial part and mold, an approach called “autonomous optimization” is used. Using a similar strategy to the one previously described, the problem is solved in parts through several optimization generations. This reduces the amount of calculations necessary to find an optimum solution. The presentation will explain how the approach can be used to minimize particle segregation in real products.

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