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Homogenizing material properties of AM parts with the help of simulation

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Additive Manufacturing has become an integral production process in the high-end industry for highly complex structures that are either too expensive or even impossible to produce via traditional production techniques. For metallic AM parts, homogeneous material properties are critical to ensure the continuous performance of the part during its life cycle. The production of highly complex designs with strict material properties pushes the boundaries of AM. To produce such parts, the machine parameters require fine turning which is a tedious and time-consuming process.

The figure above indicates failure prediction by AdditiveLab simulation software in a design, simulated in under a minute on a laptop. The manufactured part (image courtesy of Spencer Wright, is shown with failure at the same zone.

In cases where machine parameters are not properly adjusted for the production of complex designs, production failures are inevitable. Visible failures result in material and machine time wastage or even machine damages. Furthermore, without control of material properties, the parts, which might visually look acceptable, can be shipped to the user only to end up failing during additional tests or in service.

AM process simulation is a vital tool in the prevention of production failures. Simulation offers a higher-level analysis within a matter of few minutes to indicate the part’s most vulnerable zones to failure.

The picture above shows an example of a cyclic-symmetric valve geometry with varying cross-sections along with the height of the valve (right) and the simulated average temperatures throughout the manufacturing process indicating thermal-flow bottlenecks that limit the heat dissipation. Simulated via AdditiveLab Simulation software.

A fast analysis can be very powerful for simpler designs that work with standard machine parameters. However, for offering homogenous material properties, the production parameters need to be adjusted. This adjustment can be a tedious and repetitive combination of production and experimental tests, or simulation can be used instead to optimize the machine parameters. Simulation can help solve the thermal challenges by optimizing intra-layer pauses (dwell-times) to ensure homogeneous cool-down rates and the manufacturing of high-quality designs.

During AM, each production layer is exposed to heat from the laser. Post laser exposure, the layer gets to cool down for a bit, until new powder is being deposited for the next layer. When the next layer is being exposed to heat, then the previous layer is subsequently exposed to elevated temperatures from the next layer. This heating and cooling cycle is repeated in a layer-by-layer fashion. For metallic materials, different crystalline structures form depending on the cooling rate.

The figure above shows that the simulated average temperatures throughout the manufacturing process indicating thermal-flow bottlenecks that limit the heat dissipation with the original process (left) and an improved situation with a more homogeneous distribution of average temperatures in the optimized process (right). Simulated via AdditiveLab Simulation software.

Different crystalline structures result in overall different material properties and for example define if a material is more ductile or more brittle, and allows for little or more elongation. In high-end engineering industries-controlled solidification (cool down) is used to create materials that are specifically tailored to certain applications. For example, for certain metallic materials, rapid cooling rates allow an increase of hardness. In addition to that, the better control the manufacturer has over the thermal process and the cooldown rates, the better they can manipulate crystalline structures to their liking and ensure homogeneous and failure-free material properties in the manufactured design.

This particularly becomes important for dynamically loaded geometries such as engine valves which need to be manufactured flawlessly in order to ensure lifetime durability. Consider the following valve geometry:

Simulation can be utilized to optimize the thermal properties of the parts during production. The Python script from AdditiveLab software for instance automatically adjusts the intra-layer pauses to ensure homogeneous cooldown rates and to avoid temperature accumulations. The main sections such script include the preparation and execution of subsequent thermal simulations and the definition of an error function that determines the difference in cooldown rates throughout the entire valve design.

The figure above shows the dwell-times for the original manufacturing strategy (left) and the dwell-time optimized strategy (left) with longer dwell-times indicated in red. Simulated via AdditiveLab Simulation software.

Post optimization, the comparison of the average temperatures calculated over the entire building process reveals a more homogeneous distribution of average temperatures in the optimized process (right) compared to the default process with constant dwell-times between each layer (left).

With such simulation-based optimization strategies, manufacturers can improve the outcome of their manufacturing process. Thus, ensuring the generation of suitable high-end application parts that require a high level of material quality.

Those interested in having designs evaluated by the experts at AdditiveLab, or receiving training to increase knowledge in a simulation-based optimization of build configurations, should get in touch with the AdditiveLab team.

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