Simufact, part of Hexagon’s Manufacturing Intelligence division, has introduced metal binder jetting (MBJ) simulation that is enabling manufacturers to predict and prevent the distortion that sintering processes will have on parts at the design stage. The simulation tool helps manufacturers achieve the quality they require while exploiting the unique benefits MBJ offers for volume production.
In additive manufacturing, metal binder jetting has several key advantages over powder bed fusion processes; high volumes of parts can be printed with minimal spacing; no support structures are needed, and larger lot sizes are possible. It has the potential to replace low-volume, high-cost metal injection molding for everything from automotive and aircraft parts to medical applications. Because high resolution is possible, it could also reduce the cost and lead times for production of complex and lightweight metallic parts such as gears or turbine wheels.
However, early adopters can expect a steep learning curve to learn how to achieve the quality they need to exploit these benefits. One key challenge has been predicting changes during the sintering process. A part can shrink as much as 35% and the simple shrinkage models used for other processes cannot predict distortion during the post-build sintering process. Until now, costly physical trials were required to perfect the printing of each part, preventing many manufacturers realizing the low cost and flexibility MBJ offers.
Made available to existing Simufact Additive customers in August, the new tool extends its capabilities for MBJ processes. Manufacturers can predict the shrinkage caused by factors such as the thermal strain, friction, and gravity during sintering without specialist simulation knowledge. By compensating for these changes, parts can be 3D printed as they are designed, and production teams can reduce the proportion of parts that must be scrapped or re-processed. Sintering-induced mechanical stress is also predicted before print, indicating where defects might occur. Manufacturers can use this information to make changes earlier in their product development and reduce the need for redesign.
The tool can automate the model setup, preparing the CAD or CAE file for manufacturing simulation and simulations can also be automated through Python scripts. To validate the sintering compensation and increase confidence in quality, the optimized geometry from the MBJ tool can be immediately compared to both the initial design (CAD) geometry and a metrology scan of a manufactured part within user interface.
Hexagon | Simufact