Fast Cooling Simulation for the Generative Design of Injection Mold Cooling Layouts that Reduce Cycle-Time and Improve Part Quality

As new technologies and customer demands accelerate time-to-market schedules and as senior designers retire and become more scarce, simulation-driven design workflows are a key enabler in the development of plastic parts and their associated tooling. But, to truly be a game changer, such workflows need to be fast, convenient, and easy to integrate into existing design practices.

In this talk, we will present the technology behind SimForm -- a cloud-native thermal simulation tool. This innovative tool is used by part designers, tooling engineers and mold makers early in the design process. With SimForm, they gain valuable insight into the temperature distributions, hot spots, and quality issues within plastic injection molds.

Firstly, we will discuss the genesis of the physics-based solver technology at the heart of SimForm -- namely a GPU- (graphical processing unit) accelerated engine that can predict the temperature evolution within the part and mold. Though similar to other simulation products on the market, this engine does not rely on extensive model preparation by users. Rather, it uses a fast and reliable voxel-meshing technology that relieves the burden on designers and engineers and allows them to focus on their primary task of developing the best tools and products possible.

Next, we will examine the physics supported -- namely thermal conduction and fluid convection -- and some of the simulation processes developed specifically for the molding industry. As an extendible platform, we'll discuss how the engine can be used to make warpage prediction, and how it can be extended to other manufacturing industries.

Next, we will focus on the results of an experimental mold trial. We will show that a fast thermal simulation can predict the plastic temperature distribution and the temperature values within 2 degrees C of sensor values. Here, we will present:

• The equipment used, the plastic part produced, the injection mold machine parameters, and the molding process;
• The simulation project definition, input parameters, and material properties, with a focus on the assumptions made by the software, and how it chooses the initial temperatures for the mold;
• A comparison of the measured temperatures at two specific sensor locations with the simulated temperatures at the same two locations;
• A comparison of the overall temperature distribution on the part and mold with an IR camera measurement;
• A review of the cooling time predicted by the simulation and how that could be improved.

Finally, we will look to the future to see how designers can leverage fast cooling simulation for the generative design of mold cooling layouts.