EnCube
Assembly Line
Collaboration and the speed of compute
When we first started building Encube, we realized that the only way to achieve the scale and speed of compute necessary to make real manufacturing simulation a core part of the product design cycle, would be to make all compute fully distributed. Not just multi-threaded, but truly distributed, with exponentially shorter compute times achieved through horizontal cloud scaling. And at the same time also leverage GPU compute, which is far more suited to linear algebra and 3D graphics related workloads, compared to the CPU.
If we consider the case of CNC machining, the market vertical we’re diving deep into at Encube, the only meaningful way to understand manufacturability of a component is to understand what it will cost to produce. And the only way to do this reliably, is to simulate the machining process itself. Crude measures like calculating the amount of material to be removed and dividing by a constant material removal rate (which is the current standard practice) are insufficient to generate an accurate best practice cost estimate.