In-process detection · the status quo
A camera or sensor can flag a problem while the print is running. You find out sooner, but some material and machine time may already be committed.
Pre-print failure-risk prediction for FDM
AutoSTL analyzes your STL to predict failures and returns a risk map by zone and failure mode before you commit material, machine time, or operator time. Then, it optimizes your part to achieve the perfect print.
Values are illustrative, not measured results.
Cameras and sensors can flag a problem while it happens. By then, the job is running and may already have consumed operator time, machine capacity, and material. Across repeated production runs, that erodes margin and puts delivery dates at risk.
A camera or sensor can flag a problem while the print is running. You find out sooner, but some material and machine time may already be committed.
AutoSTL maps estimated risk across the geometry before slicing. You can use that evidence to review the part, orientation, and supports—and reduce the chance of an avoidable failure.
Choose the part you are about to send to production and specify your conditions
AutoSTL AI estimates failure probability by region and mode: warping, bed adhesion, overhang collapse, bridging and thin walls.
Reorient, add supports or revise the design to get the best printing parameters and export the GCODE
We're starting with a selected group of FDM print farms. Write to us and let's talk about your operation.
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