Machine Learning for Additive Manufacturing

This invention describes a method for 3D printing where a digital design of an object is first processed by a "predistorter." This predistorter modifies the design based on known imperfections of the printer or materials, ensuring the final printed object is more accurate than if printed directly.

Why it matters: Filed before the latest advancements in machine learning. The configuration data for the predistorter, which compensates for printer characteristics, can now be more effectively generated and refined using improved ML techniques, making the system more robust.

Status: ExpiredProtection ended and was never renewed
How hard to build: SpecializedSoftware logic, machine learning model

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