This invention aims to make 3D printed objects more accurate. It works by printing test objects in different spots within a 3D printer, then measuring their actual dimensions. This data is used to train a computer model, which learns how to adjust the original digital design of an object (for example, by scaling or offsetting it) before it's printed, ensuring the final physical object matches the intended size.
Why it matters: Filed before the widespread availability of highly optimized ML frameworks. Training and deploying inference models for specific data patterns has become significantly more efficient since 2021.
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