METHOD AND APPARATUS FOR FORMING INTERNAL STRUCTURES OF THREE-DIMENSIONAL (3D) OBJECTS

    公开(公告)号:US20250033112A1

    公开(公告)日:2025-01-30

    申请号:US18358369

    申请日:2023-07-25

    Abstract: A method of operating a printer to fill an internal volume of a three-dimensional object is includes determining a total number of layers required to fill an internal volume of a three-dimensional object, forming at least one floor layer within the internal volume, using a maximum individual stepout distance to generate machine-ready instructions that operate the printer to form one or more pre-determined sloped edges of a plurality of sections of a sparse infill structure in the layer of the internal volume to be filled, thereby forming at least one sparse infill layer. A drop ejecting apparatus includes a controller operatively connected to a reservoir, an ejector, and at least one actuator, the controller being configured to perform the method as described herein.

    MACHINE LEARNING FEATURE FEED RATES FOR 3D PRINTING

    公开(公告)号:US20240272612A1

    公开(公告)日:2024-08-15

    申请号:US18168126

    申请日:2023-02-13

    CPC classification number: G05B19/4099 G06N20/00 G05B2219/49023

    Abstract: Systems for and methods of providing a feed rate for three-dimensional printing a part are presented. The disclosed techniques include: obtaining computer readable toolpath instructions for the part, where the toolpath instructions specify a nominal feed rate for a toolpath segment and spatial toolpath data of the toolpath segment; providing an input including the spatial toolpath data to a trained machine learning system, where the trained machine learning system has been trained using training data including: training spatial toolpath data, training closed loop gain data, and training feed rate data; obtaining a revised feed rate for the toolpath segment different from the nominal feed rate for the toolpath segment, where the revised feed rate is output from the trained machine learning system; and providing revised computer readable toolpath instructions, where the revised machine learning toolpath instructions include the revised feed rate.

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