首页|Patent Application Titled 'Implanted 3d Printing Quality Assurance Control' Publ ished Online (USPTO 20240300183)

Patent Application Titled 'Implanted 3d Printing Quality Assurance Control' Publ ished Online (USPTO 20240300183)

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Reporters obtained the following quote from the background information supplied by the inventors: “The present invention relates generally to the field of compu ting, and more particularly to quality control in Three-Dimensional (3D) printin g. “Three-Dimensional (3D) printing, also known as Additive Manufacturing, may enab le the construction of a three-dimensional object from a computer-aided design ( CAD) model and/or a digital 3D model (e.g., print model). 3D printing may refer to a variety of processes in which material may be deposited, joined, or solidif ied under computer control to create a three-dimensional object. 3D printing may be limited to materials such as, but not limited to, metals or plastics, which may allow for sufficient temperature control to allow for 3D printing. Although three-dimensional (3D) printing has become increasingly popular, many 3D printer s may still suffer from failures. The failure rate of 3D prints may be caused by numerous factors, such as, but not limited to, running out of filament, nozzle locations relative to a print-bed, restricted print chambers, and/or faulty prin t models. There are many factors which may determine a model’s printability, inc luding, model wall thickness, orientation, strength, model density, amongst othe r factors. Additionally, 3D printing parts may be produced layer-by-layer, and a lthough these layers may adhere together it may also allow for the layers to del aminate under certain stresses, orientations, and/or conditions. The current sta te of the art fails to disclose an ability to perform a quality control validati on at each level of a print nor does it disclose a method for deriving uniquenes s of an item and/or print job.

CyborgsEmerging TechnologiesMachine LearningPatent Application

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.1)