Abstract: A method includes generating correction data for a construction material that is used by an additive-manufacturing machine to manufacture an object. This correction data compensates for an interaction of the construction material with first radiation that has been used to illuminate the construction material.

Abstract: A profilometer provides, to a controller, a feedback signal indicative of topography of an exposed surface of an object that is being manufactured by a 3d printer. The profilometer includes an emitter and a camera. The emitter illuminates a region of surface of the object with a pattern having an edge that defines a boundary of an illuminated portion of the surface. The camera receives an image that transitions between a first state in which the edge is visible in the image at a location that is indicative of the surface's depth and a second state in which the edge is not visible at all. From this second state, the controller obtains information representative of a depth of the surface.

Abstract: An approach to improving optical scanning increases the strength of optical reflection from the build material during fabrication. In some examples, the approach makes use of an additive (or a combination of multiple additives) that increases the received signal strength and/or improves the received signal-to-noise ratio in optical scanning for industrial metrology. Elements not naturally present in the material are introduced in the additives in order to increase fluorescence, scattering or luminescence. Such additives may include one or more of: small molecules, polymers, peptides, proteins, metal or semiconductive nanoparticles, and silicate nanoparticles.

Abstract: A method for additive fabrication includes determining numerical calibration transforms for calibrating an imaging sensor and a printhead assembly to a common coordinate system, where at least some of the numerical calibration transforms include nonlinear transforms.

Abstract: Tracking of measured depth with intervening depositing of one or more layers provides a way of improving the accuracy of surface reconstruction. For example, knowledge of the desired or expected thickness of each layer, in combination with the scan data is combined to yield higher accuracy than is available from scan data of a single scan alone. One application of such an accurate surface reconstruction is in a feedback arrangement in which the desired thickness of one or more subsequent layers to be deposited after scanning is determined from the estimate of the surface depth and a model of the object that is being fabricated, and by increasing accuracy of the surface depth estimate, the precision of the fabrication of the object may be increased.

Abstract: A scanning approach used in the feedback procedure is able to distinguish between different materials, for example, based on spectral properties (e.g., color) of reflectance from a partially fabricated object. Because material layers can be quite thin, and in general the materials are not completely opaque, properties of subsurface layers can greatly affect the reflectance of a thin layer of one material over a thicker section of another material. Detection of locations of thin layers after a material change takes into account the reflectance characteristics of the object before the thin layer was deposited.

Abstract: The present disclosure relates to reinforcing photopolymer resins and uses thereof, e.g., in inkjet 3D printing.

Abstract: A method and an apparatus are directed to characterizing a continuously moving 3D object via interferometry-based scanning. The method includes repeatedly forming several depth characterizations of the 3D object along respective scan lines of a plurality of scan lines on the surface of the 3D object. During this scanning, the 3D object is undergoing its continuous motion. The method further includes combining the determined depth characterization along the scan lines of the plurality of scan lines to form a depth map representing at least a depth of a portion associated with a location on the surface of the 3D object in the third direction on a grid of locations arranged in the first and second directions. Forming the depth characterizations includes scanning a frequency-dispersed pulsed optical signal in a first direction across the continuously moving 3D object, said 3D object moving in a second direction substantially orthogonal to the first direction.

Abstract: An approach to intelligent additive manufacturing makes use of one or more of machine learning, feedback using machine vision, and determination of machine state. In some examples, a machine learning transformation receives data representing a partially fabricated object and a model of an additional part (e.g., layer) of the part, and produces a modified model that is provided to a printer. The machine learning predistorter can compensate for imperfections in the partially fabricated object as well as non-ideal characteristics of the printer, thereby achieving high accuracy.