Abstract: Embodiments of the systems can be configured to receive electromagnetic emissions of a substrate (e.g., a build material of a part being made via additive manufacturing) by a detector (e.g., a multi-spectral sensor) and generate a ratio of the electromagnetic emissions to perform spectral analysis with a reduced dependence on location and orientation of a surface of the substrate relative to the multi-spectral sensor. The additive manufacturing process can involve use of a laser to generate a laser beam for fusion of the build material into the part. The system can be configured to set the multi-spectral sensor off-axis with respect to the laser (e.g., an optical path of the multi-spectral sensor is at an angle that is different than the angle of incidence of the laser beam). This can allow the multi-spectral sensor to collect spectral data simultaneously as the laser is used to build the part.

Abstract: Embodiments relate to in-situ process monitoring of a part being made via additive manufacturing. The process can involve capturing computed tomography (CT) scans of a post-built part. A neural network (NN) can be used during the build of a new part to process multi-modal sensor data. Spatial and temporal registration techniques can be used to align the data to x,y,z coordinates on the build plate. During the build of the part, the multi-modal sensor data can be superimposed on the build plate. Machine learning can be used to train the NN to correlate the sensor data to a defect label or a non-defect label by looking to certain patterns in the sensor data at the x,y,z location to identify a defect in the CT scan at x,y,z. The NN can then be used to predict where defects are or will occur during an actual build of a part.

Abstract: Embodiments of the systems can be configured to receive electromagnetic emissions of a substrate (e.g., a build material of a part being made via additive manufacturing) by a detector (e.g., a multi-spectral sensor) and generate a ratio of the electromagnetic emissions to perform spectral analysis with a reduced dependence on location and orientation of a surface of the substrate relative to the multi-spectral sensor. The additive manufacturing process can involve use of a laser to generate a laser beam for fusion of the build material into the part. The system can be configured to set the multi-spectral sensor off-axis with respect to the laser (e.g., an optical path of the multi-spectral sensor is at an angle that is different than the angle of incidence of the laser beam). This can allow the multi-spectral sensor to collect spectral data simultaneously as the laser is used to build the part.

Abstract: An additive manufacturing system may include a powder delivery device configured to direct a powder stream toward a build surface of a component, and a powder flow monitoring system. The powder delivery device defines a longitudinal axis oriented toward the build surface. The powder flow monitoring system includes an illumination device configured to illuminate at least some powder the powder stream between the powder delivery device and the build surface; and an imaging device configured to image the illuminated powder at an image plane that intersects the longitudinal axis. The illumination device and the imaging device may be registered to the powder delivery device in a plane substantially orthogonal to the longitudinal axis.

Abstract: A powder flow monitoring system may include a computing device configured to receive image data representing illuminated powder of a powder stream between a powder delivery device and a build surface of a component, generate a representation of the powder stream based on the image data, and output the representation of the powder stream for display at a display device.

Abstract: Embodiments of the systems can be configured to receive electromagnetic emissions of a substrate (e.g., a build material of a part being made via additive manufacturing) by a detector (e.g., a multi-spectral sensor) and generate a ratio of the electromagnetic emissions to perform spectral analysis with a reduced dependence on location and orientation of a surface of the substrate relative to the multi-spectral sensor. The additive manufacturing process can involve use of a laser to generate a laser beam for fusion of the build material into the part. The system can be configured to set the multi-spectral sensor off-axis with respect to the laser (e.g., an optical path of the multi-spectral sensor is at an angle that is different than the angle of incidence of the laser beam). This can allow the multi-spectral sensor to collect spectral data simultaneously as the laser is used to build the part.

Abstract: Embodiments of the systems can be configured to receive electromagnetic emissions of a substrate (e.g., a build material of a part being made via additive manufacturing) by a detector (e.g., a multi-spectral sensor) and generate a ratio of the electromagnetic emissions to perform spectral analysis with a reduced dependence on location and orientation of a surface of the substrate relative to the multi-spectral sensor. The additive manufacturing process can involve use of a laser to generate a laser beam for fusion of the build material into the part. The system can be configured to set the multi-spectral sensor off-axis with respect to the laser (e.g., an optical path of the multi-spectral sensor is at an angle that is different than the angle of incidence of the laser beam). This can allow the multi-spectral sensor to collect spectral data simultaneously as the laser is used to build the part.

Abstract: An additive manufacturing system may include an energy delivery device configured to deliver energy to a component to form a melt pool at least partially surrounded by a cooling region; and an optical system comprising: an imaging device; and an occulting device, wherein the occulting device is configured to occult at least part of thermal emissions produced by the energy and the melt pool and transmit at least some thermal emissions produced by the cooling region.

Abstract: Embodiments of the systems can be configured to receive electromagnetic emissions of a substrate (e.g., a build material of a part being made via additive manufacturing) by a detector (e.g., a multi-spectral sensor) and generate a ratio of the electromagnetic emissions to perform spectral analysis with a reduced dependence on location and orientation of a surface of the substrate relative to the multi-spectral sensor. The additive manufacturing process can involve use of a laser to generate a laser beam for fusion of the build material into the part. The system can be configured to set the multi-spectral sensor off-axis with respect to the laser (e.g., an optical path of the multi-spectral sensor is at an angle that is different than the angle of incidence of the laser beam). This can allow the multi-spectral sensor to collect spectral data simultaneously as the laser is used to build the part.

Abstract: Embodiments of the systems can be configured to receive electromagnetic emissions of a substrate (e.g., a build material of a part being made via additive manufacturing) by a detector (e.g., a multi-spectral sensor) and generate a ratio of the electromagnetic emissions to perform spectral analysis with a reduced dependence on location and orientation of a surface of the substrate relative to the multi-spectral sensor. The additive manufacturing process can involve use of a laser to generate a laser beam for fusion of the build material into the part. The system can be configured to set the multi-spectral sensor off-axis with respect to the laser (e.g., an optical path of the multi-spectral sensor is at an angle that is different than the angle of incidence of the laser beam). This can allow the multi-spectral sensor to collect spectral data simultaneously as the laser is used to build the part.

Abstract: A method for manufacturing material voxel-by-voxel using directed-energy deposition is given. Using the method, unsupported structures, via voxel-wise directed-energy deposition, with steep overhangs is described and demonstrated. Methods for forming arbitrarily-complex structures and shaped voxels and surfaces are also given. A method for forming materials with internally-varying properties is also given. The method utilizes a pulsed or modulated, rather than continuous-wave energy source, thus allowing rapid solidification of voxels, rather than contours, hatches or tracks. Tuning of pulsing or modulation, material flow, and deposition-path parameters allows the buildup of unsupported material using standard directed-energy deposition processing heads and 3-axis stages, for example. The methods are demonstrated using a modified-directed-energy-deposition processes and is applicable to powder-bed for the buildup of three-dimensional components, repair and the addition of features to existing components.

Abstract: A method for manufacturing material voxel-by-voxel using directed-energy deposition is given. Using the method, unsupported structures, via voxel-wise directed-energy deposition, with steep overhangs is described and demonstrated. Methods for forming arbitrarily-complex structures and shaped voxels and surfaces are also given. A method for forming materials with internally-varying properties is also given. The method utilizes a pulsed or modulated, rather than continuous-wave energy source, thus allowing rapid solidification of voxels, rather than contours, hatches or tracks. Tuning of pulsing or modulation, material flow, and deposition-path parameters allows the buildup of unsupported material using standard directed-energy deposition processing heads and 3-axis stages, for example. The methods are demonstrated using a modified-directed-energy-deposition processes and is applicable to powder-bed for the buildup of three-dimensional components, repair and the addition of features to existing components.