An additive manufacturing system is disclosed for use in discharging a continuous reinforcement. The additive manufacturing system may include a support, and a compactor operatively connected to and movable by the support. The compactor may be configured to apply a pressure to the continuous reinforcement during discharge. The additive manufacturing system may also include a feed roller biased toward the compactor to sandwich the continuous reinforcement between the roller and the compactor, and a cutting mechanism at least partially recessed within at least one of the feed roller and the compactor. The cutting mechanism may be configured to selectively move radially outward to engage the continuous reinforcement.

A system and methods are disclosed for producing components via additive manufacturing. In one embodiment, a three-dimensional geometry is sliced using a slicing plane to obtain a first two-dimensional geometry. A first polyline is generated based on a first skeleton of the first two-dimensional geometry, and a first slender body is generated based on the first polyline. The first slender body is subtracted from the first two-dimensional geometry to obtain a second two-dimensional geometry. A second polyline is generated based on a second skeleton of the second two-dimensional geometry. A first bundle of fibers is produced based on a segmentation of the first polyline and a second bundle of fibers is produced based on a segmentation of the second polyline. A component is produced from the first and second bundles of fibers using an additive manufacturing process.

A recoater collision prediction and calibration method for additive manufacturing and a system thereof are provided. The recoater collision prediction and calibration method includes the following steps: loading a printing image file to generate a simulated printing object according to the printing image file; performing a process thermal stress simulation on the simulated printing object to obtain a plurality of simulated deformation variables respectively corresponding to a plurality of prediction results of the simulated printing object in a vertical direction on each layer; obtaining an experimental collision height of an experimental printed object; selecting one of the plurality of simulated deformation variables according to the experimental collision height; calculating a recoater tolerance according to the one of the plurality of simulated deformation variables; calibrating a collision risk formula according to the recoater tolerance; and predicting a collision risk value between the simulated printing object and a recoater according to the collision risk formula.

Integrated process-structure-property modeling framework and method for design optimization and/or performance prediction of a material system are provided. The Integrated process-structure-property modeling framework includes a powder spreading model using a discrete element method to generate a powder bed; a thermal-fluid flow model of the powder melting process to predict voids and temperature profile; a cellular automaton model to simulate grain growth based on the temperature profile; and a reduced-order micromechanics model to predict mechanical properties and fatigue resistance of resultant structures by resolving the voids and grains.

When the temperature history in a fine mesh is obtained for the entire modeled object, it takes a huge amount of time in calculation. In order to solve the problem, An additive-manufactured object design supporting device, comprising: an analysis unit configured to analyze a modeling process of a macro-region and a micro-region by using a product shape, a material condition, and a modeling condition of a modeled object as input; a temperature history extraction unit configured to extract, from a temperature analysis result of the macro-region, a local temperature history by referring to a database that stores a temperature history of the micro-region; a mapping unit configured to map a structure distribution obtained from a temperature history distribution of the modeled object to the modeled object; and an extraction unit configured to extract a defective structure that does not satisfy a structure condition by using an allowable structure condition as input.

In an example, a method include receiving a data model of an object to be generated in additive manufacturing at a processor, the data model comprising object property data. A segmentation of a virtual build volume comprising at least a portion of the object into a plurality of nested segments may be derived. A first segment may be associated with first object generation parameters and a second segment may be associated with second, different, object generation parameters. A number of nested segments to be derived may be determined based on at least one of a geometry of the object and an intended object property.

A method of making a physical object having a desired geometry from a resin such as a dual cure resin by an additive manufacturing process such as a dual cure additive manufacturing process includes (a) entering into a processor a first input geometry for the physical object, the first input geometry corresponding to a desired geometry for the physical object; (b) modifying in the processor the first input geometry to a candidate inversely distorted input geometry for the physical object; (c) generating a simulated object from the candidate inversely distorted input geometry with a Multiphysics model simulation of the additive manufacturing process, the simulated object including distortions towards the desired geometry arising from the additive manufacturing process; (d) evaluating whether the simulated object sufficiently corresponds to the desired geometry for the physical object.

A method includes: accessing a part model comprising a three-dimensional representation of a part; accessing a material profile relating exposure energy and three-dimensional polymerization geometry of a material selected for the part; segmenting the part model into a set of model layers; detecting a first upward-facing surface in the part model; defining a first model volume in a first model layer, adjacent the first upward-facing surface, and fully contained within the part model; based on the material profile, calculating a first exposure energy predicted to yield a first three-dimensional polymerization geometry approximating a first contour of the first upward-facing surface when projected onto the material during a build; populating a first print image with the first exposure energy in a first image area corresponding to the first model volume in the first model layer; and storing the first print image in a print file for the part.

The present invention is generally directed to systems and methods for preparing and producing a custom-fitted face mask, including, as non-limiting examples, a CPAP nasal mask and a CPAP full face mask. At least one embodiment of the invention utilizes infrared (IR) lasers, such as, for example, those found on smartphone cameras, in order to generate a 3D point cloud model of an individual's face. This point cloud model is then used to produce a custom face mask cushion, which is used to customize a generic face mask to conform to the user's specific facial geometry.

A method is disclosed for generating a 3D printing file containing an object model of a part having a body and an integral electronic component. To generate the 3D printing file, a processor receives at least one geometry specification of the part to be printed and at least one component performance property of the electronic component to be printed integral to the part. An object model is determined by the processor in accordance with the at least one geometry specification of a part to be printed, the at least one component performance property of an electronic component to be printed, and at least one material property of an electronic component printing material of a 3D printer. The 3D printing file is generated by the processor and comprises the object model.