Abstract: A computing system may include a digital material collaboration engine configured to construct a digital material that is partially-defined based on input from a requestor entity of a digital material collaboration platform. The digital material may be for the manufacture of a physical product and may be partially-defined to include a physical material or product requirements for the physical product, but does not define process parameters of a manufacturing process to manufacture the physical product. The digital material collaboration engine may further be configured to receive, from provider entities of the digital material collaboration platform, proposed versions for the digital material that specify process parameters for the manufacturing process, and connect the requestor entity with a selected provider entity of the provider entities of the digital material collaboration platform based on a particular proposed version for the digital material provided by the selected provider entity.

Abstract: Systems and methods may support build direction-based partitioning for construction of a physical object through additive manufacturing. In some implementations, a system may access a surface mesh representative of a 3D object and an initial build direction for construction of the object using additive manufacturing. The system may partition the surface mesh into an initial buildable segment and a non-buildable segment based on the initial build direction. The system may iteratively determine subsequent build directions and partition off subsequent buildable segments from the unbuildable segment until no portion of the non-buildable segment remains. The determined buildable segments and correlated build directions may be provided to a multi-axis 3D printer for construction of the represented 3D object through additive manufacturing.

Abstract: A computing system may include an access engine and a defect detection engine. The access engine may be configured to access a slice contour of a given layer of a 3-dimensional (3D) object designed for manufacture through an additive manufacturing process and obtain hatch tracking for the slice contour, the hatch tracking representative of an energy path to melt metal powder for constructing the given layer through the additive manufacturing process. The defect detection engine may be configured to construct, from the slice contour, an as-built image for the given layer by rendering the hatch tracking in the slice contour; construct, from the slice contour, an idealized image for the given layer; and identify defects in the given layer via image analysis between the as-built image and the idealized image.

Abstract: A computing system may include a design access engine and a design processing engine. The design access engine may be configured to access an object design to be constructed through additive manufacturing. The design processing engine may be configured to represent the object design as a combination of coarse geometric elements and high-resolution lattice elements and process the object design based on both the coarse geometric elements and the high-resolution lattice elements. Processing of the object design may include generation of lattice infills, lattice simulations, or a combination of both.

Abstract: A method of optimizing an additive manufacturing (AM) process includes receiving at least one design parameter of the AM process, receiving information relating to uncertainty in at least one other parameter of the AM process, performing uncertainty quantification in the optimization processor based on the at least one design parameters and uncertainty information to identify a shape error in an object being produced, updating the at least one design parameter of the AM process and utilizing the updated at least one design parameter in the AM process. A system for optimizing an AM process includes a design processor to produce at least one design parameter for an object to be manufactured, and an optimization processor to receive the at least one design parameter and uncertainty information to identify a shape error in the object to be manufactured and update the design parameters based on the shape error, prior or during the manufacturing process.

Abstract: A system may include a processor configured to receive toolpaths along which a 3D printer deposits beads of material in a plurality of layers in order to additively build up a product. Based on the toolpaths, the processor may determine an image for each layer and may process the images based on a default bead size to determine a bead size image for each layer comprised of pixels having values that specify bead size for locations along the toolpaths. The image processing produces pixel values for the bead size images that vary in magnitude at different locations along the toolpaths in order to represent smaller and larger bead sizes relative to the default bead size, which smaller and larger bead sizes respectively minimize over-depositing and under-depositing of material by the 3D printer that would otherwise occur with the default bead size.

Abstract: Additive manufacturing methods and corresponding systems and computer-readable mediums. A method includes receiving, by a data processing system, a three-dimensional (3D) model of a product to be manufactured by additive manufacturing. The method includes generating, by the data processing system, a time-based heat map of temperatures of the product during manufacture. The method includes identifying, by the data processing system, hot spots in the heat map where the temperature exceeds a first predetermined threshold. The method includes adding, by the data processing system, heatsink support structures to the 3D model at locations corresponding to the hot spots to produce a modified 3D model. The method includes storing, by the data processing system, the modified 3D model.

Abstract: Additive manufacturing methods and corresponding systems and computer-readable mediums. A method includes receiving, by a data processing system, a three-dimensional (3D) model of a product to be manufactured by additive manufacturing. The method includes generating, by the data processing system, a time-based heat map of temperatures of the product during manufacture. The method includes identifying, by the data processing system, hot spots in the heat map where the temperature exceeds a first predetermined threshold. The method includes adding, by the data processing system, heatsink support structures to the 3D model at locations corresponding to the hot spots to produce a modified 3D model. The method includes storing, by the data processing system, the modified 3D model.

Abstract: A system and method are provided for adaptive domain reduction for thermo-structural simulation of an additive manufacturing process. The system may include a processor configured to carry out a simulation of a part being additively produced according to a set of tool paths. The simulation may include determining an original mesh of the part; determining an order of the elements of the original mesh to deposit; and simulating an incremental deposit of each of the elements of the original mesh for a material in the order that the elements are determined to be deposited. For each incremental deposit of an additional respective element the processor may determine thermal characteristics and structural deformation characteristics of the deposited elements.

Abstract: A method of optimizing an additive manufacturing (AM) process includes receiving at least one design parameter of the AM process, receiving information relating to uncertainty in at least one other parameter of the AM process, performing uncertainty quantification in the optimization processor based on the at least one design parameters and uncertainty information to identify a shape error in an object being produced, updating the at least one design parameter of the AM process and utilizing the updated at least one design parameter in the AM process. A system for optimizing an AM process includes a design processor to produce at least one design parameter for an object to be manufactured, and an optimization processor to receive the at least one design parameter and uncertainty information to identify a shape error in the object to be manufactured and update the design parameters based on the shape error, prior or during the manufacturing process.

Abstract: Systems and methods may support identification and redesign of critical thin segments in a 3D model that are below 3D printer resolution. Identification of critical thin segments may include segmenting cross-sectional slices of the 3D model into printable segments and non-printable segments and using a machine learning model trained using geometrical features computed on thin regions to classify the non-printable segments as critical or non-critical. Redesign of critical thin segments may include thickening the critical thin segments such that the segment size of the critical thin segments satisfy a thickening criterion with respect to the printer resolution and smoothing sharp corners added to the cross-sectional slice at an intersection between the critical thin segment and a neighboring printable segment. Redesign of the critical thin segments may account for tolerable overhang.

Abstract: A system and method are provided for adaptive domain reduction for thermo-structural simulation of an additive manufacturing process. The system may include a processor configured to carry out a simulation of a part being additively produced according to a set of tool paths. The simulation may include determining an original mesh of the part; determining an order of the elements of the original mesh to deposit; and simulating an incremental deposit of each of the elements of the original mesh for a material in the order that the elements are determined to be deposited. For each incremental deposit of an additional respective element the processor may determine thermal characteristics and structural deformation characteristics of the deposited elements.

Abstract: Methods for hybrid manufacturing and planning and corresponding systems and computer-readable mediums. A method includes receiving, by a data processing system, a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process. The method includes instantiating a virtual workpiece. The method includes instantiating the tools definitions against a manufacturing ontology to produce virtual tools. The method includes receiving operations for the virtual tools. The method includes searching for combinations of the operations to be performed on the virtual workpiece to make the virtual workpiece correspond to the CAD model. The method includes identifying possible manufacturing solutions according to the search. The method includes selecting a manufacturing plan from the possible manufacturing solutions.

Abstract: Systems and methods may support identification and redesign of critical thin segments in a 3D model that are below 3D printer resolution. Identification of critical thin segments may include segmenting cross-sectional slices of the 3D model into printable segments and non-printable segments and using a machine learning model trained using geometrical features computed on thin regions to classify the non-printable segments as critical or non-critical. Redesign of critical thin segments may include thickening the critical thin segments such that the segment size of the critical thin segments satisfy a thickening criterion with respect to the printer resolution and smoothing sharp corners added to the cross-sectional slice at an intersection between the critical thin segment and a neighboring printable segment. Redesign of the critical thin segments may account for tolerable overhang.

Abstract: Systems and methods may support build direction-based partitioning for construction of a physical object through additive manufacturing. In some implementations, a system may access a surface mesh representative of a 3D object and an initial build direction for construction of the object using additive manufacturing. The system may partition the surface mesh into an initial buildable segment and a non-buildable segment based on the initial build direction. The system may iteratively determine subsequent build directions and partition off subsequent buildable segments from the unbuildable segment until no portion of the non-buildable segment remains. The determined buildable segments and correlated build directions may be provided to a multi-axis 3D printer for construction of the represented 3D object through additive manufacturing.

Abstract: A system and method is provided for providing variation in bead size to improve geometrical accuracy of deposited layers in an additive manufacturing process. The system may include at least one processor configured to receive a plurality of toolpaths along which a 3D printer deposits beads of material in a plurality of layers in order to additively build up a product. Based on the toolpaths, the processor may determine an image for each layer and may process the images based on a default bead size to determine a bead size image for each layer comprised of pixels having values that specify bead size for locations along the toolpaths.

Abstract: A system and method is provided for facilitate lattice structure design for additive manufacturing carried out through operation of at least one processor. The processor may be configured via executable instructions included in at least one memory to receive a three dimensional (3D) model of an object. The processor may also receive effective mechanical properties for at least a portion of the 3D model to be filled by a lattice producible by a 3D printer configured to produce the object. In addition the processor may determine lattice design parameters based on the received effective mechanical properties for the portion of the design. Or in the opposite direction, the processor may determine the effective mechanical properties based on the lattice design parameter. Further, the processor may modify the 3D model to include the lattice having the determined lattice design parameters for the portion of the 3D model.

Abstract: A system and method is provided for modeling characteristics of a melt pool that forms during an additive manufacturing process. The system may include at least one processor configured to generate a data-driven model capable of predicting melt pool temperature and melt pool area for target deposit location points along at least one tool path for a three dimensional (3D) printer at which a laser of the 3D printer melts new deposits of material to buildup a product. The generation of the data-driven model may be based at least in part on melt pool temperatures and melt pool areas for a selected nearest subset of a plurality of previous deposit location points along the at least one tool path. The nearest subset may be selected based on determined spatio-temporal distance between a respective target deposit location point and each of the plurality of previous deposit location points along the at least one tool path.

Abstract: A component of a computer-aided manufacturing (CAM) system may be configured to cause a processor to generate instructions that specify how a 3D-printer additively builds an article on a build plate via depositing material from a deposition head. The 3D printer is configured to cause the deposition head to rotate in order to selectively change, an angle of a deposition axis at which the deposition head outputs material. The generated instructions specify how the deposition head is operated by the 3D printer to build the article on the build plate such that material deposited along a side wall surface of the article is provided by the deposition head having its deposition axis orientated at an angle determined based at least in part on an angular orientation of the side wall surface.

Abstract: Systems and methods for support structures for additive manufacturing of solid models. A method includes receiving a solid model, for a physical object to be manufactured, that includes a plurality of boundary representation surfaces. The method includes analyzing the b-rep surfaces to generate point samples for potential support locations. The method includes clustering points on the solid model, corresponding to at least some of the point samples, to create support locations. The method includes generating column supports in the solid model that connect to the original solid model at the support locations. The method includes storing the solid model, including the column supports.