Siemens Industry Software Gmbh

Siemens Aktiengesellschaft

Siemens Product Lifecycle Management Software Inc.

Siemens Product Lifestyle Management Inc.

David Madeley

Suraj Ravi Musuvathy

Erhan Arisoy

Livio Dalloro

Lucia Mirabella

Sanjeev Srivastava

Dirk Hartmann

Tsz Ling Elaine Tang

Prakhar Jaiswal

Nurcan Gecer Ulu

Hasan Sinan Bank

Erva Ulu

Elena Arvanitis

Omar Fergani

Edward Slavin, Iii

Tom Van 't Erve

Louis Komzsik

Timothy Ray Fithian

William Vittitow

Yi Xu

Mark R Burhop

Stefan Gavranovic

Mai-Anh T Bui

Gaurav Ameta

Timothy R Fithian

Tom Van 'T Erve

Hasan Bank

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.

Image-based defect detections in additive manufacturing

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.

Build direction-based partitioning for construction of a physical object through additive manufacturing

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.

Method and apparatus for robust reduction of shape error in laser powder deposition based additive manufacturing process due to uncertainty

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.

System and method for providing variation in bead size to improve geometrical accuracy of deposited layers in an additive manufacturing process

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.

Heat sink support structures in additive manufacturing

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. After the deposit of several layers have been simulated, subsequent simulation of elements may be carried out based on a respective modified version of the original mesh in which at least some of the layers of the original mesh previously simulated to be deposited under a current layer are retained and at least some are omitted.

System and method for adaptive domain reduction for thermo-structural simulation of additive manufacturing process

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.

Identification and redesign of critical thin segments below 3D printer resolution

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.

Apparatus and method for additive manufacturing

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.

Support structures for additive manufacturing of solid models

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Louth, United Kingdom

David Madeley