A system for diagnosing an additive manufacturing device is provided. The system includes one or more processors, one or more non-transitory memory modules communicatively coupled to the one or more processors and storing machine-readable instructions. The machine-readable instructions, when executed, cause the one or more processors to: determine parameters associated with at least one subsystem of the additive manufacturing device, the parameters being related to a build generated by the additive manufacturing device; compare the parameters with threshold values; and determine a failure mode, among a plurality of failure modes, associated with a subsystem of the at least one subsystem of the additive manufacturing device based on the comparison of the parameters with the threshold values.

Methods and apparatus to identify additively manufactured parts are disclosed. An example method of manufacturing includes layering a first set of layers of a first material via an additive manufacturing technique, the first material having a first density and layering a second set of layers of the first material via the additive manufacturing technique, the second set of layers to form a void embedded internally in the part, the void forming an indicium.

An information processing device includes a read unit, a storage unit, and a correction unit. The read unit is configured to read instruction information that causes a modeling device to execute a modeling procedure about a first modeling material body. The storage unit is configured to store modeling material body information about a second modeling material body and modeling material body information about the first modeling material body. The correction unit is configured to correct a first parameter value about the first modeling material body, which is a first parameter value contained in the instruction information read by the read unit, according to the modeling material body information about the second modeling material body and the modeling material body information about the first modeling material body stored in the storage unit.

A laser powder bed fusion additive manufacturing system for producing a part by creating a power map that is an intelligent feed forward model to control the laser powder bed fusion additive manufacturing for producing the part and using the power map to control the laser powder bed fusion additive manufacturing for producing the part. This includes an apparatus for producing a part including a powder bed, a laser that produces a laser beam, a proportional integral derivative controller that creates a power map that describes laser power requirements as the laser moves along a path, wherein the laser power requirements prevent defects in the part.

The present disclosure relates to calibrating scanner devices for positioning laser beams in a processing field, and includes, e.g.: arranging a retroreflector in the processing field of the scanner device, the processing field being formed in a processing chamber for irradiating powder layers; detecting laser radiation reflected back into the scanner device when the laser beam passes over the retroreflector; determining an actual position of the laser beam in the processing field using the detected laser radiation; and calibrating the scanner device by correcting a laser beam target position specified for the scanner device in the processing field using the determined actual position of the laser beam in the processing field.

Methods, systems, and apparatus, including medium-encoded computer program products, for designing three dimensional lattice structures include, in one aspect, a method including: creating nodes in a plane normal to an axis in accordance with a spiral, wherein proper subsets of the nodes occur at successive radii positions away from the axis in the plane normal to the axis; repositioning every other one of the proper subsets, from at least a portion of the nodes, in a direction in 3D space along the axis; creating a three dimensional (3D) structure in the 3D space, the 3D structure comprising beams placed between the repositioned and non-repositioned proper subsets; duplicating the 3D structure one or more times to form a lattice in the 3D space; and selecting at least a portion of the lattice for inclusion in a 3D model.

Disclosed herein are machine learning-based methods and systems for automated object defect classification and adaptive, real-time control of additive manufacturing and/or welding processes.

Calibration device (1) for an apparatus for additively manufacturing of three-dimensional objects, which calibration device (1) comprises at least one determination unit (2, 3) and at least one calibration unit (16, 17), wherein the at least one determination unit (2) is adapted to determine at least one geometrical parameter of a carrying element (4) of a powder module and wherein the at least one calibration unit (17) is adapted to, in particular automatically, adjust an application unit (5) of the apparatus dependent on the at least one determined geometrical parameter of the carrying element (4) and/or wherein the at least one determination unit (3) is adapted to determine at least one geometrical parameter of an application unit (5) of the apparatus and wherein the at least one calibration unit (16) is adapted to, in particular automatically, adjust a carrying element (4) of a powder module dependent on the at least one determined geometrical parameter of the application unit (5).

A method of fabricating process-equivalent test specimens to an additively manufactured component includes generating a processing history model of a component, dividing the component into regions based on input data variations in processing history, wherein each region is characterized by an identified range of input data, determining additive manufacturing processing parameters needed to additively manufacture one or more test specimens that each mimic the processing history in one of the regions, and fabricating the one or more test specimens using the processing parameters determined.

The invention concerns a method for calibration of at least one scanning system of a laser sintering or laser melt facility with the further characteristics of the preamble of Claim 1.