An electron beam melting machine and a method of operation are provided which maintains constant energy absorption within a build layer by adjusting an incident energy level to compensate for energy not absorbed by the additive powder. This unabsorbed energy is detected in the form of electron emissions, which include secondary electrons, backscattered electrons, and/or electrons which are transmitted through the build platform.

The present disclosure relates to generation of forming instructions to form one or more three-dimensional (3D) objects. Generation of the forming instructions may include selection of one or more formation variables to form at least a portion of the one or more 3D objects. Generation of the forming instructions may include selection of a speed, feature, and/or an effect manifested in at least a portion of the formed one or more 3D objects. The forming variable(s) may be associated with a patch of a model of the 3D object.

The problem of measuring the temperature of a 3D printing process is addressed by systems and methods that apply imaging spectrometry to measure blackbody radiation emitted before, during, or after a 3D printing process. The systems and methods utilize a pair of lenses, a field stop, and a wavelength separator to direct a plurality of wavelengths corresponding to the blackbody radiation to pixels of an optical detector. The plurality of wavelengths are analyzed by a controller to determine the temperature of the 3D printed component.

The problem of measuring the temperature of a 3D printing process is addressed by systems and methods that apply imaging spectrometry to measure blackbody radiation emitted before, during, or after a 3D printing process. The systems and methods utilize a pair of lenses, a field stop, and a wavelength separator to direct a plurality of wavelengths corresponding to the blackbody radiation to pixels of an optical detector. The plurality of wavelengths are analyzed by a controller to determine the temperature of the 3D printed component.

Disclosed is a system for adding material by melting powder on a determined surface of a workpiece by means of a laser beam in order to construct a volume, the system comprising: -a laser beam emitting device, -a laser scanning head provided with at least two galvanometric mirrors and provided with a lens for focusing the reflected incident laser beam on the determined surface, the system comprising the laser scanning head being held stationary relative to the workpiece while the volume is constructed, -a powder injection device positioned laterally relative to the focused reflected incident laser beam in order to distribute the powder on the determined surface, -the powder is melted by the focused reflected incident laser beam emitted on the powder distributed on the determined surface.

Disclosed is a system for adding material by melting powder on a determined surface of a workpiece by means of a laser beam in order to construct a volume, the system comprising: -a laser beam emitting device, -a laser scanning head provided with at least two galvanometric mirrors and provided with a lens for focusing the reflected incident laser beam on the determined surface, the system comprising the laser scanning head being held stationary relative to the workpiece while the volume is constructed, -a powder injection device positioned laterally relative to the focused reflected incident laser beam in order to distribute the powder on the determined surface, -the powder is melted by the focused reflected incident laser beam emitted on the powder distributed on the determined surface.

A method of feedback controlling a 3D printing process in real time, and a system therefor are disclosed. The method includes collecting big data, generated through 3D printing experiments, related to process variables of 3D printing, measurement signals, and 3D printing quality of the 3D printing object; building an artificial neural network model by performing machine-learning based on the collected big data; evaluating whether or not a 3D printing quality of the 3D printing object is abnormal in real time based on an actual measurement signal of the 3D printing object and the artificial neural network model; and feedback controlling printing quality of the 3D printing object in real time based on the evaluation result of whether or not the 3D printing quality of the 3D printing object is abnormal.

An additive manufacturing system may include an energy delivery device configured to deliver energy to a build surface of a component to form a melt pool in the build surface of the component; a powder delivery device configured to direct a powder stream toward the melt pool; a plurality of mass sensors, each mass sensor associated with a portion of the additive manufacturing system; a plurality of heat sensors; and one or more computing devices. The computing device(s) are configured to receive data from the plurality of mass sensors; determine an overall mass flux based on the data from the mass sensors; control the powder delivery device based on the overall mass flux; receive data from the plurality of heat sensors; determine an overall heat flux based on the data from the heat sensors; and control the energy delivery device based on the overall heat flux.

An additive manufacturing system may include an energy delivery device configured to deliver energy to a build surface of a component to form a melt pool in the build surface of the component; a powder delivery device configured to direct a powder stream toward the melt pool; a plurality of mass sensors, each mass sensor associated with a portion of the additive manufacturing system; a plurality of heat sensors; and one or more computing devices. The computing device(s) are configured to receive data from the plurality of mass sensors; determine an overall mass flux based on the data from the mass sensors; control the powder delivery device based on the overall mass flux; receive data from the plurality of heat sensors; determine an overall heat flux based on the data from the heat sensors; and control the energy delivery device based on the overall heat flux.

This invention teaches a quality assurance system for additive manufacturing. This invention teaches a multi-sensor, real-time quality system including sensors, affiliated hardware, and data processing algorithms that are Lagrangian-Eulerian with respect to the reference frames of its associated input measurements. The quality system for Additive Manufacturing is capable of measuring true in-process state variables associated with an additive manufacturing process, i.e. those in-process variables that define a feasible process space within which the process is deemed nominal. The in-process state variables can also be correlated to the part structure or microstructure and can then be useful in identifying particular locations within the part likely to include defects.