Abstract: 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.

Abstract: This invention teaches a multi-sensor quality inference system for additive manufacturing. This invention still further teaches a quality system that is capable of discerning and addressing three quality issues: i) process anomalies, or extreme unpredictable events uncorrelated to process inputs; ii) process variations, or difference between desired process parameters and actual operating conditions; and iii) material structure and properties, or the quality of the resultant material created by the Additive Manufacturing process. This invention further teaches experimental observations of the Additive Manufacturing process made only in a Lagrangian frame of reference. This invention even further teaches the use of the gathered sensor data to evaluate and control additive manufacturing operations in real time.

Abstract: This disclosure describes various system and methods for monitoring photons emitted by a heat source of an additive manufacturing device. Sensor data recorded while monitoring the photons can be used to predict metallurgical, mechanical and geometrical properties of a part produced during an additive manufacturing operation. In some embodiments, a test pattern can be used to calibrate an additive manufacturing device.

Abstract: 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.

Abstract: A multi-sensor, real-time, in-process current and voltage estimation system is disclosed including sensors, affiliated hardware, and data processing algorithms that allow accurate estimation of currents and voltages from magnetic and electric field measurements, respectively. Aspects of the system may be embodied in a detector that is readily attachable to conductors of an energized system for contactless current and/or voltage sensing of the conductors without requiring the conductors to be disconnected from the energized system.

Abstract: An optical manufacturing process sensing and status indication system is taught that is able to utilize optical emissions from a manufacturing process to infer the state of the process. In one case, it is able to use these optical emissions to distinguish thermal phenomena on two timescales and to perform feature extraction and classification so that nominal process conditions may be uniquely distinguished from off-nominal process conditions at a given instant in time or over a sequential series of instants in time occurring over the duration of the manufacturing process. In other case, it is able to utilize these optical emissions to derive corresponding spectra and identify features within those spectra so that nominal process conditions may be uniquely distinguished from off-nominal process conditions at a given instant in time or over a sequential series of instants in time occurring over the duration of the manufacturing process.

Abstract: 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.

Abstract: This disclosure describes various system and methods for monitoring photons emitted by a heat source of an additive manufacturing device. Sensor data recorded while monitoring the photons can be used to predict metallurgical, mechanical and geometrical properties of a part produced during an additive manufacturing operation. In some embodiments, a test pattern can be used to calibrate an additive manufacturing device.

Abstract: This disclosure describes an additive manufacturing method that includes monitoring a temperature of a portion of a build plane during an additive manufacturing operation using a temperature sensor as a heat source passes through the portion of the build plane; detecting a peak temperature associated with one or more passes of the heat source through the portion of the build plane; determining a threshold temperature by reducing the peak temperature by a predetermined amount; identifying a time interval during which the monitored temperature exceeds the threshold temperature; identifying, using the time interval, a change in manufacturing conditions likely to result in a manufacturing defect; and changing a process parameter of the heat source in response to the change in manufacturing conditions.

Abstract: 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.

Abstract: This invention teaches a multi-sensor quality inference system for additive manufacturing. This invention still further teaches a quality system that is capable of discerning and addressing three quality issues: i) process anomalies, or extreme unpredictable events uncorrelated to process inputs; ii) process variations, or difference between desired process parameters and actual operating conditions; and iii) material structure and properties, or the quality of the resultant material created by the Additive Manufacturing process. This invention further teaches experimental observations of the Additive Manufacturing process made only in a Lagrangian frame of reference. This invention even further teaches the use of the gathered sensor data to evaluate and control additive manufacturing operations in real time.

Abstract: This disclosure describes various methods and apparatus for characterizing an additive manufacturing process. A method for characterizing the additive manufacturing process can include generating scans of an energy source across a build plane; measuring an amount of energy radiated from the build plane during each of the scans using an optical sensor; determining an area of the build plane traversed during the scans; determining a thermal energy density for the area of the build plane traversed by the scans based upon the amount of energy radiated and the area of the build plane traversed by the scans; mapping the thermal energy density to one or more location of the build plane; determining that the thermal energy density is characterized by a density outside a range of density values; and thereafter, adjusting subsequent scans of the energy source across or proximate the one or more locations of the build plane.

Abstract: This disclosure describes an additive manufacturing method that includes monitoring a temperature of a portion of a build plane during an additive manufacturing operation using a temperature sensor as a heat source passes through the portion of the build plane; detecting a peak temperature associated with one or more passes of the heat source through the portion of the build plane; determining a threshold temperature by reducing the peak temperature by a predetermined amount; identifying a time interval during which the monitored temperature exceeds the threshold temperature; identifying, using the time interval, a change in manufacturing conditions likely to result in a manufacturing defect; and changing a process parameter of the heat source in response to the change in manufacturing conditions.

Abstract: This invention teaches a multi-sensor quality inference system for additive manufacturing. This invention still further teaches a quality system that is capable of discerning and addressing three quality issues: i) process anomalies, or extreme unpredictable events uncorrelated to process inputs; ii) process variations, or difference between desired process parameters and actual operating conditions; and iii) material structure and properties, or the quality of the resultant material created by the Additive Manufacturing process. This invention further teaches experimental observations of the Additive Manufacturing process made only in a Lagrangian frame of reference. This invention even further teaches the use of the gathered sensor data to evaluate and control additive manufacturing operations in real time.

Abstract: This disclosure describes various methods and apparatus for characterizing an additive manufacturing process. A method for characterizing the additive manufacturing process can include generating scans of an energy source across a build plane; measuring an amount of energy radiated from the build plane during each of the scans using an optical sensing system that monitors two discrete wavelengths associated with a blackbody radiation curve of the layer of powder; determining temperature variations for an area of the build plane traversed by the scans based upon a ratio of sensor readings taken at the two discrete wavelengths; determining that the temperature variations are outside a threshold range of values; and thereafter, adjusting subsequent scans of the energy source across or proximate the area of the build plane.

Abstract: This disclosure describes an additive manufacturing method that includes monitoring a temperature of a portion of a build plane during an additive manufacturing operation using a temperature sensor as a heat source passes through the portion of the build plane; detecting a peak temperature associated with one or more passes of the heat source through the portion of the build plane; determining a threshold temperature by reducing the peak temperature by a predetermined amount; identifying a time interval during which the monitored temperature exceeds the threshold temperature; identifying, using the time interval, a change in manufacturing conditions likely to result in a manufacturing defect; and changing a process parameter of the heat source in response to the change in manufacturing conditions.

Abstract: This disclosure describes various methods and apparatus for characterizing an additive manufacturing process. A method for characterizing the additive manufacturing process can include generating scans of an energy source across a build plane; measuring an amount of energy radiated from the build plane during each of the scans using an optical sensor; determining an area of the build plane traversed during the scans; determining a thermal energy density for the area of the build plane traversed by the scans based upon the amount of energy radiated and the area of the build plane traversed by the scans; mapping the thermal energy density to one or more location of the build plane; determining that the thermal energy density is characterized by a density outside a range of density values; and thereafter, adjusting subsequent scans of the energy source across or proximate the one or more locations of the build plane.

Abstract: Various ways in which material property variations of raw materials used in additive manufacturing can be identified and accounted for are described. In some embodiments, the raw material can take the form of powdered metal. The powdered metal can have any number of variations including the following: particle size variation, contamination, particle composition and particle shape. Prior to utilizing the powders in an additive manufacturing operation, the powders can be inspected for variations. Variations and inconsistencies in the powder can also be identified by monitoring an additive manufacturing with one or more sensors. In some embodiments, the additive manufacturing process can be adjusted in real-time to adjust for inconsistencies in the powdered metal.

Abstract: A system and a corresponding method of correcting temperature data from a non-imaging optical sensor involve collecting temperature data generated using the optical sensor. The temperature data describes temperature changes across a surface of a material during an additive manufacturing operation in which the material is heated by a heat source. The method includes estimating a size of a hot spot corresponding to a hottest region formed on the surface by the heat source; and estimating a size of a heated region corresponding to a locus of points within the field of view that contribute to the temperature data. The method further includes correcting the temperature data based on the estimated sizes of the hot spot and the heated region.

Abstract: The disclosed embodiments relate to the monitoring and control of additive manufacturing. In particular, a method is shown for removing errors inherent in thermal measurement equipment so that the presence of errors in a product build operation can be identified and acted upon with greater precision. Instead of monitoring a grid of discrete locations on the build plane with a temperature sensor, the intensity, duration and in some cases position of each scan is recorded in order to characterize one or more build operations.