According to examples, a three-dimensional (3D) fabrication system may include a controller to identify a feature of an object to be fabricated and based on the identified feature having a size that is smaller than a predefined size, determine a thermal support for the identified feature. The controller may also control fabrication components to form, through application of energy, the determined thermal support from a first set of particles, form an intermediate section adjacent to the formed thermal support from a second set of particles, and form, through application of energy, the feature adjacent to the intermediate section from a third set of particles, in which heat from the thermal support is to reduce a thermal bleed rate of the third set of particles.

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.

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.

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.

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.

A system for determining a temperature of an object includes a three-dimensional (3D) printer configured to successively deposit a first layer of material, a second layer of material, and a third layer of material to form the object. The 3D printer is configured to form a recess in the second layer of material. The material is a metal. The system also includes a temperature sensor configured to be positioned at least partially with the recess and to have the third layer deposited thereon. The temperature sensor is configured to measure a temperature of the first layer of material, the second layer of material, the third layer of material, or a combination thereof.

A method (P) for determining trajectory followed by a laser beam for selective additive manufacture of a three-dimensional object comprises: a) determining, on a predetermined reference path (Ti), a plurality of reference points (T.sub.ij), b) determining a plurality of adjacent points (T.sub.i+1j) located on the same side of the reference path, each adjacent point (T.sub.i+1j) being associated with a reference point (T.sub.ij) and being such that a simulated adjacent melt zone that surrounds said adjacent point (T.sub.i+1j) and a simulated reference melt zone that surrounds the reference point (T.sub.ij) have an overlap corresponding to a fraction of a transverse width of the simulated reference melt zone that is comprised between a predetermined minimum fraction (αmin) and a predetermined maximum fraction (αmax), c) determining an adjacent path (T.sub.i+1) passing through the plurality of determined adjacent points, and d) iterating steps a) to c) using the adjacent path, defined as a new reference path, so as to determine, on each iteration, a new adjacent path, all of the adjacent paths thus determined defining the trajectory.

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.

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.

A system and method of monitoring a powder-bed additive manufacturing process is provided where a layer of additive powder is fused using an energy source and electromagnetic emission signals are measured by a melt pool monitoring system to monitor the print process. The measured emission signals are analyzed to identify outlier emissions and clusters of outliers are identified by assessing the spatial proximity of the outlier emissions, e.g., using clustering algorithms, spatial control charts, etc. An alert may be provided or a process adjustment may be made when a cluster is identified or when a magnitude of a cluster exceeds a predetermined cluster threshold.