Abstract: 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.

Abstract: A powder processing machine includes a work bed, a powder deposition device operable to deposit powder in the work bed, at least one energy beam device operable to emit an energy beam with a variable beam power and direct the energy beam onto the work bed with a variable beam scan rate to melt and fuse regions of the powder, and a controller operable to dynamically control at least one of the beam power or the beam scan rate to change how the powder melts and fuses. The controller is configured to determine whether an instant set of process parameters falls within a defect condition or a non-defect condition and adjust at least one of the beam power or the beam scan rate responsive to the defect condition such that the instant set of process parameters falls within the non-defect condition.

Abstract: A method of monitoring an additive manufacturing build process includes first and second phases. The first phase includes depositing a powder layer onto a powder bed. A topographical profile of the powder bed is captured with a profilometer. An image of the powder bed is captured with a camera. The image and topographical profile are combined to create a data set that is transferred to a machine learning algorithm. A set of training data is generated and includes a set of deviations from a nominal model. The second phase includes depositing a powder layer onto the powder bed. An image of the powder bed is captured and compared to the set of training data. Deviations from the nominal model of the first powder bed are determined. Any deviations that are greater than a numerical threshold are labelled and identified as a defect which includes its type and severity.

Abstract: A method for monitoring an additive manufacturing process during fabrication of a component part is disclosed. In various embodiments, the method includes the steps of selecting a sensing matrix; orienting a sensor toward a surface of the component part; generating a discrete time signal, based on data obtained from the sensor, the discrete time signal being representative of a process condition of the component part while the component part is undergoing the additive manufacturing process; compressing the discrete time signal using the sensing matrix to form a compressed measurement signal; and storing the compressed measurement signal in a storage device while the component part is undergoing the additive manufacturing process. In various embodiments, selecting the sensing matrix comprises selecting a basis function. In various embodiments, the basis function is determined using a random time sampling.

Abstract: A process for coating a gas turbine blade with an abrasive. The process includes positioning the gas turbine blade in a nest, the gas turbine blade comprising a tip having a top surface; prepositioning a metal powder material on the top surface; fusing the metal powder material to the top surface by use of a laser to form a base layer on the top surface; prepositioning an abrasive composite material on the base layer opposite the top surface; fusing the abrasive composite material to the base layer by use of the laser to form an abrasive coating on the base layer; and removing the gas turbine blade from the nest.

Abstract: 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.

Abstract: A powder processing machine includes a work bed, a powder deposition device operable to deposit powder in the work bed, at least one energy beam device operable to emit an energy beam with a variable beam power and direct the energy beam onto the work bed with a variable beam scan rate to melt and fuse regions of the powder, and a controller operable to dynamically control at least one of the beam power or the beam scan rate to change how the powder melts and fuses. The controller is configured to determine whether an instant set of process parameters falls within a defect condition or a non-defect condition and adjust at least one of the beam power or the beam scan rate responsive to the defect condition such that the instant set of process parameters falls within the non-defect condition.