Abstract: A metal matrix composite to high tolerate wear as a property has been produced by infiltration casting of a Fe Alloy and a spinel ceramic by using a material design for i) metal transport phenomena conditions, ii) predefined wetting and capillarity and iii) processing child insert/mother casting methodology to produce a final casting in shape and form to meet the needs of a mining end user.

Abstract: A metal matrix composite to high tolerate wear as a property has been produced by infiltration casting of a Fe Alloy and a spinel ceramic by using a material design for i) metal transport phenomena conditions, ii) predefined wetting and capillarity and iii) processing child insert/mother casting methodology to produce a final casting in shape and form to meet the needs of a mining end user.

Abstract: An example method that includes receiving a geometry of a component that includes a plurality of locations on a surface of the component; determining a first target trajectory including a first plurality of target trajectory points and a second target trajectory including a second plurality of target trajectory points, the first and second trajectories offset in a first direction, and the first and second plurality of trajectory points offset in a second direction; determining a respective target coating thickness of the coating based on a target coated component geometry and the geometry; and determining a respective motion vector of a coating device based on the first and second target trajectories to deposit the respective target coating thickness.

Abstract: An example method that includes receiving, by a computing device, a geometry of the component that includes a plurality of locations on a surface of the component; determining, by the computing device, a respective target thickness of the coating for each respective location of the plurality of locations based on a target coated component geometry and the geometry of the component; and determining, by the computing device, a number of passes or velocity of a coating device for each respective position of a plurality of positions to achieve the respective target thickness for each respective location.

Abstract: An example method that includes receiving a first geometry of a component in an uncoated state and a second geometry of the component in a coated state; determining a first difference between the second geometry and a first simulated geometry based on the first geometry and a first spray law comprising a plurality of first spray law parameters; iteratively adjusting at least one first spray law parameter to determine a respective subsequent spray law; iteratively determining a respective subsequent difference between the second geometry and a subsequent simulated geometry based on the first geometry and the subsequent respective spray law; selecting a subsequent spray law from the respective subsequent spray laws based on the respective subsequent differences; and controlling a coating process based on the selected subsequent spray law.

Abstract: An example method that includes receiving a geometry of an uncoated component and a measured coating thickness of a coated test; determining a simulated coating thickness based on the geometry and a first spray law including a plurality of first spray law parameters; determining a difference between the simulated coating thicknesses and the measured coating thickness; iteratively adjusting at least one first spray law parameter to determine a respective subsequent spray law and determining a respective subsequent difference between the measured coating thickness and a subsequent simulated coating thickness based on the geometry and the respective subsequent spray law; selecting a subsequent spray law from the plurality of respective subsequent spray laws based on the respective subsequent differences; and controlling a coating process based on the selected subsequent spray law to compensate for the difference.

Abstract: An example system includes at least one acoustic sensor and one optical sensor to monitor a thermal spray system controlled by a plurality of control parameters and performing a process associated with a plurality of process outputs. The system includes a computing device including a machine learning module and a control module. The machine learning module is configured to determine, based on at least the plurality of control parameters, an at least one time-dependent acoustic data signal, an at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning. The control module is configured to control the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges.

Abstract: An example method that includes receiving a geometry of a component that includes a plurality of locations on a surface of the component; determining a first target trajectory including a first plurality of target trajectory points and a second target trajectory including a second plurality of target trajectory points, the first and second trajectories offset in a first direction, and the first and second plurality of trajectory points offset in a second direction; determining a respective target coating thickness of the coating based on a target coated component geometry and the geometry; and determining a respective motion vector of a coating device based on the first and second target trajectories to deposit the respective target coating thickness.

Abstract: An example method that includes receiving a geometry of an uncoated component and a measured coating thickness of a coated test; determining a simulated coating thickness based on the geometry and a first spray law including a plurality of first spray law parameters; determining a difference between the simulated coating thicknesses and the measured coating thickness; iteratively adjusting at least one first spray law parameter to determine a respective subsequent spray law and determining a respective subsequent difference between the measured coating thickness and a subsequent simulated coating thickness based on the geometry and the respective subsequent spray law; selecting a subsequent spray law from the plurality of respective subsequent spray laws based on the respective subsequent differences; and controlling a coating process based on the selected subsequent spray law to compensate for the difference.

Abstract: An example method that includes receiving, by a computing device, a geometry of the component that includes a plurality of locations on a surface of the component; determining, by the computing device, a respective target thickness of the coating for each respective location of the plurality of locations based on a target coated component geometry and the geometry of the component; and determining, by the computing device, a number of passes or velocity of a coating device for each respective position of a plurality of positions to achieve the respective target thickness for each respective location.

Abstract: An example method that includes receiving a first geometry of a component in an uncoated state and a second geometry of the component in a coated state; determining a first difference between the second geometry and a first simulated geometry based on the first geometry and a first spray law comprising a plurality of first spray law parameters; iteratively adjusting at least one first spray law parameter to determine a respective subsequent spray law; iteratively determining a respective subsequent difference between the second geometry and a subsequent simulated geometry based on the first geometry and the subsequent respective spray law; selecting a subsequent spray law from the respective subsequent spray laws based on the respective subsequent differences; and controlling a coating process based on the selected subsequent spray law.

Abstract: An example method that includes receiving, by a computing device, a geometry of the component that includes a plurality of locations on a surface of the component; determining, by the computing device, a respective target thickness of the coating for each respective location of the plurality of locations based on a target coated component geometry and the geometry of the component; and determining, by the computing device, a number of passes or velocity of a coating device for each respective position of a plurality of positions to achieve the respective target thickness for each respective location.

Abstract: An example method that includes receiving a geometry of a component that includes a plurality of locations on a surface of the component; determining a first target trajectory including a first plurality of target trajectory points and a second target trajectory including a second plurality of target trajectory points, the first and second trajectories offset in a first direction, and the first and second plurality of trajectory points offset in a second direction; determining a respective target coating thickness of the coating based on a target coated component geometry and the geometry; and determining a respective motion vector of a coating device based on the first and second target trajectories to deposit the respective target coating thickness.

Abstract: An example method that includes receiving a first geometry of a component in an uncoated state and a second geometry of the component in a coated state; determining a first difference between the second geometry and a first simulated geometry based on the first geometry and a first spray law comprising a plurality of first spray law parameters; iteratively adjusting at least one first spray law parameter to determine a respective subsequent spray law; iteratively determining a respective subsequent difference between the second geometry and a subsequent simulated geometry based on the first geometry and the subsequent respective spray law; selecting a subsequent spray law from the respective subsequent spray laws based on the respective subsequent differences; and controlling a coating process based on the selected subsequent spray law.

Abstract: An example method that includes receiving a geometry of an uncoated component and a measured coating thickness of a coated test; determining a simulated coating thickness based on the geometry and a first spray law including a plurality of first spray law parameters; determining a difference between the simulated coating thicknesses and the measured coating thickness; iteratively adjusting at least one first spray law parameter to determine a respective subsequent spray law and determining a respective subsequent difference between the measured coating thickness and a subsequent simulated coating thickness based on the geometry and the respective subsequent spray law; selecting a subsequent spray law from the plurality of respective subsequent spray laws based on the respective subsequent differences; and controlling a coating process based on the selected subsequent spray law to compensate for the difference.

Abstract: An example system includes at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by a thermal spray system performing a process associated with a plurality of process attributes. The example system includes a computing device including an acoustic data signal module and a control module. The acoustic data signal processing module may transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum. The control module may determine a process attribute of the plurality of process attributes that deviates from a predetermined operating range by identifying at least one characteristic of the frequency-domain spectrum, selecting at least one component of the thermal spray system based on the process attribute, and controlling the thermal spray system to adjust the process attribute toward the predetermined operating range by sending a control signal to the at least one component.

Abstract: An example system includes at least one acoustic sensor and one optical sensor to monitor a thermal spray system controlled by a plurality of control parameters and performing a process associated with a plurality of process outputs. The system includes a computing device including a machine learning module and a control module. The machine learning module is configured to determine, based on at least the plurality of control parameters, an at least one time-dependent acoustic data signal, an at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning. The control module is configured to control the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges.

Abstract: An example method that includes receiving, by a computing device, a geometry of the component that includes a plurality of locations on a surface of the component; determining, by the computing device, a respective target thickness of the coating for each respective location of the plurality of locations based on a target coated component geometry and the geometry of the component; and determining, by the computing device, a number of passes or velocity of a coating device for each respective position of a plurality of positions to achieve the respective target thickness for each respective location.

Abstract: An example method that includes receiving a geometry of a component that includes a plurality of locations on a surface of the component; determining a first target trajectory including a first plurality of target trajectory points and a second target trajectory including a second plurality of target trajectory points, the first and second trajectories offset in a first direction, and the first and second plurality of trajectory points offset in a second direction; determining a respective target coating thickness of the coating based on a target coated component geometry and the geometry; and determining a respective motion vector of a coating device based on the first and second target trajectories to deposit the respective target coating thickness.

Abstract: An example method that includes receiving a first geometry of a component in an uncoated state and a second geometry of the component in a coated state; determining a first difference between the second geometry and a first simulated geometry based on the first geometry and a first spray law comprising a plurality of first spray law parameters; iteratively adjusting at least one first spray law parameter to determine a respective subsequent spray law; iteratively determining a respective subsequent difference between the second geometry and a subsequent simulated geometry based on the first geometry and the subsequent respective spray law; selecting a subsequent spray law from the respective subsequent spray laws based on the respective subsequent differences; and controlling a coating process based on the selected subsequent spray law.