Abstract: Method, and corresponding system, for receiving and adaptively compressing sensor data for an operating manufacturing machine. The method includes determining the sensor data values at the working tool positions based on a time correlation of the values of the sensor data relative to time and the working tool positions relative to time. Tool control magnitude values relative to the working tool positions are determined based on the process data. The method further includes determining a magnitude differential, relative to the working tool positions, between the sensor data values and the tool control magnitude values. Scoring data is determined by applying a scoring function to the magnitude differential. The magnitude differential data is compressed based at least in part on the scoring data. The method further includes decompressing the magnitude differential data and determining the sensor data values versus the working tool positions based on the magnitude differential data.

Abstract: Method, and corresponding system, for receiving and adaptively compressing sensor data for an operating manufacturing machine. The method includes determining the sensor data values at the working tool positions based on a time correlation of the values of the sensor data relative to time and the working tool positions relative to time. Tool control magnitude values relative to the working tool positions are determined based on the process data. The method further includes determining a magnitude differential, relative to the working tool positions, between the sensor data values and the tool control magnitude values. Scoring data is determined by applying a scoring function to the magnitude differential. The magnitude differential data is compressed based at least in part on the scoring data. The method further includes decompressing the magnitude differential data and determining the sensor data values versus the working tool positions based on the magnitude differential data.

Abstract: Method, and corresponding system, for iteratively distributing improved process parameters to a fleet of additive manufacturing machines. The method includes receiving sensor data from a sensor for a first machine of the fleet of machines. The method further includes comparing the sensor data values at the working tool positions of the plurality of layers to reference data values at the working tool positions for the plurality of layers to determine a set of comparison measures for the first machine. The method further includes selecting a machine from among the first machine and at least a second machine of the fleet of machines based at least in part on the comparison measures of each of the machines. The method further includes receiving, from the selected machine, process parameters of the selected machine; and transmitting at least part of the process parameters of the selected machine to other machines of the fleet.

Abstract: Method, and corresponding system, for receiving and adaptively compressing sensor data for an operating manufacturing machine. The method includes determining the sensor data values at the working tool positions based on a time correlation of the values of the sensor data relative to time and the working tool positions relative to time. Tool control magnitude values relative to the working tool positions are determined based on the process data. The method further includes determining a magnitude differential, relative to the working tool positions, between the sensor data values and the tool control magnitude values. Scoring data is determined by applying a scoring function to the magnitude differential. The magnitude differential data is compressed based at least in part on the scoring data. The method further includes decompressing the magnitude differential data and determining the sensor data values versus the working tool positions based on the magnitude differential data.

Abstract: Method, and corresponding system, for receiving and processing sensor data for an additive manufacturing machine. The method includes determining values of the sensor data relative to time; and determining tool positions relative to time based on process data which controls operation of the additive manufacturing machine. The method further includes determining the sensor data values at the working tool positions based on a correlation of the values of the sensor data relative to time and the working tool positions relative to time. A representation of the sensor data values at the working tool positions is displayed by a user interface device.

Abstract: Method, and corresponding system, for producing an alert during manufacture of a part formed by a plurality of layers. The method includes determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time. During the manufacturing process, the sensor data values at the working tool positions of at least one of the plurality of layers are compared to reference data values at the working tool positions for the at least one layer to determine a comparison measure for the at least one layer. An alert is transmitted if the determined comparison measure of a layer is not within a defined range. A defined action is applied to the manufacturing process based on the transmitted alert.

Abstract: Method, and corresponding system, for iteratively distributing improved process parameters to a fleet of additive manufacturing machines. The method includes receiving sensor data from a sensor for a first machine of the fleet of machines. The method further includes comparing the sensor data values at the working tool positions of the plurality of layers to reference data values at the working tool positions for the plurality of layers to determine a set of comparison measures for the first machine. The method further includes selecting a machine from among the first machine and at least a second machine of the fleet of machines based at least in part on the comparison measures of each of the machines. The method further includes receiving, from the selected machine, process parameters of the selected machine; and transmitting at least part of the process parameters of the selected machine to other machines of the fleet.

Abstract: Method, and corresponding system, for producing an alert during manufacture of a part formed by a plurality of layers. The method includes determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time. During the manufacturing process, the sensor data values at the working tool positions of at least one of the plurality of layers are compared to reference data values at the working tool positions for the at least one layer to determine a comparison measure for the at least one layer. An alert is transmitted if the determined comparison measure of a layer is not within a defined range. A defined action is applied to the manufacturing process based on the transmitted alert.

Abstract: Method, and corresponding system, for receiving and adaptively compressing sensor data for an operating manufacturing machine. The method includes determining the sensor data values at the working tool positions based on a time correlation of the values of the sensor data relative to time and the working tool positions relative to time. Tool control magnitude values relative to the working tool positions are determined based on the process data. The method further includes determining a magnitude differential, relative to the working tool positions, between the sensor data values and the tool control magnitude values. Scoring data is determined by applying a scoring function to the magnitude differential. The magnitude differential data is compressed based at least in part on the scoring data. The method further includes decompressing the magnitude differential data and determining the sensor data values versus the working tool positions based on the magnitude differential data.

Abstract: Method, and corresponding system, for receiving and processing sensor data for an additive manufacturing machine. The method includes determining values of the sensor data relative to time; and determining tool positions relative to time based on process data which controls operation of the additive manufacturing machine. The method further includes determining the sensor data values at the working tool positions based on a correlation of the values of the sensor data relative to time and the working tool positions relative to time. A representation of the sensor data values at the working tool positions is displayed by a user interface device.

Abstract: Method, and corresponding system, for producing an alert during manufacture of a part formed by a plurality of layers. The method includes determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time. During the manufacturing process, the sensor data values at the working tool positions of at least one of the plurality of layers are compared to reference data values at the working tool positions for the at least one layer to determine a comparison measure for the at least one layer. An alert is transmitted if the determined comparison measure of a layer is not within a defined range. A defined action is applied to the manufacturing process based on the transmitted alert.

Abstract: A method of generating an output vector to identify a character-of-interest using a sparse distributed memory (SDM) module. The method includes obtaining a feature vector having a vector address. The feature vector is based on a character-of-interest in an acquired image. The method also includes identifying activated locations from hard locations by determining relative distances between the vector address and the stored vector location addresses. Stored content counters of the activated locations include first and second stored sub-sets of counters. The method also includes combining the counters of the first stored sub-sets of the activated locations using a first summation thread to provide a first combined sub-set of values. The method also includes combining the counters of the second stored sub-sets of the activated locations using a second summation thread to provide a second combined sub-set of values. The first and second summation threads are run in parallel.

Abstract: A system and method for identifying characters using a processor and a sparse distributed memory (SDM) module. The system and method are configured to receive image data relating to an object having a surface with physical markings thereon. The physical markings include characters-of-interest. The system and method are also configured to analyze the image data to convert at least one of the characters-of-interest in the image data into a corresponding feature vector. The system and method are also configured to identify the characters-of-interest using the feature vector and the SDM module. A suggested identity for the characters-of-interest is provided.

Abstract: A system and method of processing an acquired image to identify characters-of-interest in the acquired image. The method includes obtaining image data of a surface of an object. The image data includes a plurality of image pixels having corresponding light intensity signals. The light intensity signals are based on whether the corresponding image pixel correlates to a morphological change in the surface of the object. The method also includes determining a line section of the image data. The line section includes one of the character lines and has character image portions. The method also includes analyzing the light intensity signals of the image pixels in the character image portions to determine a common height of the characters-of-interest. The method also includes removing extraneous areas of the character image portions based on the common height of the characters-of-interest to provide trimmed image portions.

Abstract: A system and method for identifying characters-of-interest from markings on a surface of an object. The system includes a vector-generating module configured to receive and analyze an image of the markings to provide a feature vector having a vector address. The system also includes a sparse distributed memory (SDM) module. The SDM module includes hard locations having stored vector location addresses within an address space and stored content counters. The location addresses form multiple concentrated groups within the address space. The concentrated groups are associated with different characters of an identification system. The system also includes an identification module that is configured to identify the character(s)-of-interest using the SDM module.

Abstract: A method of generating an output vector to identify a character-of-interest using a sparse distributed memory (SDM) module. The method includes obtaining a feature vector having a vector address. The feature vector is based on a character-of-interest in an acquired image. The method also includes identifying activated locations from hard locations by determining relative distances between the vector address and the stored vector location addresses. Stored content counters of the activated locations include first and second stored sub-sets of counters. The method also includes combining the counters of the first stored sub-sets of the activated locations using a first summation thread to provide a first combined sub-set of values. The method also includes combining the counters of the second stored sub-sets of the activated locations using a second summation thread to provide a second combined sub-set of values. The first and second summation threads are run in parallel.

Abstract: A system and method for identifying characters using a processor and a sparse distributed memory (SDM) module. The system and method are configured to receive image data relating to an object having a surface with physical markings thereon. The physical markings include characters-of-interest. The system and method are also configured to analyze the image data to convert at least one of the characters-of-interest in the image data into a corresponding feature vector. The system and method are also configured to identify the characters-of-interest using the feature vector and the SDM module. A suggested identity for the characters-of-interest is provided.