General Electric Company

Adam Joseph McCann

Brandon Stephen Good

Li Zhang

Jacob Berlier

Lynn Ann DeRose

Joseph James Salvo

John William Carbone

William Leonard

Nichole Lea Wood

Bouchra Bouqata

Daniel John Messier

Alisher Maksumov

Hasan Imamus Saleheen

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.

Systems and methods for receiving sensor data for an operating additive manufacturing machine and adaptively compressing the sensor data based on process data which controls the operation of the machine

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.

Identifying and distributing optimal machine parameters within a fleet of additive manufacturing machines

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.

Systems and methods for receiving sensor data for an operating additive manufacturing machine and mapping the sensor data with process data which controls the operation of the machine

The present disclosure relates to cell processing techniques. By way of example, a cell processing system may include a plurality of tracking devices coupled to a respective plurality of sample processing containers and storing sample identification information for a patient sample for use with sample processing devices configured to process the patient sample according to workflow steps of a processing protocol. A plurality of readers are configured to receive signals from the plurality of tracking devices. A controller may be coupled to the plurality of readers and configured to determine if the patient sample is processed according to the processing protocol based at least in part on the signals from the plurality of tracking devices.

Cell processing techniques

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.

Systems and methods for receiving sensor data for an operating manufacturing machine and producing an alert during manufacture of a part

Example embodiments of a method, apparatus, and computer readable medium for a gateway with common data format are generally described herein. The gateway may include memory to store data in a common data format to be operated on by applications, and network interfaces configured to interface an application to a remote device via a network. The gateway may further include protocol adapters configured to communicate with the remote device using a communication protocol of the remote device, and data adapters configured to convert data between a format of the remote device and the common data format. The gateway may further include a protocol selector module configured to select a protocol adapter where a selected protocol adapter communicates with a remote device, and a data adapter selector module configured to select a data adapter where a selected data adapter adapts data between the remote device and the common format.

Intelligent gateway with a common data format

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.

System and method for identifying a character-of-interest

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.

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Schenectady, NY, United States of America

Adam Joseph McCann