Patents by Inventor Xiaohu PING
Xiaohu PING has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20230410412Abstract: Methods and apparatus for sensor-based part development are disclosed. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to translate at least one user-defined material property selection into a desired process observable, the desired process observable including a meltpool property, perform voxel-based autozoning of an input part geometry, the input part geometry based on a computer-generated design, and output a voxelized reference map for the input part geometry based on the desired process observable and the voxel-based autozoning.Type: ApplicationFiled: June 14, 2022Publication date: December 21, 2023Inventors: Subhrajit Roychowdhury, Rogier Sebastiaan Blom, Steven J. Duclos, Anthony J. Vinciquerra, Xiaohu Ping, Voramon S. Dheeradhada
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Publication number: 20230400833Abstract: Methods and apparatus for sensor-based part development are disclosed. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to identify a reference process observable of a computer-generated part, receive input from at least one sensor during three-dimensional printing to identify an estimated process observable using feature extraction, and adjust at least one three-dimensional printing process parameter to reduce an error identified from a mismatch between the estimated process observable and the reference process observable.Type: ApplicationFiled: June 14, 2022Publication date: December 14, 2023Inventors: Subhrajit Roychowdhury, Naresh S. Iyer, Sanghee Cho, Rogier Sebastiaan Blom, Brent Brunell, Xiaohu Ping, Sharath Aramanekoppa
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Patent number: 11609549Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures forming a plurality of parts, wherein the parts are manufactured with an additive manufacturing machine; determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure; generating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set; generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon; mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and generating a dictionary of optimized scan parameter sets to fabricate geometric strType: GrantFiled: June 28, 2021Date of Patent: March 21, 2023Assignee: General Electric CompanyInventors: Subhrajit Roychowdhury, Alexander Chen, Xiaohu Ping, John Erik Hershey
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Publication number: 20230046049Abstract: An additive manufacturing apparatus, a computing system, and a method for operating an additive manufacturing apparatus are provided. The method includes obtaining two or more images corresponding to respective build layers at a build plate, wherein each image comprises a plurality of data points comprising a feature and corresponding location at the build plate; removing variation between the features of the plurality of data points; and normalizing each feature to remove location dependence in the plurality of data points.Type: ApplicationFiled: August 10, 2021Publication date: February 16, 2023Inventors: Saikat K. Ray Majumder, Naresh S. Iyer, Xiaohu Ping, Subhrajit Roychowdhury
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Patent number: 11580430Abstract: Determining a quality score for a part manufactured by an additive manufacturing machine based on build parameters and sensor data without the need for extensive physical testing of the part. Sensor data is received from the additive manufacturing machine during manufacture of the part using a first set of build parameters. The first set of build parameters is received. A first algorithm is applied to the first set of build parameters and the received sensor data to generate a quality score. The first algorithm is trained by receiving a reference derived from physical measurements performed on at least one reference part built using a reference set of build parameters. The quality score is output via the communication interface of the device.Type: GrantFiled: January 25, 2019Date of Patent: February 14, 2023Assignee: General Electric CompanyInventors: Lembit Salasoo, Vipul K. Gupta, Xiaohu Ping, Subhrajit Roychowdhury, Justin Gambone, Jr., Naresh Iyer, Xiaolei Shi, Mengli Wang
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Publication number: 20230029806Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a parameter development module comprising a processor, a defined geometry for one or more parts, wherein the parts are manufactured with an additive manufacturing machine, and wherein a stack is formed from one or more parts; fabricating the one or more parts with the additive manufacturing machine based on a first parameter set; collecting in-situ monitoring data from one or more in-situ monitoring systems of the additive manufacturing machine for one or more parts; determining whether each stack should receive an additional part based on an analysis of the collected in-situ monitoring data; and fabricating each additional part based on the determination the stack should receive the additional part. Numerous other aspects are provided.Type: ApplicationFiled: October 17, 2022Publication date: February 2, 2023Inventors: Vipul Kumar GUPTA, Natarajan CHENNIMALAI KUMAR, Anthony Joseph VINCIQUERRA, Laura Cerully DIAL, Voramon Supatarawanich DHEERADHADA, Timothy HANLON, Lembit SALASOO, Xiaohu PING, Subhrajit ROYCHOWDHURY, Justin John GAMBONE
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Patent number: 11472115Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a parameter development module comprising a processor, a defined geometry for one or more parts, wherein the parts are manufactured with an additive manufacturing machine, and wherein a stack is formed from one or more parts; fabricating the one or more parts with the additive manufacturing machine based on a first parameter set; collecting in-situ monitoring data from one or more in-situ monitoring systems of the additive manufacturing machine for one or more parts; determining whether each stack should receive an additional part based on an analysis of the collected in-situ monitoring data; and fabricating each additional part based on the determination the stack should receive the additional part. Numerous other aspects are provided.Type: GrantFiled: March 21, 2019Date of Patent: October 18, 2022Assignee: General Electric CompanyInventors: Vipul Kumar Gupta, Natarajan Chennimalai Kumar, Anthony Joseph Vinciquerra, Laura Cerully Dial, Voramon Supatarawanich Dheeradhada, Timothy Hanlon, Lembit Salasoo, Xiaohu Ping, Subhrajit Roychowdhury, Justin John Gambone
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Publication number: 20210325849Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures forming a plurality of parts, wherein the parts are manufactured with an additive manufacturing machine; determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure; generating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set; generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon; mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and generating a dictionary of optimized scan parameter sets to fabricate geometric strType: ApplicationFiled: June 28, 2021Publication date: October 21, 2021Inventors: Subhrajit ROYCHOWDHURY, Alexander CHEN, Xiaohu PING, John Erik HERSHEY
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Publication number: 20210283717Abstract: An example additive manufacturing apparatus includes an energy source to melt material to form a component in an additive manufacturing process, a camera aligned with the energy source to obtain image data of the melted material during the additive manufacturing process, and a controller to control the energy source during the additive manufacturing process in response to processing of the image data. The controller adjusts control of the energy source based on a correction determined by: applying an artificial intelligence model to image data captured by a camera during an additive manufacturing process, the image data including an image of a melt pool of the additive manufacturing process; predicting an error in the additive manufacturing process using an output of the artificial intelligence model; and compensating for the error by generating a correction to adjust a configuration of the energy source during the additive manufacturing process.Type: ApplicationFiled: March 13, 2020Publication date: September 16, 2021Inventors: Naresh S. Iyer, Subhrajit Roychowdhury, Christopher D. Immer, Xiaohu Ping, Rogier S. Blom, Jing Yu
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Patent number: 11079739Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures forming a plurality of parts, wherein the parts are manufactured with an additive manufacturing machine; determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure; generating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set; generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon; mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and generating a dictionary of optimized scan parameter sets to fabricate geometric strType: GrantFiled: February 25, 2019Date of Patent: August 3, 2021Assignee: General Electric CompanyInventors: Subhrajit Roychowdhury, Alexander Chen, Xiaohu Ping, John Erik Hershey
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Patent number: 10884396Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a platform comprising a segmentation module and a processor, a defined geometry for one or more geometric structures forming one or more parts, wherein the parts are manufactured with an additive manufacturing machine; generating a build file including an initial parameter set to fabricate each part; fabricating the part based on the build file; receiving sensor data for the fabricated part; generating a parameter set for each layer that forms the part, via execution of an iterative learning control process for each layer; generating raw power data for each layer that forms the part, using the processor, based on the generated parameter set; applying a noise reduction process to the raw power data; and generating a segmented build file, using the segmentation module, via application of the noise reduction process on the raw power data. Numerous other aspects are provided.Type: GrantFiled: February 27, 2019Date of Patent: January 5, 2021Assignee: GENERAL ELECTRIC COMPANYInventors: Subhrajit Roychowdhury, Vipul Kumar Gupta, Randal T Rausch, Justin John Gambone, Xiaohu Ping, Alexander Chen, John Erik Hershey
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Publication number: 20200298499Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a parameter development module comprising a processor, a defined geometry for one or more parts, wherein the parts are manufactured with an additive manufacturing machine, and wherein a stack is formed from one or more parts; fabricating the one or more parts with the additive manufacturing machine based on a first parameter set; collecting in-situ monitoring data from one or more in-situ monitoring systems of the additive manufacturing machine for one or more parts; determining whether each stack should receive an additional part based on an analysis of the collected in-situ monitoring data; and fabricating each additional part based on the determination the stack should receive the additional part. Numerous other aspects are provided.Type: ApplicationFiled: March 21, 2019Publication date: September 24, 2020Inventors: Vipul Kumar GUPTA, Natarajan CHENNIMALAI KUMAR, Anthony Joseph VINCIQUERRA, Laura Cerully DIAL, Voramon Supatarawanich DHEERADHADA, Timothy HANLON, Lembit SALASOO, Xiaohu PING, Subhrajit ROYCHOWDHURY, Justin John GAMBONE
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Publication number: 20200272128Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a platform comprising a segmentation module and a processor, a defined geometry for one or more geometric structures forming one or more parts, wherein the parts are manufactured with an additive manufacturing machine; generating a build file including an initial parameter set to fabricate each part; fabricating the part based on the build file; receiving sensor data for the fabricated part; generating a parameter set for each layer that forms the part, via execution of an iterative learning control process for each layer; generating raw power data for each layer that forms the part, using the processor, based on the generated parameter set; applying a noise reduction process to the raw power data; and generating a segmented build file, using the segmentation module, via application of the noise reduction process on the raw power data. Numerous other aspects are provided.Type: ApplicationFiled: February 27, 2019Publication date: August 27, 2020Inventors: Subhrajit ROYCHOWDHURY, Vipul Kumar GUPTA, Randal T RAUSCH, Justin John GAMBONE, Xiaohu PING, Alexander CHEN, John Erik HERSHEY
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Publication number: 20200272127Abstract: According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures forming a plurality of parts, wherein the parts are manufactured with an additive manufacturing machine; determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure; generating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set; generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon; mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and generating a dictionary of optimized scan parameter sets to fabricate geometric strType: ApplicationFiled: February 25, 2019Publication date: August 27, 2020Inventors: Subhrajit ROYCHOWDHURY, Alexander CHEN, Xiaohu PING, John Erik HERSHEY
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Publication number: 20200242496Abstract: Determining a quality score for a part manufactured by an additive manufacturing machine based on build parameters and sensor data without the need for extensive physical testing of the part. Sensor data is received from the additive manufacturing machine during manufacture of the part using a first set of build parameters. The first set of build parameters is received. A first algorithm is applied to the first set of build parameters and the received sensor data to generate a quality score. The first algorithm is trained by receiving a reference derived from physical measurements performed on at least one reference part built using a reference set of build parameters. The quality score is output via the communication interface of the device.Type: ApplicationFiled: January 25, 2019Publication date: July 30, 2020Inventors: Lembit SALASOO, Vipul K. GUPTA, Xiaohu PING, Subhrajit ROYCHOWDHURY, Justin GAMBONE, JR., Naresh IYER, Xiaolei SHI, Mengli WANG
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Publication number: 20200242495Abstract: Providing updated build parameters to an additive manufacturing machine to improve quality of a part manufactured by the machine. Sensor data is received from the additive manufacturing machine during manufacture of the part using a first set of build parameters. The first set of build parameters is received. An evaluation parameter is determined based on the first set of build parameters and the received sensor data. Thermal data is generated based on a thermal model of the part derived from the first set of build parameters. A first algorithm is applied to the received sensor data, the determined evaluation parameter, and the generated thermal data to produce a second set of build parameters, the first algorithm being trained to improve the evaluation parameter. The second set of build parameters is output to the additive manufacturing machine to produce a second part.Type: ApplicationFiled: January 25, 2019Publication date: July 30, 2020Inventors: Subhrajit ROYCHOWDHURY, Alexander CHEN, Xiaohu PING, Justin GAMBONE, JR., Thomas CITRINITI, Brian BARR