公开(公告)号：US11079739B2

公开(公告)日：2021-08-03

申请号：US16284409

申请日：2019-02-25

Applicant: General Electric Company

Inventor： Subhrajit Roychowdhury ,  Alexander Chen ,  Xiaohu Ping ,  John Erik Hershey

IPC: G05B19/4099 ,  B33Y50/00 ,  B29C64/386 ,  B29C64/153 ,  B22F10/20 ,  B22F10/30

Abstract: 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 structures with a material used in additive manufacturing. Numerous other aspects are provided.

公开(公告)号：US11472115B2

公开(公告)日：2022-10-18

申请号：US16360180

申请日：2019-03-21

Applicant: General Electric Company

Inventor： 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

IPC: G06F19/00 ,  B29C64/393 ,  B29C64/153 ,  B22F10/20 ,  B33Y10/00 ,  B33Y30/00 ,  B33Y40/00 ,  B33Y50/02 ,  B22F3/24 ,  B22F10/30

Abstract: 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.

公开(公告)号：US12017301B2

公开(公告)日：2024-06-25

申请号：US16818650

申请日：2020-03-13

Applicant: General Electric Company

Inventor： Naresh S. Iyer ,  Subhrajit Roychowdhury ,  Christopher D. Immer ,  Xiaohu Ping ,  Rogier S. Blom ,  Jing Yu

IPC: B23K26/342 ,  B23K26/03 ,  B23K26/06 ,  B23K26/073 ,  B23K26/082 ,  B23K31/00 ,  B33Y10/00 ,  B33Y30/00 ,  B33Y50/02

CPC classification number: B23K26/342 ,  B23K26/032 ,  B23K26/0626 ,  B23K26/073 ,  B23K26/082 ,  B23K31/003 ,  B23K31/006 ,  B33Y10/00 ,  B33Y30/00 ,  B33Y50/02

Abstract: 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.

公开(公告)号：US20230410412A1

公开(公告)日：2023-12-21

申请号：US17840401

申请日：2022-06-14

Applicant: General Electric Company

Inventor： Subhrajit Roychowdhury ,  Rogier Sebastiaan Blom ,  Steven J. Duclos ,  Anthony J. Vinciquerra ,  Xiaohu Ping ,  Voramon S. Dheeradhada

IPC: G06T15/08 ,  G05B19/4099 ,  B33Y50/00 ,  B29C64/386

CPC classification number: G06T15/08 ,  G05B19/4099 ,  G05B2219/35134 ,  B29C64/386 ,  G05B2219/49023 ,  B33Y50/00

Abstract: 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.

公开(公告)号：US20230046049A1

公开(公告)日：2023-02-16

申请号：US17398604

申请日：2021-08-10

Applicant: General Electric Company

Inventor： Saikat K. Ray Majumder ,  Naresh S. Iyer ,  Xiaohu Ping ,  Subhrajit Roychowdhury

IPC: B22F10/28 ,  B33Y50/02 ,  B33Y10/00 ,  G06T7/00 ,  G06N3/08

Abstract: 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.

公开(公告)号：US11580430B2

公开(公告)日：2023-02-14

申请号：US16257367

申请日：2019-01-25

Applicant: General Electric Company

Inventor： Lembit Salasoo ,  Vipul K. Gupta ,  Xiaohu Ping ,  Subhrajit Roychowdhury ,  Justin Gambone, Jr. ,  Naresh Iyer ,  Xiaolei Shi ,  Mengli Wang

IPC: G06N7/00 ,  G06N20/00 ,  G06F30/00 ,  B22F10/20 ,  B33Y10/00 ,  B33Y50/02 ,  G06F119/18 ,  B22F10/30

Abstract: 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.

公开(公告)号：US20240342831A1

公开(公告)日：2024-10-17

申请号：US18752404

申请日：2024-06-24

Applicant: General Electric Company

Inventor： Naresh S. Iyer ,  Subhrajit Roychowdhury ,  Christopher D. Immer ,  Xiaohu Ping ,  Rogier S. Blom ,  Jing Yu

IPC: B23K26/342 ,  B23K26/03 ,  B23K26/06 ,  B23K26/073 ,  B23K26/082 ,  B23K31/00 ,  B33Y10/00 ,  B33Y30/00 ,  B33Y50/02

CPC classification number: B23K26/342 ,  B23K26/032 ,  B23K26/0626 ,  B23K26/073 ,  B23K26/082 ,  B23K31/003 ,  B23K31/006 ,  B33Y10/00 ,  B33Y30/00 ,  B33Y50/02

Abstract: 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.

公开(公告)号：US12023860B2

公开(公告)日：2024-07-02

申请号：US17967391

申请日：2022-10-17

Applicant: General Electric Company

Inventor： 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

IPC: B29C64/153 ,  B22F10/20 ,  B22F10/31 ,  B22F10/85 ,  B29C64/393 ,  B33Y50/00 ,  B22F3/24 ,  B22F10/28 ,  B22F10/30 ,  B22F10/366 ,  B22F12/90 ,  B33Y10/00 ,  B33Y30/00 ,  B33Y40/00 ,  B33Y50/02

CPC classification number: B29C64/153 ,  B22F10/20 ,  B22F10/31 ,  B22F10/85 ,  B29C64/393 ,  B33Y50/00 ,  B22F2003/245 ,  B22F10/28 ,  B22F10/30 ,  B22F10/366 ,  B22F12/90 ,  B33Y10/00 ,  B33Y30/00 ,  B33Y40/00 ,  B33Y50/02

Abstract: 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.

公开(公告)号：US20230400833A1

公开(公告)日：2023-12-14

申请号：US17840386

申请日：2022-06-14

Applicant: General Electric Company

Inventor： Subhrajit Roychowdhury ,  Naresh S. Iyer ,  Sanghee Cho ,  Rogier Sebastiaan Blom ,  Brent Brunell ,  Xiaohu Ping ,  Sharath Aramanekoppa

IPC: G05B19/4099

CPC classification number: G05B19/4099 ,  G05B2219/49023

Abstract: 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.

公开(公告)号：US11609549B2

公开(公告)日：2023-03-21

申请号：US17360790

申请日：2021-06-28

Applicant: General Electric Company

Inventor： Subhrajit Roychowdhury ,  Alexander Chen ,  Xiaohu Ping ,  John Erik Hershey

IPC: G05B19/4099 ,  B33Y50/00 ,  B29C64/386 ,  B29C64/153 ,  B22F10/20 ,  B22F10/30

Abstract: 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 structures with a material used in additive manufacturing. Numerous other aspects are provided.