Invention Grant
- Patent Title: Machine learning with fast feature generation for selective laser melting print parameter optimization
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Application No.: US16855186Application Date: 2020-04-22
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Publication No.: US11487271B2Publication Date: 2022-11-01
- Inventor: Jing Bi , Victor George Oancea
- Applicant: Dassault Systemes Simulia Corp
- Applicant Address: US MA Waltham
- Assignee: Dassault Systemes Simulia Corp
- Current Assignee: Dassault Systemes Simulia Corp
- Current Assignee Address: US MA Waltham
- Agency: Sheehan Phinney Bass & Green PA
- Main IPC: G05B19/4099
- IPC: G05B19/4099 ; G06N20/00 ; G06F30/10 ; B33Y50/02 ; B29C64/153 ; B29C64/393 ; G06F30/27 ; G06F119/18 ; G06F111/18 ; G06F113/10

Abstract:
A method includes identifying machine process parameters for an additive manufacturing process to produce a part, providing a real-world sensor to sense a characteristic associated with a real-world version of the additive manufacturing process, receiving sensor readings from the real-world sensor while the machine is performing the real-world version of the additive manufacturing process, generating, with a computer-based processor, physics-based features associated with the additive manufacturing process, and training a machine-learning software model based at least in part on the machine process parameters, the sensor readings, and the physics-based features to predict a behavior of the real-world sensor.
Public/Granted literature
- US20200341452A1 MACHINE LEARNING WITH FAST FEATURE GENERATION FOR SELECTIVE LASER MELTING PRINT PARAMETER OPTIMIZATION Public/Granted day:2020-10-29
Information query
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