Invention Grant
- Patent Title: Real-time adaptive control of additive manufacturing processes using machine learning
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Application No.: US16234325Application Date: 2018-12-27
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Publication No.: US10539952B2Publication Date: 2020-01-21
- Inventor: Edward Mehr , Tim Ellis , Jordan Noone
- Applicant: Relativity Space, Inc.
- Applicant Address: US CA Inglewood
- Assignee: Relativity Space, Inc.
- Current Assignee: Relativity Space, Inc.
- Current Assignee Address: US CA Inglewood
- Agency: Wilson Sonsini Goodrich & Rosati
- Main IPC: G05B19/4099
- IPC: G05B19/4099 ; G06N20/00 ; G06N3/04 ; G06N20/10 ; G06N3/08 ; G06N7/02 ; G06N5/00 ; G06N7/00

Abstract:
Methods for control of post-design free form deposition processes or joining processes are described that utilize machine learning algorithms to improve fabrication outcomes. The machine learning algorithms use real-time object property data from one or more sensors as input, and are trained using training data sets that comprise: i) past process simulation data, past process characterization data, past in-process physical inspection data, or past post-build physical inspection data, for a plurality of objects that comprise at least one object that is different from the object to be fabricated; and ii) training data generated through a repetitive process of randomly choosing values for each of one or more input process control parameters and scoring adjustments to process control parameters as leading to either undesirable or desirable outcomes, the outcomes based respectively on the presence or absence of defects detected in a fabricated object arising from the process control parameter adjustments.
Public/Granted literature
- US20190227525A1 REAL-TIME ADAPTIVE CONTROL OF ADDITIVE MANUFACTURING PROCESSES USING MACHINE LEARNING Public/Granted day:2019-07-25
Information query
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