US 12,472,693 B2
Additive manufacturing-coupled digital twin ecosystem
Stephen Jonathan Davis, Eastleigh (GB); and Jonathan Mark Dunsdon, Murphys, CA (US)
Assigned to General Electric Company, Schenectady, NY (US)
Filed by General Electric Company, Schenectady, NY (US)
Filed on Jun. 15, 2020, as Appl. No. 16/901,147.
Claims priority of provisional application 62/862,011, filed on Jun. 14, 2019.
Claims priority of provisional application 62/862,016, filed on Jun. 14, 2019.
Prior Publication US 2020/0391446 A1, Dec. 17, 2020
Int. Cl. B29C 64/393 (2017.01); B29C 64/171 (2017.01); B29C 64/188 (2017.01); B33Y 10/00 (2015.01); B33Y 30/00 (2015.01); B33Y 40/10 (2020.01); B33Y 40/20 (2020.01); B33Y 50/02 (2015.01); G05B 17/02 (2006.01)
CPC B29C 64/393 (2017.08) [B29C 64/171 (2017.08); B29C 64/188 (2017.08); G05B 17/02 (2013.01); B33Y 10/00 (2014.12); B33Y 30/00 (2014.12); B33Y 40/10 (2020.01); B33Y 40/20 (2020.01); B33Y 50/02 (2014.12)] 19 Claims
OG exemplary drawing
 
1. A system for making or repairing a specified part, the system including:
a processor; and
a memory including instructions that, when executed by the processor, cause the processor to perform operations comprising:
receiving, from a machine communicatively coupled with the processor, a set of data including at least one of sensor data or inspection data, the set of data associated with at least one of an additive manufacturing process, a reductive manufacturing process, a repair process, a pre-treatment step, or a post-treatment step, wherein the set of data is for manufactured parts similar to the specified part;
creating an optimized manufacturing process to make or repair the specified part, the creating including:
generating, in real time, a surrogate model corresponding with a physics-based model of the specified part as-manufactured, wherein the surrogate model forms a digital twin of the specified part, wherein the digital twin includes: a first model-including a relationship between the set of data and the physics-based model; and a second model of a spectrum of operating environments and as-operated data acquired from actual performance of the manufactured parts over a lifetime of the manufactured parts as operated while deployed in the field, the as-operated data acquired from actual performance of the manufactured parts similar to the specified part as operated while deployed in the field across the spectrum of operating environments, the operating environments including operational conditions that the manufactured parts similar to the specified part are exposed to in operation in the field; and
determining a process parameter for the optimized manufacturing process based on the surrogate model and a target performance for the specified part as operated in the field; and
executing, based on the digital twin, the optimized manufacturing process to either repair or make the specified part, the optimized manufacturing process implementing the process parameter.