Digital-twin-enabled artificial intelligence system for distributed additive manufacturing

Patent metadata

Field	Value
Publication number	US-12585231-B2
Application number	US-202318180006-A
Country	US
Kind code	B2
Filing date	Mar 7, 2023
Priority date	Dec 18, 2020
Publication date	Mar 24, 2026
Grant date	Mar 24, 2026

Abstract

An information technology system for a distributed manufacturing network includes an additive manufacturing platform configured to manage workflows for a set of distributed manufacturing network entities associated with the distributed manufacturing network. The information technology system includes a set of digital twins generated by the additive manufacturing platform. The information technology system includes an artificial intelligence system configured to be executed by a data processing system in communication with the additive manufacturing platform. The artificial intelligence system is trained to generate process parameters for the workflows managed by the additive manufacturing platform using data collected from the set of distributed manufacturing network entities. The information technology system includes a control system configured to adjust the process parameters during an additive manufacturing process performed by at least one of the set of distributed manufacturing network entities.

First claim

The invention claimed is:

1 . An information technology system for a distributed manufacturing network, the information technology system comprising:
an additive manufacturing platform, implemented by at least one processor, configured to manage workflows for a set of distributed manufacturing network entities associated with the distributed manufacturing network,
wherein at least one distributed manufacturing network entity of the set of distributed manufacturing network entities is a mobile distributed manufacturing network entity that is deployed to a point of service,
wherein the mobile distributed manufacturing network entity is configured to manufacture at least one of: tools or parts to support at least one of: repairs or replacements performed at the point of service, and
wherein the additive manufacturing platform is configured to generate a set of digital twins;
an artificial intelligence system configured to be executed by a data processing system, implemented by the at least one processor, in communication with the additive manufacturing platform,
wherein the artificial intelligence system is configured to execute a set of simulations using the set of digital twins,
wherein the set of digital twins integrates with an instruction set according to which a product digitally represented by the set of digital twins was additively manufactured,
wherein the artificial intelligence system is trained to generate process parameters for the workflows managed by the additive manufacturing platform using data collected from the set of distributed manufacturing network entities and using the data collected from the set of simulations, and
wherein the artificial intelligence system is configured to execute the set of simulations and generate the process parameters while the mobile distributed manufacturing network entity is in transit to the point of service; and
a control system, implemented by the at least one processor, configured to adjust the process parameters during an additive manufacturing process performed by at least one distributed manufacturing network entity of the set of distributed manufacturing network entities.

2 . The information technology system of claim 1 wherein the set of distributed manufacturing network entities comprises:
a first additive manufacturing unit configured to perform a first additive manufacturing process; and
a second additive manufacturing unit configured to perform a second additive manufacturing process,
wherein the first additive manufacturing process is different than the second additive manufacturing process.

3 . The information technology system of claim 1 wherein the set of distributed manufacturing network entities includes at least one hybrid additive manufacturing unit.

4 . The information technology system of claim 1 wherein the additive manufacturing platform is cloud-based.

5 . The information technology system of claim 1 wherein the set of digital twins is used by the additive manufacturing platform to manufacture a physical replica of the product digitally represented in the set of digital twins.

6 . The information technology system of claim 1 wherein the artificial intelligence system includes an adaptive intelligence system in communication with a plurality of sensors and configured to receive current sensor data from the plurality of sensors for use in generating the set of digital twins.

7 . The information technology system of claim 1 wherein the artificial intelligence system is distributed across more than one distributed manufacturing network entity from the set of distributed manufacturing network entities.

8 . The information technology system of claim 1 wherein the artificial intelligence system works with the set of digital twins to simulate a performance of the product.

9 . The information technology system of claim 1 wherein the process parameters include at least one of: an extrusion temperature, a rate of material deposition, a tool path, a voltage setting of a heating apparatus, an exposure pattern, a layer height, a printing surface temperature, a layer height, a layer thickness, a build speed, a build material flow rate, a part orientation, an air gap, a shape and volume information for holes, spacing information, void information, lumen information, gap information, conduit information, a support structure setting, an ambient condition, a pressure, a raw material condition, a viscosity, a part condition, or a stress concentration.

10 . The information technology system of claim 1 wherein the instruction set includes at least one of: shape information, material layering information, functional information, or operational parameter information.

11 . The information technology system of claim 10 wherein the instruction set includes material layering information.

12 . The information technology system of claim 10 wherein the instruction set includes operational parameter information.

13 . The information technology system of claim 12 wherein the operational parameter information includes at least one of: extrusion temperature, rate of material deposition, tool path, exposure pattern, layer height, printing surface temperature, or layer thickness.

14 . The information technology system of claim 1 wherein the artificial intelligence system generates the instruction set.

15 . The information technology system of claim 14 wherein the instruction set is generated from a text description.

16 . The information technology system of claim 1 wherein the instruction set is determined based on the set of simulations of the set of digital twins.

17 . The information technology system of claim 1 wherein the instruction set is a proprietary instruction set, and use of the proprietary instruction set triggers a royalty payment to an owner of the proprietary instruction set.

18 . The information technology system of claim 1 further comprising a distributed ledger system, wherein the instruction set is tokenized, and the tokenized instruction set is stored on the distributed ledger system.

19 . The information technology system of claim 18 wherein the instruction set is tokenized as a 256-bit integer.

20 . The information technology system of claim 18 wherein the distributed ledger system provides provable access to the instruction set by at least one of: cryptographic proofs or zero-knowledge proof techniques.

21 . The information technology system of claim 1 further comprising a matching system that matches the instruction set with at least one distributed manufacturing entity of the set of distributed manufacturing network entities.

22 . The information technology system of claim 1 wherein the instruction set includes at least one of: product design, material for printing, quantity to be printed, price that a user is willing to pay for a print, or a timeline for completing printing.

23 . An information technology method for a distributed manufacturing network, the information technology method comprising:
managing workflows for a set of distributed manufacturing network entities associated with the distributed manufacturing network,
wherein at least one distributed manufacturing network entity of the set of distributed manufacturing network entities is a mobile distributed manufacturing network entity that is deployed to a point of service, and
wherein the mobile distributed manufacturing network entity is configured to manufactu

Assignees

• Strong Force Vcn Portfolio 2019 Llc

Inventors

• Cella Charles Howard
• Bliven Brent
• Sharma Kunal

Classifications

• G06Q2220/00

  Business processing using cryptography · CPC title

• G06Q10/087

  Inventory or stock management, e.g. order filling, procurement or balancing against orders · CPC title

• G06Q10/06316

  Sequencing of tasks or work · CPC title

• G06F9/5055

  considering software capabilities, i.e. software resources associated or available to the machine · CPC title

• G05B23/0281

  Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis · CPC title