Patents by Inventor Luke S. HENDRIX

Luke S. HENDRIX has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230350380
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Application
    Filed: July 10, 2023
    Publication date: November 2, 2023
    Applicant: Xometry, Inc.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Patent number: 11698623
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Grant
    Filed: May 23, 2022
    Date of Patent: July 11, 2023
    Assignee: Xometry, Inc.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Publication number: 20220365509
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Application
    Filed: May 23, 2022
    Publication date: November 17, 2022
    Applicant: Xometry, Inc.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Patent number: 11347201
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Grant
    Filed: July 14, 2020
    Date of Patent: May 31, 2022
    Assignee: XOMETRY, INC.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Publication number: 20200348646
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Application
    Filed: July 14, 2020
    Publication date: November 5, 2020
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Patent number: 10712727
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Grant
    Filed: February 10, 2020
    Date of Patent: July 14, 2020
    Assignee: XOMETRY, INC.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Publication number: 20200183355
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Application
    Filed: February 10, 2020
    Publication date: June 11, 2020
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Patent number: 10558195
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Grant
    Filed: April 26, 2019
    Date of Patent: February 11, 2020
    Assignee: XOMETRY, INC.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Publication number: 20190271966
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Application
    Filed: April 26, 2019
    Publication date: September 5, 2019
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Patent number: 10281902
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Grant
    Filed: November 1, 2016
    Date of Patent: May 7, 2019
    Assignee: Xometry, Inc.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Patent number: 10274933
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Grant
    Filed: July 26, 2018
    Date of Patent: April 30, 2019
    Assignee: Xometry, Inc.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Publication number: 20180341246
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Application
    Filed: July 26, 2018
    Publication date: November 29, 2018
    Applicant: Xometry, Inc.
    Inventors: Valerie R. Coffman, Yuan Chen, Luke S. Hendrix, William J. Sankey, Joshua Ryan Smith, Daniel Wheeler
  • Publication number: 20180120813
    Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.
    Type: Application
    Filed: November 1, 2016
    Publication date: May 3, 2018
    Applicant: Xometry, Inc.
    Inventors: Valerie R. COFFMAN, Yuan CHEN, Luke S. HENDRIX, William J. SANKEY, Joshua Ryan SMITH, Daniel WHEELER