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23 条记录 (耗时 0.017 秒)

    SYSTEMS AND METHODS FOR VIRTUAL ENVIRONMENT FOR REINFORCEMENT LEARNING IN MANUFACTURING
    3.
    发明申请
    SYSTEMS AND METHODS FOR VIRTUAL ENVIRONMENT FOR REINFORCEMENT LEARNING IN MANUFACTURING 有权

    公开(公告)号：US20210132580A1

    公开(公告)日：2021-05-06

    申请号：US17092118

    申请日：2020-11-06

    申请人： D.P. TECHNOLOGY CORP. ,  L'INSTITUT POLYTECHNIQUE DE GRENOBLE

    发明人： Frederic Vignat ,  Rafael Magalhaes ,  Luc Manzetti

    IPC分类号： G05B19/4065 ,  G06N20/00 ,  G05B19/402

    摘要： Systems, devices, and methods including: receiving, by an interpreter component having a processor with addressable memory, a first state of a tool of a computer numerical control (CNC) machine; determining, by the interpreter component, a reward and a value of the reward based on the received first state, where the reward is at least one of: positive and negative; transmitting, by the interpreter component, a set of information comprising the determined reward and the value of the reward to an agent component; performing, by the agent component, at least one action to generate a tool path and to proceed to a second state, where the second state is combined with the first state; and determining, by the agent component, the generated tool path based on the determined reward and value associated with the at least one action.

    INTELLIGENT PREDICTIVE ENGINE FOR MANAGEMENT AND OPTIMIZATION OF MACHINING PROCESSES FOR A COMPUTER NUMERICAL CONTROL (CNC) MACHINE TOOL
    4.
    发明申请
    INTELLIGENT PREDICTIVE ENGINE FOR MANAGEMENT AND OPTIMIZATION OF MACHINING PROCESSES FOR A COMPUTER NUMERICAL CONTROL (CNC) MACHINE TOOL 有权

    公开(公告)号：US20210026327A1

    公开(公告)日：2021-01-28

    申请号：US16939035

    申请日：2020-07-26

    申请人： D.P. TECHNOLOGY CORP.

    发明人： Olivier Thenoz

    IPC分类号： G05B19/414 ,  G05B19/4097 ,  G05B19/18 ,  G06N20/00 ,  G06F9/54

    摘要： Systems, devices, and methods for managing and optimizing a machining process for a computer numerical control (CNC) machine tool with a virtual machine-aware kernel. The virtual machine-aware kernel may predict steps for the manufacturing of a virtual machine part by constructing a virtual model of a CNC machine to mimic the CNC machine. The virtual machine-aware kernel may receive as input virtual data to simulate the real life conditions of the CNC machine milling processes for manufacturing of a machine part. The virtual machine-aware kernel may check, improve, and optimize the program data using the digital representation as a predictive model. Therefore, the virtual machine-aware kernel may allow for intelligent, real-time decision making to avoid defective manufacturing of a machine part.

    Systems and methods for automated prediction of machining workflow in computer aided manufacturing
    8.
    发明授权
    Systems and methods for automated prediction of machining workflow in computer aided manufacturing 有权

    公开(公告)号：US11693394B2

    公开(公告)日：2023-07-04

    申请号：US17191386

    申请日：2021-03-03

    申请人： D.P. TECHNOLOGY CORP.

    发明人： Tania Campanelli ,  Daniele Spitaletta ,  Luigi Galavotti

    IPC分类号： G05B19/418

    CPC分类号： G05B19/4188 ,  G05B19/4183 ,  G05B19/41815 ,  G05B19/41865

    摘要： Systems, devices, and methods including selecting one or more sequences of machining types for a feature of one or more features, where the selection of the one or more sequences of machining types is based on the feature and a database of prior selections of machining types; selecting one or more tools for the selected one or more sequences of machining types, where the selection of the one or more tools is based on the feature, the selected one or more sequences of machining types, and a database of prior selections of one or more tools; and selecting one or more machining parameters for the selected one or more tools, where the selected machining parameters are based on the feature, the selected one or more sequences of machining types, the selected one or more tools, and a database of prior selections of one or more machining parameters.

    Systems and methods for virtual environment for reinforcement learning in manufacturing
    9.
    发明授权
    Systems and methods for virtual environment for reinforcement learning in manufacturing 有权

    公开(公告)号：US11609546B2

    公开(公告)日：2023-03-21

    申请号：US17092118

    申请日：2020-11-06

    申请人： D.P. TECHNOLOGY CORP. ,  L'INSTITUT POLYTECHNIQUE DE GRENOBLE

    发明人： Frederic Vignat ,  Rafael Magalhaes ,  Luc Manzetti

    IPC分类号： G05B19/406 ,  G05B19/4065 ,  G06N20/00 ,  G05B19/402

    摘要： Systems, devices, and methods including: receiving, by an interpreter component having a processor with addressable memory, a first state of a tool of a computer numerical control (CNC) machine; determining, by the interpreter component, a reward and a value of the reward based on the received first state, where the reward is at least one of: positive and negative; transmitting, by the interpreter component, a set of information comprising the determined reward and the value of the reward to an agent component; performing, by the agent component, at least one action to generate a tool path and to proceed to a second state, where the second state is combined with the first state; and determining, by the agent component, the generated tool path based on the determined reward and value associated with the at least one action.

    Methods, devices, and systems for part-to-build
    10.
    发明授权
    Methods, devices, and systems for part-to-build 有权

    公开(公告)号：US11017596B2

    公开(公告)日：2021-05-25

    申请号：US16806829

    申请日：2020-03-02

    申请人： D.P. TECHNOLOGY CORP.

    发明人： Nicolas Béraud

    IPC分类号： G06T17/20 ,  G06T19/20 ,  G06T7/70 ,  G06T17/05 ,  B33Y50/00 ,  G06F30/17 ,  G06F30/20

    摘要： Methods, devices, and systems for determining a job file for a three-dimensional printing machine based on part-to-build data. Embodiments include determining the part-to-build data based on: determining part data from a received computer-aided design (CAD) file, generating orientation data, generating support data, generating feature data, and generating slicing data. In some embodiments, determining the job file may be further based on generating nesting matrix associated with the part-to-build data.