ADJUSTMENT METHOD FOR SHUT-OFF NOZZLE, SHUT-OFF NOZZLE, INJECTION DEVICE, AND INJECTION MOLDING MACHINE

    公开(公告)号:US20240351256A1

    公开(公告)日:2024-10-24

    申请号:US18634904

    申请日:2024-04-13

    发明人: Kiyotaka NAKAYAMA

    IPC分类号: B29C45/23 B29C45/74

    CPC分类号: B29C45/231 B29C45/74

    摘要: An adjustment method for a shut-off nozzle provided in an injection device, the shut-off nozzle including a nozzle portion having an injection flow path and a needle hole, a needle valve movably insertable into the needle hole, a cylinder component driving the needle valve, a bracket rotatably support the cylinder component at a rear end, and a fixing device fixing the bracket to a fixing member of the injection device, the adjustment method including: releasing the fixing device to allow the bracket to slide by a predetermined width relative to the fixing member, heating the injection device and the nozzle portion, driving the cylinder component to bring the needle valve to a most forward position and adjusting a slide position of the bracket, and fastening the fixing device to fix the bracket to the fixing member.

    Dataset Creation Method, Learning Model Generation Method, Non-Transitory Computer Readable Recording Medium, and Dataset Creation Device

    公开(公告)号:US20240326306A1

    公开(公告)日:2024-10-03

    申请号:US18291483

    申请日:2022-06-01

    IPC分类号: B29C45/76

    摘要: Physical quantity data indicating the state of a molded product produced by changing a first molding condition parameter set in a molding machine such that the quality of the molded product is degraded or the state of the molding machine is acquired, physical quantity data indicating the state of a molded product produced by changing a second molding condition parameter set in the molding machine or the state of the molding machine is acquired, the second molding condition parameter before change, the physical quantity data obtained at this time, the second molding condition parameter after change, and the physical quantity data obtained when setting the second molding condition parameter after change are stored in association with each other, and a dataset for machine learning is created by repeating the change of the first and second molding condition parameters and the acquisition of the physical quantity data.

    Reinforcement Learning Method, Non-Transitory Computer Readable Recording Medium, Reinforcement Learning Device and Molding Machine

    公开(公告)号:US20240227266A9

    公开(公告)日:2024-07-11

    申请号:US18279166

    申请日:2022-03-17

    发明人: Takayuki Hirano

    IPC分类号: B29C45/76

    CPC分类号: B29C45/76 B29C2945/76979

    摘要: A reinforcement learning method of a learning machine including a first agent adjusting a manufacture condition of a manufacturing device based on observation data obtained by observing a state of the manufacturing device and a second agent having a functional model or a functional approximator representing a relationship between the observation data and the manufacture condition in a different way from the first agent, comprises: adjusting the manufacture condition searched by the first agent that is performing reinforcement learning, using the observation data and the functional model or the functional approximator of the second agent; calculating reward data in accordance with a state of a product manufactured by the manufacturing device under the manufacture condition adjusted; and performing reinforcement learning on the first agent and the second agent based on the observation data and the reward data calculated.

    INDUSTRIAL MACHINE
    7.
    发明公开
    INDUSTRIAL MACHINE 审中-公开

    公开(公告)号:US20240198572A1

    公开(公告)日:2024-06-20

    申请号:US18519041

    申请日:2023-11-26

    发明人: Ryo OKAWACHI

    摘要: A higher-level substrate and lower-level substrates communicatively connected to the higher-level substrate are provided. The higher-level substrate is configured to obtain identification information from each of the lower-level substrates at first timing, to obtain identification information from each of the lower-level substrates at second timing following the first timing, and when the identification information obtained at the first timing is different from the identification information obtained at the second timing, notify a user of substrate replacement of that lower-level substrate for each lower-level substrate.

    Reinforcement Learning Method, Non-Transitory Computer Readable Recording Medium, Reinforcement Learning Device and Molding Machine

    公开(公告)号:US20240131765A1

    公开(公告)日:2024-04-25

    申请号:US18279166

    申请日:2022-03-16

    发明人: Takayuki Hirano

    IPC分类号: B29C45/76

    CPC分类号: B29C45/76 B29C2945/76979

    摘要: A reinforcement learning method of a learning machine including a first agent adjusting a manufacture condition of a manufacturing device based on observation data obtained by observing a state of the manufacturing device and a second agent having a functional model or a functional approximator representing a relationship between the observation data and the manufacture condition in a different way from the first agent, comprises: adjusting the manufacture condition searched by the first agent that is performing reinforcement learning, using the observation data and the functional model or the functional approximator of the second agent; calculating reward data in accordance with a state of a product manufactured by the manufacturing device under the manufacture condition adjusted; and performing reinforcement learning on the first agent and the second agent based on the observation data and the reward data calculated.