MACHINE-LEARNING METHOD, MACHINE-LEARNING DEVICE, MACHINE-LEARNING PROGRAM, COMMUNICATION METHOD, AND CONTROL DEVICE
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United States of America
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Issued Date -
Dec 12, 2024
app pub date -
Sep 30, 2022
filing date -
Sep 30, 2022
priority date (Note) -
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status (Latency Note)
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Abstract
A reward for a decision result of an isostatic pressurization processing condition is calculated based on a state variable including at least one physical quantity related to a workpiece and at least one isostatic pressurization processing condition, a function for deciding at least one isostatic pressurization processing condition from the state variable is updated based on the reward, and updating of the function is repeated to decide an isostatic pressurization processing condition that maximizes the reward. The isostatic pressurization processing condition is at least one of a first parameter related to the workpiece, a second parameter related to a pre-process of the isostatic pressurization processing, and a third parameter related to an operating condition of an isostatic pressurization device, and the at least one physical quantity is at least one of physical quantities related to densification and green compaction of the workpiece.
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