Information processing device, information processing method, information processing program, and kneading method

The information processing device uses data analysis and machine learning to stabilize natural rubber viscosity during kneading, addressing inconsistencies in existing methods by accurately controlling the process.

WO2026105579A1PCT designated stage Publication Date: 2026-05-21BRIDGESTONE CORP
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
BRIDGESTONE CORP
Filing Date
2025-10-29
Publication Date
2026-05-21

AI Technical Summary

Technical Problem

Existing methods for stabilizing the viscosity of natural rubber during kneading fail to account for various conditions beyond rotor power and material temperature, leading to inconsistent results in subsequent processing.

Method used

An information processing device that acquires and analyzes inspection, logistics, and mixer data to infer and control the kneading process using a machine learning model, ensuring the natural rubber reaches a desired viscosity without relying on experience.

Benefits of technology

Enables precise control of natural rubber viscosity, reducing the need for human intervention and maintaining accuracy in kneading processes.

✦ Generated by Eureka AI based on patent content.

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Abstract

An information processing device 10 comprises: an acquisition unit that acquires inspection data that is information related to the quality of natural rubber, logistics data that is information related to production, shipment, and arrival of the natural rubber, and mixer data that is information on a kneading step for kneading the natural rubber with a mixer; an inference unit that infers a condition value in the kneading step for the natural rubber by inputting, to a learning model trained by machine learning by associating at least one of the previously acquired inspection data, logistics data, and mixer data with the viscosity of the kneaded natural rubber, at least the one of the newly acquired inspection data, logistics data, and mixer data that is of the same type as that of the data used during the training; and a control unit that controls the mixer on the basis of the condition value inferred by the inference unit.
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