一种基于大数据的生产工艺调控方法及系统

By combining big data and artificial intelligence technologies, a production process control system was built, which solved the problems of insufficient real-time monitoring and optimization in traditional methods. This enabled real-time optimization of product quality and intelligent management of the production process, thereby improving production efficiency and reducing costs.

CN120764771BActive Publication Date: 2026-07-17SUZHOU NANYUAN INTELLIGENT EQUIP TECH CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SUZHOU NANYUAN INTELLIGENT EQUIP TECH CO LTD
Filing Date
2025-07-02
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Traditional production process control methods rely on manual inspection, lacking real-time monitoring and big data analysis. This results in the inability to adjust product quality in a timely manner, difficulty in identifying key factors, production waste and inefficiency, and an inability to achieve intelligent manufacturing.

Method used

By leveraging big data analytics and artificial intelligence technologies, a production process control system based on sensor data is constructed. This system includes data cleaning, fusion, classification, model optimization, and closed-loop feedback. It monitors product quality in real time and automatically adjusts process parameters. Combined with historical data mining optimization strategies, it achieves refined production management.

Benefits of technology

It enables real-time monitoring and optimization of product quality, reduces production waste, improves production efficiency, lowers costs, and achieves intelligent production management, meeting the development needs of modern manufacturing.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明涉及智能制造领域,公开了一种基于大数据的生产工艺调控方法,包括:根据传感器组采集生产过程中的原始数据,对采集到的所述原始数据进行数据清洗,以得到清洗后的生产过程数据;根据所述清洗后的生产过程数据进行融合处理,以得到融合生产过程数据集;根据所述工况分类数据建立初始预测模型,以得到各工况对应的初始预测模型数据;本发明通过大数据分析对生产工艺进行调控,能够实时监控产品质量,通过预测与优化调整工艺参数,从而有效提高产品质量并减少质量偏差,通过数据清洗、融合、分类与模型优化等步骤使得生产过程中的关键因素得以精准识别和调整,从而减少不必要的生产浪费,提高生产效率。
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