智能工厂管控平台数据集
收藏国家基础学科公共科学数据中心2024-03-05 收录
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数据集包含构建智能工厂管控平台的数据集,包括平台研发的基础数据,平台测试的数据。集成大规模定制下的智能供应链集成关键技术以及大数据驱动的智能分析与决策优化技术,根据家电制造企业供应链特点,建立了基于复杂网络的供应链全流程数据集成模型,基于工业互联网等技术对现有MES、ERP、PLM、SCADA、iWMS五大系统进行集成互联,实现了应用系统与生产过程的无缝整合,集成研发了智慧企业网络协同制造集成平台原型。平台原型在胶州空调工厂进行了验证,平台的运行将传统工厂的订单人为排产到生产线体,颠覆为用户订单信息自动排产到线体,由订单信息驱动着生产线的生产组装,通过数据系统支撑,通过用户信息互联与可视,保障工厂高精度、高效率的实现大规模定制产品的生产。采集地点:青岛鹏海软件研发中心,采集时间:2023年4月20日,数据量12.0MB。
This dataset is developed for building a smart factory management and control platform, covering basic R&D data of the platform and test data for platform validation. It integrates key technologies of intelligent supply chain integration under mass customization scenarios, as well as big data-driven intelligent analysis and decision optimization technologies. Based on the supply chain characteristics of home appliance manufacturing enterprises, a full-process data integration model of the supply chain based on complex networks has been established. Leveraging industrial internet and related technologies, the five core systems including MES, ERP, PLM, SCADA and iWMS are integrated and interconnected, realizing seamless integration between application systems and production processes. A prototype of the intelligent enterprise network collaborative manufacturing integration platform has been developed and validated at the Jiaozhou Air Conditioner Factory. The platform revolutionizes the traditional manual order scheduling to production lines by automatically scheduling user orders to corresponding production lines, where production and assembly are driven by order information. Supported by data systems, along with user information interconnection and visibility, it enables the factory to achieve high-precision and high-efficiency mass customization production. The dataset was collected at the Qingdao Penghai Software R&D Center on April 20, 2023, with a total data volume of 12.0 MB.
提供机构:
青岛鹏海软件有限公司
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集是智能工厂管控平台的数据集,包含平台研发和测试的基础数据,集成了智能供应链集成和智能分析与决策优化技术,实现了工厂生产线的自动排产和高效生产。数据量为12.35MB,包含两个文件,格式为docx和sql。
以上内容由遇见数据集搜集并总结生成



