首页> 外文期刊>Procedia CIRP >Lean Data in Manufacturing Systems: Using Artificial Intelligence for Decentralized Data Reduction and Information Extraction
【24h】

Lean Data in Manufacturing Systems: Using Artificial Intelligence for Decentralized Data Reduction and Information Extraction

机译:制造系统中的精益数据:使用人工智能进行分散数据约简和信息提取

获取原文
           

摘要

In the course of digitization, a drastically increased amount of acquired data in production systems can be observed. Nevertheless, only a minor part of the acquired data is practically used for near real-time analysis and optimization within production systems. This paper introduces a concept for the realization of a decentralized data analysis integration. Therefore, an analysis system using artificial neural networks is conducted at the measurement point in the main supply of a production plant, to classify different operating states. The classification accuracy in all evaluation models is at least 99.82% and proves that it is capable to recognize the operating states of a production machinery reliably. The significantly, without loss of information, reduced amount of data is handed over to a superordinate instance of the production system for further use of data.
机译:在数字化过程中,可以观察到生产系统中获取的数据量急剧增加。尽管如此,实际上只有很小一部分采集的数据用于生产系统内的近实时分析和优化。本文介绍了实现分散数据分析集成的概念。因此,在生产工厂的主电源的测量点处使用了人工神经网络的分析系统,以对不同的运行状态进行分类。所有评估模型中的分类准确性至少为99.82%,并证明它能够可靠地识别生产机械的运行状态。在不损失信息的情况下,将数量减少的大量数据移交给生产系统的上级实例,以进一步使用数据。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号