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A Case of Applying AI to an Ethylene Plant

机译:将AI施加到乙烯植物的情况

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摘要

Unexpected equipment failures or maintenance may result in unscheduled plant shutdowns in continuously operating petrochemical plants such as ethylene plants. To avoid this, the operation status needs to be continuously monitored. However, since troubles in plants have various causes, it is difficult for human workers to precisely grasp the plant status and notice the signs of unexpected failures and need for maintenance. To solve this problem, we worked with a customer in an ethylene plant and developed a solution based on AI analysis. Using AI analysis based on customer feedback, we identified several factors from numerous sensor parameters and created an AI model that can grasp the plant status and detect any signs of abnormalities. This paper introduces a case study of AI analysis carried out in an ethylene plant and the new value that AI technology can offer to customers, and then describes how to extend the solution business with AI analysis.
机译:意外的设备故障或维护可能导致连续运行的石化植物如乙烯植物的未划分的工厂停工。 为避免这种情况,需要连续监控操作状态。 然而,由于植物中的麻烦具有各种原因,人工工人难以精确地掌握工厂状态并注意到意外故障的迹象并需要维护。 为了解决这个问题,我们与乙烯厂的顾客合作,并根据AI分析开发了一种解决方案。 使用基于客户反馈的AI分析,我们确定了来自许多传感器参数的几个因素,并创建了一种可以掌握工厂状态并检测到任何异常迹象的AI模型。 本文介绍了在乙烯工厂中进行的AI分析的案例研究,以及AI技术可以向客户提供的新价值,然后介绍如何通过AI分析扩展解决方案业务。

著录项

  • 来源
    《Yokogawa Technical Report》 |2020年第1期|共6页
  • 作者单位

    AI Business Development Department Information Technology Center IA Products and Service Business Headquarters;

    Information Technology Center IA Products and Service Business Headquarters;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 电机;
  • 关键词

  • 入库时间 2022-08-20 07:57:52

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