Plant Operator Support using Industrial Artificial Intelligence

IF 0.4 Q4 AUTOMATION & CONTROL SYSTEMS
Arzam Kotriwala, Ruomu Tan, Pablo Rodriguez, Marcel Dix, Benedikt Schmidt, Anne Lene Rømuld
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引用次数: 0

Abstract

Despite the high degree of automation in industrial control systems, human operators in industrial plants play a critical role in ensuring uptime, production quality, and safety. Plant operators do so by not only monitoring the process but also intervening when the process runs into unusual or exception situations. In this paper, we present to ensure smooth plant operation by automatically identifying and investigating potential upcoming issues as well as providing recommendations to plant operators on how to address them with confidence. This is achieved by applying Artificial Intelligence (AI) techniques including deep learning, process mining, and graph search, on historical industrial process data such as alarm and event data, audit trails, engineering documents, and safety procedures. Our solution has been validated on data from the Draugen oil field operated by the Norwegian oil and gas company, OKEA.
使用工业人工智能的工厂操作员支持
尽管工业控制系统的自动化程度很高,但工业工厂中的人工操作员在确保正常运行时间、生产质量和安全方面发挥着关键作用。工厂操作员不仅通过监控过程,而且在过程遇到不寻常或异常情况时进行干预来做到这一点。在本文中,我们介绍了如何通过自动识别和调查潜在的潜在问题来确保工厂顺利运行,并就如何自信地解决这些问题向工厂操作员提供建议。这是通过对历史工业过程数据(如报警和事件数据、审计跟踪、工程文档和安全程序)应用人工智能(AI)技术(包括深度学习、过程挖掘和图形搜索)来实现的。我们的解决方案已经在挪威石油和天然气公司OKEA运营的Draugen油田的数据上得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ATP Magazine
ATP Magazine AUTOMATION & CONTROL SYSTEMS-
自引率
66.70%
发文量
41
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