Plant Operator Support using Industrial Artificial Intelligence

Autor/innen

  • Arzam Kotriwala ABB Corporate Research Center
  • Ruomu Tan ABB Corporate Research Center
  • Pablo Rodriguez ABB Corporate Research Center
  • Marcel Dix ABB Corporate Research Center
  • Benedikt Schmidt ABB Process Automation Germany
  • Anne Lene Rømuld OKEA

DOI:

https://doi.org/10.17560/atp.v65i10.2676

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.

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Veröffentlicht

03.11.2023

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Rubrik

Hauptbeitrag / Peer-Review