Successfully field-tested on data accessed from Norway’s OKEA oil platform, Draugen, ABB’s Augmented Operator meets the strenuous requirements of real-world industrial settings. In this way, ABB’s Augmented Operator will help operators to grapple with and resolve abnormal plant situations. These tools access and analyze existing data sources such as historical process, alarm and event data, audit trails, engineering documents, standards, and safety procedure. ABB developed comprehensive and easy-to-use decision-support tools using deep learning and transformer models, process mining, graph search and causal analysis methods. The Augmented Operator project was initiated in 2020, thanks to a long term association between the oil and gas company, OKEA, and ABB, with the aim of supporting plant operators to achieve operational excellence. Recognizing these possibilities, ABB has taken the initiative to develop analytical tools to get the most out of this data. centerīy combining data with deep learning models, profound and transformative opportunities are possible. ![]() 01 The Draugen oil platform, operated by OKEA in the Norwegian Sea. ![]() To ensure consistent and efficient operation, operators can now draw on the vast amount of available relevant industrial data. ![]() Ruomu Tan, Benedikt Schmidt, Benjamin Kloepper, Arzam Kotriwala, Pablo Rodriguez ABB Process Automation, Corporate Research Ladenburg, Germany, Divya Sheel, Chandrika KR ABB Process Automation, Corporate Research Bangalore, India, Anne Lene Rømuld OKEA Kristiansund, Norway Hadil Abukwaik Former ABB employeeĬontrol room operator actions have a significant and direct impact on uptime, product quality and production output as well as safety basically on all aspects of industrial plant performance →01.
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