Journal of the Japanese Association for Petroleum Technology
Online ISSN : 1881-4131
Print ISSN : 0370-9868
ISSN-L : 0370-9868
Lecture
The cases and the future of plant data analysis with AI technology
Katsuhiro Ochiai Takuya Ono
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JOURNAL FREE ACCESS

2018 Volume 83 Issue 2 Pages 162-166

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Abstract

In the fields of oil refining, chemicals, natural resource development, power generation, gas and LNG, etc., “System Invariant Analysis Technology” detects signs of anomalies through the real-time analysis of plant operation data. SIAT is an AI technology designed by NEC to identify the cause-and-effect relationship of large amounts of sensor data. This supports plant owners in preventing occurrences of operation trouble.

JGC and NEC jointly analyzed operation data of a number of plants and found anomalous signs at locations separate from the functional failure of each equipment. These examples show that process engineering knowledge combined with advanced AI such as SIAT works quite effective for reduction of plant downtime.

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© 2018 Japanese Association for Petroleum Technology
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