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Eneos and PFN achieve breakthrough in autonomous plant operation

| By Mary Bailey

ENEOS Corp. (Tokyo, Japan) and Preferred Networks, Inc. (PFN) announced that they have succeeded in operating a butadiene extraction unit autonomously at ENEOS Kawasaki Refinery’s petrochemical plant for two consecutive days using a new artificial intelligence system.

Jointly developed by ENEOS and PFN, the AI system automates large-scale, complex operations of oil refineries and petrochemical plants that currently require experienced operators.

The companies expect the AI system will help them improve safety and stability of plant operations by reducing dependence on operators’ varying skill levels. ENEOS’s research has shown that the two-day trial is the first successful case in Japan of an AI-enabled autonomous operation at an actual petrochemical plant.

ENEOS and PFN’s joint effort to build an autonomous plant operation system started in 2019 with a strategic alliance formed in response to the growing concern around shortage of human resources due to the aging of skilled operators with manual operation experience. Currently, oil refineries and petrochemical plants are monitored and operated by such operators on a 24-hour basis.

The AI was designed to predict the plant’s unit future sensor values and valve operation requirements based on past data of complex correlations between several similar values generated via simulated data. The trial lasted two days, in which the system managed to monitor 25 important factors, including internal temperature, pressure, flowrate and product conditions, all while autonomously adjusting 12 different valves.

ENEOS and PFN will continue their trials with the butadiene extraction unit to achieve stable operations that are unaffected by operators’ skill levels, and subsequently extend its use to other major plant units including crude distillation units on the same site and other refineries. The companies also aim to implement a new AI-based autonomous plant operation model that can increase production and energy efficiencies.