Control room operators are the backbone of industries like nuclear, oil and gas, petrochemicals, and process industries. They manage intricate systems, oversee critical processes, and react quickly to unforeseen incidents to ensure safety, efficiency, and continuity in operations. But with Artificial Intelligence (AI) and machine learning breaking new ground, one question stands at the forefront of industry discussions: Can AI replace these operators?

Operators in today’s modern control rooms face serious challenges to understand what’s going on inside their plants as the number of alarms increase. Configuring an alarm has never been easier.

The history of Artificial Intelligence goes all the way back to the classical antiquity where the idea of intelligent robots (such as Talos) and artificial beings, such as Galatea and Pandora, were a part of Greek Mythology (McCorduck, P., 2004). Talos was a giant automatic machine circling the shores and protecting Europe from pirates and invaders.

Most production losses and safety-related issues begin as minor incidents that escalate into larger problems. The question is, how can we leverage data to prevent these small incidents from becoming major disturbances? The ideal goal is to operate as close as possible to theoretical efficiency limits while maintaining effective incident management.

Tackling Plant Performance Challenges

Downtime in production facilities is costly. Whether due to technical faults, operational challenges, or organizational issues, the consequences often include lost productivity and increased risks. Fortunately, digitalization offers powerful tools to minimize these disruptions. By leveraging data-driven insights and advanced technology, control room operators can enhance their situational awareness and make faster, more effective decisions. But with digitalization comes the challenge of ensuring it truly adds value without creating complications.