Emerson’s Jonas Berge authored the article, Automation and AI for Operational Excellence in Refining and Petrochemicals, for the upcoming October 29-30 Asian Downstream Summit.
Jonas opens the article by highlighting the importance of automation for manufacturers and producers.
Plant automation, which includes industrial AI, is key when building new plants. An advanced automation strategy for a high degree of automation, a plant autonomous to a greater degree, makes that project more viable thus accelerating the project final investment decision (FID) by giving credibility to meeting the plant operational excellence objectives set by government and investors around safety, sustainability, reliability, and production.
He shares how automation enables greater performance across many dimensions, including safety, sustainability, reliability, and production.
From a safety perspective, plant automation helps improve operator performance, removes personnel from hazardous locations, and enhances overall situational awareness. For example, plant operators:
…practice on a virtual plant, a digital twin of the plant, in the safety of a classroom where they can make mistakes without repercussions. Console operators practice tasks like startup and shutdown of a unit, feed or grade change, as well as response to process upsets or abnormal situations. This is enabled by a digital twin process model and operator training simulator (OTS) software. Similarly, field operators practice tasks like startup and shutdown of a unit, loading and unloading, batch charging and dispensing, and cleaning. This is made possible by life-like 3D plant model immersive simulator software, digital twin process model, and virtual reality (VR) goggles.
From a sustainability perspective, automation enables a shift towards net zero by reducing emissions, increasing energy efficiency, and minimizing losses. Some examples Jonas provides in improving energy efficiency include monitoring poor valve performance, detecting steam trap failures, tracking energy flows, and monitoring heat exchanger performance.
From a reliability perspective, an aspirational goal is zero downtime. Monitoring the integrity of the plant assets and enabling predictive maintenance practices are two ways to drive toward this goal. He shares how automation is crucial for predictive maintenance.
Automatically predict pump problems like bearing failures, cavitation, strainer plugging, mechanical seal failure, and motor winding insulation breakdown. This is made possible by non-intrusive wireless vibration sensor measuring hourly, and other sensors, used in conjunction with a causal AI pump condition monitoring app interpreting data. Similarly, monitor air-cooled heat exchanger fans and cooling tower gearboxes. Blowers, fans, and compressors are also monitored in similar fashion.
Production improvements include greater agility, leaner operations, increased quality, and greater throughput. Jonas shares examples of improving agility.
Automation makes plants like refineries more flexible in selecting feedstock and final product slate to quickly respond to customer demand and market opportunities. Automatically monitor piping and vessel corrosion rate and estimate remaining useful life (RUL) to optimize refinery crude blend such as incorporating high-TAN opportunity crudes. This is made possible by non-intrusive wireless ultrasonic thickness (UT) transmitter measuring wall thinning twice a day and causal AI corrosion monitoring app interpreting data.
Read the article for many more examples in each of these areas, as well as how AI assists the engineers managing the automation system. Visit the Boundless Automation section on Emerson.com for more on how AI and automation technologies enable greater operational performance.
