In today's rapidly evolving industrial landscape, process plants are increasingly turning to artificial intelligence (AI) to streamline operations, improve efficiency, and unlock new opportunities. With advancements in technology and a wealth of historical data, these plants have the potential to leverage AI to gain valuable insights and enhance decision-making processes. In this blog, we will explore how AI is revolutionizing the operations of process plants and why they are uniquely positioned to benefit from its applications.

A typical process plant relies on sensors to collect thousands of process measurements, including flows, temperatures, pressures, and levels. These measurements provide vital information to the control logic for various controls within the plant. However, most industry players do not have robust programs to manage the accuracy and reliability of these critical process measurements. Maintenance requests are generally initiated only when plant operators observe issues with measurements, creating gaps in coverage.

To control a single process measurement, process plants employ basic single-variable control loops. These loops regulate a single input to achieve a desired set point, such as a specific flow value. While effective in isolating and controlling individual variables, these loops do not take into account the real-world interaction of other process variables. Additionally, when multiple single-variable control loops within the same system are not coordinated, they can negatively impact other process variables, leading to inefficiencies in operations.

To overcome the limitations of single-variable control loops, process plants employ advanced regulatory controls (ARCs). These controls integrate multiple single-variable controllers using logic strategies such as feed-forward, ratio, cascade, and auctioneering control. By accounting for real-world interactions, ARCs mitigate the negative impact on critical process variables. While ARCs can be implemented directly within the control system without additional tools, they can become increasingly susceptible to instrument failures as control schemes become more complicated.

Advanced process controls (APCs) represent the next level of control algorithms in process plants. APCs regulate multiple process variables using different control algorithms and work towards achieving specific objectives, such as higher efficiency, throughput, and quality. These controls balance interactions between basic process control loops within a process unit. While some APCs create process models and control multiple variables, others use a rules-based approach like fuzzy logic to imitate human operators' knowledge and actions. While APCs offer significant benefits, they require ongoing maintenance to adapt to changing process conditions.

One of the main challenges faced by process plants is the sheer size and complexity of their existing regulatory and APC systems. With thousands of process measurements and control loops, identifying areas for improvement that would have the most significant impact becomes a daunting task. This is where AI can play a crucial role in helping plant operators unlock additional potential.

Some APC vendors have started integrating elements of advanced analytics (AA) and AI to enhance the accuracy of their process models. While these efforts are commendable, the real potential lies in building AA and AI capabilities within the organization and applying them across the entire process plant. AI-based solutions excel in processing vast amounts of process data and identifying potent opportunities that may go unnoticed by humans.
By leveraging AI, process plants can discover patterns and insights that may not be easily visible to subject matter experts. These insights can be utilized to optimize traditional process control and operations, leading to improved performance and efficiency. AI can help owners and operators make data-driven decisions, enhancing their ability to streamline operations and identify new opportunities for growth.

AI is revolutionizing the way process plants operate, offering new avenues for growth, efficiency, and optimization. With a wealth of historical data and existing subject matter expertise, process plants are well positioned to leverage AI's capabilities and unlock new opportunities. By embracing AI's potential, these plants can enhance decision-making processes, improve operational efficiency, and stay ahead in an increasingly competitive industrial landscape.