Control systems technology has come a long way over the last 70 years, said Sujit John, Lead System Consultant, Yokogawa Engineering Asia, at the opening of his presentation, Driving Towards Industrial Transformation & IT/OT Convergence, on Day 2 of ARC Industry Forum Asia 2021. The pneumatic-based systems of the 1950s gave way to electrical relay systems in the 1960s and then in the mid-1970s to distributed control systems (DCS), which started off as essentially closed Unix-based systems but evolved to much more open Windows-based platforms once that operating system became ubiquitous in the 1990s.
The needs and demands of customers in the process industries have also not stood still. as they face challenges, like increased regulations, labor cost pressures amidst skills shortages and an aging workforce, and the continuing need to maximize asset utilization and optimize production. These challenges translate to a need to reduce the total cost of ownership of the control systems investments, something that can be facilitated by bringing proven IT technologies to the OT environment, including cloud, edge, and data analytics.
Mr. John cited the examples of the Open Process Automation (OPA) and NAMUR Open Architecture (NOA) initiatives, which are looking to ease control systems ownership headaches by reducing system lifecycle costs, facilitating upgrades and replacements, allowing software portability, integrating best-in-class products, creating open standards-based systems that provide multi-vendor interoperability, and future proofing. Yokogawa has been a strong supporter of OPA since its launch and continues to work with the likes of ExxonMobil in the testbed and trial phases of the multi-year initiative.
Yokogawa has also been active in MTP, or Modular Type Package, a standards effort from NAMUR that aims to meet industry demands for flexibility and scalability through the use of standardized equipment data models and description language to integrate modular production units. The company partnered with Evonik for the first commercial MTP installation and continues to work with the German chemical company on other MTP projects.
Beyond the adoption of open architectures, there are great benefits for customers who can embrace digital transformation and move completely to be part of the digital era. Enabling technologies include the cloud, which industrial companies can leverage to meet increasing demands for faster delivery and full-scale production, and advanced analytics, where the use of artificial intelligence can help seize opportunities through deep operational insights and confident decision making.
Another key step towards digitalization, said Mr John, is IT/OT integration, which enables high-level business strategy and corporate planning decisions to be effectively translated into day-to-day facility operations. Benefits of IT/OT integration include enhanced visibility through the integration of processes, data and operations, faster decision making from having available the right real-time information, and improved effectiveness through better understanding of causes and effects in plant operations.
From Automated to Autonomous
While the automation of the process industries has become highly refined and sophisticated over the years, increasingly complex facilities are making it harder and harder for humans to oversee and intervene on everything that is happening in the plant to maintain sufficiently stable, efficient and process conditions. Hence, what is needed is to move beyond industrial automation and enter a new era of industrial autonomy, where plant assets and operations develop learning and adaptive capabilities that allow response with minimal human interaction. This is a transition that Yokogawa terms IA2IA.
But how can we get to industrial autonomy? Sujit John outlined Yokogawa’s phased approach that encompasses three technology stages: Integration, Transition, Artificial. The first step is about “connecting the unconnected”, such that the various assets within a single plant and across geographically isolated plants can be integrated and visualized. It is characterized by on premise industrial controllers, human operations, and centralized engineering.
Integrating all plant level information onto a common platform sets the stage for Transition, where the aim is to make and derive business sense and actionable insights using machine learning and mathematical models hosted on the cloud. This phase is characterized by industrial controllers on and off premise, remote engineering, and a mix of human and machine operations.
The final step towards autonomy, Artificial, makes use of on-demand virtualization of operations locally and globally, with cloud technology as standard, and bidirectional machine learning based feedback and control using tried and tested algorithms. This stage is characterized by virtualized control systems, on-demand human engineering, and a plant that can learn and operate autonomously with minimum human intervention.