FEATURE PROCESS AUTONOMY FROM INDUSTRIAL AUTOMATION TO AUTONOMY


Bert Konings, marketing director for Yokogawa Europe, describes the path to the fully autonomous process plant, and says, that while we are not there yet, we can expect to see some functions become autonomous, based on the application, needs and cost-benefit ratios


I


n a business environment ruled by high volatility, uncertainty, complexity, and


ambiguity, manufacturers in process industries must achieve stable and profitable operations. To meet these challenges, companies are embracing emerging digital technologies to transform operations, control costs, reduce downtime, and improve profitability. Digitalisation improves efficiencies while


also allowing companies to develop new production, operations, and distribution capabilities. Applying advanced intelligence and cognitive technologies likewise enables organisations to respond dynamically to changes in demand and customise product, ensure high product quality, and optimise production processes in real time. To be autonomous means to be


independent or to be able to govern oneself. Autonomy is different from automation, which performs a sequence of highly structured pre-programmed tasks requiring human oversight and intervention. The tasks could take minutes, hours, or even longer—as is the case with steady-state continuous operations. In between these undertakings, humans must perform as well, and they are ultimately responsible for the safe, timely, and profitable completion of the operation. Autonomy goes beyond automation by adding layers


42 JULY/AUGUST 2020 | PROCESS & CONTROL


of smart sensing and machine cognition to anticipate and adapt to unforeseen circumstances, removing the need for human intervention.


LEVELS OF AUTONOMY Autonomy will permeate process plants in multiple functional domains, including process control and operations, planning and scheduling, supply chain management, field operations, maintenance, and engineering. For field operations, this means going from low levels of autonomy, where all field operations are done by humans; to semi- autonomous, where the system guides operators and instructs them on how to accomplish a task. Further autonomy


Several mixed states or levels of autonomy will be possible in the future, but plant personnel will need to be part of operations to work with industrial automation and autonomous systems


Much of the technology and data enabling autonomy already exists. A significant portion of the data emanates from sensors in the control network or is obtainable with wireless sensors


requires converting manual tasks to fully automated tasks that require human action only as an exception. When autonomous operations are


achieved, field operation requires no human interaction at all. For both field operations and maintenance, robotics will play a key role and conduct routine operator rounds, collect samples, perform monitoring and inspection, and carry out surveillance. When looking beyond the individual


plant, we can start to consider the autonomous interaction of data and resources between separate plants, which we call symbiotic autonomy. In a world that now expects corporations to consider their operations from the point of view of planetary sustainability, this approach can deliver multi-win outcomes for a much wider range of stakeholders. Much of the technology and data


enabling autonomy already exists. A significant portion of the data emanates from sensors in the control network or is obtainable with wireless sensors. Various technologies, such as AI, can process the data and add intelligence. While not required for low-autonomy levels, AI may be essential to achieve high levels of autonomy, where the need exists to develop an all-encompassing architecture to integrate multiple domains both internally and externally. With process industries moving closer to


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