Yokogawa Electric Corp. and JSR Corp. announce the successful conclusion of a field test in which AI was used to autonomously run a chemical plant for 35 days, a world first, according to Hydrocarbonprocessing.
This test confirmed that reinforcement learning AI can be safely applied in an actual plant. The demonstration shows that this technology can control operations that have been beyond the capabilities of existing control methods and have up to now necessitated the manual operation of control valves based on the judgements of plant personnel. The initiative described here was selected for the 2020 Projects for the Promotion of Advanced Industrial Safety subsidy program of the Japanese Ministry of Economy, Trade and Industry.
Control in the process industries spans a broad range of fields, from oil refining and petrochemicals to high-performance chemicals, fiber, steel, pharmaceuticals, foodstuffs and water. All of these entail chemical reactions and other elements that require an extremely high level of reliability.
In this field test, the AI solution successfully dealt with the complex conditions needed to ensure product quality and maintain liquids in the distillation column at an appropriate level while making maximum possible use of waste heat as a heat source. In so doing it stabilized quality, achieved high yield and saved energy. While rain, snow and other weather conditions were significant factors that could disrupt the control state by causing sudden changes in the atmospheric temperature, the products that were produced met rigorous standards and have since been shipped.
The AI used in this control experiment, the Factorial Kernel Dynamic Policy Programming (FKDPP) protocol, was jointly developed by Yokogawa and the Nara Institute of Science and Technology (NAIST) in 2018, and was recognized at an IEEE International Conference on Automation Science and Engineering as being the first reinforcement learning-based AI in the world that can be utilized in plant management. Through initiatives including the successful conduct of a control training system experiment in 2019, and an experiment in April 2020 that used a simulator to recreate an entire plant, Yokogawa has confirmed the potential of this autonomous control AI.
Given the numerous complex physical and chemical phenomena that impact operations in actual plants, there are still many situations where veteran operators must step in and exercise control. Even when operations are automated using PID control and APC, highly-experienced operators have to halt automated control and change configuration and output values when, for example, a sudden change occurs in atmospheric temperature due to rainfall or some other weather event. This is a common issue at many companies’ plants. The results of this test suggests that this collaboration between Yokogawa and JSR may have opened a path forward in resolving this longstanding issue.
Yokogawa Electric vice president and head of Yokogawa Products Headquarters, Kenji Hasegawa said, “The success of this field test came from bringing together the deep knowledge of the production process and operational aspects that only the customer can provide, and Yokogawa’s strength of leveraging measurement, control, and information to produce value. It suggests that an autonomous control AI (FKDPP) can significantly contribute to the autonomization of production, maximization of ROI, and environmental sustainability around the world. Yokogawa led the world in the development of distributed control systems that control and monitor the operation of plant production facilities, and has supported the growth of a range of industries. With our gaze fixed firmly on a world of autonomous operation that forms the model for the future of industries, we are now promoting the concept of IA2IA – Industrial Automation to Industrial Autonomy. To achieve strong and flexible production that takes into consideration the impact of differences in humans, machines, materials, and methods, the 4Ms, in the energy, materials, pharmaceuticals, and many other industries, we will accelerate the joint development of autonomous control AI with our customers around the world.”
As MRC reported before, in January, 2022, Yokogawa was selected by ExxonMobil as the system integrator for the first field trial of an open process automation (OPA) system designed to operate an entire production facility. The field trial will take place at an ExxonMobil manufacturing facility located on the US Gulf Coast, replacing the existing distributed control system (DCS) and programmable logic controllers (PLC) with a single, integrated system that meets the open process automation standard (O-PAS). The project will incorporate enhanced control capabilities enabled through the implementation of OPA technologies and interfaces.
We remind that, earlier this month, ExxonMobil and SABIC successful started up Gulf Coast Growth Ventures world-scale manufacturing facility in San Patricio County, Texas. The new facility will produce materials used in packaging, agricultural film, construction materials, clothing, and automotive coolants. The operation includes a 1.8 MM metric tpy ethane steam cracker, two polyethylene (PE) units capable of producing up to 1.3 MM metric tpy, and a monoethylene glycol (MEG) unit with a capacity of 1.1 MM metric tpy.
Ethylene and propylene are the main feedstocks for the production of polyethylene (PE) and polypropylene (PP), respectively.
According to MRC''s ScanPlast report, Russia's estimated PE consumption totalled 2,487,450 tonnes in 2021, up by 13% year on year. Shipments of all grades of ethylene polymers increased. At the same time, PP shipments to the Russian market totalled 1,494.280 tonnes, up by 21% year on year. Deliveries of homopolymer PP and PP block copolymers increased, whreas.shipments of PP random copolymers decreased significantly.
MRC