The Refinery of the Future
Published on : Tuesday 06-12-2022
AI is becoming a natural part and extensive use in a well-managed role in refinery businesses for high GRM, says Jasbir Singh.
Considering the top 10 fastest growing markets of the next generation by Oxford Economics, most of them are in Asia with India in the lead position with 6.5%, second is Philippines, third Indonesia, fourth China, and fifth Malaysia in terms of projected (GDP) growth. The demand for refined fuel and petrochemical products is impacted by economic growth in Asian countries. The major challenges are seen as how the industries can expand but it remains flexible to meet the upcoming demand.
Intelligent, adaptable and flexible production and supply chain
The future plants will be fully demand driven with the quick decisions and approvals at all levels simultaneously. Training workers for indepth subject knowledge needs to be constantly given as the customer demands the output better than the other competitors. Human machine interface for visual tracking with integrated systems will be provided to the customer, like how the product chain from one end to other is better optimised to meet the demand and improve profitability shared between each other. Refinery and petrochemical companies need to digitalise with application of powerful artificial intelligence (AI) having analytical good algorithms to understand business opportunities presented by the market to meet the supreme quality and delivery. The system needs to be made highly adoptable.
The refiners of the next generation will operate with the knowledge worker’s seamless data exchange at every level. Planning, scheduling and manufacturing will be integrated. The production planner system will be supported by an AI expert on visual systems with a defined dashboard, showing operations, demand, sales, and sustainability. The optimal scheduling for production, sales and delivery is now made fully autonomous.
Use of prescriptive maintenance for defined failures
Use of prescriptive maintenance systems will stabilise the situation that can improve the stage planning for shutdown, time, duration and level of maintenance requirement in the refinery. The refinery can buy crude alternatives available for low-cost production to improve the gross refining margin (GRM). Trained data-based AI supported dashboard helps the operators to derive the best possible asset utilisation, with increased safety and quality. This integrated scheduler works autonomously to provide closed loop optimisation results, with AI assisted advanced process control (APC) software.
In leveraging the Industrial Internet of Things (IIoT), data sensors will be pervasive in this plant. Real time analytics deployed at the edge will provide process stream compositions. Catalyst nano sensors will add to the array of data to better drive control over the process performance. All of which will drive APC and the underlying control software to operate via dynamically adjusted setpoints to achieve and exceed plan. Major process units and equipment in the next generation refinery will be smart plant building blocks. This built-in intelligence will greatly improve its ability to run process operating limits, which will be critical to asset flexibility.
Advanced capability of digital software analytical systems will bring humans out of danger at even remote areas of the refinery or petrochemical units. Further intelligence is derived from new development of sensor data, prescriptive maintenance with AI solutions and unit analytics. The refiner will have the information to better understand actual asset conditions, deteriorating trends, risks and if emergencies to act. It reduces the requirement for workers to be physically present all the time or on schedule to inspect the equipment and other issues. AI enabled stations with advanced solutions are provided at strategic locations to manage start-up and shutdown procedures from even distance and remote locations.
The unit in-charge of the refinery uses the intelligence data output having an AI based decision tool to model the right configuration of the plant to suit requirements changing on demand from time to time. The prescriptive maintenance system on top, not only highlights the future failure models of prediction for equipment and overall unit. It links the planning and process operating changes. This approach reduces the risk of future failure being delayed or completely eliminated.
Advanced industrial robotics solutions enable the refiner to perform multiple tasks even without sending workers to dangerous situations. The integration of process operation and intelligent measurement of reliability, planning and its execution will reduce the requirement for workers to access the dangerous areas, which may become risky places and face the dangerous situations.
Digitalisation of plant with IIoT sensors for data acquisition and transmission
The highly competitive refinery is facing the demand changing patterns, complex modelling and exponentially data volumes generation. The plant should be able to compete with the highest-level performers in the world with increased worker’s safety, high process performance and improved profitability. This refinery of the future is taking advantage of IIoT technologies by taking data from pumps, rotary equipment and with machine learning develops new insights of the plant to enhance its decision-making process. IIoT being used as remote wireless sensors in the shortest time is more popular in the plants. Real time analytics on IIoT can be deployed at the edge configuration and may provide a better process stream understanding. The development of nano sensors adds the advantage of arrays of data to improve the drive control for the reliable process performance. These data are collected from the advanced Neno sensors that provide APC the real time information and its control software dynamically adjusted setpoints to achieve right output. The process units and its equipment will be more effective to become a smart plant with autonomous operation. The in-built intelligence in the system improves its ability to function within defined and precise operating limits. This increases the life of critical assets functionality and its reliability.
Modelling of the units in the plant
Online model for system optimisation integrated with overall process control is constantly watching and optimising the use of energy and utility requirements for the right operation of the asset with optimum cost. The refinery is becoming more hypercompetitive over the period, due to globalisation effect and dynamic market demand.
Conclusion
The future of automation will work on augmented intelligence, with AI to support the development of human intelligence. Human intelligence with the use of AI is complementary for growth oriented operations. Considering the outcome of augmented intelligence including IDP, AI chatbots, together with predictive analytics, and automated reporting, AI is becoming a natural part and extensive use in a well-managed role in refinery businesses for high GRM. Cybersecurity capabilities of the digital platform and prompt warnings will be built into each layer of the refinery operation.
Jasbir Singh is an Automation Expert having long experience in Factory Automation, Line Automation, Implementation Strategist, Business Coach, Regular writer on automation, Artificial Intelligence, Robots/Cobots, Digital Technology, Network Communication, Industrial Internet of Things (IIoT), Wireless Communication, Block Chain and use of advance digital technologies. He has established a long association with Business Houses/large production houses to improve factory automation in their production lines as well as productivity improvement in factories in India and overseas; and in advising and designing the units to transform into digital platforms by use of Artificial Intelligence. Email: [email protected]
