Digital twin benefits for process manufacturers
There are many different elements of digital twin technology that can benefit the process manufacturing sector.
Digital twin insights
- Digital twins drive agility and the convergence of understanding to enable effective decision-making by providing full knowledge of its historical performance
- Digital twins can drive improvements through advanced data analytics and operational insights by utilizing massive amounts of information.
A digital twin is a representation of a human, device, system, or process that replicates an actual process and has full knowledge of its historical performance. Digital twins drive agility and the convergence of understanding to enable effective decision-making and to determine strategies in order to maximize safety, reliability and profitability by simulating devices, systems or processes to forecast future performance.
A digital twin captures data to determine real-time performance. This data can be used across the entire life cycle of an asset for optimization and predictive maintenance.
Digital twins are able to drive improvements through advanced data analytics and operational insight; guide day-to-day decisions with in-depth, accurate data; utilize massive amounts of plant information to enable better decision-making; and ensure that actual performance meets planned performance.
The current digital twin solution for plant, which is a virtual replica of an actual plant, which consists of a process digital twin and an asset digital twin. Both link with real plant operations and handle the data of the real plant and are continuously updated with real conditions. They are able to replicate reality, simulate it, and optimize the activities revolving around it. As such, digital twins constitute an evolving digital profile of the historical and current behavior of a physical object or process, and this profile can help optimize business performance.
The process and asset digital twins will be closely connected in an integrated solution. Asset integrity information is part of the feedback loop to operators, giving full visibility of process impacts on mechanical assets, while process data is a critical input of predictive maintenance algorithms, allowing the recognition of process patterns which could lead to asset failure.
Asset digital twin
An asset digital twin is based on a 3D model as a repository of asset information and of cumulative data completed by properties and documents, such as manuals or operating procedures generated during all life cycle phases of the asset. The twin encompasses technical documents produced during Engineering Procurement and Construction (EPC). It expands with maintenance plans developed by vendors, and it is continuously updated with maintenance and inspection reports. The fundamental backbone of digital-enabled solutions during plant operations, it is supplied with key information during the EPC cycle at a marginal cost.
Three benefits of an asset digital twin include:
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Improved reliability and availability of assets by decreasing plant upsets due to human errors in planning and execution.
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Reduction in maintenance time, effort, and costs by increasing the reliability and productivity of day-to-day activities.
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Reduction in turnaround duration through better planning of activities on a 3D model, thus increasing plant availability.
Process digital twin
The process digital twin is becoming a key enabling factor for the new technologies connected to plant operation and optimization, through the integration of the process model, the process optimization engine, and real-time data from the plant. The process optimization engine leverages thermodynamics to simulate the process and optimize its operations. As a further improvement, it is also possible to enhance and reinforce the thermodynamics model with machine learning algorithms to simulate the process and optimize its operations as precisely as possible, integrating production programs and economics in order to maximize the plant margin.
Process digital twin benefits include:
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An increase in plant margin and productivity by support operation in day-to-day activities, optimizing the plant operating conditions, fast de-bottlenecking, and reducing the utilities consumption.
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Support for operation decision-making by the application of the operator training simulator.
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Individual point solutions with digital twins do exist today, serving different purposes such as fit-for-purpose simulation models and individual data sources.
A future digital twin will be a one multi-purpose digital twin, which aligns the asset life cycle and value chain, a multi-purpose dynamic simulator (MPDS), and ubiquitous data sources. It is unrealistic to assume this future state can be achieved in one step, but it becomes more likely through the connectivity of valuable high-performing individual elements.
Just one example to demonstrate the benefits of a digital twin application would be for a corrosion prediction and digital advisory system.
If there is a gas leak in a facility the first question will always be “where is the leak?” Then more questions arise – How can the leak be stopped? Why did it happen? And how can the plant be safely shutdown to avoid an accident?
Once the situation has been controlled controlling the situation, a team will be tasked with identifying the reason for the leak and the to identify the losses plant incurred.
Corrosion is a slow poison to plant equipment and pipelines and its effects are often only apparent when the system has already sufficiently corroded – with destruction either imminent or already having occurred.
– This originally appeared on Control Engineering Europe’s website. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media & Technology, cvavra@cfemedia.com.
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