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JUL-AUG 2019

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FACTORY AUTOMATION INTECH JULY/AUGUST 2019 23 cess that accurately mimics actual performance, in real time, that is executable and can be manip - ulated, allowing a better future to be developed. A digital twin is useful for the entire life cycle of an asset. It is ideally created during the ini - tial study to evaluate the feasibility and process model of the asset. It is then used and further developed during the design, construction, and commissioning of the asset, thereby facilitating the optimal design of the asset and the train- ing of the staff who will operate it. During the bulk of a plant's life cycle, operation, and main- te nance, the digital twin can be employed for op timization and predictive maintenance. The digital twin enables everyone to see in- side assets and processes and perceive things that are not being directly measured. They are wired so that insights are instantly available without end users having to wrangle data and models, and they run in a consistent way that FAST FORWARD l The energy and chemical industries need digital twins for effective decision making. l An integrated production management system digital twin operates across the entire process manufacturing supply chain and asset life cycle. l Where possible, the cloud should be exploited to host the digital twin. essary to account for the multidimensional fac- tors and nonlinear trade-offs that make effective decision making a challenge. The digital twin allows "What if?" and "What's best?" scenarios to be run automatically on ac - tual plant data to determine available strate- gies that maximize profitability. Experts can then review the recommended strategies to assess the effect of each approach without dis - rupting the live process. A digital twin works in the present, mirroring the actual device, system, or process in simulated mode, but with full knowledge of its historical performance and an accurate understanding of its future potential. Therefore, the digital twin can exist at any level within the traditional ISA-95 ar - chitecture and can be defined as a decision sup- port tool that enables improved safety, reliability, and profitability in design or operations. It is a virtual/digital copy of a device, system, or pro - Figure 2. Digital twinning is a type of analytics technology. Desired outcome Data-driven decisions based on ... Analytics category Available analytics technology Oversight (Best decision action) Foresight Insight Hindsight Future Past & present Prescriptive analytics "What should happen?" Predictive analytics "What will/might/can happen?" Diagnostic analytics "Why is it happening/why did it happen?" Descriptive analytics "What is happening/happened?" Graphical Statistical Advanced statistical First principles Dashboards Data mining Spreadsheets Machine/deep learning Digital twin Optimization Performance monitoring Cognitive analytics Planning Pattern recognition Regression Scheduling Heuristics Simulation Figure 1. Sample of profit gaps in refinery operations. FCC yield management

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