99 gains, enabling chemical manufacturers to gain ground amid a crowded global stage. Traditionally, digital twins have been used to build plants. How can ‘lifecycle’ digital twins optimise benefits from project phases to operations support? APS enables the lifecycle digital twin by creating a simulation model at the conceptual design phase, which then evolves throughout the project’s lifecycle. This model integrates sizing, control loops and all necessary information up to the plant’s startup. After commissioning, the same model can connect to real-time data, enabling troubleshooting and operational optimisation. This approach eliminates the need for separate design and operations process simulators, streamlining efficiency and accuracy. Can you give us an insight into how APS is supporting and transforming the industrial chemicals sector specifically? The technology enables quick process modelling and iteration, reducing the time required for testing and scaling new chemical formulations. Engineers benefit from an openmodel writing environment that allows them to create new operating units when they need to, without complicating coding. APS can connect to real-time operational data through AVEVA PI System, allowing companies to adjust operations based on actual chemical plant performance. Critically, APS also helps companies reduce energy consumption and optimise chemical reactions, lowering operational costs and carbon footprints. In addition, APS can be incorporated into integrated AI-driven analytics solutions, which help identify inefficiencies and opportunities for improvement while predicting chemical hazards before they occur. How does APS, running on Microsoft Azure, enable agile development of new processes and products to support chemicals customers? APS running on Azure leverages the power of the cloud to provide fast, flexible and scalable process simulation, allowing companies to reduce time to market and develop more innovative and sustainable products. Historically, process engineers may have had to carry several heavy laptops and wait days for model results. With the cloud, engineers simply require a browser and a high-speed internet connection to run complex models. APS running on the cloud allows global teams to work on the same digital twin model, ensuring consistency. This saves time, costs, and valuable personnel hours, particularly in a landscape where chemical engineering resources are increasingly scarce. Companies can also scale their computing power based on project needs, reducing reliance on expensive on-premises infrastructure. By speeding up design cycles, enabling AI-driven process optimisation and ensuring sustainability, APS helps chemical companies innovate faster, reduce costs and stay competitive in a rapidly evolving market. How is AI shaping the future of process simulation within chemicals? AI is revolutionising process simulation by making models smarter, predictive and selfoptimising. APS can be connected with popular machine learning packages like Open Neural Network Exchange for high-speed simulated modelling, allowing the digital twin to analyse trends, optimise conditions and recommend real-time adjustments. To learn more, visit: bit.ly/3QLzDhi INDUSTRIALS & MANUFACTURING Photo: iStock/ianyu wu
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