Hybrid Modeling: Asset Optimization through the Fusion of AI and Expertise
We will introduce how the hybrid model synchronizes models from different functional areas to enhance the safety, reliability, and profitability of assets.
AspenTech has devised a method to integrate first-principles-based process simulation models and expertise with AI and analytics algorithms. The resulting application software is a hybrid modeling system that can achieve more than either first-principles modeling or AI alone. With AspenHybridModels, the following becomes possible: - Modeling processes and equipment that are difficult to model using first principles alone. - Providing comprehensive and highly accurate models more quickly with less reliance on expertise. - Optimizing and evaluating optionality across multiple assets to select the best strategy for achieving goals. - Creating accurate and purpose-built models that enable the optimization of closed-loop production. Download this white paper to learn how to operate assets more safely, reliably, and profitably with hybrid models.
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Case Study: Mitsubishi Chemical Uses Aspen Hybrid Model to Detect and Avoid Product Quality Issues
Mitsubishi Chemical was facing difficulties in detecting and resolving product quality issues on schedule in specific polymer processes. Therefore, they found an opportunity to address these issues by collaborating with AspenTech. By using Aspen Hybrid Models, the company's process engineers were able to create robust and high-performance models that accurately predict quality issues and support preventive measures. 【Value Created by Adopting AspenTech Products】 • Detection and avoidance of potential quality issues • Significant reduction in on-site sampling work • Shortened time to realize operator value For more details, please refer to the related catalog.
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[Case Study: New Listing] Nissan Chemical Improves the Speed and Accuracy of Steam Reforming Equipment Models with Aspen Hybrid Model
Nissan Chemical Corporation is considering modeling an ammonia plant and conducting a study on cost reduction, initially focusing on steam reforming. The company has struggled to accurately model processes and assets using existing rigorous reactor simulations. This requires temperature profiles of process fluids, and accurately estimating or measuring the temperature distribution within the reactor has been challenging. Due to such constraints in conventional models, the company wanted to try a different approach. Ultimately, they chose Aspen Hybrid Models and Aspen Plus based on first principles. 【Twice the speed】Build models that surpass conventional ones more quickly 【Up to 1%】Cost reduction rate achievable through optimization of steam input 【Improved accuracy and sustainability】Enhance predictive insights through the use of AI For more details, please refer to the related catalog.
