Process Digital Twin

[Description]

• Online dynamic digital twin models (Aspen Plus Dynamics, Aspen Custom Modeler) for a VCM plant, including an EDC (Ethylene Dichloride) cracker and the purification units
• The digital twin models feature automatic tuning capabilities, enabling them to mirror and accurately represent plant performance in real time
• Rigorous radical reaction models and coke formation kinetics for the interior surfaces of EDC cracker tubes
• Representation of the dynamic behaviors of heat exchangers and separation columns and their performance degradation over time

[Description]

• Comprehensive PDH plant coverage, including the Oleflex reactor and downstream separation columns
• Online digital twin system for real-time optimal point prediction
• Dynamic process visualization using Aspen One Process Explorer for enhanced insights and monitoring

[Description]

• Highly detailed polymer kinetics and thermodynamics to guarantee model accuracy and precision
• Dynamic polymer plant models calibrated with historical production data spanning multiple polymer grades
• Operational excellence features, supporting real-time optimization, production strategy testing (start-up, shutdown, grade changes), and effective debottlenecking/troubleshooting
• Comprehensive training tool for engineers, functioning as a simulator for operator lessons and skill enhancement

[Description]

• Steady-state digital twin system for nine refinery processes, covering both upstream and downstream operations, using HYSYS Equation-Oriented (EO) modeling
• Established an online, plant-wide digital twin system to provide real-time insights and optimize refinery operations
• Created various tools and functionalities to enhance the usability of the online digital twin models across multiple processes
• Enabled comprehensive process monitoring and optimization, improving overall refinery efficiency and decision-making capabilities

[Description]

• Preparation and integration of plant data: Secure and review plant history data, finalize plant data and tag lists, and connect them to the IP.21 RTDB
• Utilize the M1 model as a dynamic mirroring digital twin for real-time operations, and the M2 model as a reconciliation digital twin to track and predict performance degradation in the LNG heat exchanger, compressor, and compander systems. Conduct thorough testing and refinement to ensure optimal functionality
• Successful SAT Completion: The site acceptance test (SAT) using real-time plant data was successfully passed and approved by the customer

[Description]

• Developed an online Digital Twin (DT) simulator for an alkylphenol manufacturing plant, incorporating a 32-column Simulated Moving Bed (SMB) process and downstream distillation columns for solvent recovery
• Supports real-time operation by obtaining data from the DCS or plant historian, predicting current and future plant performance, and assisting operators with actionable insights
• Enhances monitoring capabilities by estimating compositions in parts of the plant lacking online analyzers
• Maintains simulation accuracy through automated re-validation and updates, depending on the model parameters of interest

[Description]

• TBR is one of the gas-liquid reaction types that perform hydrogenation and is used in various processes in commercial scale plant
• Hydrodynamic behavior inside the reactor varies depending on the operating conditions, and the hydrogenation reactivity is sensitively affected accordingly
• Dynamic TBR model was constructed using Aspen Custom Modeler. The 1-D (axial) and 2-D (axial and radial) distributed models established 3 phase (solid-gas-liquid) mass & heat balance based on reaction kinetics confirmed through experiments

[Description]

• Implement rigorous chemical equilibrium modeling in the solution phase, incorporating species concentrations, pH, selectivity, lumped kinetics in the solid phase, and material balance
• Apply a 1-D model to account for axial dispersion effects within the column
• Assume constant liquid velocity per column and explicitly calculate pressure drop based on liquid velocity
• Model 30 cation exchange columns with a globally constant temperature assumption
• Simulate true counter-current movement of the solid phase relative to the fluid phase flow direction

[Description]

• Reactor simulation model for pharmaceutical API manufacturing
• Set up the online model using Aspen Online
• Configure the IP.21 real-time database to integrate plant data
• Map tags and establish connections between the online model and IP.21
• Develop a web application for user interaction and data visualization
• Integrate IP.21 with the web application for seamless real-time data access

[Description]

Looking for Expert Aspen Modeling and Simulation Consulting? Contact us today! Here’s what we promise:

• Tailored approaches to develop and optimize process models, including steady-state, dynamic, and custom models, designed to meet your specific requirements
• Comprehensive support for process design, scale-up, and optimization projects using Aspen software
• Global top-tier expert assistance in diagnosing and resolving modeling challenges, as well as validating models against plant or experimental data to guarantee accuracy and reliability
• Hands-on training and consulting to help you internalize best practices and maximize the potential of Aspen modeling tools