Refinery Plant
Fluidized Catalytic Cracking Process
[Implemented]
- Online digital twin model (Aspen HYSYS) for Fluidized Catalytic Cracking (FCC) process
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Key features:
- Storing and transmitting industrial big data
- Advanced visualization of plant data and digital twin metadata
- Develop enhanced process drawings (Meta-PFD, Meta-P&ID)
- KPIs monitoring and analysis at real-time
[BENEFITS]
- Real-time monitoring and analysis of process sensor data alongside digital twin metadata
- Management of KPIs with customizable datasheets and 2D/3D visualizations
Bio Process
Bio-Membrane Purification Cascade
[Implemented]
- Online Clean-in-Place (CIP) prediction model (Python ML) for membrane processes in a biomanufacturing plant
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Key features:
- Advanced visualization of real-time flux for cascade membranes
- Empirical modeling approach utilizing historical big data
- Real-time prediction of the remaining time required to clean the interior of each membrane
[BENEFITS]
- The prediction model enables the selection of optimal criteria to reduce CIP frequency
- Optimizes energy consumption by preventing CIP overlaps
Sustainable Hydrogen
Autonomous Green H₂ Operation
[Implemented]
- Online dynamic digital twin models (Aspen software) for a green H₂ plant located in a remote site
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Key features:
- Digital twin-assisted control and autonomous operation
- Mirroring digital twins for the solar energy storage system and water electrolyzer unit
- Representation of the dynamic behavior of charging and discharging cycles during daytime
- Currently an ongoing project
[BENEFITS]
- Optimization of system integration to minimize hydrogen production costs
- Enhanced efficiency of the energy storage system by accounting for daytime variations
