Research Offer
Comprehensive research capabilities and advanced methodologies for industrial and academic collaboration
Numerical Modelling
Finite Element Method
- Modelling of technological processes with commercial software (Abaqus, ANSYS, Forge, ADINA)
- Development of in-house FEM codes for various processes (rolling, extrusion, etc.)
- Dedicated System for FEM Simulation
- Additive Manufacturing (3D Printing) Simulation
- Development of rheological models
Microscale modelling
- Modeling of phase transformations
- Thermodynamic calculations
- Microstructure evolution modeling during thermal and mechanical processing
- High-performance stochastic modeling for microstructure prediction
Multiscale modelling
- Complex rheological analysis across multiple length scales
- Microstructural modeling integrated with macroscale process simulations
- Cellular Automata Finite Element (CAFE) methods
- Multilevel Finite Element (FE2) approaches
- Adaptive Multiscale Modelling Methodology
- Integration of fine scale models with commercial and in-house FEM software
- Statistical Similar Volume Element (SSRVE) method
Analysis of numerical models
- Sensitivity analysis of numerical models and process parameters
- Uncertainty quantification and propagation in simulation models
- Parameter identification using inverse methods and optimization techniques
- Model validation and verification
Industry 4.0
Digital Twin Technology
- Design and industrial implementation of Digital Twins
- Application of Digital Twin for manufacturing process optimization
- Integration of sensor data with virtual models for predictive maintenance
- Real-time analysis and optimization using Digital Twin
Industry Information Systems
- Design of information systems supporting manufacturing processes
- Integration of advanced technologies in production environments
- Development of smart manufacturing execution systems
- Human-Machine Interface (HMI) design and optimization
Manufacturing Process Optimization
- Multi-step technological process optimization
- Multi-criteria optimization
- Real-time process control and adaptive optimization
- Integration of AI algorithms with manufacturing systems
- Quality prediction and control using machine learning
Artificial Intelligence and Data Science
- Machine learning and deep learning for materials science applications
- Reinforcement Learning for process control
- Explainable AI (XAI) for manufacturing decision support
- Big Data analytics and data mining for manufacturing processes
- Knowledge-based systems and ontology development
- Data mining techniques for manufacturing process improvement
Cyber-Physical Systems
- Design and implementation of cyber-physical systems for manufacturing
- Integration of physical processes with computational intelligence
- Real-time control systems
- Computer vision applications for process monitoring and control
- Cloud and edge computing
Virtual and Augmented Reality Applications
- VR/AR training systems for industrial operations
- Immersive simulation environments for process visualization
- Mixed reality solutions for maintenance and assembly procedures
- Advanced visualization systems for complex data analysis