Three fields of expertise

The Ghent University M&F industrial research platform brings together experts from three domains:

  • Electromechanical engineering: multi-physic modelling of physical phenomena in actuators and systems forms a strong basis. (Hybrid) models are developed and used for the design, soft sensing, optimisation, condition monitoring and advanced (yet industry friendly) control of motion products. Digital twin technology and AI control for electromechanical systems. Our test benches allow to validate smart motion products in an emulated relevant environment (TRL4/5).
  • Industrial systems engineering: we design, optimise and validate flexible (hybrid) assembly cells incl. the task allocation and the virtual commissioning based on digital twin. Strategies for production and maintenance are combined with quality control strategies & supply chain logistics. Our lab infrastructure resembles real industrial assembly cells and factory settings.
  • Digital engineering: our researchers are working on transfer, cross-context & data-efficient machine learning with expert in the loop functionality for industry 4.0. Furthermore, they develop AR/VR/MR industry relevant tools, and our dynamic visualisations support our anomaly detection tools.

 The combined expertise allows us to innovate and perform research in the field of Smart Motion Products and Smart Production Systems.


A list of our professors and their expertise is available here.

Electromechanical Engineering

Based on our electromechanical engineering competences, we are working on

  • Optimal synthesis and control of motion systems: tools are developed to (co-)design and optimally control systems to maximize performance, our hybrid model based control approach opens up trustworthy and explainable AI enabled model based control engineering;  
  • Smartness in motion systems: we are integrating sensors or develop virtual sensors based on a digital twin approach to add smartness to components and subsystems in order for them to robustly operate over a wide range of boundary conditions; 
  • Innovative actuators: we design and validate new types of more efficient, more robuust, ... machines which open up new architectures in motiion products;


Our competences include

  • System level design of smart motion systems including their control: new architectures, component sizing, component selection, component & architecture validation, trajectory optimisation
  • Hybrid & physical based modelling of physical phenomena in AND multi-physical design of drive trains
    • Thermal systems: heat transfer in complex heat exchangers and cooling plates; innovative cooling of power electronics and electrical machines (e.g. heat pipes); thermodynamics (e.g. heat recovery)
    • Fluid dynamics systems using Computational Fluid Dynamics (CFD): numerical optimisation of multi-scale flow and heat problems; fluid structure interaction (FSI) incl. unsteady flows in complex moving geometries
    • Electro-mechanical actuator systems (electrical machines and drives): innovative electrical machines and their fault tolerant machine control; co-design of power electronics, electrical machines, system architecture and control; co-simulation of mechanical structure and actuator system; tribology and lubrication incl. sensing of contact surfaces; experimental and numerical research; EMC of electrical drives
  • Sensing, control and condition monitoring of cyberphysical systems
    • Sensing: virtual sensors/soft sensors of electromechanical machines based on digital twins with hybrid modelling which includes machine learning, data mining, evolutionary optimization
    • Control: Stability and stabilisation, optimization of dynamical systems; synchronisation of oscillators & control of discrete event systems; AI based control that is trustworthy and explainable
    • Optimisation: optimization of nonlinear dynamical systems incl. non-linear and user friendly MPC; modeling and regulation of Lagrangian and Hamiltonian systems


Industrial Systems Engineering


Our competences include:

  • Specifying and validating flexible architectures for assembly based on innovative automation concepts and increased connectivity;
  • Organising multi-criteria evaluation of future assembly work cells including flexibility and human factors;
  • Developing tools for the operational support within hybrid work cells;
  • Setting up context aware information for human centered assembly work cells;
  • Designing new strategies for the supply and presentation of parts to an assembly station
  • Logistics and supply chain
  • Material handling and warehousing
  • Production planning and control
  • Integrated production and (preventive/selective) maintenance planning

Digital Engineering

Within industry 4.0 data is playing a pivotal role, in this field we

  • Develop and apply black boc machine (deep) learning tecniques, including machine learning and semantics to include expert knowledge to obtain interpretable outputs;
  • Develop innovative data and hybrid drive modelling algorithms to increase the accuracy of machinery and factory models, discover new knowledge and to allow tuning of physical models;
  • Develop cross-context models to allow machine learning models to adapt to new contexts wherin machines and factories need to operate;
  • Introduce virtual, augmented and mixed reality into the manufacutring industry based on/inspired by the gaming industry.