One research question that interest me is how to create a robust and flexible manufacturing that can manage unpredicted events. An event may be a production stop due to e.g. a dropped product or a mechanical breakdown, or a rapid change in the production plan due to changes in demand or new product variants. Rapid re-programming and / or control systems that make its own decisions are essential elements to handle this.
Another interesting research question is how to optimise an industrial manufacturing. To optimise is to determine the best values for a number of variables to achieve a specified objective. There are many objectives to be achieved simultaneously in industrial manufacturing, e.g. high production, low power consumption and low wear on the equipment, while it is hundreds or many more variables possible to adjust. High demands are placed on both the optimisation strategy and algorithm.
A common denominator for these interests is the need for a virtual manufacturing model. A computer simulation model, a virtual manufacturing, has to be developed where robots, machines, humans, measurement and control systems must be included and simulated. By using this model, then programming, verification and optimisation be performed without disturbing ongoing production or even before the equipment is available.
Teach at our engineering programs (mechanical and electric), master's (robotics and production) and commissioned education within the control engineering, automation and simulation. Supervising theses, mainly students of the master's program in robotics. Assistant supervisor of Emile Glorieux who began his PhD studies in 2013 at University West.
Industrial Automation, Flexible Automation, Virtual Manufacturing, Off-line Programming, Virtual Commissioning, Multi-agent, Simulation-based Optimisation.