Manufacturing - Mechatronics
The research group has a strong national & international profile, being represented on the EPSRC College of Peers and on the UK Mechatronics Forum since its foundation in 1990, and acting as external examiners for many UK Universities. Members of the group are Visiting Professors, Academy of Science members or invited lecturers from around the world.
The majority of the research activities are industrially funded or supported. Many companies form a secure working partnership to research and develop products and processes for mutually beneficial exploitation.
The group has an interest in a range of activities which promote and support Mechatronics. Mechatronics is, by its very nature, integrative and draws upon many technologies in the realisation of intelligent products, processes and systems.
Fundamental Research
The group conducts projects concerning the fundamental aspects of the enabling technologies that facilitate mechatronics. Modelling & Simulation Sensors and Actuators Mechanisms & Dynamics Control Machine Vision Interfacing Systems Integration Artificial Intelligence Knowledge Engineering
Design & Embodiment
Once the fundamental enabling technologies are understood the process of design may begin following established methodologies. The generally complex procedure is exacerbated by consideration of trade offs in mechanical, electrical and electronic capabilities as well as in hardware versus software functionality. Mechatronics is clearly an applied discipline and thus it requires manufactured artifacts to demonstrate the principles. Manufacturing processes may demand enhanced precision or complexity and this must be taken into account.
Operation
Once a machine is designed and built, it needs to be maintained. An intelligent machine can monitor its own operation and predict when failures of components or systems may occur due to normal wear and tear. Condition Based Maintenance may then be used for optimal plant efficiency and process availability. A truly intelligent machine learns from its previous data (experience) and builds Knowledge which it may then exploit.