Engineering support system for sustainable optimization of automation task supervision

The main objectives of this PhD are the conception and development of an Engineering Support System (ESS) for sustainable optimization of automation tasks supervision which is a set of formalisms, methods and tools introduced to support the control engineer in the design phase of optimized supervisor solutions. The ESS is based on the IEC 61499 standard and on a new formalism for the control problem description and specification that leads the control engineer within all the control design phases, in order to obtain high performance manufacturing systems while pursuing optimization of key parameter indicators, including for example minimal energy consumption and emissions. To such an aim it enables the possibility to formalize the control supervision problem into a constrained optimization problem to be solved with the most appropriate optimization algorithm selecting the most interesting optimization objective. Finally, an innovative virtual commissioning platform is proposed. It allows to validate the developed automation tasks supervision system using the real targets running the control solution connected with the virtual model of the system to be controlled in place of the real one. Two applications of the developed engineering support system has been addressed considering an industrial painting plant and a reconfigurable manufacturing system test-bed owned by the University of Michigan which is a production plant composed by three robotic cells which allows to realize different type of products starting from raw plastic blocks. The performance reached by both the two application cases addressed are explained in the thesis as proof of the effectiveness of the engineering support system developed as the main result of the PhD activities.