Artificial immune systems based multi-agent architecture to perform distributed diagnosis

Cyber-physical systems (CPS) emerge as a new idea to implement new manufacturing paradigms. There paradigms aim at answering the socio-economic factors that characterise modern enterprises, such as mass customisation and new markets. The authors propose an architecture that performs distributed diagnosis. The proposed solution uses artificial immune systems (AIS) to perform evolutionary diagnose. Industrial approaches to machine diagnosis are centralised. The authors pretend to make a CPS capable of distributed diagnosis with learning capabilities. An architecture capable of machine diagnosis and learning is also presented. This is done by bio-inspired algorithms. These were rated by a fuzzy inference system. The algorithms were tested for situations a system may endure and for their learning capability. The results of the obtained research, study and development are hereby presented. These results constitute proof of the sustainability of the AIS paradigm as a solution to distributed diagnosis.