Self-learning embedded services for integration of complex, flexible production systems

Abstract

A new approach, based on self-learning embedded services, allowing for high adaptation and integration of complex, flexible production systems is presented. The context sensitive solution for adaptation of discrete, flexible assembly/manufacturing lines is proposed. The proposed solution includes context extractor, adapter and self-learning modules allowing for integration of the control and so-called secondary processes depending on the extracted context. Both context extraction and adapter are continuously learning and improving their performance. Service Oriented Architecture principles are used to implement these modules. Generic solution and specific applications in three various manufacturing environments are presented.