Self-Learning Production Systems (SLPS) — Energy management application for machine tools

In an increasingly globalised environment, modern manufacturing companies struggle to improve their integrated monitoring and control solutions with respect to total cost of ownership by reducing down-times during production, improving system performances and throughput and enabling for a faster fault detection as well as reducing energy consumption. The research currently done under the scope of Self-Learning Production Systems (SLPS) tries to fill this gap by providing an innovative and integrated approach for developing more intelligent monitoring and control solutions. This paper introduces the research background and describes the generic SLPS architecture with the main focus on the Adapter component, which represents the entity responsible for adapting the system behaviour based on the available contextual information. The envisioned Adapter architecture as well as the generic Adaptation Process are introduced. The proposed solution was then employed to manage the energy consumed by machine tools in CNC machines, taking into account machine idle times patterns. Both the objectives and approach of this application scenario are presented, as well as the Adapter role whenever the system needs to be adapted to improve the manufacturing line sustainability.