After four years of research, the Power-OM project, led by the IK4-Tekniker center, is complete, having featured the participation of Fagor Automation and others. The companies that make up this consortium are Goratu (Basque Country), Artis (Germany), Predict (France), Monition Limited (United Kingdom), and the Luleå University of Technology (Sweden).
With a budget of 3.8 million euro, funded by the EU through the 7th Framework Program, it has developed a smart maintenance system that proposes the use of the electric current consumption signal as a new way of incorporating predictive maintenance techniques and improve productiveness by addressing three aspects: optimizing maintenance strategies, managing energy consumption in a more efficient way, and improving the reliability of the equipment and critical elements to reduce downtime.
Aitor Alzaga, researcher at IK4-Tekniker and Chief Science Officer of the Power-OM project, explains that this novel strategy evaluates the health of the machine through the execution of testing cycles specifically designed for the diagnosis of the most critical machine components, thus generating a report of the machine condition. After processing, the result of the test is generated: a “fingerprint” of the machine, which can be compared to others for an evaluation of the most critical components, in particular the spindle and linear guides of the machine.
In addition, the project included the development of a cloud platform that collects the information obtained and allows a comparative analysis with other machines.
Through the incorporation of this smart maintenance system in the industry, the project aims to reduce unexpected failures by 75% in these components, reduce power consumption by 5% and increase the reliability of spindles and linear guides by 25%.
