AFM is the manager and coordinator of the project led by Nicolás Correa, in which the following companies also take part: Ibarmia, GNC Hypatia, Shuton, Talleres MYL, Álava Ingenieros, MonoM (formerly ThingsO2), Inmapa Aeronáutica, together with the research bodies: Tecnalia Research & Innovation, the University of Burgos and the University of the Basque Country UPV/EHU. The initiative is financed by the Centre for Industrial Technological Development (CDTI) and the Ministry of Science and Innovation of Spain.
The global objective of the SMART-EASY project is to develop a new concept of autonomous and intelligent machine-tool which, on the one hand, assists its manufacturer users in the different stages associated to advanced manufacturing (parts preparation, launching of processes, executing operations, etc.) and, on the other hand, supervises these manufacturing operations and, where applicable, adopts decisions aimed at optimising its quality and productivity, thereby reducing the overall need for human supervision and intervention during the different stages of production.
With this project outlook, the companies in the consortium, which synergistically cover the different stages in the manufacturing value chain, are developing different hardware and software solutions, key among which are the following:
- A system based on artificial vision, which assists the user in positioning and aligning the machine parts.
- Thermal twins for machines that enable application of online offsetting techniques for thermal errors.
- A system to oversee the stability and productivity of manufacturing processes that includes a diagnostic and online action system to detect the presence of any error or deviation.
- A system to monitor the health status of the more critical components of the machine by executing regular checking cycles: Fingerprint of the machine and its components.
- A system to record information on manufacturing processes, such as tools, surface quality, cutting parameters, etc.: Process fingerprint.
- A tool manager based on process data that enables parameters such as status and the remaining life of these tools to be estimated.
With the integration and implementation of these results, the project consortium expects to achieve reductions of up to 50% in times and costs associated to the operation’s definition and launch phase, reductions of over 15% in maintenance costs on milling machines, and reductions of over 20% in consumables, lubricants and coolants used in machining operations.
The SMART-EASY project requires digital competencies and projects like DTAM will help to develop them for the current and future workers. DTAM Training Course will consist of approximately 25 training units on digital and transversal skills relevant for IT and OT technicians in AM environments that contribute to the major areas of Industry 4.0 and the foreseen sections of Big Data, Machine Learning, Sensors and Cybersecurity.