SPAIN : MULTIPLE INDUSTRIES
SMART-EASY
Advanced digital manufacturing platform
PROJECT OBJECTIVE
Sensorized machine tools
The SMART-EASY project aimed to develop a new generation of sensorized machine tools with machine vision technologies to generate digital operating environments that simplify and streamline manufacturing and predictive maintenance processes to ensure optimized manufacturing in terms of efficiency, quality, reliability and productivity.
From the data extracted from the sensors connected to each machine and thanks to the application of machine learning and knowledge management techniques, a digital twin was developed for each machine capable of analyzing the results with respect to the defined patterns of normal operation and quality of the parts. This was intended to provide users with assistance tools that suggest new manufacturing processes and strategies, detect the state of health of the most critical components and suggest the best predictive maintenance and error correction actions.
This Advanced Manufacturing Digital Platform project was developed by a Spanish consortium of eight leading companies in the different stages of the manufacturing value chain, who decided to join forces. The consortium was led by Nicolás Correa, a Burgos-based manufacturer of high-volume milling machines. It was joined by Álava Ingenieros, MonoM, Ibarmia, GNC Hypatia, Shuton, MYL and Inmapa-Aeronáutica. They also had the collaboration of Tecnalia, the University of Burgos and the University of the Basque Country.
Date of execution:
February 2019 - February 2023
Location:
Spain
Sector:
Process industry, machine tools
Client:
How we made it happen
Data acquisition and processing
MonoM, a company of the Alava Group, participated in the definition of the digital model or twin of the machine tool, as well as in the definition of the predictive maintenance using in the definition of the model or digital twin of the machine tool, as well as in the definition of predictive maintenance using machine learning algorithms applied to the machine tool signals recorded in its CNC and other additional signals.
In this way, it was possible to define the wear of the machine depending on the process it was undergoing at any given moment in order to create behavior patterns and anticipate failures. For its part, Álava Ingenieros participated in this project by defining the needs of massive sensorization of the machines and in the definition of the technological solution for the detection of anomalies during the manufacturing process of the parts.
In addition, Álava Ingenieros was in charge of the acquisition and processing of the data extracted from all the sensors installed in the machines to contribute to the updating and generation of the digital twins. It was also in charge of the development and programming of the control parameters, supervision and analysis of deviations in the machining process.
RESULTS AND ACHIEVEMENTS
Improved process efficiency
This new manufacturing process enabled users to reduce 60% of the time and costs associated with launching new manufacturing operations, as well as reducing energy and material consumption by 20%. It also enabled an unattended machining operation and improved all quality levels.
Through this system, for the first time in history, those responsible for the manufacturing process were able to have at all times a complete X-ray not only of each machine tool installed in the plant, but also of any of its components and of the entire manufacturing process. In addition, these X-rays could be stored over time to form a history that will help in the management and supervision of the process.
60%
of reduction in time and associated costs
20%
reduction in energy and material consumption
OUR EXPERIENCE
