Within the field of Artificial Perception, Vision systems are tools that permit perceiving reality by means of electronic cameras. These can be constructed based on different technologies, so, in many cases, they enable us to perceive what the human eye cannot see.
Vision technologies offer the possibility of automating a large number of industrial processes with a much greater precision than is possible with human work. These processes include quality controls, dimensional control, stock control in logistics, contactless deformation measurement, or robot guiding, among others.
The characteristics of the technology, especially its speed and the fact that no contact is required, are allowing the replacement of manual and undesired operations (or in some cases, the execution of tasks that cannot be done by other means), also contributing towards the digitalization of companies, as they incorporate relevant information about production processes.
Some of the benefits afforded by this technology include: real time quality control, early defects detection and real time monitoring of the production process.
The aim is to tap into technology to detect anomalies (surface defects or rejects of another type) in welded joints or additive manufactured parts.
This technology is being applied to extremely high frequency (1 second cycle time) welding processes, as well as to detect defects on variable and irregular surfaces, proving the versatility of the technology.
Integration of vision-based quality control system in production lines that are permitting the availability of on-site quality-related information. This technology is being applied in a way that cuts across many sectors such as capital goods, energy or transport.
3D information generation and acquisition techniques are highly evolved and mature. There are different systems on the market that are based on these techniques (stereoscopy, triangular laser, etc.), which permit the robust and reliable acquisition of geometries or volumes, and with high quality data. Among the many possible applications, 3D inspection permits the external inspection of welding beads or components constructed by additive manufacturing.
Based on this technology and supported by CAD/CAM solutions, LORTEK has developed an automatic arc welding repair system for high value added parts (see success case).
Incorporation of vision technologies to control stock in industrial warehouses, and automate orders in order to reduce the amount of company stock to a minimum.
Derived from different industrial projects already executed at LORTEK, the vision department has libraries dedicated to image processing for the automatic control of quality systems. This entails a reduced ramp-up in new computer-assisted vision projects in industrial contexts.
Quality control of welded joints of safety components, in high takt time production line, with cycle times of close to 1 second.
An artificial vision-based system was designed, manufactured, and developed to provide a solution to this problem, consisting of introducing three cameras, each positioned at 120º, to permit the reconstruction of circular welding. This reconstruction is used to analyze the welding quality with previously trained Deep Learning-based algorithms. The result of this is a device that determines if the part is good or bad, rejecting it from the production line, preventing its delivery to the customer, and also avoiding operations on already faulty parts.
Challenges to be faced in the coming years:
He has proven experience in process monitoring and non-destructive testing (NDT) by means of optical techniques. He is the author of several scientific articles and multiple papers at international congresses related to structural integrity (prediction of component lifecycle, and NDT (thermography, acoustic emission, etc.). He has also participated in numerous international research groups, noteworthy among which are, COMBILASER (H2020-FoF1), WELDMINDT (Clean-Sky) or DELASTI (Clean Sky). His participation (co-leader) in the first group is very relevant, working to introduce intelligence in complex processes such as those based on laser manufacturing.
Previously, he had worked at other centres of the partnership, developing measurement and inspection processes (for machine-tools, aeronautical industry, etc.).
Senior researcher in Advanced Manufacturing at LORTEK since 2013. He is currently leading projects in intelligent systems (based on self-learning concepts) to predict and avoid the appearance of defects in high added value processes, such as laser processes (welding and additive).
