in processes

Monitoring and Sensing

Joining processes are widely used in many industrial sectors such as the automotive, aeronautical, oil & gas, etc. to manufacture critical components. Likewise, additive manufacturing processes are becoming increasingly important in industrial production, with new applications emerging from one day to the next. However, process stability plays a crucial role, as slight deviations can generate non-conformities or defects in critical applications.

LORTEK uses (online) monitoring techniques, which permit assessing and diagnosing, and even taking corrective actions to prevent the occurrence of non-conformities. This is done with one single ambition: to improve quality. There are two fields of application where identifying anomalies is extremely important:

  • Welded joints of high added value components, where subsequent inspection is too late.
  • Additive manufacturing of parts by means of SLM, LMD or WAAM technology for sectors where costly inspection procedures are required (X-rays, for example).

Figure 1.

To this end, LORTEK uses optical technologies, such as the measurement of emissions by photodiodes, thermal imaging, laser-assisted stroboscopic vision systems, acoustic emission sensors, 3D laser triangulators, spectrometry, or interferometer systems. All of these technologies can be integrated into the processes, thus offering a robust solution for complex problems.

All of this has the strong backing of LORTEK's knowledge in joining and additive processes, as well as the modelling of these processes.

This results in the following benefits:

  • Increase in robustness of production processes.
  • Process control by means of visualization techniques.
  • Detection of anomalies and anticipation of possible non-conformities (early detection).
  • Monitoring-based process control.
  • Quality control.
  • Knowledge about the use of the production system and improvement of its efficiency.
  • Reduction of need for post-process controls, and reduction of quality-associated costs.

Example of techniques

Thermal imaging or thermography is used to analyze different industrial processes, and in particular, in joining and additive processes, as energy input excesses (high temperature) may be associated with process instability, and may generate pores. In contrast, the absence of energy input (low temperature), gives rise to lack of fusion.

Likewise, vapour emitted by the molten metal during the welding process is characteristic of the composition of the metal that is melted (see Figure 3). Thus, analyzing this vapour, by monitoring the plasma during the welding process, is helpful in identifying process anomalies, for example, the absence of a component in the spectrum of the molten metal may be associated with lack of fusion.

Finally, LORTEK implements fusion process visualization techniques, which consist of introducing stroboscopic concepts by means of pulsed lasers, which permit visualizing the metal fusion process – which accounts for the origin of many defects -. The geometry of the molten bath is measured by means of these techniques, and events that may generate defects are detected.

Figure 2. Visualization of the molten bath to diagnose the fusion process by means of these techniques.
Figure 3. Different laser process monitoring techniques: a) thermal imaging, b) plasma spectrum, and c) design and configuration of a monitoring system.

What we are currently working on

WELD-PHONE CAMERA: Development that groups together sensors that help to extract the most information from a fusion process:

  1. thermal
    • by thermographic imaging.
  2. visual
    • by inserting stroboscopic laser light.
  3. geometric
    • by incorporating structured light.
  4. acoustic
    • by inserting microphones.

It is, therefore, a system that permits visualizing (visual image), feeling (thermal), and hearing (acoustic), with the aim of coping with the challenge of detecting online defects.

Figure 4. WELD-PHONE CAMERA: Sensor fusion to extract information from different sources.

Development that permits extracting information about the height of the bead deposited, and correcting it if necessary, and also studying the dynamic of the molten bath, especially wet welding angle estimations. This permits diagnosing the process stability.

Figure 5. Measurement of the height and dynamic of the melt-pool; two different filler material moments with different parameters in LMD, which give rise to different wet welding angles (top image), and bead height measurement (bottom image).


Synchronization between monitoring and capture of machine data for representation and three-dimensional analysis. Intuitive visualization of the influence of the different parameters on quality.

Figure 6. Digitalized LMD; 3D speed maps, melt-pool size/temperature, and even geometry.


SLM process monitoring by means of a group of photodiodes operating at 10,000 Hz, thus generating volumes with all the data captured, for subsequent analysis. These analyses permit identifying the occurrence of anomalies.


Monitoring permits optimizing the welded joint process, establishing the process limits, understanding how the defects are generated, and increasing the quality of welded products. In this sense, LORTEK has designed and developed an intelligent robotized welding cell, by integrating a series of sensors and capturing critical process parameters in real time (voltage, intensity, wire speed, welding feed speed, gas flow, torch position, etc.). The subsequent analysis of these data permits advancing towards zero defect production.

LORTEK is currently working on monitoring and controlling the topography of the welding bead (joint detection, joint monitoring, control over welding penetration, bead shape measurement), temperature, and molten bath behaviour.

Figure 7. Arc welding process monitoring.

Specific Equipment


  • Digital cameras with different speeds.


  • Photodiodes and pyrometers with acquisition capacity up to 10,000 Hz.





  • Spectrometer to measure the spectral emission of welding and additive processes, which permits analyzing not only the radiation emitted from a process, but also from its components. It covers a wide range of the spectrum, from 200 nm to 1100 nm.


  • MWIR (Mid Wave InfraRed; 1-5 µm) thermographic camera, with 32 pixels x 32 pixels resolution, and high acquisition frequency: 1000 Hz.


  • Welding camera that consists of a CMOS camera with 300 fps acquisition frequency, synchronized with a pulsed laser that permits visualization the fusion process both in welding and in additive.


  • SLM process monitoring system to obtain 3D volumes that contains information of the emissions during the process.

Publications and downloads

Ander Muniategui; Aitor García de la Yedra; Jon Ander del Barrio; Manuel Masenlle; Xabier Angulo; Ramón Moreno
Mass production quality control of welds based on image processing and deep learning in safety components industry.
Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111720L
García de la Yedra, A, Pfleger, M, Aramendi, B, et al
Online cracking detection by means of optical techniques in laser‐cladding process
Struct Control Health Monit. 2019; 26:e2291. ISSN:1545-2263

Success Cases

Online cracking detection during Laser Metal Deposition process


Online cracking detection during Laser Metal Deposition process.


Acoustic emission system based on an optical microphone that detects cracks in the part, thanks to the energy released during the fracturing process. This enables us to know if the part has been manufactured with zero defects, or not.

Partners or strategic alliances



Challenges to be faced in the coming years:

SLM process monitoring: Quality control

Development of a quality control tool that analyzes the monitored signals, thus allowing the early detection of deviations during the process.

Development of WELD-PHONE camera

Development of a sensor fusion system for application in arc welding processes, which cuts across other metal melting processes. It is a tool with three perceptions: it visualizes feels and hears. This system includes:

  • Vision systems (Visual).
  • Thermal image (Feels).
  • Acoustic signals (Hears).

Online bead height control

Development of an online bead height measurement system, to be able to take corrective actions if the bead does not satisfy minimum requirements. Applicable to welding and additive processes.

Francisco Javier Huertos

Main Researcher in Sensing & Control systems and Robotics.

Engineer in Automation and Industrial Electronics by Mondragon Unibertsitatea and Master’s Degree in Systems and Control Engineering by the Complutense University of Madrid / UNED. He is currently a senior researcher in LORTEK’s intelligent manufacturing group, leading control, robotics and industrial process automation activities. Among other projects, he is the coordinator of the European project, HyperCOG. He also has more than 10 years’ experience as a researcher at different R&D centres of the ArcelorMittal group (Belgium and Spain), leading and participating in several international and national research and development projects.