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IK4 Doctorados



Industrial projects research oriented companies of manufacturing industry.



Flexible robotic system geared towards the inspection of surface integration


START: 10/2018




Inspections for monitoring the manufacture of parts are unavoidable in industry. This is an area where, even today, inspection is being done manually, either through using penetrant liquids or magnetic-particle methods depending on the manufactured part. In any case, it concerns inspections which are not only completely manual but are also subjective, that"s to say, dependent on the operator performing the inspection.

In this context, a dual necessity arises to investigate, on one hand, an automation of the inspections, i.e. robotisation of the inspection, and, on the other, the development of an objective, and automated inspection system. The thesis presented here covers these two fields.

The elimination of classic and standardised techniques such as penetrant liquids or industry magnetic particles involves incorporating emerging and innovative technologies such as active thermography. Through this technology there is excitation of the parts to be inspected either by laser or by induction, and then captured with a thermographic IR camera. When there is a defect, this is reflected in the camera recordings showing a localised surface warming. Various processing techniques exist to detect the defects present by means of this warming. IK4-Lortek propose training in the inspection technique, both on an experimentation level and as one of processing and detection, using as a base the programming language Python and image libraries such as OpenCV. In particular, it will be applied to inspection of parts in industrial settings.

In regards to robotics, this is an area which has been gaining lots of momentum in industry for several years now, with the aim not only of bringing about automation, but also in order to increase manufacturing production and equip it with new sensors which may be able to monitor the process. For this reason research must be carried out in the thesis on the robotised system which is best adapted to the inspection section. All this involves acquiring knowledge of robotics, determination and optimisation of trajectories using CAD/CAM Tebis, etc. software. In addition, there will be work on 3D computer vision topics for referencing of objects automatically and in artificial intelligence based on “reinforced learning” with the aim of implementing self-learning strategies to define an optimised inspection.

In a generic way, the following phases are addressed in chronological order throughout the thesis:

·         A first experimentation and manual phase in which basic knowledge is acquired for the surface inspection of parts using active thermography, focusing on processing and detection.

·         In the second phase computer or artificial vision is introduced with the aim of referencing the parts automatically.

·         The student will be getting stronger in the third phase: Will do in-depth study into the  capacities and advantages of robotisation (to consider robotics in a collaborative way if it were possible), such as the knowledge required to program a robot to carry out inspections. This will also involve working on the definition and optimisation of trajectories in CAD/CAM.

·         The final phase will focus on the use of artificial intelligence to implement self-learning strategies with the purpose of defining an optimised inspection.

Department or unit of the Associates Technology Center

Intelligent manufacturing

Investigation line

Advanced surface inspection + Robotics

Start date planned


Obtaining date of the doctor degree




  •          Master of engineering in automation, electronics or robotics.
  •          Knowledge of Artificial Vision.
  •          Advisable: Knowledge of robotics, knowledge of Vision Guided Robotics (VGR), Knowledge of expert systems, Python, OpenCV.
  •          High level of English.
  •          Interest in research.


This thesis will be part of a framework collaboration between IK4-LORTEK (experts in materials, bonding and additive manufacturing technologies) and the MGEP group of Robotics and Automation. Both IK4-LORTEK and MGEP may make their robot inspection cells available for the thesis.


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