Author
Listed:
- Shahram Sheikhi
(Department Mechanical Engineering and Production, Institute for Materials Science and Welding, Berliner Tor 13., 20099 Hamburg, Germany)
- Eduard Mayer
(Department Mechanical Engineering and Production, Institute for Materials Science and Welding, Berliner Tor 13., 20099 Hamburg, Germany)
- Jochen Maaß
(Department Informations-und Elektrotechnik, Berliner Tor 7, 20099 Hamburg, Germany)
- Florian Wagner
(Gall and Seitz Systems GmbH, Vogelreth 2-4, 20457 Hamburg, Germany)
Abstract
Implementing digitalization in the field of production represents a major hurdle for some small- and medium-sized enterprises (SMEs) due to the ensuing demands on employees and, in some cases, the significant financial investment required. The RobReLas research project has developed a system whose purpose is to enable an economical solution to this dilemma for SMEs in the field of automated, robot-based reconditioning of components. A laser scanner was integrated in the robot’s control. The data generated by the scanner are used to mathematically describe the virtual area of the surface to be laser-treated. The scanner recognizes the relevant area within the robot’s predefined work space by defining the maximum length and width of the relevant component. The system then automatically applies predefined and qualified repair strategies in the virtual area. Tests on nickel-based blades demonstrated the system’s economic potential, showing a reduction in reconditioning time of about 70% compared to the conventional reconditioning method. The main advantage of the system is the fact that a basic knowledge of operating robots is sufficient for the attainment of repeatable results. Further, no additional CAD/CAM workstations are required for implementation.
Suggested Citation
Shahram Sheikhi & Eduard Mayer & Jochen Maaß & Florian Wagner, 2020.
"Automated Reconditioning of Thin Wall Structures Using Robot-Based Laser Powder Coating,"
Sustainability, MDPI, vol. 12(4), pages 1-13, February.
Handle:
RePEc:gam:jsusta:v:12:y:2020:i:4:p:1477-:d:321462
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