In order to diminish any flaws or imperfections from previous manufacturing procedures, and to receive the manufactured part in its final form, the process of deburring is a crucial and important part of the manufacturing cycle of a product, that follows material removal processes. During deburring, the last layer of material is removed from the surface of the manufactured component. This happens in small quantities without altering its shape. Automatic control is making its presence stronger in manufacturing applications of the industrial field. The process of deburring can be described as time-consuming and tiresome, when executed by a human, due to the high level of accuracy and the high amount of time required for the process to be completed, also counting in multiple quality checks that need to be brought through until the product is complete. The human factor also increases the likelihood of error during the process, which most of the times proves to be irreversible, causing the part to be discarded.
Considering the purposes mentioned above, it is clear that using an automated system like a robot arm, can not only enhances the efficiency of the procedure, but also relieves the human operator from tiresome and potentially harmful operations. This project presents work conducted in terms of research, so that a robotic arm can be integrated inside the manufacturing process and conduct deburring operations. The basic concept is that the automated mechanism (robotic arm) will be able to recognize and control its operation, changing it respectively during movement without processing a surface, and when it performs the process of deburring. The basic principle followed is a force-position hybrid control system, offering increased maneuverability and rigidness that assist minimizing manufacturing inconsistencies as well as tool wear. The process of deburring was modelled and through a series of experiments the model was tested by simulating a deburring process in real conditions. The model and calculations were created, conducted and hosted with Matlab, and the experiments were conducted using a KUKA LWR IV robotic arm.