## 1 Introduction
The need to predict fatigue strength is the most important challenge for airlines and passengers using the services of the abovementioned companies [19], along with monitoring trends [20; 21]. From the point of view of a manufacturer of aviation components, the main goal is to minimize operating costs, which refers to the economic parameters of the production process. The automation of the production process will enable much greater control by eliminating the impact of the human factor on the final condition of the product, and enabling the control and optimization of the parameters of the brushing process, which will reduce production costs by reducing the time spent on the edge deburring process. Many studies have been written regarding work related to the implementation of industrial robots for machining operations. These studies clearly indicate a number of advantages thanks to the introduction of robotization, in the form of increased repeatability or cost reduction. Industrial robots have been successfully used for milling, deburring, polishing, or machining thin-walled elements [22]. In the scientific literature, a number of articles dealing with various methods of optimizing the deburring process can be found. Over the years, various approaches to achieving the desired machining accuracy have been described. In order to increase the accuracy of machining with the application of a robot, work was carried out to optimize the trajectory of the robot's movement based on a dynamic model of the robot [23], as well as by real-time force control [24; 25]. Laser trackers were used as an alternative to force control in order to track the required path of the robot, which led to an increase in machining accuracy [26]. Work was also carried out to optimize the deburring process in relation to the structural stiffness of the robot used [27]. The authors of [28] describe the process of optimizing the parameters in the process of belt grinding and deburring steel according to the surface roughness and material removal rate. Both indicators are considered, and experimental results have shown that the comprehensive target can be effectively used as a metric to control grinding performance and process improvement. In [29; 30; 31; 32], the Taguchi design method was widely used to optimize the milling parameters for surface roughness. In [33], the authors presented and discussed the concept of the project of the sensor-less force control of automatic grinding and deburring through an adjustable mechanism. In [34; 35], the authors show that the key to high-quality polishing and deburring is maintaining a constant contact stress between the grinding tool and the work piece. Excessive or insufficient clamping force significantly worsens the surface roughness. The study in [36] aims to provide insight into the development and evaluation of force-guided machining processes. The focus was on the deburring and grinding scenario. Deburring implements a force-dependent feed-rate control, while the grinding use case implements force (pressure) control. The authors of [37] indicate that controlling the clamping force on the work pieces is a difficult task in industrial deburring operations. To solve this problem, a constant force mechanism based on a combination of positive and negative stiffness mechanisms has been proposed. The analyzed works clearly indicate the possible advantages related to the implementation of robots for individual production operations. Considering the multitude of studies, it was decided to prepare a laboratory stand in order to verify the feasibility of brushing the blades produced for the needs of modern jet engines. The analyzed works related to the optimization of the deburring process [23; 24; 25; 26] indicate that in order to carry out the process of optimizing the brushing operation, it is necessary to determine the key parameters of the process and then to understand their mutual interaction.