Thin-walled parts, especially those with complex surface geometries, are prone to geometric inaccuracies and structural distortions, which can lead to issues during finishing operations like sanding. Using a toolpath based on the reference part to machine deformed workpieces may compromise surface quality or even damage the machined surface. In robotic applications, force control is often used to adapt the toolpath, but its ability to compensate for tool orientation remains limited. Digitizing the part allows for toolpath and tool orientation corrections before machining, preventing surface defects caused by workpiece deviations. This paper proposes an algorithm for toolpath and tool orientation correction, with the developed software solution simulated on a virtual twin of the robot control unit.

The variations in the physical and mechanical properties of different types of stones have a significant impact on the dynamics of the machining process. Hardness stands out as one of the most crucial properties of stone, directly affecting cutting forces and, consequently, the stability of tools and/or workpieces. Therefore, an analysis was conducted on the application of cutting forces and servomotor current signals of the main spindle and feed drives of the drilling machine in the classification of stone hardness. Stone samples were drilled using a newly designed drill bit with internally cooling capabilities. Laboratory testing with this type of drill bit revealed notably lower cutting forces and reduced tool wear intensity. In comparison to experiments conducted with commercially available industrial drill bits, the analyzed signals exhibited significantly improved accuracy in stone hardness classification, surpassing 98%. This high precision is evidently attributed to the absence of adverse effects caused by stone particles in the cutting zone, effectively eliminated by the analyzed internally cooled drill bit.