<p>Industrial robots have become an integral part of the manufacturing sector and are claiming significant role as positioning systems for manufacturing processes. In the context of machining, robots are utilized in tasks, such as deburring polishing or drilling of large-scale components, thanks to their flexibility. However, their lack of structural stiffness - close to 2% of machine tools - limits their potential applications. Academic research on optimization of workpiece placement and robot posture during machining has shown that these two methods have potential in increasing the machining performance of robots. The main gap of existing approaches is the lack of interfacing with the CAM to make them practical for use by non-experts in industrial scenarios. This work tries to address this gap, by presenting a combined workpiece placement and posture optimization approach, viable, industrial applications. The basis of the work is a synthetic dataset generated from a high-fidelity Multi-Body model of the robot. Machining feature extraction from the 3D model takes place and the optimal placement for the workpiece and orientation of each feature is calculated. Then, the toolpath is generated in the CAM and the redundant angle of the robotic arm is optimized to maximize stiffness and kinematic performance of the robot. The method is validated in a physical case study, showing increased dimensional accuracy and reduced vibrations during the machining process.</p>