Robotic face milling path correction and vibration reduction
In this paper two different process models which can predict the mean value components of the tool forces when milling aluminium, bronze and steel with an industrial robot have been estimated. The parameters in the process models were depth and width of cut, while feedrate and cutting speed were found from the tool manufacturer's datasheets. The models were estimated from a large set of machining experiments. Different measurement sets were used for parameter estimation and for model verification. The estimated models were found to be accurate. For the experiments in aluminium and the model using only the depth of cut as parameter, the average error was about 18N. For the model using both depth and width of cut as parameters the average error was about 7N or less in all three materials. The intended application area for the identified process model is in offline programming and toolpath adjustment for robotic milling of hard materials. With a process model such as the one presented in this paper and estimates of the robot's joint stiffness values, the toolpath can be adjusted to counteract deflections of the tool during milling operations.