Abstract
Among the advantages of using industrial robots for machining applications instead of machine tools are flexibility, cost effectiveness, and versatility. Due to the kinematics of the articulated robot, the system behaviour is quite different compared with machine tools. Two major questions arise in implementing robots in machining tasks: one is the robot’s stiffness, and the second is the achievable machined part accuracy, which varies mainly due to the huge variety of robot models. This paper proposes error prediction model in the application of industrial robot for machining tasks, based on stiffness and accuracy limits. The research work includes experimental and theoretical parts. Advanced machining and inspection tools were applied, as well as a theoretical model of the robot structure and stiffness based on the form-shaping function approach. The robot machining performances, from the workpiece accuracy point of view were predicted.
Highlights
Among the benefits in applying robots to machining tasks that were first reported in the 1990s were increased flexibility and lower costs
This paper proposes error prediction model in the application of industrial robot for machining tasks, based on stiffness and accuracy limits
R0 = [ x0, y0, z0,1] and rn = [xn, yn, zn,1], In Equation (1), x0, y0, and z0 are the coordinates of an functional point (FP) referring to the frame S0 whereas, xn, yn, and zn are those referring to the frame Sn; and 0An is the 4 × 4 manipulating matrix of the form-shaping function (FSF) presenting a product of the cofactor-matrices i−1Ai associated with the ith link ( i = 1, 2, n ) of the form-shaping system (FSS)
Summary
Among the benefits in applying robots to machining tasks that were first reported in the 1990s were increased flexibility and lower costs. In robotic milling applications, the process final results are unwanted trajectory deviations, which lead to errors in target dimensions and reduced surface quality of the workpiece (WP). These deviations are mainly caused by static offset overlaid with low frequency tool oscillation [3]. The accuracy of robots in machining was reported for various operation types and under several processing conditions, for example, a deviation error of 0.19 - 0.55 mm was obtained for the KUKA KR 125 robot in milling with a 300 N load [6]. The developed software, based on the form-shaping function (FSF) approach and previously applied for modelling machine tools [11] [12], is used here for the first time for articulated robot research
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