Abstract
The relative low stiffness of industrial robots is a major limitation on the development of flexible and reconfigurable systems in applications in which process forces and vibration lead into significant tool path deviations with respect to the programmed path as in the case of robotic machining. This paper presents a novel factorial procedure that allows for the preliminary study of the main conditions in robotic machining operations and it determines the critical factors that are affecting the machining path of any robotic cell in order to obtain the process conditions with lower path deviations. In this procedure the most influential robotic machining constraints were identified and classified, the factorial design of experiments was used to enable the execution of the experimental tests and the machining tool path deviation predictive methodology (PREMET) was used to determine the cutting tool path deviation between the programmed and the experimental path as a function of the process variables. Experimental trials have been carried out in order to determine the main factors that affect the robotic machining and influence the main constraints of the process, showing a reduction greater than a 36% of the cutting tool path deviation in groove milling of aluminum. The critical factors identified in order of importance are: hardness of the material, location of the workpiece, orientation of milling head relative to working direction and cutting conditions. This procedure can be extended to future factorial studies to improve the precision of robotic machining (in operations such as face milling, contouring, pocketing) and to establish design criteria for machining robotic cells.
Highlights
The use of anthropomorphic robots, which offer a more affordable cost, has spread widely for the development of more flexible and reconfigurable manufacturing systems for handling, assembly, welding, and painting, among others
The factorial procedure was designed to establish the relationship between the main machining conditions imposed on the robot and the simulate deviation of the cutting tool path through the predictive methodology (PREMET), and in this way to determine which are the critical factors that most affect the machining path of any robotic cell
The evaluation of the machining path deviation results obtained after applying the factorial procedure, get a reduction of the error of 36.39% for Al and 17.11% for PUR 300. the precision has been improved from an experimental deviation error of 0.685 mm to 0.352 mm for PUR 300 and from
Summary
The use of anthropomorphic robots, which offer a more affordable cost, has spread widely for the development of more flexible and reconfigurable manufacturing systems for handling, assembly, welding, and painting, among others. In other manufacturing processes, such as industrial machining operations, robotic systems are less widespread used because process forces generate significant path deviations from the programmed path, which limit their use in the production of parts with acceptable manufacturing tolerances in sectors such as automation, aeronautics and naval application [1]. There is a trend towards directly applying a conventional machining approach to robotic systems [2]. Using this philosophy, there have been many failures, since the. Sci. 2020, 10, 8885 substantial difference between the two manufacturing systems requires prior study to guide the solutions of each application. Knowledge of robotics and machining technology must be properly combined to obtain an acceptable degree of success [3]
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