The widespread adoption of Robotic Deburring (RD) can be effectively enhanced by the availability of methods and integrated tools capable of quickly analyzing the overall process performance in a virtual environment. On the other hand, despite the current availability of several CAM tools, the tuning of an RD process parameters is still mainly based on several physical tests, which drastically reduce the robotic cell productivity. The reason is that several potential sources of errors, which are unavoidable in the physical cell, are simply neglected in state-of-the-art CAM software. For instance, the effectiveness of a RD process is highly influenced by the limited accuracy of the robot motions and by the unpredictable variety of burr size/shape. In most cases, it is strictly necessary to maintain a uniform contact pressure between the tool and the workpiece at all times, despite the burr thickness, so that either an active force feedback or a passive compliant spindle must be employed. Focusing on the latter solution, the present paper proposes a Virtual Prototype (VP) of a radially-compliant spindle, suitable to quickly assess deburring efficiency in different case scenarios. The proposed VP is created by integrating a 3D multi-body model of the spindle mechanical structure with the behavioural model of the process forces. Differently from previous literature and from state-of-the-art CAM packages, the proposed VP allows to quickly estimate the process forces (accounting for the presence of workpiece burr and tool compliance) and the optimal deburring parameters, which are readily provided as contour maps of the envisaged deburring error as function of the cutting parameters. As an industrial case study, a commercial compliant spindle is considered and numerical simulations are provided, concerning the prediction of the surface finishing accuracy for either optimal or sub-optimal parameter tuning.

Design Optimization of Cutting Parameters for a Class of Radially-Compliant Spindles via Virtual Prototyping Tools

BERSELLI, GIOVANNI;RAZZOLI, ROBERTO
2019-01-01

Abstract

The widespread adoption of Robotic Deburring (RD) can be effectively enhanced by the availability of methods and integrated tools capable of quickly analyzing the overall process performance in a virtual environment. On the other hand, despite the current availability of several CAM tools, the tuning of an RD process parameters is still mainly based on several physical tests, which drastically reduce the robotic cell productivity. The reason is that several potential sources of errors, which are unavoidable in the physical cell, are simply neglected in state-of-the-art CAM software. For instance, the effectiveness of a RD process is highly influenced by the limited accuracy of the robot motions and by the unpredictable variety of burr size/shape. In most cases, it is strictly necessary to maintain a uniform contact pressure between the tool and the workpiece at all times, despite the burr thickness, so that either an active force feedback or a passive compliant spindle must be employed. Focusing on the latter solution, the present paper proposes a Virtual Prototype (VP) of a radially-compliant spindle, suitable to quickly assess deburring efficiency in different case scenarios. The proposed VP is created by integrating a 3D multi-body model of the spindle mechanical structure with the behavioural model of the process forces. Differently from previous literature and from state-of-the-art CAM packages, the proposed VP allows to quickly estimate the process forces (accounting for the presence of workpiece burr and tool compliance) and the optimal deburring parameters, which are readily provided as contour maps of the envisaged deburring error as function of the cutting parameters. As an industrial case study, a commercial compliant spindle is considered and numerical simulations are provided, concerning the prediction of the surface finishing accuracy for either optimal or sub-optimal parameter tuning.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/861748
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