Optimization of Process Parameters of Edge Robotic Deburring with Force Control

Burghardt, Andrzej; Szybicki, Dariusz; Kurc, Krzysztof; Muszyńska, Magdalena

doi:10.1515/ijame-2016-0060

Cited by 12 publications

(8 citation statements)

References 5 publications

(5 reference statements)

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“…Therefore, the main applications of this software are related to processes where forces must be controlled. The main applications are force monitoring in the processes of machining [12] or polishing [13][14][15]. Robotic joining technologies in which forces play an important role also make extensive use of the capabilities of the Test Signal Viewer software.…”

Section: State Of Knowledgementioning

confidence: 99%

TCP Parameters Monitoring of Robotic Stations

et al. 2022

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The impulse for writing the paper is the observation of the works related to the implementation of robotization of processes such as machining, glue application, welding and painting. The abovementioned processes, in addition to the correct implementation of the trajectory, require the definition of various parameters (e.g., speed) in the robot’s software. In the trajectories where the reconfiguration of the robot arms is observed, there are significant errors in the implementation of the defined speed. Robotic technology suppliers, in the event of speed disturbances, manually increase the defined speed value or experimentally select other parameters. It is a cumbersome process, and the lack of information about the process parameters makes it time-consuming and inaccurate. In this paper, one representative process is selected, namely machining performed with various tools by ABB robots. In order for the robotic process to be controlled, it is necessary to compare the defined path with the speed profile. Then, the speed parameters can be controlled and corrected. The approach proposed in the paper allows for improving the quality of implemented robotic processes. It presents the available IT tools for station monitoring and how to use them. The advantages of the proposed solutions and their limitations are shown in the examples of implementation of robotic stations in the industry.

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Section: State Of Knowledgementioning

confidence: 99%

TCP Parameters Monitoring of Robotic Stations

et al. 2022

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“…Accuracy performance is the main index that evaluates the effectiveness of machining, fabrication, and deburring [6][7][8]. The factors affecting the accuracy of machine tools mainly include geometric errors, thermal errors, load-induced structural deformation errors, and servo errors [9,10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Error Sensitivity Analysis Method for a Parallel Spindle Head

Wang,

Li,

2023

Robotics

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Geometric errors are the main factors affecting the output accuracy of the parallel spindle head, and it is necessary to perform a sensitivity analysis to extract the critical geometric errors. The traditional sensitivity analysis method analyzes the output position and orientation errors independently, defining multiple sensitivity indices and making it difficult to determine critical geometric errors. In this paper, we propose sensitivity indices that can comprehensively consider position and orientation errors. First, the configuration of the hybrid machine tool is introduced, and the TCP position error model is derived. Then, the tool radius and the effective cutting length are introduced, and the sensitivity indices are defined. After that, the sensitivity analysis of the 3-DOF parallel spindle head is performed using the proposed sensitivity indices, and six critical geometric errors are extracted. The machining accuracy of the parallel spindle head can be greatly improved by improving the critical geometric errors. The proposed sensitivity analysis method can provide important guidance for machine tool accuracy design.

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“…However, the implementation of sensors and complex control algorithms in an "outof-the-box" robotic deburring cell is a major obstacle in transitioning the technology from a clean research laboratory environment to a highly stressed industrial environment. As an alternative, an industry-oriented engineering approach to optimize the deburring parameters considering spindle speed, feed rate and contact force was presented in [18]. In another study, improved control of the robotic deburring process was achieved by shifting the force control from the robot to a simpler external mechanism that is easier to control and designed to compensate for high nominal forces by varying its stiffness [19].…”

Section: Introductionmentioning

confidence: 99%

Stiffness-Based Cell Setup Optimization for Robotic Deburring with a Rotary Table

2021

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Deburring is recognized as an ideal technology for robotic automation. However, since the low stiffness of the robot can affect the deburring quality and the performance of an industrial robot is generally inhomogeneous over its workspace, a cell setup must be found that allows the robot to track the toolpath with the desired performance. In this work, the problems of robotic deburring are addressed by integrating components commonly used in the machining industry. A rotary table is integrated with the robotic deburring cell to increase the effective reach of the robot and enable it to machine a large workpiece. A genetic algorithm (GA) is used to optimize the placement of the workpiece based on the stiffness of the robot, and a local minimizer is used to maximize the stiffness of the robot along the deburring toolpath. During cutting motions, small table rotations are allowed so that the robot maintains high stiffness, and during non-cutting motions, large table rotations are allowed to reposition the workpiece. The stiffness of the robot is modeled by an artificial neural network (ANN). The results confirm the need to optimize the cell setup, since many optimizers cannot track the toolpath, while for the successful optimizers, a performance imbalance occurs along the toolpath.

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Optimization of Process Parameters of Edge Robotic Deburring with Force Control

Cited by 12 publications

References 5 publications

TCP Parameters Monitoring of Robotic Stations

TCP Parameters Monitoring of Robotic Stations

A Novel Error Sensitivity Analysis Method for a Parallel Spindle Head

Stiffness-Based Cell Setup Optimization for Robotic Deburring with a Rotary Table

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