Contribution Ratio Assessment of Process Parameters on Robotic Milling Performance

Abstract

Robotic milling has broad application prospects in many processing fields. However, the milling performance of a robot in a certain posture, such as in face milling or grooving tasks, is extremely sensitive to process parameters due to the influence of the serial structure of the robot system. Improper process parameters are prone to produce machining defects such as low surface quality. These deficiencies substantially decrease the further application development of robotic milling. Therefore, this paper selected a certain posture and carried out the robotic flat-end milling experiments on a 7075-T651 high-strength aeronautical aluminum alloy under dry conditions. Milling load, surface quality and vibration were selected to assess the influence of process parameters like milling depth, spindle speed and feed rate on the milling performance. Most notably, the contribution ratio based on the analysis of variance (ANOVA) was introduced to statistically investigate the relation between parameters and milling performance. The obtained results show that milling depth is highly significant in milling load, which had a contribution ratio of 69.25%. Milling depth is also highly significant in vibration, which had a contribution ratio of 51.41% in the X direction, 41.42% in the Y direction and 75.97% in the Z direction. Moreover, the spindle speed is highly significant in surface roughness, which had a contribution ratio of 48.02%. This present study aims to quantitatively evaluate the influence of key process parameters on robotic milling performance, which helps to select reasonable milling parameters and improve the milling performance of the robot system. It is beneficial to give full play to the advantages of robots and present more possibilities of robot applications in machining and manufacturing.

Structural Potting of Large Aeronautic Honeycomb Panels: End-Effector Design and Test for Automated Manufacturing

“…The milling process parameters can also be specifically defined for a robotic arm implementation. In [ 48 ], the authors found that spindle speed dictates the surface roughness, while milling depth dictates the vibration. The problem of milling parts with low rigidity is a common topic in the aircraft industry, requiring vibration-controlled approaches [ 49 ].…”

Influence of machining parameters on dynamic errors in a hexapod machining cell

“…Hence, a comprehensive understanding of the impact of machining parameters on dynamic errors in HMC is crucial for achieving high-quality robotic machining in HMC. Current research on robotic machining primarily focuses on investigating the impact of machining parameters on machining quality [25,35], vibration analysis in relation to machining parameters [11], prediction of machining quality based on parameters and vibrations [12], and more [38]. However, there is still a need for further understanding of the relationship between machining parameters and dynamic errors in robotic machining.…”

Stability Analysis of Milling Chatter in Six-Degree-of-Freedom Industrial Robots

“…The selection of reasonable milling parameters plays an important role in the effective avoidance of chatter for six-DOF robots. Studies have shown that milling parameters such as spindle speed, radial depth of cut, and axial depth of cut have certain effects on chatter stability [17][18][19] . But the effect of feed rate is generally ignored.…”