Experimental study of stability prediction for high-speed robotic milling of aluminum

Hao, Daxian; Wang, Wei; Liu, Zhaoheng; Chen, Yun

doi:10.1177/1077546319880376

Cited by 28 publications

(6 citation statements)

References 30 publications

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“…This fact underlines that the AVC needs an accurate identification of the disturbance frequency to guarantee the disturbance compensation.The AVC system shows the reduction of vibrations in the middle–high-frequency range. In particular, the FFT analysis (Figure 11) states a vibration peak at 308 Hz that is presumably generated by the chatter phenomenon (Ford et al, 2014; Hao et al, 2020). It is demonstrated that this disturbance influences the workpiece quality surface and accuracy and produces harsh noise and accelerate tool wear.…”

Section: Experimental Tests and Results In Mimo Configurationmentioning

confidence: 99%

Active vibration control development in ultra‐precision machining

Aggogeri

Merlo

Pellegrini

2020

Journal of Vibration and Control

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This study presents a combined feedback–feedforward adaptive regulator applied to an active vibration control tool holder platform to contain the effect of machining vibrations. The proposed mechatronic solution can be integrated in a milling machine tool as an interface between the beam ( Z-axis) and the tool holder. The aim is to counteract vibrations in the broadband frequency range (100 Hz–900 Hz), controlling the tool position in real time. The active vibration control system is based on the harmonic steady-state concept due to the sinusoidal representation of the disturbance signals. The study focuses on the regulator architecture and the main logics applied to satisfy the required performance. A full investigation is executed through simulations and experimental campaigns, proving the disturbance reduction. The active vibration control system is implemented on a 4-axis machine tool and validated using multitonal disturbances. The system is evaluated in compensating a set of undesired effects, such as vibrations generated by unbalanced tools or hard material cutting processes. The obtained results show a maximum reduction of the vibration amplitude by 43.7% at the critical frequency.

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Section: Experimental Tests and Results In Mimo Configurationmentioning

confidence: 99%

Active vibration control development in ultra‐precision machining

Aggogeri

Merlo

Pellegrini

2020

Journal of Vibration and Control

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“…Substitute the harmonic solution ( ) : ( ) (10) 4.1.3 The limit cutting depth of the regenerative chatter…”

Section: Regenerative Chatter Dynamic Modelmentioning

confidence: 99%

“…However, some researchers [10][11][12] found through experimental research that regenerative chatter is the main reason for the instability of robot high-speed milling process. Chatter will not only affect the machining quality, reduce the tool life, and even damage the robot.…”

Section: Introductionmentioning

confidence: 99%

Optimization of redundant degree of freedom in robot milling considering chatter stability

Liu

Wang

et al. 2022

Preprint

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Aiming at the redundant degree of freedom problem of six axis industrial robot performing five axis milling task, a new optimization method of robot milling redundant degrees of freedom considering chatter stability was proposed. Taking the limit cutting depth of robot milling regenerative chatter as the optimization objective, and combined with the constraints of robot motion performance (avoiding joint limit, singular pose and collision), a redundant degree of freedom optimization model considering chatter stability was established. The milling experimental results showed that the new optimization method of robot milling redundant degrees of freedom considering chatter stability proposed in this paper can effectively avoid robot milling regenerative chatter and improve machining quality and efficiency.

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“…Hao et al conducted an experimental study of stability prediction for high-speed robotic milling of aluminum. Modal tests were conducted on a milling robot by using a laser tracker and a displacement sensor [ 15 ]. Yin et al studied the machining error prediction and compensation technology for a stone-carving robotic manipulator.…”

Section: Introductionmentioning

confidence: 99%

Contribution Ratio Assessment of Process Parameters on Robotic Milling Performance

Dai

Yue

et al. 2022

Materials

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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.

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Experimental study of stability prediction for high-speed robotic milling of aluminum

Cited by 28 publications

References 30 publications

Active vibration control development in ultra‐precision machining

Active vibration control development in ultra‐precision machining

Optimization of redundant degree of freedom in robot milling considering chatter stability

Contribution Ratio Assessment of Process Parameters on Robotic Milling Performance

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