A Method for Mode Coupling Chatter Detection and Suppression in Robotic Milling

Cen, Lejun; Melkote, Shreyes N.; Castle, James; Appelman, Howard

doi:10.1115/1.4040161

Cited by 37 publications

(7 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The author established a 2DOF dynamic model of the robotic arm milling process by simplifying the cutting force, and obtained the stability criterion in the machining plane by using BIBO stability criterion. Cen et al (Cen et al, 2018; investigated the effect of cutting force on the mode coupling chatter of robotic arm milling, and improved the criterion proposed by Pan et al via introducing the conservative matrix transformation to optimize the feed rate. Mousavi et al (2018) focused on the dynamic model-based predictions of stable and unstable zones along a robotic machining trajectory with one degree of functional redundancy.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional stability analysis of robotic machining process

Dai

Chen

et al. 2019

View full text Add to dashboard Cite

Purpose Since robot’s structural stiffness is usually less than 1 N/µm, mode coupling chatter occurs frequently during robotic milling process, and chatter frequency is close to the natural frequency of the robot itself. Chatter not only affects the surface quality but also damages the robot and reduces the positioning accuracy. Therefore, it is necessary to predict chatter in robotic machining process. Design/methodology/approach A three-dimensional dynamic model for robot’s spatial milling plane is established, and a corresponding stability criterion is obtained. First, the cutting force in milling plane is transformed into the coordinate system of the robot principal stiffness direction based on homogeneous transformation matrix. Then the three-dimensional stability criterion under milling process can be obtained by using system stability analysis. Furthermore, the circle diagram of mode coupling chatter stability is drawn. Each feeding direction’s stability under the two processing forms, referred as spindle vertical milling and spindle horizontal milling, is analyzed. Findings The experimental results verify that the three-dimensional stability criterion can avoid chatter by selecting machining feed direction in stable area. Originality/value This paper established a three-dimensional dynamic model in robot’s spatial milling plane and proposed a three-dimensional stability criterion according to the Routh criterion. The work is also expected to be an efficient tool in the development of robotic milling technology.

show abstract

Section: Introductionmentioning

confidence: 99%

Three-dimensional stability analysis of robotic machining process

Dai

Chen

et al. 2019

View full text Add to dashboard Cite

show abstract

“…They subsequently developed a stability chart that can be used to select chatter-free spindle speeds when machining aluminum. In their robotic milling experiments on a KUKA KR210 IR, Cen et al [23] also found that chatter instability occurs more readily when milling in one Cartesian coordinate direction compared to milling in a direction orthogonal to it. Mousavi et al [24] have also shown that the natural frequencies of a serial-link robot can vary significantly along a tool path due to a continuously changing robot configuration.…”

Section: Robot Stiffnessmentioning

confidence: 99%

Robots in machining

et al. 2019

View full text Add to dashboard Cite

Robotic machining centers offer diverse advantages: large operation reach with large reorientation capability, and a low cost, to name a few. Many challenges have slowed down the adoption or sometimes inhibited the use of robots for machining tasks. This paper deals with the current usage and status of robots in machining, as well as the necessary modelling and identification for enabling optimization, process planning and process control. Recent research addressing deburring, milling, incremental forming, polishing or thin wall machining is presented. We discuss various processes in which robots need to deal with significant process forces while fulfilling their machining task.

show abstract

“…However, the research on robotic milling technology has mainly focused on improving the robotic machining accuracy and the vibration suppression during the milling process, and the research and comprehensive analysis on the influence of milling parameters on milling load, surface quality and vibration during robotic milling are insufficient. Therefore, it is necessary to study the effects of process parameters on robotic milling performance [ 10 , 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Contribution Ratio Assessment of Process Parameters on Robotic Milling Performance

Dai

Yue

et al. 2022

Materials

View full text Add to dashboard Cite

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.

show abstract

A Method for Mode Coupling Chatter Detection and Suppression in Robotic Milling

Cited by 37 publications

References 24 publications

Three-dimensional stability analysis of robotic machining process

Three-dimensional stability analysis of robotic machining process

Robots in machining

Contribution Ratio Assessment of Process Parameters on Robotic Milling Performance

Contact Info

Product

Resources

About