Stiffness analysis and optimization in robotic drilling application

Yin, Bo; Liao, Wenhe; Tian, Wei; Zhang, Jin; Zhang, Lin

doi:10.1016/j.precisioneng.2017.04.001

Cited by 107 publications

(45 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Karim et al [61] presented a detailed experimental modal analysis within robot workspace in machining, of which results demonstrated that high TCP positions tend to change the main oscillation direction, and linear interpolation for eigenfrequencies was recognised as unsuitable for some parts of the workspace. Cutting tool direction was optimised by Bu et al [62]. In their method, a Cartesian compliance model of robot stiffness was developed, together with a quantitative evaluation index of processing performance.…”

Section: Robot Stiffnessmentioning

confidence: 99%

Industrial robotic machining: a review

Wang

2019

Int J Adv Manuf Technol

227

View full text Add to dashboard Cite

For the past three decades, robotic machining has attracted a large amount of research interest owning to the benefit of cost efficiency, high flexibility and multi-functionality of industrial robot. Covering articles published on the subjects of robotic machining in the past 30 years or so; this paper aims to provide an up-to-date review of robotic machining research works, a critical analysis of publications that publish the research works, and an understanding of the future directions in the field. The research works are organised into two operation categories, low material removal rate (MRR) and high MRR, according their machining properties, and the research topics are reviewed and highlighted separately. Then, a set of statistical analysis is carried out in terms of published years and countries. Towards an applicable robotic machining, the future trends and key research points are identified at the end of this paper.

show abstract

Section: Robot Stiffnessmentioning

confidence: 99%

Industrial robotic machining: a review

Wang

2019

Int J Adv Manuf Technol

227

View full text Add to dashboard Cite

show abstract

“…On this basis, different sampling postures of nine sampling positions could be obtained, as shown in Figure 1(b) [21]. Moreover, the joint stiffness tends to be stable with more than 10 groups sampling configurations in a stiffness identification experiment [22][23][24]. Therefore, in each sampling position of a grid space, more than two configurations should be used to ensure the accuracy of stiffness identification results.…”

Section: Space Gridding Principle Analysismentioning

confidence: 99%

Variable stiffness identification and configuration optimization of industrial robots for machining tasks

Jiao¹,

Tian²,

Zhang³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Industrial robots are increasingly used in machining tasks because of their high flexibility and intelligence. However, the low structural stiffness of the robot seriously affects the positional accuracy and machining quality of robot operation equipment. Studying robot stiffness characteristics and optimization methods is an effective way to improve robot stiffness performance. Accordingly, aiming at the poor accuracy of stiffness modeling caused by approximating stiffness of each joint as constant, a variable stiffness identification method is proposed based on space gridding. Then, a task-oriented axial stiffness evaluation index is proposed to realize quantitative assessment of the stiffness performance in the machining direction. Besides, by analyzing the redundant kinematic characteristics of the robot machining system, a configuration optimization method is further come up with to maximize the index. For a large number of points or trajectory processing tasks, a configuration smoothing strategy is proposed to achieve fast acquisition of optimized configurations. Finally, experiments on a KR500 robot are conducted to verify the feasibility and validity of proposed stiffness identification and configuration optimization methods.

show abstract

“…In order to establish the compensation strategy for hole diameter error in robotic helical milling, the robot operation stiffness needs to be analyzed first. The robot used in this paper is a novel 5-DOF hybrid robot named TriMule which Li, Xu, Wen, Qin and Huang, Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol.13, No.2 (2019) have been proposed by Tian et al(2017). As shown in Fig.…”

Section: Robot Deformation During the Helical Milling Process 21 Robmentioning

confidence: 99%

“…Meanwhile, as an essential step in the aircraft assembly, there have also been many studies on robotic drilling operation. Bu et al (2017) proposed a Cartesian compliance model to describe the drilling robot stiffness, and a quantitative evaluation index of the robots processing performance is defined. With the optimization of performance index in the cutting tool direction, higher accuracy of machined hole can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Deformation analysis and hole diameter error compensation for hybrid robot based helical milling

Wen

et al. 2019

JAMDSM

View full text Add to dashboard Cite

As an innovative machining process for hole-making, helical milling (also known as orbital drilling) presents great potential in machining aircraft structures due to temperature and cutting force reduction, flexible kinematics, and improved borehole quality. Meanwhile, the application of hybrid robot with their high accuracy and better stiffness are increased in aircraft assembly machining operations. Combining these two advanced technologies, this paper focuses primarily on the investigation of the TriMule hybrid robot elastic deformation during helical milling hole-making process and its influence on the diameter error of machined hole. The elastic deformation of series and parallel parts under cutting force condition was investigated by finite element simulation software SAMCEF. The TriMule robot helical milling experiments were also carried out to determine the variation of hole diameter error, and an offline compensation method with modifying the eccentricity at different hole depth was proposed based on the established diameter error model. From experimental verification results, it can be found that the hole diameter error of TriMule robot helical milling can be reduced and the consistency of hole diameter accuracy can be significantly improved by proposed error compensation method.

show abstract

Stiffness analysis and optimization in robotic drilling application

Cited by 107 publications

References 24 publications

Industrial robotic machining: a review

Industrial robotic machining: a review

Variable stiffness identification and configuration optimization of industrial robots for machining tasks

Deformation analysis and hole diameter error compensation for hybrid robot based helical milling

Contact Info

Product

Resources

About