Machining with flexible manipulator: toward improving robotic machining performance

Zhang, Hui; Wang, Jianjun; Zhang, G.; Gan, Zhongxue; Pan, Zengxi; Cui, Huanqing; Zhu, Zhenqi

doi:10.1109/aim.2005.1511161

Cited by 103 publications

(74 citation statements)

References 8 publications

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“…Zhang et al note that the stiffness for a typical industrial robot is around 1 N/μm, whereas a typical machine tool has stiffness greater than 50 N/μm and also expresses accuracy concerns for robotic machining due to machining forces and imperfect kinematic models [14]. This is supported by Doukas et al who present experimental results on deflection behaviour [15].…”

Section: Introductionsupporting

confidence: 74%

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Barnfather

Goodfellow

Abram

2017

Int J Adv Manuf Technol

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Portable robotic machine tools potentially allow feature machining processes to be brought to large parts in various industries, creating an opportunity for capital expenditure and operating cost reduction. However, robots lack the machining capability of conventional equipment, which ultimately results in dimensional errors in parts. This work showcases a low-cost hexapod-based robotic machine tool and presents experimental research conducted to investigate how the widely researched robotic machining challenges, e.g. structural dynamics and kinematics, translate to achievable tolerance ranges in real-world production to highlight currently feasible applications and provide a context for considering technology improvements. Machining trials assess the total dimensional errors in the final part over multiple geometries. A key finding is error variation which is in the sub-millimetre range, although, in some cases, upper tolerance limits < 100 μm are achieved. Practical challenges are also noted. Most significantly, it is demonstrated that dimensional machining error is mainly systematic in nature and therefore that the total error can be dramatically reduced with in situ measurement and compensation. Potential is therefore found to achieve a flexible, highperformance robotic machining capability despite complex and diverse underlying scientific challenges. Overall, the work presented highlights achievable tolerances in lowcost robotic machining and opportunities for improvement, also providing a practical benchmark useful for process selection.

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Section: Introductionsupporting

confidence: 74%

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Barnfather

Goodfellow

Abram

2017

Int J Adv Manuf Technol

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“…The hurdle is the relatively low stiffness of industrial robots. To tackle this problem, one solution is to compensate for the compliance of the robot by adding a servo reference offset, calculated by means of the flexible multibody dynamic model with measured tool force as an input Zhang et al (2005). However, this compensation loop will have a relatively low bandwidth for larger robots, which will motivate to use also other sensor arrangements.…”

Section: Possible Future Directions Of Robot Control Developmentmentioning

confidence: 99%

Robot Control Overview: An Industrial Perspective

Brogårdh¹

2009

MIC

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One key competence for robot manufacturers is robot control, defined as all the technologies needed to control the electromechanical system of an industrial robot. By means of modeling, identification, optimization, and model-based control it is possible to reduce robot cost, increase robot performance, and solve requirements from new automation concepts and new application processes. Model-based control, including kinematics error compensation, optimal servo reference-and feed-forward generation, and servo design, tuning, and scheduling, has meant a breakthrough for the use of robots in industry. Relying on this breakthrough, new automation concepts such as high performance multi robot collaboration and human robot collaboration can be introduced. Robot manufacturers can build robots with more compliant components and mechanical structures without loosing performance and robots can be used also in applications with very high performance requirements, e.g., in assembly, machining, and laser cutting. In the future it is expected that the importance of sensor control will increase, both with respect to sensors in the robot structure to increase the control performance of the robot itself and sensors outside the robot related to the applications and the automation systems. In this connection sensor fusion and learning functionalities will be needed together with the robot control for easy and intuitive installation, programming, and maintenance of industrial robots.

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“…Zhang and Pan had reported a method to control the machining error based on deflection compensation and adaptive material removal rate (MRR) [38][39][40]. The deflection compensation was based on a stiffness matrix in Cartesian space that the researchers had developed based on experiments.…”

Section: Vibration or Chattering Analysismentioning

confidence: 99%

Robot machining: recent development and future research issues

Chen

Dong

2012

Int J Adv Manuf Technol

234

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Early studies on robot machining were reported in the 1990s. Even though there are continuous worldwide researches on robot machining ever since, the potential of robot applications in machining has yet to be realized. In this paper, the authors will first look into recent development of robot machining. Such development can be roughly categorized into researches on robot machining system development, robot machining path planning, vibration/chatter analysis including path tracking and compensation, dynamic, or stiffness modeling. These researches will obviously improve the accuracy and efficiency of robot machining and provide useful references for developing robot machining systems for tasks once thought to only be capable by CNC machines. In order to advance the technology of robot machining to the next level so that more practical and competitive systems could be developed, the authors suggest that future researches on robot machining should also focus on robot machining efficiency analysis, stiffness mapbased path planning, robotic arm link optimization, planning, and scheduling for a line of machining robots.

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Machining with flexible manipulator: toward improving robotic machining performance

Cited by 103 publications

References 8 publications

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Robot Control Overview: An Industrial Perspective

Robot machining: recent development and future research issues

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