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Robotic machining of aluminum alloy: evaluation of performance and part accuracy

Zhang, Jingxin LU (2022) MMTM05 20221
Production and Materials Engineering
Abstract
The automated machining is typically performed by CNC (Computer Numerical Control) machinery due to the high stiffness and accuracy provided by these machines, which are expensive and comparably big. For softer materials, such as aluminum, machining is possible using the less stiff industrial robot arm. This is attractive because the robot arm has a much lower cost than CNC combined with a larger work volume. Machining packages are now available for several robot brands, enabling robots to read and execute CNC G-code. It is particularly beneficial for small and medium enterprises. Robot arms are, however, less stiff and strong, resulting in less accuracy.
In this thesis, the idea was that by using the IRB 2400 robot to mill typical... (More)
The automated machining is typically performed by CNC (Computer Numerical Control) machinery due to the high stiffness and accuracy provided by these machines, which are expensive and comparably big. For softer materials, such as aluminum, machining is possible using the less stiff industrial robot arm. This is attractive because the robot arm has a much lower cost than CNC combined with a larger work volume. Machining packages are now available for several robot brands, enabling robots to read and execute CNC G-code. It is particularly beneficial for small and medium enterprises. Robot arms are, however, less stiff and strong, resulting in less accuracy.
In this thesis, the idea was that by using the IRB 2400 robot to mill typical process paths to evaluate the performance and part accuracy in robotic machining of aluminum alloy. A pre-study towards a standard proposal for measuring robotic machining performance was performed.
Proper process parameters for robotic milling were applied, and the robot’s task was to repeatedly mill parts in different postures. The path accuracy, microstructure, and milling forces were analyzed. Results showed that the posture of the robot has a significant effect on path accuracy. With a proper posture, the path accuracy could be under 0.01mm. (Less)
Please use this url to cite or link to this publication:
author
Zhang, Jingxin LU
supervisor
organization
course
MMTM05 20221
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Robotic machining, Path accuracy, Performance, Posture.
report number
CODEN:LUTMDN/(TMMV-5344)/1-80/2022
language
English
id
9089622
date added to LUP
2022-06-17 10:37:37
date last changed
2022-06-17 14:33:04
@misc{9089622,
  abstract     = {{The automated machining is typically performed by CNC (Computer Numerical Control) machinery due to the high stiffness and accuracy provided by these machines, which are expensive and comparably big. For softer materials, such as aluminum, machining is possible using the less stiff industrial robot arm. This is attractive because the robot arm has a much lower cost than CNC combined with a larger work volume. Machining packages are now available for several robot brands, enabling robots to read and execute CNC G-code. It is particularly beneficial for small and medium enterprises. Robot arms are, however, less stiff and strong, resulting in less accuracy.
In this thesis, the idea was that by using the IRB 2400 robot to mill typical process paths to evaluate the performance and part accuracy in robotic machining of aluminum alloy. A pre-study towards a standard proposal for measuring robotic machining performance was performed.
Proper process parameters for robotic milling were applied, and the robot’s task was to repeatedly mill parts in different postures. The path accuracy, microstructure, and milling forces were analyzed. Results showed that the posture of the robot has a significant effect on path accuracy. With a proper posture, the path accuracy could be under 0.01mm.}},
  author       = {{Zhang, Jingxin}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Robotic machining of aluminum alloy: evaluation of performance and part accuracy}},
  year         = {{2022}},
}