Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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Predictive Maintenance of the Robot Trouble Using the Machine Learning Method

Machine Learning기법을 이용한 Robot 이상 예지 보전

  • Choi, Jae Sung (Department of Semiconductor Equipment Engineering, Far East University)
  • 최재성 (극동대학교 반도체장비공학과)
  • Received : 2020.01.31
  • Accepted : 2020.03.18
  • Published : 2020.03.31
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Abstract

In this paper, a predictive maintenance of the robot trouble using the machine learning method, so called MT(Mahalanobis Taguchi), was studied. Especially, 'MD(Mahalanobis Distance)' was used to compare the robot arm motion difference between before the maintenance(bearing change) and after the maintenance. 6-axies vibration sensor was used to detect the vibration sensing during the motion of the robot arm. The results of the comparison, MD value of the arm motions of the after the maintenance(bearing change) was much lower and stable compared to MD value of the arm motions of the before the maintenance. MD value well distinguished the fine difference of the arm vibration of the robot. The superior performance of the MT method applied to the prediction of the robot trouble was verified by this experiments.

Keywords

References

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