Robot accuracy degradation sensing, monitoring, and assessment are critical activities in many industrial robot applications, especially when it comes to the high accuracy operations which may include welding, material removal, robotic drilling, and robot riveting. The degradation of robot tool center accuracy can increase the likelihood of unexpected shutdowns and decrease manufacturing quality and production efficiency. The development of monitoring, diagnostic and prognostic (collectively known as prognostics and health management (PHM)) technologies can aid manufacturers in maintaining the performance of robot systems. PHM can provide the techniques and tools to support the specification of a robot’s present and future health state and optimization of maintenance strategies. This paper presents the robotic PHM research and the development of a quick health assessment at the U.S. National Institute of Standards and Technology (NIST). The research effort includes the advanced sensing development to measure the robot tool center position and orientation; a test method to generate a robot motion plan; an advanced robot error model that handles the geometric/nongeometric errors and the uncertainties of the measurement system, and algorithms to process measured data to assess the robot’s accuracy degradation. The algorithm has no concept of the traditional derivative or gradient for algorithm converging. A use case is presented to demonstrate the feasibility of the methodology.
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July 2019
Research-Article
Industrial Robot Accuracy Degradation Monitoring and Quick Health Assessment
Guixiu Qiao,
Guixiu Qiao
1
Mem. ASME
100 Bureau Drive, Gaithersburg, MD 20899
e-mail: guixiu.qiao@nist.gov
National Institute of Standards and Technology
,100 Bureau Drive, Gaithersburg, MD 20899
e-mail: guixiu.qiao@nist.gov
1Corresponding author.
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Brian A. Weiss
Brian A. Weiss
Mem. ASME
100 Bureau Drive, Gaithersburg, MD 20899
e-mail: brian.weiss@nist.gov
National Institute of Standards and Technology
,100 Bureau Drive, Gaithersburg, MD 20899
e-mail: brian.weiss@nist.gov
Search for other works by this author on:
Guixiu Qiao
Mem. ASME
100 Bureau Drive, Gaithersburg, MD 20899
e-mail: guixiu.qiao@nist.gov
National Institute of Standards and Technology
,100 Bureau Drive, Gaithersburg, MD 20899
e-mail: guixiu.qiao@nist.gov
Brian A. Weiss
Mem. ASME
100 Bureau Drive, Gaithersburg, MD 20899
e-mail: brian.weiss@nist.gov
National Institute of Standards and Technology
,100 Bureau Drive, Gaithersburg, MD 20899
e-mail: brian.weiss@nist.gov
1Corresponding author.
Manuscript received March 18, 2019; final manuscript received April 26, 2019; published online May 14, 2019. Assoc. Editor: Y. Lawrence Yao.
This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.
J. Manuf. Sci. Eng. Jul 2019, 141(7): 071006 (7 pages)
Published Online: May 14, 2019
Article history
Received:
March 18, 2019
Revision Received:
April 26, 2019
Accepted:
April 28, 2019
Citation
Qiao, G., and Weiss, B. A. (May 14, 2019). "Industrial Robot Accuracy Degradation Monitoring and Quick Health Assessment." ASME. J. Manuf. Sci. Eng. July 2019; 141(7): 071006. https://doi.org/10.1115/1.4043649
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