Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

Fault Characteristics Analysis of Industrial Robot Based on Fault Tree

Authors
Jian Jiao, Xuejiao Zheng
Corresponding Author
Jian Jiao
Available Online May 2017.
DOI
10.2991/icmeit-17.2017.32How to use a DOI?
Keywords
Industrial Robot, Fault characteristics, Predictive maintenance.
Abstract

In order to construct the predictive maintenance optimization model, this paper takes the robotic intelligent processing and production workstation as an example, and analyzes the fault characteristics of the equipment on the workstation and the fault characteristics of the key components. The failure characteristics of the equipment can be characterized and the fault characteristic parameters need to be monitored, and the failure threshold is finally determined. This method can make the multi-equipment system maintenance timing planning and processing to get a reasonable arrangement and organization.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
Series
Advances in Computer Science Research
Publication Date
May 2017
ISBN
978-94-6252-338-8
ISSN
2352-538X
DOI
10.2991/icmeit-17.2017.32How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jian Jiao
AU  - Xuejiao Zheng
PY  - 2017/05
DA  - 2017/05
TI  - Fault Characteristics Analysis of Industrial Robot Based on Fault Tree
BT  - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
PB  - Atlantis Press
SP  - 179
EP  - 182
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-17.2017.32
DO  - 10.2991/icmeit-17.2017.32
ID  - Jiao2017/05
ER  -