Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

A Review of Sensor Layout for Condition Monitoring during Discrete-part Manufacturing

Authors
Kang He, Nan Wang, Lin Zhu
Corresponding Author
Kang He
Available Online November 2017.
DOI
10.2991/amms-17.2017.96How to use a DOI?
Keywords
sensor deployment; optimization; condition monitoring; discrete-part manufacturing
Abstract

This paper presents in a unified way, the various strategies of optimal sensor placement for condition monitoring during discrete parts manufacturing. The objective of this paper, is to survey the current state of optimal sensor layout with two modules: sensor optimized layout for single target and sensor placement strategy under multi-targets and multi - monitoring requirements. Each approach is outlined. Finally, the recommendations and challenges faced by industry and academia are discussed and several principle conclusions are drawn.

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/).

Download article (PDF)

Volume Title
Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
Series
Advances in Intelligent Systems Research
Publication Date
November 2017
ISBN
10.2991/amms-17.2017.96
ISSN
1951-6851
DOI
10.2991/amms-17.2017.96How 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  - Kang He
AU  - Nan Wang
AU  - Lin Zhu
PY  - 2017/11
DA  - 2017/11
TI  - A Review of Sensor Layout for Condition Monitoring during Discrete-part Manufacturing
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 444
EP  - 447
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.96
DO  - 10.2991/amms-17.2017.96
ID  - He2017/11
ER  -