A predictive maintenance method for products based on big data analysis

DOI

10.2991/meita-15.2015.71How to use a DOI?

Keywords

Predictive maintenance, PLM, IoT, R&M, O&M, big data, data mining

Abstract

Recently, withmanufacturing enterprises have begun to widely useadvanced information technology to real-time monitor of their business and product, a large amount of data related to product lifecycle were produced. Typical challenges for maintenanceunder the environment of big data is facing now are lacking of timely and accurate data of products, and lackingof useful pattern and knowledge of product lifecycle. To address this problem,in this research, by using the technologies of Internet of Things (IoT), anarchitecture of Research and Manufacturing (R&M) and Operation and Maintenance (O&M) process big data acquisition was proposed. Based on the R&M and O&M big data, a real-time decision making method for predictive maintenance was discussed, and the data flow model of predictive maintenance based on big data mining was also established.

Copyright

© 2015, 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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TY  - CONF
AU  - Shan Ren
AU  - Xin Zhao
PY  - 2015/08
DA  - 2015/08
TI  - A predictive maintenance method for products based on big data analysis
BT  - Proceedings of the 2015 International Conference on Materials Engineering and Information Technology Applications
PB  - Atlantis Press
SP  - 385
EP  - 390
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-15.2015.71
DO  - 10.2991/meita-15.2015.71
ID  - Ren2015/08
ER  -