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A Manufacturing Big Data Solution for ActivePreventive Maintenance
Guangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology, South China University of Technology.
School of Mechanical and Automotive Engineering, South China University of Technology.
School of Mechanical and Automotive Engineering, South China University of Technology.
School of Mechanical and Automotive Engineering, South China University of Technology.
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2017 (English)In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050Article in journal (Refereed) Epub ahead of print
Abstract [en]

Industry 4.0 has become more popular due to recent developments in Cyber-Physical Systems (CPS), big data, cloud computing, and industrial wireless networks. Intelligent manufacturing has produced a revolutionary change, and evolving applications such as product lifecycle management are becoming a reality. In this paper, we propose and implement a manufacturing big data solution for active preventive maintenance in manufacturing environments. First, we provide the system architecture that is used for active preventive maintenance. Then, we analyze the method used for collection of manufacturing big data according to the data characteristics. Subsequently, we perform data processing in the cloud, including the cloud layer architecture, the real-time active maintenance mechanism, and the off-line prediction and analysis method. Finally, we analyze a prototype platform and implement experiments to compare the traditionally-used method with the proposed active preventive maintenance method. The manufacturing big data method used for active preventive maintenance has the potential to accelerate implementation of Industry 4.0.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-64511DOI: 10.1109/TII.2017.2670505OAI: oai:DiVA.org:ltu-64511DiVA: diva2:1115220
Available from: 2017-06-26 Created: 2017-06-26 Last updated: 2017-06-26

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