A Manufacturing Big Data Solution for Active Preventive Maintenance

Industry 4.0 has become more popular due to recent developments in cyber-physical systems, 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 offline 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.

[1]  Miriam Schleipen.  OPC UA supporting the automated engineering of production monitoring and control systems , 2008, 2008 IEEE International Conference on Emerging Technologies and Factory Automation.

[2]  Hashem M. Hashemian,et al.  State-of-the-Art Predictive Maintenance Techniques* , 2011, IEEE Transactions on Instrumentation and Measurement.

[3]  Xun Xu,et al.  From cloud computing to cloud manufacturing , 2012 .

[4]  Depei Qian,et al.  Differentiating data collection for cloud environment monitoring , 2013, 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013).

[5]  Yeu-Shiang Huang,et al.  Two-Dimensional Warranty With Reliability-Based Preventive Maintenance , 2013, IEEE Transactions on Reliability.

[6]  Lei Yu,et al.  Efficient Data Collection for Large-Scale Mobile Monitoring Applications , 2014, IEEE Transactions on Parallel and Distributed Systems.

[7]  Yunhao Liu,et al.  Big Data: A Survey , 2014, Mob. Networks Appl..

[8]  Uwe Mönks,et al.  Fast classification in industrial Big Data environments , 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

[9]  Gabriella Balestra,et al.  Preventive Maintenance Prioritization Index of Medical Equipment Using Quality Function Deployment , 2015, IEEE Journal of Biomedical and Health Informatics.

[10]  C. K. M. Lee,et al.  Research on IoT based Cyber Physical System for Industrial big data Analytics , 2015, 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).

[11]  Shijun Liu,et al.  IBDP: An Industrial Big Data Ingestion and Analysis Platform and Case Studies , 2015, 2015 International Conference on Identification, Information, and Knowledge in the Internet of Things (IIKI).

[12]  Tarik Taleb,et al.  An Unlicensed Taxi Identification Model Based on Big Data Analysis , 2016, IEEE Transactions on Intelligent Transportation Systems.

[13]  Daqiang Zhang,et al.  Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination , 2016, Comput. Networks.

[14]  Daqiang Zhang,et al.  Cloud-Integrated Cyber-Physical Systems for Complex Industrial Applications , 2015, Mobile Networks and Applications.

[15]  Wendong Wang,et al.  Energy-Efficient Software-Defined Data Collection by Participatory Sensing , 2016, IEEE Sensors Journal.

[16]  Shiyan Hu,et al.  Preventive Maintenance for Advanced Metering Infrastructure Against Malware Propagation , 2016, IEEE Transactions on Smart Grid.

[17]  Itai Regev,et al.  Segmentation Models for the Duration of Expected Preventive Maintenance in Semiconductor Fabs , 2016, IEEE Transactions on Semiconductor Manufacturing.

[18]  Zhezhuang Xu,et al.  Joint Clustering and Routing Design for Reliable and Efficient Data Collection in Large-Scale Wireless Sensor Networks , 2016, IEEE Internet of Things Journal.

[19]  Jiafu Wan,et al.  Implementing Smart Factory of Industrie 4.0: An Outlook , 2016, Int. J. Distributed Sens. Networks.

[20]  Mianxiong Dong,et al.  RMER: Reliable and Energy-Efficient Data Collection for Large-Scale Wireless Sensor Networks , 2016, IEEE Internet of Things Journal.

[21]  Houbing Song,et al.  Internet of Things and Big Data Analytics for Smart and Connected Communities , 2016, IEEE Access.