The purpose of this paper is to propose a comprehensive framework for integrating big data analytics (BDA) into cyber-physical system (CPS) solutions. This framework provides a wide range of functions, including data collection, smart data preprocessing, smart data mining and smart data visualization.
The architecture of CPS was designed with cyber layer, physical layer and communication layer from the perspective of big data processing. The BDA model was integrated into a CPS that enables managers to make sound decisions.
The effectiveness of the proposed BDA model has been demonstrated by two practical cases − the prediction of energy output of the power grid and the estimate of the remaining useful life of the aero-engine. The method can be used to control the power supply system and help engineers to maintain or replace the aero-engine to maintain the safety of the aircraft.
The communication layer, which connects the cyber layer and physical layer, was designed in CPS. From the communication layer, the redundant raw data can be converted into smart data. All the necessary functions of data collection, data preprocessing, data storage, data mining and data visualization can be effectively integrated into the BDA model for CPS applications. These findings show that the proposed BDA model in CPS can be used in different environments and applications.
All the authors contributed equally to this paper.
Luo, S., Liu, H. and Qi, E. (2019), "Big data analytics – enabled cyber-physical system: model and applications", Industrial Management & Data Systems, Vol. 119 No. 5, pp. 1072-1088. https://doi.org/10.1108/IMDS-10-2018-0445
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