RFID-based Production Data Analysis in an IoT-enabled Smart Job-shop
Under industry 4.0, Internet of Things (IoT), especially
radio frequency identification (RFID) technology, has been
widely applied in manufacturing environment. This technology
can bring convenience to production control and production
transparency. Meanwhile, it generates increasing production data
that are sometimes discrete, uncorrelated, and hard-to-use. Thus,
an efficient analysis method is needed to utilize the invaluable
data. This work provides an RFID-based production data analysis
method for production control in IoT-enabled smart job-shops.
The physical configuration and operation logic of IoT-enabled
smart job-shop production are firstly described. Based on that,
an RFID-based production data model is built to formalize and
correlate the heterogeneous production data. Then, an eventdriven
RFID-based production data analysis method is proposed
to construct the RFID events and judge the process command
execution. Furthermore, a near big data approach is used to
excavate hidden information and knowledge from the historical
production data. A demonstrative case is studied to verify the
feasibility of the proposed model and methods. It is expected
that our work will provide a different insight into the RFIDbased
production data analysis.
KeyWords
Data analysis, IoT, production control, RFID,
smart job-shop.
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