Food Science of Animal Resources (한국축산식품학회지)

Korean Society for Food Science of Animal Resources (한국축산식품학회)
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RFID-based Supply Chain Process Mining for Imported Beef

  • Kang, Yong-Shin (u-SCM Research Center, Nano Information Technology Academy, Dongguk University) ;
  • Lee, Kyounghun (u-SCM Research Center, Nano Information Technology Academy, Dongguk University) ;
  • Lee, Yong-Han (Department of Industrial and Systems Engineering, Dongguk University) ;
  • Chung, Ku-Young (Department of Animal Resources Science, Sangji University)
  • Received : 2013.04.30
  • Accepted : 2013.07.22
  • Published : 2013.08.31
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Abstract

Through the development of efficient data collecting technologies like RFID, and inter-enterprise collaboration platforms such as web services, companies which participate in supply chains can acquire visibility over the whole supply chain, and can make decisions to optimize the overall supply chain networks and processes, based on the extracted knowledge from historical data collected by the visibility system. Although not currently active, the MeatWatch system has been developed, and is used in part for this purpose, in the imported beef distribution network in Korea. However, the imported beef distribution network is too complicated to analyze its various aspects using ordinary process analysis approaches. In this paper, we suggest a novel approach, called RFID-based supply chain process mining, to automatically discover and analyze the overall supply chain processes from the distributed RFID event data, without any prior knowledge. The proposed approach was implemented and validated, by using a case study of the imported beef distribution network in Korea. Specifically we demonstrated that the proposed approach can be successfully applied to discover supply chain networks from the distributed event data, to simplify the supply chain networks, and to analyze anomaly of the distribution networks. Such novel process mining functionalities can reinforce the capability of traceability services like MeatWatch in the future.

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References

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