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A market-based approach for dynamic vehicle deployment planning using radio frequency identification (RFID) information

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  • Kim, Jindae
  • Ok, Chang-Soo
  • Kumara, Soundar
  • Yee, Shang-Tae

Abstract

Recently active radio-frequency identification (RFID) has drawn a lot of attention because of its capability to provide visibility of a dynamically moving object in a constantly changing operational environment by enabling instant identification and automatic information transfer. When a vehicle moves around in an automotive manufacturing plant shipment yard, the RFID system keeps track of the vehicle's location in near real-time until it is shipped to a dealer. These real-time location data from the RFID can be utilized to make a better decision to deploy a finished vehicle to a parking slot in the shipment yard. This paper presents an approach for RFID-enabled finished vehicle deployment planning, which is based on market-based decision-making framework having a multiagent computational architecture to process and coordinate real-time changes in vehicle locations and make a timely decision. Experimental results using simulation show that the proposed vehicle deployment planning approach improves a great deal of vehicle deployment performance in terms of the operational time, shipment yard utilization, and labor consumption.

Suggested Citation

  • Kim, Jindae & Ok, Chang-Soo & Kumara, Soundar & Yee, Shang-Tae, 2010. "A market-based approach for dynamic vehicle deployment planning using radio frequency identification (RFID) information," International Journal of Production Economics, Elsevier, vol. 128(1), pages 235-247, November.
    • Handle: RePEc:eee:proeco:v:128:y:2010:i:1:p:235-247
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    1. Yingfeng Zhang & Geng Zhang & Yang Liu & Di Hu, 2017. "Research on services encapsulation and virtualization access model of machine for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1109-1123, June.
    2. Zhang, Yingfeng & Zhang, Geng & Du, Wei & Wang, Junqiang & Ali, Ebad & Sun, Shudong, 2015. "An optimization method for shopfloor material handling based on real-time and multi-source manufacturing data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 282-292.
    3. Zhi-Hua Hu & Yingxue Zhao & Sha Tao & Zhao-Han Sheng, 2015. "Finished-vehicle transporter routing problem solved by loading pattern discovery," Annals of Operations Research, Springer, vol. 234(1), pages 37-56, November.

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