RFID systems optimisation through the use of a new RFID network planning algorithm to support the design of receiving gates

Henriette Knapp () and Giovanni Romagnoli ()
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Henriette Knapp: University of Parma
Giovanni Romagnoli: University of Parma

Journal of Intelligent Manufacturing, 2023, vol. 34, issue 3, No 24, 1389-1407

Abstract: Abstract Radio frequency identification (RFID) is a widespread technology used in several different industries. One of its common use cases in logistics is the automation of goods receipt. RFID gates are often deployed, to automatically detect tagged items or load carriers during their passage through the goods receipt gate. At present, however, the design of RFID gates is often based on estimations, and their commissioning is mostly approached via trial and error. Even if the RFID network planning problem is known in the literature, existing algorithms cannot be applied to the design of RFID gates due to some limitations. In this paper, we propose a new evolutionary RFID network planning algorithm to design RFID gates optimally. The objective of our algorithm is to minimise the number of antennas and to adjust their mounting heights and angles. The algorithm ensures a tag coverage of at least 99%, prevents reflections on the ground, and can be used in the future as a standard for planning and commissioning RFID-enabled goods receipt gates. To demonstrate the applicability of our algorithm, we deployed it in a case study involving logistics of the automotive sector. The results of the deployment confirm the quality of our approach, as the RFID gate optimised by the algorithm deployed 4 antennas, with a vertical coverage rate of 99.96%, an horizontal coverage rate of 89.66%, and very interesting values of other evaluation functions, namely load balance and overlapping rate.

Keywords: Radio-frequency identification (RFID); RFID network planning; Evolutionary algorithm; RFID receiving gate; Automotive industry; Logistics (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10845-021-01858-0

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