Logistics exceptions monitoring for anti-counterfeiting in RFID-enabled supply chains

Abstract

In recent years, the radio frequency identification (RFID) technology has been used as a promising tool for anti-counterfeiting in RFID-enabled supply chains due to its track-and-trace abilities of contactless object identification with the unique electronic product code (EPC). While this system does improve its performance in many ways, uncertainties of daily operations might bring about one or more logistics exceptions, which would further trigger other dependent exceptions. These exceptions could be well organized and exploited by adversaries to fool the system for counterfeiting while related reports are unfortunately very few. In this paper, we presented our results focusing on the inter-dependencies between those logistics exceptions and the detecting intelligence in a resource-centric view. A cause-effect relational diagram is first developed to explicitly express the relations among those logistics exceptions by incorporating the taxonomy of exceptions and resource-based theory, and then an improved intelligent exception monitoring system is designed to achieve the goal of autonomous, flexible, collaborative and reliable logistics services. Finally, a case study of two typical logistics exceptions indicates that our proposed cause-effect diagram outperforms the extant approaches in the understanding of group logistics exceptions, which enables the designed monitoring system to perform well for anti-counterfeiting.