Embedded devices for supply chain applications: Towards hardware integration of disparate technologies

  • Authors:

  • Ahmed Musa;Angappa Gunasekaran;Yahaya Yusuf;Abdelrahman Abdelazim

  • Affiliations:

  • Division of Systems and Operations, Lancashire Business School, University of Central Lancashire, Preston PR1 2HE, United Kingdom;Department of Decision and Information Sciences, Charlton College of Business, University of Massachusetts-Dartmouth, United States;Division of Systems and Operations, Lancashire Business School, University of Central Lancashire, Preston PR1 2HE, United Kingdom;College of Engineering, American University of the Middle East, Egaila, Kuwait

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2014

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Abstract

The emergence of the RFID technology and its application to supply chain processes has in particular led to the creation of such standards as the EPCglobal's model of supply networks as a tool for materializing intra- and inter-enterprise visibility of resources and products, collaboration and integration. Among other critical uses, RFID has been deployed by supply networks to improve asset utilization, effectively combat counterfeiting, and advance targeted product recalls. However, new affordable and deployable technologies and microsensors have recently appeared and keep maturing. This paper discusses the needs and the possibilities that exist for leveraging these technologies and sensors with RFID to guarantee continuous and seamless visibility of all assets (fixed and mobile resources and field personnel) of smart enterprises, thereby expanding and complementing the roles of RFID. It examines the design challenges for the integration of these technologies for advanced logistics operations at the level of product classes or their instances. It then outlines our development of an embedded microsystem that combines RFID, GPRS, GPS and environmental sensors for applications in logistics. The prototyped microsystem demonstrated the feasibility of the multi-sensor integration paradigm that the paper proposes.