Adetiloye, Kehinde Oluyemisi (2012) Design of RFID-enabled Aircraft Reverse Logistics Network Simulation. Masters thesis, Concordia University.
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Abstract
The reverse logistics (RL) of aircrafts pose a big challenge to its owners due to the complexity of its RL network, and the inherit problems of realizing a reliable system for efficiently monitoring and tracking the numerous parts of end-of-life (EOL) aircrafts in the RL network. Radio frequency identification (RFID) technology, through its automatic and wireless data capture capability, offers great potential for counteracting this problem. Although widespread and cost-effective, traditional barcode system, unlike RFID technology, requires manual scanning and line-of-sight for its use.
In this research, thorough review of literature was conducted to identify the technological and economical impacts of RFID technology in both forward and RL network, and the knowledge acquired was employed to develop a scenario based approach for determining suitable RFID solutions for use in different sections of the EOL aircraft RL network. Process maps for case-level barcode tagging, item-level RFID tagging, case-level RFID tagging and pallet-level RFID tagging in EOL aircraft RL were developed and simulated in Arena simulation software in order to comparatively analyze the Return-On-Investment (ROI) of the different RFID technology levels.
The results of our research, focusing on passive RFID technology, demonstrate that use of RFID technology in EOL aircraft RL network offers great potential compared to barcode system; however, the high initial investment cost of RFID technology deployment may necessitate proper planning, such as business process re-engineering (BPR), tag reuse and phased implementation, to achieve more positive ROI.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering |
|---|---|
| Item Type: | Thesis (Masters) |
| Authors: | Adetiloye, Kehinde Oluyemisi |
| Institution: | Concordia University |
| Degree Name: | M.A. Sc. |
| Program: | Quality Systems Engineering |
| Date: | September 2012 |
| Thesis Supervisor(s): | Awasthi, Anjali and Hammad, Amin |
| Keywords: | Reverse logistics, EOL aircrafts, Radio Frequency Identification (RFID), Simulation model, ROI. |
| ID Code: | 974802 |
| Deposited By: | KEHINDE OLUYEMI ADETILOYE |
| Deposited On: | 25 Oct 2012 15:35 |
| Last Modified: | 18 Jan 2018 17:39 |
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