Enhancement of design and development of Radio Frequency Identification (RFID) zigbee mesh network for material flow system

Methods of manually recording data, using barcodes and tracking distance constraints are problems encountered during handling of materials inside a manufacturing facility. However, Radio Frequency Identification (RFID) technology is not new but now as an effort to automate the operation and process of the mill to achieve optimum production. The aim of this study is to develop a production line monitoring system to track the current location of processed products where it underestimates and takes time to be tracked clearly by traditional methods. This proposed system is named Smart Material Flow System (Smart MFS) is to improve the efficiency of locating product in real time in the industrial plant. This novel system was developed based on the Waterfall model. The research methodology involves two parts namely hardware and software. The hardware combines passive RFID and active RFID while the software a General User Interface (GUI) for users to interact with electronic devices through graphical icons and visual indicators. The system WAS implemented in the Wireless Mesh Network (WMN) environment whose performance is assessed in terms of maximum read range for indoor environment, output power level versus read range, multi tags communication efficiency. The results of the assessment indicate that the maximum reading range is 2.45 meters for passive wireless communication, while 95 meters for active wireless communication. The power level for active wireless communication indicates that as output power increases, the distance of active wireless communication readings also increases. The communication efficiency of various tags can reach 100% of data received at a distance of 15 meters. The findings show that Smart MFS can be used to improve product location accuracy in real-time where Smart MFS has the ability to detect and track material flows from warehouse until shipping to overcome uncontrolled manual tracking and reduce labor costs.