Optimization of supply chain management by simulation based RFID with XBEE Network - Soomro, Aftab Ahmed (2015)
The aim of every Supply Chain Management (SCM) is to reduce the operational cost and maximize the benefits. These necessitate the use of advance technology to optimize the operational activities. Among the widely used technology in recent years is Radio Frequency Identification (RFID). It is an advanced Auto-ID wireless network based configuration system used for identification and tracking of items movement data. Technically, basic requirements for deploying RFID network are to identify the number of readers needed, location of the readers and the efficient parameter setting for each reader. Among the problems associated with RFID technology are the multi-objective optimizations, which include tags coverage, economic efficiency, interference and load balance. In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. This algorithm computes the optimal results of objective functions in a scientific manner. However, RFID reader is an expensive and has limited data transmission range. It alone cannot transmit data to the main server. Thus, its communication range was enhanced by the integration of RFID with XBee (ZigBee) wireless mesh network devices. Furthermore, the identification data need to be monitored and transmitted to the business organizations, which are connected through the network. This has been achieved by the integration of RFID-XBee network with database connectivity through Internet of Things (IoT). This integrated system provides the visibility of items at real time identification and tracking activity at single control platform. This system also provides data sharing activity with business enterprises using IoT. The benefits of this system include reduction of shrinkage and data transfer time in global network. This system also increases the accuracy, productivity and improves delivery of service in supply chain to the optimum level. This would contribute towards a more sustainable and green supply chain management.