“Integration of Machine Vision and Radio Frequency Identification (RFID) by understanding variables influencing the RFID system”
Sai Kiran Camsarapalli
Committee Members: Dr. Lash Mapa, Dr. Gokarna Aryal , Dr. Mohammad Zahraee
Machine-vision programs are used as a tool in the chain of events that will lead to making a final decision or used to make a final decision based on pre-determined attributes. A typical example would be an application involving explicitly defined single-variable pass-fail criteria where the task is to check several critical quality characteristics of an item and reject it if any of the characteristics is out of compliance. RFID systems that have interrogators (readers) are placed on manufacturing lines and conveyor lines to control and verify inventory accuracy. The read-write capability of tags on the item could be programmed to indicate the status and this feature could be used to write real-time information such as operation summary, data on critical quality characteristics and final decision on pass-fail information on the chip of the tag. The tag will then become a permanent record of the item and its history along the supply chain and information retrieval by other parties becomes possible. The problem with successful RFID implementation is the lack of application specific optimization. In a manufacturing environment the variation in product, speed of conveyor, tag position, distance of tag from antenna cannot be generalized. To gain optimum performance from an RFID system these factors should be optimized. The aim of this study is to investigate the relationship between speed of the conveyor belt, type, orientation and placement of the tag. Full factorial and fractional factorial designs are considered to determine the effect of critical factors and the interaction between them based on tag readability. Recommendations are provided for the combinations of the potential factors and their levels in order to obtain the best possible readability. This research describes a system that has been developed to integrate the vision assisted fault diagnosis to continuously monitor items and record critical characteristics associated with it that can be retrieved, on a RFID tag.