Radio Frequency Identification (RFID) is an automatic identification technology, relying on storing and remotely retrieving data using devices called RFID tags. This technology is being used in enterprise supply chain management-related applications to improve the efficiency of inventory tracking and management. However, this technology has not been able to realize its promised potential because of several factors, such as lack of congruous worldwide standards, privacy issues and less than perfect read rates in supply chain applications. This research aimed to evaluate the readability issues commonly faced by tagged cases of palletized consumer products. The variables studied in this research were product-package type, tag type, tag location on cases, pallet pattern and forklift speed through a RFID portal representative of a dock door in a warehouse. To determine which variables were the most significant, a binary logistic regression was run. The number of tags read was inputted for the number of events and total number of products per pallet as the number of trials. The variables product content, pallet pattern, and speed, and all interactions were then included in the model. It was observed that readability greatly varies for different product-package systems, with paper towels producing near-perfect reads, followed by bottled water and carbonated soda cans. The slower the forklift truck speed, the better the readability across the board, and the best pallet patterns were dependent on the product-package type. For bottled water, the best pallet pattern was column, and for carbonated soda, the interlocking pattern.


Industrial Technology



URL: https://digitalcommons.calpoly.edu/it_fac/32