Adaptive inventory management using RFID data
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In this paper, inventory management of time-sensitive materials using RFID data is studied using simulation. Based on the production data obtained from a manufacturing company, three inventory management models that rely on RFID data for tracking and dispatching of time-sensitive materials on a shop floor is presented. The complexity of the models ranges from statically-set, fixed baseline inventory models to dynamic, forecast-integrated inventory control schemes. This study compares the inventory models on the basis of service level, cost, inventory and waste reduction, and decision-making complexity. A comparative analysis of the models is presented in a simulation environment, which also demonstrates the overall benefits and effectiveness of RFID technologies in providing low-cost manufacturing solutions, reduced inventory levels, and lower overall waste. The forecast-integrated inventory model is developed based on a trend-adjusted exponential smoothing algorithm, with two smoothing parameters, α and β, used as coefficients for the average production demand and its trend, respectively. The study shows that the desired level of system performance can be achieved by adjusting the values of the smoothing parameters.
KeywordsSupply Chain Service Level Inventory Model Inventory Level Inventory Management
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This study was partially funded by the Air Force Research Lab (FA8650-04-C-704) through the Center for Aerospace Manufacturing Technologies (CAMT) at the University of Missouri-Rolla.
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