A Comparative Study of RFID System Performance in Large-Scale Network Planning Facility

Abstract

Big data in manufacturing fields present several challenges leads to reduce profitability and missed opportunity for innovation. One of the used strategies is the use of radio frequency identification system.  considered a business strategy to increase productivity, speed up decision-making, and enhance production monitoring and control while preserving the structure and integrity of current manufacturing systems. The present research compares five artificial inelegant algorithms based on RFID system in facility layout design to investigate the fitness of each algorithm in manufacturing big data processing. The objective functions have been used are the minimum number of required readers, minimum readers overlap, and maximum tags coverage. The contribution in this work is the workability of each algorithm in different facility design condition based on design alternatives. the results present that cuckoo search (CS) has the optimum fitness reach to 74.68% in big data and large area condition while particle swarm optimization (PSO) observed optimum fitness 74.46% in small data and large area. The simulation results illustrate the applicability and robustness of the proposed method, with the characteristics maintaining exceptional approximation capabilities even in high-dimensional spaces.