Analysis of learning pallets in flexible scheduling by closed queue network

Abstract

Within the paper, application of learning pallets in an assembly system for real-time scheduling problems is presented. A specific fuzzy inference system (controller) is adopted to enable the pallets to learn from their experiences regarding some key metrics. In order to analyze the performance of this system and the learning pallets with a robust mathematical analysis, the similarity of this assembly network to the BCMP networks in closed queuing theory, is underlined. The results prove this resemblance and show the suitability of its algorithm for analyzing such closed networks.