Abbas Shabbir Ezzy

Papers

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About

Abbas Shabbir Ezzy is a researcher focused on industrial automation and logistics systems, with a particular emphasis on enhancing material handling efficiency through technology. His key research areas include automated guided vehicles (AGVs), warehouse automation, and the integration of intelligent systems to streamline supply chain operations. Ezzy’s major contribution lies in proposing practical, scalable solutions for automating the warehouse picking process, addressing the growing demand for large-scale material movement while reducing reliance on manual labor. His most-cited work, "Automated logistic systems: needs and implementation" (2020), which has garnered 5 citations, outlines a framework for deploying AGVs to optimize logistics workflows, offering a blueprint for industries seeking to modernize their operations. This paper underscores his ability to bridge theoretical concepts with real-world application, making his research valuable for both academics and practitioners in manufacturing and logistics. Ezzy’s work contributes to the broader push toward Industry 4.0, where automation and data-driven decision-making are transforming traditional warehouses into agile, cost-effective hubs. His insights are particularly relevant for students and researchers exploring the intersection of robotics, systems engineering, and operational efficiency.