Menyhárt, JózsefJoseph, Jesse Nomshu2025-01-302025-01-302024-09-23https://hdl.handle.net/2437/386233The thesis explores strategies to enhance supply chain efficiency and resilience through advanced technologies and innovative practices. It identifies key challenges such as transportation delays, inefficiencies, and data security risks that hinder operational performance in manufacturing. By leveraging tools like AI, IoT, and real-time analytics, the research highlights solutions for optimizing inventory management, improving demand forecasting, and fostering collaboration among stakeholders. Sustainable logistics practices and resilient frameworks are emphasized to reduce costs and environmental impact while meeting market demands. The study concludes that integrating technology, strategic partnerships, and data-driven decision-making is essential for manufacturing competitiveness in a dynamic global market. These insights provide actionable recommendations for industry professionals and policymakers.49enSupply Chain OptimizationManufacturing IndustryAutomationEngineering SciencesHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.