International Journal of Industrial Engineering: Theory, Applications, and Practice
Doi
Abstract
In the Industry 4.0 era, achieving high energy efficiency and flexibility in manufacturing systems remains a critical challenge, particularly in the integration of Automated Guided Vehicles with on-board batteries. This study addresses this gap by introducing a novel evolutionary approach that simultaneously optimizes task scheduling, transport operations, and vehicle battery management—pioneering a comprehensive solution for manufacturing efficiency. Unlike traditional methods, our approach not only reduces lead times and operational costs but also extends battery lifespan through improved energy management strategies. Experimental results demonstrate significant advancements, including a 29.25% improvement in battery levels and a 3.64% reduction in production time. These results surpass established benchmarks in 88.23% of test cases. These outcomes not only enhance sustainability and operational resilience but also provide actionable insights for implementing more efficient and competitive Industry 4.0 manufacturing systems. By addressing critical challenges in energy and operational management, this study lays the groundwork for future innovations in sustainable and adaptive manufacturing practices
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