Jacob Daniel Maywald

Papers

Total Citations

H-Index

About

Jacob Daniel Maywald is a rising scholar at the forefront of logistics and human-robot collaboration, with a focused expertise in optimising hybrid warehouse systems. His most-cited work, "Optimising human-robot collaboration for efficiency in retail warehousing" (2025), investigates the performance of Autonomous Mobile Robot (AMR)–human teams in order-picking operations. Maywald’s key contribution lies in identifying optimal resource allocation strategies and assessing how warehouse layout design—particularly the placement of cross-aisles—can significantly enhance operational throughput. Though early in his career, his research addresses a critical gap in retail logistics: balancing automation with human flexibility to maximise efficiency. With 1 citation to date, his work is gaining traction among practitioners and academics seeking data-driven solutions for modern warehousing challenges. Maywald’s findings offer actionable insights for designing collaborative workspaces that leverage both robotic precision and human adaptability, positioning him as an emerging voice in industrial engineering and supply chain innovation. His research promises to shape future warehouse designs and workforce integration strategies in an increasingly automated world.