Engineering a Scalable AMR-Based Material Handling System: A Case Study from a High-Volume Electric Vehicle Manufacturing Facility

Material transport remains one of manufacturing’s least optimized functions—high in frequency, safety critical, and still heavily reliant on forklifts and manual routing. This paper presents the design, simulation, and deployment of an industrial-scale pilot Autonomous Mobile Robot (AMR) material-handling system in a high-volume electric vehicle manufacturing facility, developed as a standardized framework for next-generation smart and sustainable factories.

Through a multi-phase project spanning more than eight months, a cross-functional engineering team designed AMRs in-house and executed a comprehensive facility layout redesign that combined SLAM-based navigation with dolly recognition, dynamic fleet coordination, and power infrastructure planning. Using FlexSim simulations, the team modeled material handling routes, traffic zones, and charging logic to predict congestion and optimize flow before implementation. Physical integration included widened aisles for safety, guarded docking bays, smart charging infrastructure, and a centralized control area for fleet supervision. A plant-wide 5G network enabled low-latency communication among AMRs, fleet management, and warehouse systems, supporting adaptive rerouting and predictive traffic control.

The deployed system autonomously delivers more than 10 different vehicle parts to over 25 production locations, achieving approximately 90 percent automation with throughput and delivery accuracy comparable to optimized manual operations. A structured human–AMR interaction framework—featuring touchscreen coordination, targeted operator training, alerting systems, and real-time performance dashboards—reduced manual intervention to below 12 percent.

The deployment demonstrates a scalable, data-driven model for facility design and material-handling automation. It highlights how Industrial Engineers can integrate digital twins, layout planning, and human factors to shape the next generation of adaptive and resilient manufacturing facilities.

Joshua Joseph is the Autonomous Mobile Robot (AMR) Launch Engineer at Tesla who led the pilot deployment and is now scaling up the system to transform material flow across new and existing factories. His work bridges factory operations and robotics integration, connecting AMRs with fleet management, warehouse software, PLCs, and analytics dashboards to deliver measurable efficiency gains and enhance human–robot collaboration on the production floor.

Joshua earned his Master’s in Mechanical Engineering from Northeastern University, where he taught Smart Factory Systems labs and also conducted research on Robotic Process Automation (RPA) at the Kostas Research Institute. His professional focus includes scalable AMR deployment frameworks, interoperability standards, and data-driven automation strategies that connect industrial engineering and robotics.

He serves as the Regional Young Professional Representative for the South Central U.S. Division of IISE and is a Certified Automation Professional (CAP) Associate with the International Society of Automation (ISA).