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Autonomous vehicles as self-driving assembly items: rethinking internal logistics in automotive assembly

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  • Tom Kathmann
  • Daniel Reh
  • Julia C. Arlinghaus

Abstract

This paper investigates the use of autonomous vehicles (AVs) as self-driving assembly items to transform internal material handling and supply chain integration within automotive manufacturing. By enabling vehicles to autonomously navigate through their own assembly process, the concept offers a flexible and cost-efficient alternative to traditional conveyor systems. Based on a multiple case study of three battery electric vehicle (BEV) assembly systems, supported by expert workshops and interviews, we analyse the economic and structural impacts of this approach. Our findings show that infrastructure-supported AV systems can reduce conveyor-related capital expenditures by up to 25%. A total cost of ownership (TCO) analysis over 50 years confirms long-term viability. The study also provides planning guidelines for implementation, including layout restructuring and buffer design. This research contributes to integrated supply management by quantifying the financial and operational implications of AV-based internal logistics and offering practical insights for smart manufacturing transformation.

Suggested Citation

  • Tom Kathmann & Daniel Reh & Julia C. Arlinghaus, 2026. "Autonomous vehicles as self-driving assembly items: rethinking internal logistics in automotive assembly," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 18(2), pages 184-216.
    • Handle: RePEc:ids:ijisma:v:18:y:2026:i:2:p:184-216
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