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Home 2026

An End-to-End Material Flow Strategy Framework for Heavy-Duty Electric Vehicle Powertrain Production

Authors: Olasubomi Akanbi, Evans Abiodun Sunday, Olaitan Shakirat Ganiu, WSN 215 (2026) 160-191

2026-06-01
Reading Time: 4 mins read
0

https://doi.org/10.65770/JMJW4287

ABSTRACT

The transition toward electrified transportation has intensified the need for highly coordinated and efficient manufacturing systems capable of supporting heavy-duty electric vehicle (HDEV) powertrain production at scale. This review proposes an end-to-end material flow strategy framework that integrates upstream material sourcing, in-plant logistics, and downstream distribution into a unified, data-driven production ecosystem. The study synthesizes existing literature on advanced manufacturing systems, lean material handling, digital twin integration, and Industry 4.0-enabled supply chain optimization to identify critical gaps in current HDEV production architectures. Particular emphasis is placed on the complexity of battery systems, electric drivetrains, and power electronics, which require synchronized material flow due to their high value, sensitivity, and production interdependencies. The framework introduces a multi-layered approach encompassing demand forecasting, inventory optimization, real-time tracking, and adaptive scheduling supported by IoT-enabled sensors and predictive analytics. It further evaluates the role of automation technologies such as autonomous mobile robots (AMRs), automated storage and retrieval systems (AS/RS), and cyber-physical systems in reducing bottlenecks and improving throughput efficiency. Environmental considerations are also incorporated through closed-loop material flow strategies that promote recycling, remanufacturing, and circular resource utilization. By aligning operational efficiency with sustainability objectives, the proposed framework supports cost reduction, reduced lead times, and enhanced system resilience. The review concludes by highlighting implementation challenges, including data integration barriers, infrastructure limitations, and workforce adaptation, while outlining future research directions in AI-driven optimization and decentralized manufacturing networks. This work contributes a comprehensive and scalable material flow model tailored to the unique demands of heavy-duty electric vehicle powertrain production, offering both theoretical insights and practical guidance for industry stakeholders.

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WSN 215 (2026) 160-191


 

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Tags: Heavy-Duty Electric VehiclesIndustry 4.0Material Flow OptimizationPowertrain ManufacturingSmart Logistics SystemsSustainable Production Systems.
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