Kumuyi, Olakunle Abimbola (2025) Lean in logistics through autonomous last-mile delivery. International Journal of Science and Research Archive, 14 (2). pp. 753-763. ISSN 2582-8185
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Abstract
Efficient last-mile delivery is essential in modern commerce, yet it poses challenges in timeliness, cost-effectiveness, and customer satisfaction. Between 41% and 53% of supply chain expenses, particularly in the United States, are attributed to this final leg. Autonomous technology, with its complex algorithms and driverless vehicles, is capable of revolutionizes last-mile delivery by optimizing routing and scheduling, reducing labor costs, and ensuring the fastest delivery routes. Real-time inventory management can further integrate lean principles into last-mile delivery, and therefore enhancing operational efficiency. This project explores the synergy between autonomous technology and lean concepts, aiming to eliminate non-value-added tasks, maximize resource utilization, and enhance overall efficiency, in terms of travel time reduction, with focuses specifically on develop countries with supporting technologies to support autonomous vehicles and robot technologies infrastructures in place. The research focused on leveraging available traffic data from autonomous technology can enable continuous improvement, enhancing productivity and customer satisfaction. Additionally, incorporating autonomous technology can enhance the reliability and safety of last-mile delivery operations through cost reduction, time reduction, and route flexibility. This research primarily examines the impact of traffic lights on traditional delivery vans, using New York City streets as a case study. A comprehensive model has been developed to quantify the cost implications of traffic light delays, providing a structured method to evaluate these inefficiencies. The model offers a practical approach that can be applied globally users simply need to input relevant parameters, and the system will compute the time, cost, and overall impact of such delays. Additionally, the study highlights the advantages of autonomous delivery systems, particularly drones, over conventional delivery methods. By utilizing this model, businesses and policymakers can make data-driven decisions to optimize last-mile logistics and enhance delivery efficiency. Recommendations include utilizing autonomous technology to meet environmental preservation requirements and offering eco-friendly delivery options. The convergence of lean principles and autonomous technologies offers transformative opportunities, enabling businesses to fulfill consumer demands, reduce costs, operate sustainably, and enhance efficiency.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/ijsra.2025.14.2.0404 |
Uncontrolled Keywords: | Lean Logistics; Last-Mile Delivery; Autonomous Delivery Vehicles (ADVs); Traffic Light Delays; Route Optimization; Cost Reduction; Environmental Sustainability; Supply Chain Efficiency; Machine Learning in Logistics; Customer Satisfaction |
Depositing User: | Editor IJSRA |
Date Deposited: | 11 Jul 2025 16:47 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/416 |