RETRACTED: A viability study using conceptual models for last mile drone logistics operations in populated urban cities of India
Abstract Emerging Unmanned Aerial Vehicle (UAV) technologies have been under spotlight worldwide due to a promising spectrum of applications. Despite interesting use‐cases receiving worldwide media attention, drones are expected to have their most significant impact on supply chain and logistics sys...
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Veröffentlicht in: | IET collaborative intelligent manufacturing 2021-09, Vol.3 (3), p.262-272 |
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Sprache: | eng |
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Zusammenfassung: | Abstract Emerging Unmanned Aerial Vehicle (UAV) technologies have been under spotlight worldwide due to a promising spectrum of applications. Despite interesting use‐cases receiving worldwide media attention, drones are expected to have their most significant impact on supply chain and logistics systems in highly populated urban cities once the regulations for commercial purposes are lifted. This article proposes two models of drone‐delivery technology that can serve as a potential replacement in the Indian truck‐delivery system. First, a drone–truck hybrid delivery model is proposed with trucks carrying multiple drones. Second, a stand‐alone drone‐delivery model is proposed with separate charging infrastructural facilities at specific points. The two proposed models' findings present the advantages of significantly reducing carbon emissions, delivery costs, and time compared to truck‐based delivery. The hybrid drone–truck model eliminates the need for separate charging facilities saving initial infrastructural costs. In contrast, the stand‐alone drone model utilizes the current warehouse location facilities with charging stations on specific points for ease of adoption. This research presents initial viability suggesting that the drone technology can solve the current operational challenges in India's urban cities. Furthermore, vital factors are discussed to enable stakeholders to select a model for drone logistics systems planning and experimentations. |
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ISSN: | 2516-8398 |
DOI: | 10.1049/cim2.12006 |