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- W4283156590 abstract "Cross-docking is important for logistics because it reduces inventory, lead-times, and shipments. However, dynamic imbalances between supply and demand usually results in some inventory being warehoused in cross-docks. Therefore, flexible automation using robots, such as automated guided vehicles (AGV), can be used to improve performance of cross-docking, a trend in industry. This paper focuses on mathematical modeling of cross-docking operations when packages are moved in AGVs. A model based on Mean Value Analysis (MVA) is developed for determining the number of AGVs and estimating the service rate. This service rate is used as a parameter in a fork/join queuing model to characterize the performance of cross-docks in which outbound trucks get their packages directly from in-bound trucks as well as warehouses by estimating the queue lengths and mean sojourn times. The efficacy of the combined MVA and fork/join analytical models is verified using a discrete-event simulation as a case study, which shows that the models are largely in agreement in a test range with difference of 28% at the lowest throughput tested. Future study could use advances in sensors and Industry 4.0 for estimating parameters in the proposed models and improve performance and sustainability." @default.
- W4283156590 created "2022-06-21" @default.
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- W4283156590 date "2022-06-20" @default.
- W4283156590 modified "2023-09-25" @default.
- W4283156590 title "Design and analysis of AGV-based cross-docking operations using analytical models" @default.
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- W4283156590 doi "https://doi.org/10.1080/21693277.2022.2083714" @default.
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