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Design and Performance Estimation of Mixed-Robotic Fulfillment System

Cheng Chi, Shasha Wu, Luyao Wang, Yaohua Wu

Year
2021
Citations
2

Abstract

E-commerce retailers face the challenge to assemble a large number of time-critical picking orders. Common parts-to-picker autonomous intelligent warehouses such as automated vehicle storage and retrieval system and robotic mobile fulfillment system are often a little ill-suited for these prerequisites. A mixed-robotic fulfillment system is a hybrid robot picking system based on multi-device collaboration. It is a fusion innovation of traditional automated vehicle storage and retrieval system and robotic mobile fulfillment system. This paper comprehensively considers the characteristics of the system and customer demand, through the construction of a queuing network model to evaluate the performance of the system. A series of problems such as order service time, throughput capacity, and vehicle quantity configuration are analyzed experimentally. The validity of the model is verified by a simulation model.

Keywords

Computer scienceQueueing theoryService (business)ThroughputReal-time computingArtificial intelligenceEmbedded systemComputer networkOperating system

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