Relocation and storage assignment strategy evaluation in a multiple-deep tier captive automated vehicle storage and retrieval system with undetermined retrieval sequence

Author(s):  
Jakob Marolt ◽  
Nenad Kosanić ◽  
Tone Lerher
2021 ◽  
Author(s):  
Jakob Marolt ◽  
Nenad Kosanić ◽  
Tone Lerher

Abstract This paper studies multiple-deep automated vehicle storage and retrieval systems (AVS/RS) known for their high throughput performance and flexibility. Compared to a single-deep system, multiple-deep AVS/RS has a better space area utilisation. However, a relocation cycle occurs, reducing the throughput performance whenever another stock-keeping unit (SKU) blocks a retrieving SKU. The SKU retrieval sequence is undetermined, meaning that the arrangement is unknown, and all SKUs have an equal probability of retrieval. In addition to the shuttle carrier, a satellite vehicle is attached to the shuttle carrier and is used to access storage locations in multiple depths. A discrete event simulation of multiple-deep AVS/RS with a tier captive shuttle carrier was developed. We focused on the dual command cycle time assessment of nine different storage and relocation assignment strategies combinations in the simulation model. The results of a simulation study for (i) Random, (ii) Depth-first and (iii) Nearest neighbour storage and relocation assignment strategies combinations are examined and benchmarked for five different AVS/RS case study configurations with the same number of storage locations. The results display that the fivefold and sixfold deep AVS/RS outperform systems with fewer depths by utilising Depth-first storage and Nearest neighbour relocation assignment strategies.


Author(s):  
Cheng Chi ◽  
Shasha Wu ◽  
Luyao Wang ◽  
Yaohua Wu

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.


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