scholarly journals Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System

2019 ◽  
Vol 11 (14) ◽  
pp. 3817 ◽  
Author(s):  
Emanuele Guerrazzi ◽  
Valeria Mininno ◽  
Davide Aloini ◽  
Riccardo Dulmin ◽  
Claudio Scarpelli ◽  
...  
Keyword(s):  
Energy Recovery ◽  
Retrieval System ◽  
Autonomous Vehicle ◽  
Operating Characteristics ◽  
Storage And Retrieval ◽  
Energy Evaluation ◽  
System A ◽  
Retrieval Systems ◽  
Recovery System ◽  
Automated Warehouses

With the rise of a consciousness in warehousing sustainability, an increasing number of autonomous vehicle storage and retrieval systems (AVS/RS) is diffusing among automated warehouses. Moreover, manufacturers are offering the option of equipping machines with energy recovery systems. This study analyzed a deep-lane AVS/RS provided with an energy recovery system in order to make an energy evaluation for such a system. A simulator able to emulate the operation of the warehouse has been developed, including a travel-time and an energy model to consider the real operating characteristics of lifts, shuttles and satellites. Referring to a single command cycle with a basic storing and picking algorithm for multiple-depth channels, energy balance and recovery measurements have been presented and compared to those of a traditional crane-based system. Results show significant savings in energy consumption with the use of a deep-lane AVS/RS.

Relocation and Storage Assignment Strategies Evaluation in a Multiple-deep Tier-captive Automated Vehicles Storage and Retrieval System with Undetermined Retrieval Sequence

2021 ◽  
Author(s):  
Jakob Marolt ◽  
Nenad Kosanić ◽  
Tone Lerher
Keyword(s):  
Retrieval System ◽  
Discrete Event ◽  
Nearest Neighbour ◽  
Throughput Performance ◽  
Storage And Retrieval ◽  
Event Simulation ◽  
Retrieval Systems ◽  
Storage Assignment ◽  
And Storage

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.

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