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Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems
Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems
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Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems
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Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems
Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems

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Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems
Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems
Journal Article

Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems

2017
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Overview
Shuttle-based compact systems are new automated multideep unit-load storage systems with lifts that can potentially achieve both low operational cost and large volume flexibility. In this paper, we develop novel queuing network models to estimate the performance of both single-tier and multitier shuttle-based compact systems. Each tier is modeled as a multiclass semi-open queuing network, whereas the vertical transfer is modeled using an open queue. For a multitier system, the models corresponding to tiers and vertical transfer are linked together using the first and second moment information of the queue departure processes. The models can handle both specialized and generic shuttles and both continuous and discrete lifts. The accuracy of the models is validated through both simulation and a real case. Errors are acceptable for conceptualizing initial designs. Numerical studies provide new design insights. Results show that the best way to minimize expected throughput time in single-tier systems is to have a depth/width ratio around 1.25. Moreover, specialized shuttles are recommended for multitier systems because the higher cost of generic shuttles is not balanced by savings in reduced throughput time and equipment needs.
Publisher
INFORMS,Transportation Science & Logistic Society of the Institute for Operations Research and Management Sciences,Institute for Operations Research and the Management Sciences