The simulation research of distribution center sorting system based on flexsim

Liu, Tongjuan

doi:10.1109/csae.2012.6272662

Cited by 1 publication

(1 citation statement)

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“…There are also examples of DES applied to modelling and simulating complex control algorithms of objects ows in the internal transport operations [31]. Discrete Event Simulation has also been employed in the study of different sorting systems [32] and the analysis and optimization of sorting strategies of logistics distribution centers [33].…”

Section: Research Background and Contributionmentioning

confidence: 99%

An integrated simulation modelling approach for a warehouse 4.0

Ferrari¹,

Zenezini²,

Carlin³

et al. 2021

Preprint

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In a progressively unstable business environment characterized by customers' demand challenging to predict, innovative solutions must be developed to respond to the growing need for flexibility in supply chain operations. In this scenario, the innovations of Industry 4.0 allow exploiting new methods for the development, management, and improvement of processes. Supply chain operations can significantly benefit from implementing one of these innovations, namely Warehouse automation, which is composed of automated retrieval and storage systems (AS/RS) and mobile robots (MR). This article contributes provides a hybrid virtual model based on Agent-Based Modeling and Simulation (ABMS) and Discrete Event Simulation (DES) paradigms of an integrated warehouse system, aiming to an ex-ante evaluation of the level of performance of the various logistic flows and the impact of operating parameters. The system into analysis consists of an automated warehouse with a maxi-shuttle-type translator, enslaved by mobile industrial robots and interfaced with a laboratory factory system equipped with an assembly station. Four experiments are carried out to analyze the warehousing system's performance by varying different parameters and design configurations. Results show that the model can determine the best design trade-off in terms of performance and is able to identify the bottlenecks of the system.

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Section: Research Background and Contributionmentioning

confidence: 99%