Performance estimation of a passing-crane automated storage and retrieval system - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue International Journal of Production Research Année : 2022

Performance estimation of a passing-crane automated storage and retrieval system

Wanying Amanda Chen
  • Fonction : Auteur
René de Koster
  • Fonction : Auteur

Résumé

Storage and retrieval automation has progressed rapidly. One such popular storage and retrieval system deploys two passing aisle-bound cranes. Each crane can access every location in the rack. To pass the other crane and prevent collision, each crane has to timely move the platform to an appropriate level and simultaneously rotate it. We develop a queuing model with preemptive-resume interrupted service to estimate the system response time (and hence throughput capacity) while considering two I/O point positions, random storage, and a crane assignment policy where all requests are shared between the cranes. The analytical models are validated with simulation based on the data from real cases. We find that a design with I/O points located in the middle of the rack will increase the interference, but it has a high relative throughput because of the reduced expected travel time. Compared with a system with one crane, a two-crane system has interference, but it can improve the system efficiency, especially in large systems with high job arrival rates. The model can be extended to other systems where multiple cranes are used in a single travel aisle with crane interference, e.g. passing cranes operating in a container stack lane.
Fichier non déposé

Dates et versions

hal-04325530 , version 1 (06-12-2023)

Identifiants

  • HAL Id : hal-04325530 , version 1

Citer

Wanying Amanda Chen, Yeming Gong, René de Koster. Performance estimation of a passing-crane automated storage and retrieval system. International Journal of Production Research, 2022, 60 (4), 1210-1230 p. ⟨hal-04325530⟩

Collections

EMLYON
13 Consultations
0 Téléchargements

Partager

Gmail Mastodon Facebook X LinkedIn More