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

Abstract

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.

Keywords:

• Warehousing
• AS/R system
• passing cranes
• queuing model with interruption
• analytical and simulation modelling
• performance analysis

Acknowledgments

This research was supported in part by National Natural Science Foundation of China [grant number 72001189], Zhejiang Natural Science Foundation [grant number LQ19G030004], Qianjiang River Talent Scholarship (grant number QJC1802002), NSFC Key Project (Grant No. number 71620107002), and NSSFC Major Project (16ZDA013). Wanying Chen is particially supported by Qianjiang New Area and Wahaha Group. Yeming Gong is supported by Business Intelligence Center (BIC) and Shanghai campus of EMLYON.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported in part by National Natural Science Foundation of China [grant number 72001189], Zhejiang Natural Science Foundation [grant number LQ19G030004], Qianjiang River Talent Scholarship (grant number QJC1802002), NSFC Key Project (Grant No. number 71620107002), National Social Science Foundation of China (NSSFC) Major Project (16ZDA013), Qianjiang New Area and Wahaha Group. Yeming Gong is supported by Business Intelligence Center (BIC) and Shanghai campus of EMLYON.

Notes on contributors

Wanying (Amanda) Chen

Wanying (Amanda) Chen is a Lecturer of Management and E-business school and PI of NSFC project at Zhejiang Gongshang University, Hangzhou, China. She holds a Ph.D. and MSc from University of Lyon, France. She was a post-doc researcher at DISP, France. She also worked in the CIRRELT, Canada, as a researcher. She has published one book ”Disaster Response”. She published more than 10 research articles, in journals such as International Journal of Production Research, International Journal of Production Economics, European Journal of Operational Research, Omega, and Operations Research for Health Care. She received the “Qianjiang talent” scholarship in 2018 and “Best Thesis Award” in 2015.

Yeming Gong

Yeming (Yale) Gong is a Professor of Management Science at EMLYON Business School, France. He is Director of Business Intelligence Center. He holds a Ph.D. from Rotterdam School of Management, Erasmus University, Netherlands. He has published two books “Stochastic Modelling and Analysis of Warehouse Operations” in Erasmus and “Global Operations Strategy: Fundamentals and Practice” in Springer. He published 70 articles in journals including International Journal of Production Research, International Journal of Production Economics, European Journal of Operational Research, Production and Operations Management, IIE Transaction, Annals of OR, OMEGA, Computers & Industrial Engineering, and IEEE Transactions on Engineering Management. Prof. Gong received “2010 the Best Paper Award in Design and Manufacturing” from IIE, 2019 “Outstanding Paper Award” from ASCOM, and “Erasmus Scholarship for Teaching” from European Union.

René B. M. de Koster

René (M.) B.M. de Koster is a professor of logistics and operations management at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University (RSM). His research interests are warehousing, material handling, container terminal operations, behavioural operations and sustainable logistics. He is the author and editor of eight books and over 200 papers published in books and journals such as International Journal of Production Research, Operation Research, Production and Operations Management, Journal of Operations Management, Transportation Science, European Journal of Operational Research, and Interfaces. He is in the editorial boards of eight academic journals, a fellow of two research schools, member of the European Logistics Association (ELA) R&D board, member of the BVL Scientific Advisory Board, the AIRL board of directors, chairman of three Dutch logistics awards, chairman of Stichting Logistica, and founder of the Material Handling Forum. For eight years, he chaired RSM's Department of Management of Technology and Innovation. He is involved in teaching at RSM at all levels: bachelor, master, post-experience, and executive development. He also lectures at Université Catholique du Louvain (Belgium), USTC Hefei (PRC), and the University of Pretoria (South Africa). He holds the honorary Francqui chair for Hasselt University in 2018.