PhD Defence Kaveh Azadeh
In his dissertation ‘Robotized Warehouses: Design and Performance Analysis’, Kaveh Azadeh structured the latest automated technologies and overviewed these technologies and the research. He also reviewed the modeling techniques used and the research opportunities they provide. Moreover, he investigated the vertical storage and retrieval system, an emerging robotic technology for e-commerce warehouses, and studies systems in which robots collaborate with a human picker to efficiently pick the orders by reducing the pickers’ unproductive walking time. Kaveh has defended his dissertation on Friday, 26 February at 13:00h. His supervisors were Prof. René de Koster (RSM) and Dr Debjit Roy (RSM). The members of the Doctoral Committee were Prof. Kai Furmans (Karlsruher Institut für Technologie), Prof. Rommert Dekker (ESE), Dr. Niels Agatz (RSM), Prof. Rob Zuidwijk (RSM), Prof. Yeming Gong (EMLYON Business School) and Dr. Jennifer Pazour (Rensselaer Polytechnic Institute).
About Kaveh Azadeh
Kaveh Azadeh was born in Tehran (Iran) on March 21, 1988. He studied Electrical Engineering at the University of Tehran in Iran. In May 2013, he received his M.Sc. degree in Industrial Engineering from the University of Central Florida (UCF) in the USA. He then spent a year as a lead researcher in the Logistics Delivery System Design Laboratory at UCF. In 2014, Kaveh joined the department of Technology and Operations Management at Rotterdam School of Management, Erasmus University, under the supervision of Professor René De Koster and Dr. Debjit Roy.
Kaveh's research interests include the design, analysis, and optimization of intra-logistic systems focusing on the stochastic modeling and the performance evaluation of various robotized order picking systems. His works have been published in Transportation Science and have been presented in several international conferences, including INFORMS Annual Meeting, European Conference on Operational Research, POMS Annual Meeting, IFORS Conference, International Conference on Computational Logistics, and International Conference on Logistics and Maritime Systems. He has also served as a reviewer of various journals, including Transportation Science and OR Spectrum.
Thesis Abstract
Warehouse automation requires considerable scale and a long-term vision, as the investments can be earned back only in the medium and longer-term. Furthermore, there is no one-size-fits-all solution for warehouse automation and depending on the type of the warehouse and its position within the supply chain, different automation should be considered. The majority of warehouse research still focuses on conventional storage and order picking methods. Due to rapid system developments, it is time for an update, as the new technologies have provided new and interesting research opportunities. Therefore, in Chapter 2, we structure the latest automated technologies and overview these technologies and the research. We also review the modeling techniques used and the research opportunities they provide. Chapter 3 investigates the vertical storage and retrieval system, an emerging robotic technology for e-commerce warehouses. We build a framework to analyze and optimize the performance of the system. We also compare the effects of different robot blocking protocols on the system throughput. Finally, we compare the operational costs of the vertical and conventional horizontal systems. The results show that the vertical system produces a similar or higher system throughput with a lower operating cost compared with the horizontal system in almost all scenarios. In Chapter 4, we study systems in which robots collaborate with a human picker to efficiently pick the orders by reducing the pickers’ unproductive walking time. Particularly we investigate how higher pick performance can be achieved by dynamically switching between different pick strategies. The results show that a dynamic switching policy can lower operational costs by up to 7 percent. However, these cost savings decrease as the number of robots per picker increases.
Read Kaveh's dissertation here
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Photos: Michelle Muus Fotografie
