Does battery management matter? Performance evaluation and operating policies in a self-climbing robotic warehouse |
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| Institution: | 1. School of Management and E-business, Zhejiang Gongshang University, Hangzhou 310018, PR China;2. Artificial Intelligence in Management Institute, Emlyon Business School, Ecully, France;3. S.f.Holding Co., Ltd, PR China;4. School of Management, Huazhong University of Science and Technology, PR China;1. Università degli Studi di Brescia, Department of Economics and Management, Via S. Faustino 74/b, BS 25122, Italy;2. Technische Universität Dresden, Faculty of Mathematics, Zellescher Weg 12-14, Dresden 01069, Germany;3. Friedrich-Alexander-Universität Erlangen-Nürnberg, Industrial Organization and Energy Markets, Lange Gasse 20, Nürnberg 90403, Germany;4. Energie Campus Nürnberg, Fürther Str. 250, Nürnberg 90429, Germany;1. Neoma Business School, Mont Saint-Aignan, France;2. Department of Industrial Engineering and Management, American University of Beirut, Beirut, Lebanon;3. Department of Economics & Business, Colorado School of Mines, Golden, CO, 80401, USA;1. Computer Science and Information Systems Department, University of Limerick, Limerick, Ireland;2. Université de Lorraine, CNRS, LORIA, Metz F-57000, France;3. Université de Lorraine, LCOMS, Metz F-57000, France;4. Huawei Technologies, France Research Center, Boulogne-Billancourt, France;1. IMB UMR CNRS 5251, Inria Bordeaux Sud-Ouest, Université de Bordeaux, 200 Avenue de la Vieille Tour, Talence, 33405, France;2. Dipartimento di Ingegneria dell’Energia Elettrica e dell’Informazione “Guglielmo Marconi”, Universit di Bologna, Viale del Risorgimento, 2, Bologna, 40136, Italy;1. School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China;2. School of Business Administration, Zhejiang University of Finance & Economics, Hangzhou 310018, China |
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| Abstract: | Our research is motivated by battery management in a new self-climbing robotic (SCR) system. The SCR system fully depends on battery-powered robots for tote movements. Therefore, battery management plays an important role and considerably impacts the system performance. This paper investigates the decision of battery charging technology (fast charging versus slow charging) taking into account the battery degradation, the battery charging policy (priority charging policy and dedicated charging policy), and the optimal number of chargers in the system. The paper also optimizes battery management in the SCR system by establishing semi-open queuing networks (SOQNs). The analytical models are solved by the approximate mean value analysis and are validated by simulation models. We find several interesting managerial insights: (1) In the operational policies, although fast charging can decrease the throughput time, we find a new condition when slow charging outperforms fast charging in robotic warehouses. (2) The priority charging policy is more cost-effective than the dedicated charging policy. (3) We also find a decision tool to determine the optimal number of chargers to satisfy the maximum allowed throughput time with the minimum cost. |
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