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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