The Internet of Things (IoT) became the most impactful development worldwide. This development influenced many businesses to adapt and shift to online business or so-called e-commerce. Amazon as an e-commerce platform offered hundreds of millions of products for sales, as on June 20th, 2017 offered 372 million products online [1]. With this amount of products, amazon used the Robotic Mobile Fulfillment System (RMFS) as their warehouse system. In this study, a simulation of the RMFS was built used NetLogo to maximize the pod utilization and minimize the energy consumption of the warehouse.
This study combined 3 SKU to Pod assignments and 4 Replenishment policies. SKU to Pod has the role to improve the pod utilization by increase pick unit in each visit. Pod with more SKU types is likely to fulfill more orders. Replenishment policy has the role to maintain the inventory of the warehouse and keep the pod at a high service level. Other than that, replenishment triggers reduced visits to the picking station. A pod that doesn’t have sufficient capacity couldn’t be assigned with new order although it already has the most order assigned.
This approach showed improvement by assigned different SKU classes in one pod and considering SKU inventory also with pod urgency level. Maintained the inventory level in the warehouse above 59% of total inventory influenced the warehouse performance. There was increasing of 17.83% in pod utilization and reducing of 14.75% in energy consumption.

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