With the growth in e-commerce and customer demands to get their deliveries faster, there’s an increased demand from logistic companies for automated e-fulfillment centers. Automated Guided Vehicles (AGV) are needed at high levels in these sophisticated e-fulfillment centers using automation and robots on a larger scale. At these fulfillment centres, AGVs help with the rapid and accurate transfer of goods from storage to the shipping dock. It is very important to improve the efficiency of AGV operations for high throughput and competitiveness in e-commerce. In this study, fuzzy association rules mining (FARM) was used to find the correlation between environmental factors and order-picking performance of AGVs. Reviewing the derived rules can help practitioners identify important factors affecting the picking time required and the AGV picking efficiency. By focusing on these parameters, it is possible to set the appropriate picking criteria that optimize the order picking efficiencies, which will enable the e-fulfilment centres to meet rising customer expectations of speedy delivery while also being good for the sustainability and growth of e-fulfilment businesses.