This paper addresses the fluid nature of 3D printing consumables and the stochastic uncertainty in customized production material demands by developing a novel fluid-type queueing inventory model that incorporates multiple servers and synchronous maintenance periods under an (s, Q) replenishment policy. Utilizing queueing theory and inventory theory, this study investigates the impact of key system parameters and cost variables on average inventory levels, ordering rates, material shortages, and optimal replenishment strategies under a lost-sales mechanism. The research reveals three main findings: First, the joint probability distribution of inventory and queue length exhibits a product-form stochastic decomposition structure, indicating that replenishment policies and service processes can be optimized relatively independently, thereby providing a theoretical foundation for hierarchical decision-making in enterprises. Second, equipment maintenance duration has minimal impact on inventory-related metrics but significantly affects lost sales volume, enabling firms to flexibly schedule maintenance plans with minimizing lost sales as the primary objective; Third, numerical results demonstrate that inventory holding cost emerges as the dominant cost driver, with accurate demand characterization offering greater cost reduction potential than improvements in replenishment lead time.