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Distributed additive manufacturing (AM) has emerged as an innovative service-oriented paradigm for decentralized production of personalized products. In this paper, a resource sharing problem for product service system (PSS)- and cloud-enabled additive manufacturing platforms is addressed. A PSS-enabled business model is proposed to share resources. A deep reinforcement learning approach for resource sharing is then presented to have excellent potential based on a real-life case company that provides AM services for dental clinics and hospitals through producing 3D printed dental crowns and bridges, teeth and brackets. This case company is a national high-tech enterprise providing a 3D professional printing solutions in Nanjing, China. Using the datasets from the case company, the validation results show the feasibility and practicality of the proposed approach. • A PSS-enabled business model is proposed to facilitate resource sharing. • A deep reinforcement learning-based model is developed to share resources. • A real-life case is used to verify the practicability of the proposed method. • The proposed model is effective and applicable to the large-scale implementation. [ABSTRACT FROM AUTHOR]