The continuous fast-changing of production requirements and the development of advanced information technology have promoted the development of the production system in a more knowledgeintensive, resources-decentralized, and autonomous collaborative manner. In order to provide guidelines for the smart transformation of the production shop floor, this paper proposes a smart production system with a three-layer framework defined as the social production system (Social-PS) by integrating cyber-physical system (CPS), knowledge graph technology, and production-event driven model. The concept of smart resources (include smart operator, smart machine, smart workpiece, and smart gateway), social sensor, the unified information model is clarified to construct the physical carrier of Social-PS. The unified knowledge repository's overall construction method based on the knowledge graph is elaborated to provide taskresource-associated heterogeneous production data sharing and management for human-machine collaboration. Subsequently, to support the production dynamic monitoring and interaction, a productionevent and active knowledge indexing model is proposed. Furthermore, to validate the proposed Social-PS framework, a software and hardware integrated prototype system is implemented to demonstrate the knowledge-driven human-machine collaboration of the production process, which provides a basis for realizing smart and autonomous production collaboration.

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Additive manufacturing (AM) systems are currently evolving into network-based models, where the distributed manufacturing resources from multiple enterprises are coordinated to complete product orders. The layer-by-layer approach of AM technologies gives manufacturers unprecedented freedom to create complex parts tailored to customer needs, but this comes at slow build rates. Consequently, for AM to become mainstream in the industry, challenges in production planning remain to be addressed to increase AM system productivity. This paper considers two practical problems encountered in AM systems, namely, production planning and part-to-printer assignment, and a series of heuristic algorithms are proposed to solve these problems. In particular, an approach for automatically determining part orientation, part-to-printer allocation, and nesting of multiple parts for a distributed network of fused filament fabrication three-dimensional printers is described to reduce the total production cost and time regarding the context of social manufacturing. The proposed method is implemented through a web application. The case study, using real-world parts and comparative analysis findings, indicated that the proposed method produces high-performance results.

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