Social Production System: A Three-Layer Smart Framework for Implementing Autonomous Human-Machine Collaborations in a Shop Floor
Social Production System: A Three-Layer Smart Framework for Implementing Autonomous Human-Machine Collaborations in a Shop Floor
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DOI：
10.1109/access.2021.3050236
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发表时间：
2021
期刊：
影响因子：
3.9
通讯作者：
Haoliang Shi;Maolin Yang;P. Jiang
中科院分区：
文献类型：
--
作者：
Haoliang Shi;Maolin Yang;P. Jiang
生产需求的不断快速变化和先进信息技术的发展，促使生产系统向知识密集、资源分散、自主协同的方向发展。为指导生产车间的智能化改造，提出了一种集成信息物理系统（CPS）、知识图技术和生产事件驱动模型的三层智能生产系统框架--社会化生产系统（Social-PS）。明确了智能资源（包括智能操作员、智能机器、智能工件、智能网关）、社会传感器的概念，建立了统一的信息模型，构建了Social-PS的物理载体。阐述了基于知识图的统一知识库的总体构建方法，为人机协作提供任务资源关联的异构生产数据共享和管理。在此基础上，提出了一种支持生产过程动态监控和交互的生产事件主动知识索引模型。此外，为了验证所提出的Social-PS框架，实现了一个软硬件集成的原型系统，展示了知识驱动的生产过程人机协同，为实现智能化、自主化的生产协同提供了基础。
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 knowledge-intensive, 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 task-resource-associated heterogeneous production data sharing and management for human-machine collaboration. Subsequently, to support the production dynamic monitoring and interaction, a production-event 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.