群智制造环境下大规模知识图谱构建与可信服务组合优化研究

Due to the advancements of new information technologies including cloud computing, internet of things, big data and socialized networks, the crowd intelligence has become an emerging problem solving methodology by combining the wisdom from crowds of people or machines. Based on the applicants’ previous work including manufacturing servitization, collaborative manufacturing and social networks, the proposed project will take into account the characteristics such as socialized interconnection, collaborative intelligence, personalized demands and diversified services in the crowd intelligence-based manufacturing environments, and explore how to satisfy the requirements of crowd intelligence-based manufacturing to extract and merge the semantic knowledge and seamlessly collaborate and optimize the trustworthy services. It proposes crowd intelligence-driven construction of large scale knowledge graph, resource sensing and service encapsulation, social recommendation of trustworthy services, and trustworthy composition and optimization of services. It aims to develop a prototype system for large scale resource management and optimization toward the crowd intelligence-based manufacturing. It provides the new theoretic framework and technical methodology to solve the problems of large scale personalized user demands and complicated sharing, collaboration and interaction among cross-domain manufacutring resources. It will promote the transformation of “Made-in-China 2025” plan in our country to the deep collaborative mode based on crowd intelligence-based manufacturing service ecosystems, enhance the upgrading of the collaborative service capabilities among small and medium enterprises, and bring great economic and social effects.

云计算、物联网、大数据和社会化网络等新兴信息技术的发展催生了“群智”这一种通过汇聚群体智慧协同解决问题的新模式。本项目在申请者已有的关于制造业服务化、协同制造、社交网络等研究成果基础之上，针对群智制造环境所具有的互联社会化、群智协同化、制造服务化、需求个性化、服务多元化等特征，研究如何满足群智制造模式对语义知识抽取与融合以及可信服务协同与优化的要求，突破众智驱动的大规模知识图谱构建、物联制造资源感知与服务封装、可信服务社会化推荐、可信服务组合优化等四项关键技术，开发一个面向群智制造的大规模资源管理与优化原型系统。该项目将为解决未来制造业中大规模个性化的用户需求以及跨领域制造资源的复杂共享、协同与交互等问题提供新思路、新方法与新技术，对促进“中国制造2025”计划向群智制造服务生态系统的深度协作模式转移，促进中小制造企业的协同服务能力转型升级，具有重要意义。

随着群智制造环境下跨企业的业务协作、互联共享和协同进化日益融入产品全生命周期，并以此提高企业的生产精益化、敏捷化、柔性化和服务增值能力，这对智能装备、电子信息、远程诊断、检验检测、业务运营等制造资源和服务的动态共享与优化整合能力的要求也越来越高，迫切需要突破制造资源整合瓶颈，深化制造资源协同服务，构建开放、共享、协作的群智制造服务生态系统。. 本项目针对群智制造环境所具有的互联社会化、群智协同化、制造服务化、需求个性化、服务多元化等特征，研究了如何满足群智制造模式对语义知识抽取与融合以及可信服务协同与优化的要求，突破了众智驱动的大规模知识图谱构建、物联制造资源感知与服务封装、可信服务社会化推荐、可信服务组合优化等四项关键技术，开发了面向群智制造的大规模资源管理与优化原型系统。该项目将为解决未来制造业中大规模个性化的用户需求以及跨领域制造资源的复杂共享、协同与交互等问题提供新思路、新方法与新技术，对促进“中国制造 2025”计划向群智制造服务生态系统的深度协作模式转移，促进中小制造企业的协同服务能力转型升级，具有重要意义。. 该研究取得了丰硕的成果。课题组获授权了10项中国国家发明专利，获得了3项软件著作权。课题组发表了标注有该项国家自然科学基金资助的37篇SCI/SSCI源国际学术期刊论文，包括IEEE Transactions on Systems Man Cybernetics-Systems、Journal of Intelligent Manufacturing、International Journal of Production Research、Information Sciences、IEEE Transactions on Knowledge and Data Engineering、Journal of Manufacturing Systems等，超额并高质量地完成了目标任务。