从互联网和海量数据中快速获取知识并服务于人，帮助人们灵捷地应对多样的、不确定的、复杂任务，是知识自动化的根本任务。如何实现大数据、知识与人三者之间的动态闭环反馈及实时交互，是知识自动化的关键科学问题。流程工业制定生产计划时仍然依赖于人的经验，难以全面考虑人和社会因素的影响，本项目提出基于CPSS方法的流程工业知识自动化的基本框架。为此，本项目研究精准感知与原料和产品相关的跨媒体数据获取和知识提取技术，研究生产现场大数据的聚合和知识提取技术，研究人机物灵捷交互的技术和工具，最后拟构建流程工业生产计划知识自动化系统服务平台，包括专业情报系统，生产计划系统和知识查询和推送系统，并在青岛德铸特钢有限公司进行实际运行和验证分析。本课题力图推动基于CPSS的知识自动化系统和技术在流程工业生产计划中得到应用，为流程工业转型升级和由大变强进行有益的探索。

Acquiring knowledge from the Internet and Big data quickly and helping people agilely deal with uncertainty, diversity, and complexity are the main tasks of knowledge automation. How to make data and knowledge interact timely and do closed loop feedback with people is the key scientific problem of knowledge automation. Production planning-making mainly relies on people's experience, which nearly consider nothing about the factors of people and society. This project proposes basic framework of knowledge automation in process industry based on CPSS. Firstly,we are going to invesigate how to acquire data and distill knowledge accurately and intelligently from social media which are related with the materials and products; secondly, we will make data aggregation and knowledge extraction from the big data at the production site; and finally, we will constrct technologies and tools for people to interact agilely with machines. The project aims to build a service platform of knowledge automation for production planning in process industry, which includes professional intelligence system, production planning system and knowledge searching and pushing system, and verify the platform in Shengli oil refinery of Qingdao De Zhu Special Steel co.,LTD. The project tries to promote researches and technologies of knowledge automation based on CPSS, and then apply them to product planning in process industry. This project will be beneficial for process industry's transformation and upgrading.