复杂工业过程智能优化决策系统的现状与展望
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摘要
流程工业是制造业的重要组成部分,是我国国民经济和社会发展的重要支柱产业.新一代信息技术和人工智能技术为流程工业的发展带来新的挑战和机遇.只有与流程工业的特点与目标密切结合,充分利用大数据,将人工智能、移动互联网、云计算、建模、控制与优化等信息技术与工业生产过程的物理资源紧密融合与协同,实现流程工业智能优化制造,才可能实现流程工业的跨越式发展.本文聚焦流程工业的复杂生产过程,从其智能优化决策系统的角度,描述了复杂工业过程优化决策系统的问题、回顾总结了复杂工业过程全流程优化决策系统的现状,分析了智能优化决策系统的必要性,提出了智能优化决策系统的发展目标及愿景,并对智能优化决策系统的下一步重点研究方向进行了展望.
Process industry is an important part of manufacturing industry and an important pillar industry of national economic and social development in China. The new generation of information technology and artificial intelligence technology bring new challenges and opportunities to the development of process industry. To realize the leapfrog development of intelligent manufacturing of process industry, we need to closely combine with the characteristics and objectives of process industry and make full use of big data. We also need the integration and coordination of artificial intelligence, information technology, mobile internet, cloud computing, modeling, control and optimization and the physical resources of industrial production process. From the point of view of intelligent optimal decision-making system for complex industrial process, this paper describes the decision-making process, decision-making content and problems of complex industrial process. It reviews and summarizes the status of the decision-making system for the whole process of complex industries,and analyzes on the necessity of intelligent optimal decision-making system. And the development vision and goal of intelligent optimal decision-making system have been proposed. Finally, the future direction of intelligent optimization decision system is prospected.
Process industry is an important part of manufacturing industry and an important pillar industry of national economic and social development in China. The new generation of information technology and artificial intelligence technology bring new challenges and opportunities to the development of process industry. To realize the leapfrog development of intelligent manufacturing of process industry, we need to closely combine with the characteristics and objectives of process industry and make full use of big data. We also need the integration and coordination of artificial intelligence, information technology, mobile internet, cloud computing, modeling, control and optimization and the physical resources of industrial production process. From the point of view of intelligent optimal decision-making system for complex industrial process, this paper describes the decision-making process, decision-making content and problems of complex industrial process. It reviews and summarizes the status of the decision-making system for the whole process of complex industries,and analyzes on the necessity of intelligent optimal decision-making system. And the development vision and goal of intelligent optimal decision-making system have been proposed. Finally, the future direction of intelligent optimization decision system is prospected.
引文
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2 Chai Tian-You, Ding Jin-Liang, Gui Wei-Hua, Qian Feng.Research on the development strategy of knowledge automation of big data and manufacturing process. Beijing:Science Press, 2018.(柴天佑,丁进良,桂卫华,钱锋.大数据与制造流程知识自动化发展战略研究.北京:科学出版社, 2018.)
3 Gui Wei-Hua, Wang Cheng-Hong, Xie Yong-Fang, Song Su, Meng Qing-Feng, Ding Jin-Liang. The necessary way to realize great-leap-forward development of process industries. Bulletin of National Natural Science Foundation of China. 2015, 29(5):337-342(桂卫华,王成红,谢永芳,宋苏,孟庆峰,丁进良.流程工业实现跨越式发展的必由之路.中国科学基金, 2015, 29(5):337-342)
4 Qian F, Zhong W, Du W. Fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Engineering, 2017, 3(2):154-160
5 Chai Tian-You. The challenge of control and optimization theory method for production and manufacturing process optimization control. Acta Automatica Sinica, 2009,35(6):641-649(柴天佑.生产制造全流程优化控制对控制与优化理论方法的挑战.自动化学报, 2009, 35(6):641-649)
6 Chai Tian-You, Ding Jin-Liang, Wang Hong, Su ChunYi. Hybrid intelligent optimization control for complex industrial processes. Acta Automatica Sinica, 2008, 34(5):505-515(柴天佑,丁进良,王宏,苏春翌.复杂工业过程运行的混合智能优化控制方法.自动化学报, 2008, 34(5):505-515)
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