流程工业智能优化制造

柴天佑, 丁进良

中国工程科学 ›› 2018, Vol. 20 ›› Issue (4) : 51-58.

PDF(1113 KB)
PDF(1113 KB)
中国工程科学 ›› 2018, Vol. 20 ›› Issue (4) : 51-58. DOI: 10.15302/J-SSCAE-2018.04.009
专题研究

流程工业智能优化制造

作者信息 +

Smart and Optimal Manufacturing for Process Industry

Author information +
History +

摘要

本文在分析流程工业的特点、运行现状和国际智能制造发展状况的基础上,提出了我国流程工业智能制造的新模式——智能优化制造。在分析流程企业采用的由企业资源计划、制造执行系统、过程控制系统组成的三层架构和控制与管理信息化系统的发展状况基础上,提出了未来流程企业应采用的智能优化制造的架构和系统愿景功能,分析了实现愿景功能所需要攻克的关键共性技术和对自动化、计算机和通信、数据科学挑战的科学问题,提出了突出流程工业战略地位、实施战略规划与顶层设计等发展流程工业智能优化制造的建议。

Abstract

Based on the in-depth analysis of features of the process industry, the state of art of its operation control, and the global development of intelligent manufacturing, a new mode of intelligent manufacturing for the process industry, i.e., smart and optimal manufacturing, is proposed. After analysis of the development situation of the existing three-tier architecture (consisting of enterprise resource planning, manufacturing execution system, and process control system) and the control and management informatization system adopted by process enterprises, a smart and optimal manufacturing framework and prospects for future process enterprises are presented, followed by the analysis of key generic technologies that are critical for the successful deployment of intelligent manufacturing in the process industry. The fundamental challenges and open scientific problems to be addressed jointly by the communities of automation, computer and communication, and data science are also presented. Moreover, suggestions on the future development and deployment of smart and optimal manufacturing in the process industry are offered, include emphasizing the strategic position of the process industry, actualizing the strategic planning and top-level design.

关键词

流程工业 / 智能优化制造 / 发展愿景 / 科学挑战

Keywords

process industry / smart and optimal manufacturing / development vision / scientific challenges

引用本文

导出引用
柴天佑, 丁进良. 流程工业智能优化制造. 中国工程科学. 2018, 20(4): 51-58 https://doi.org/10.15302/J-SSCAE-2018.04.009

参考文献

[1]
Smart Manufacturing Leadship Coalition. Implementing 21st cen-tury smart manufacturing [R]. Washington DC: Smart Manufactur-ing Leadship Coalition, 2011.
[2]
德国联邦教育与研究部. 把握德国制造业的未来, 实施“ 工业4.0” 攻略的建议 [R]. 波恩: 德国联邦教育与研究部, 2013.
[3]
Gil Y, Greaves M, Hendler J, et al. Amplify scientific discovery with artificial intelligence [J]. Science, 2014, 346: 171–172.
[4]
中国工程院, 国家自然科学基金委员会. 大数据与制造流程知识自动化发展战略研究 [R]. 北京: 中国工程院, 国家自然科学基金委员会, 2016.
[5]
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 [J]. 自动化学报, 2009, 35(6): 641–649.
[6]
柴天佑, 金以慧, 任德祥, 等. 基于三层结构的流程工业现代集成制造系统 [J]. 控制工程, 2002, 9(3): 1–6.
[7]
柴天佑. 工业过程控制系统研究现状与发展方向 [J]. 中国科学: 信息科学, 2016, 46(8): 1003–1015.
[8]
Executive Office of the President. Artificial intelligence, automa-tion and the economy [R]. Washington DC: Executive Office of the President, 2016.
[9]
Executive Office of the President, National Science and Technolo-gy Council, Committee on Technology. Preparing for the future of artificial intelligence [R]. Washington DC: Executive Office of the President, National Science and Technology Council, Committee on Technology, 2016.
[10]
柴天佑. 制造流程智能化对人工智能的挑战 [J]. 中国科学基金, 2018 (3): 251–256.
[11]
Chai T Y, Qin S J, Wang H. Optimal operational control for com-plex industrial processes [J]. Annual Reviews in Control, 2014, 38(1): 81–92.
[12]
Chai T Y, Ding J L, Yu G, et al. Integrated optimization for the au-tomation systems of mineral processing [J]. IEEE Transactions on Automation Science and Engineering, 2014, 11(4): 965–982.
[13]
McKinsey Global Institute. Disruptive technologies: Advances that will transform life, business, and the global economy [R]. Chicago: McKinsey Global Institute, 2013.
[14]
Lamnabhi-Lagarrigue F, Annaswamy A, Engell S, et al. Systems & control for the future of humanity, research agenda: Current and future roles, impact and grand challenges [J]. Annual Reviews in Control, 2017, 43: 1–64.
基金
中国工程院咨询项目“‘互联网+’行动计划的发展战略研究”(2016-ZD-03);中国工程院咨询项目“新一代人工智能引领下的智能制造研究”(2017-ZD-08-03)
PDF(1113 KB)

Accesses

Citation

Detail

段落导航
相关文章

/