化学工业多尺度融合的智能制造模式——互联化工

doi:10.16085/j.issn.1000-6613.2019-1835

摘要/Abstract

摘要：

化工过程通过物质和能量的可控转化和传递来实现化工产品制备，具有多相性、非线性、非平衡、多尺度和多时空域等特性，化工行业智能制造发展的关键是实现多尺度条件下的互联协同与过程高效。一方面，化工过程多尺度互联机制的认识和调控是化工过程系统的安全可靠运行的关键；另一方面，实现化工过程多尺度下的互联、融合与协同是化工产业绿色发展的路径。鉴于此，本文提出了化学工业面向多尺度融合的智能制造模式——互联化工，给出了“互联化工”的概念、目标、特点和架构，并讨论了互联化工的相关关键技术，包括化学工业多层级的信息物理系统、云制造，以及全生命周期的安全管理技术、耦合互锁机制下的动态安全监控与决策模型、基于区块链的互联化工数据安全技术。

关键词: 多尺度, 智能制造, 互联化工, 系统工程

Abstract:

The manufacture of chemical products is realized through the controlled conversion and transfer of mass and energy in chemical processes with diversity features, such as polyphasic, nonlinear, non-equilibrium, multi-scale and multi-spatial etc. The key of the development of intelligent manufacturing in the chemical industry is to achieve the interconnection between the involved subsystems and high process efficiency under multi-scale conditions. On the one hand, the understanding and regulation of the multi-scale interconnection mechanism of chemical processes is crucial for the safe and reliable operation of chemical systems. On the other hand, the realization of the interconnection, integration and collaboration between the subsystems at multiple scales in the chemical processes is the way for the green development of the chemical industry. Therefore, this work proposed an intelligent manufacturing mode for multi-scale integration in the chemical industry, which was identified as interconnected chemical engineering. In this paper, the concept, objectives, features and technical framework of interconnected chemical engineering were provided. The key technologies of interconnected chemical engineering were discussed. They included multi-level cyber-physical systems in the chemical industry, cloud manufacturing, the secure technologies of product lifecycle management, the model of dynamic safety monitoring and decision-making under the coupling and interlocking mechanism, and blockchain-based security technology with interconnected chemical data.

Key words: multiscale, intelligent manufacturing, interconnected chemical engineering, systems engineering

中图分类号:

TQ086

吉旭, 党亚固, 周利, 戴一阳. 化学工业多尺度融合的智能制造模式——互联化工[J]. 化工进展, 2020, 39(8): 2927-2937.

Xu JI, Yagu DANG, Li ZHOU, Yiyang DAI. Interconnected chemical engineering: an intelligent manufacture mode of chemical industry emphasizing the integration of multiscale[J]. Chemical Industry and Engineering Progress, 2020, 39(8): 2927-2937.

参考文献

1	孙宏伟. 化学工程的发展趋势——认识时空多尺度结构及其效应[J]. 化工进展, 2003, 22(3): 224-227.
1	SUN Hongwei. Focus of chemical engineering —— understanding space-time multi-scale structure[J]. Chemical Industry and Engineering Progress, 2003, 22(3): 224-227.
2	杨宁, 李静海. 化学工程中的介尺度科学与虚拟过程工程: 分析与展望[J]. 化工学报, 2014, 65(7): 2403-2409.
2	YANG Ning, LI Jinghai. Mesoscience in chemical engineering and virtual process engineering: analysis and perspective[J]. CIESC Journal, 2014, 65(7): 2403-2409.
3	杨友麒. 从CIMS走向供应链的动态优化[J]. 计算机与应用化学, 2001, 18(1): 1-11.
3	YANG Youqi. From CIMS toward supply chain dynamic optimization [J]. Computers and Applied Chemistry, 2001, 18(1): 1-11.
4	GIL Y, GREAVES M, HENDLER J, et al. Amplify scientific discovery with artificial intelligence[J]. Science, 2014, 346(6206): 171-172.
5	白颐. “十四五”我国石化和化工行业高质量发展分析[J]. 化学工业, 2019, 37(4): 1-5, 11.
5	BAI Yi. Analysis of “14th Five Years” China’s petrochemical and chemical industry high quality development[J]. Chemical Industry, 2019, 37(4): 1-5, 11.
6	YUAN Zhihong, QIN Weizhong, ZHAO Jinsong. Smart manufacturing for the oil refining and petrochemical industry[J]. Engineering, 2017, 3(2): 179-182.
7	钱锋, 杜文莉, 钟伟民, 等. 石油和化工行业智能优化制造若干问题及挑战[J]. 自动化学报, 2017, 43(6): 893-901.
7	QIAN Feng, DU Wenli, ZHONG Weiming, et al. Problems and challenges of smart optimization manufacturing in petrochemical industries[J]. Acta Automatica Sinica, 2017, 43(6): 893-901.
8	JI Xu, HE Ge, XU Juanjuan, et al. Study on the mode of intelligent chemical industry based on cyber-physical system and its implementation[J]. Advances in Engineering Software, 2016, 99: 18-26.
9	中国石油和化学工业联合会智能工厂应用体系研究课题组. 石化行业智能工厂应用体系研究[J]. 中国石油和化工经济分析, 2016(11): 21-24.
9	Smart Factory Application System Research Group of CPCIF. Research on application system of smart factory in petrochemical industry[J]. Economic Analysis of China Petroleum and Chemical Industry, 2016(11): 21-24.
10	赵俊贵, 李德芳, 覃伟中. 中国石化智能工厂建设推进制造业迈向中高端[J]. 化工管理, 2015(31): 13-15.
10	ZHAO Jungui, LI Defang, QIN Weizhong. Sinopec’s smart factory construction promotes manufacturing to move toward high end[J]. Chemical Enterprise Management, 2015(31): 13-15.
11	覃伟中, 冯玉仲, 陈定江, 等. 面向智能工厂的炼化企业生产运营信息化集成模式研究[J]. 清华大学学报(自然科学版), 2015(4): 373-377, 469.
11	QIN Weizhong, FENG Yuzhong, CHEN Dingjiang, et al. Study on the information integration of production and operation for smart refinery[J]. Journal of Tsinghua University (Science and Technology), 2015(4): 373-377, 469.
12	PAN M, SIKORSKI J, AKROYD J, et al. Design technologies for eco-industrial parks: from unit operations to processes, plants and industrial networks[J]. Applied Energy, 2016, 175: 305-323.
13	桂卫华, 王成红, 谢永芳, 等. 流程工业实现跨越式发展的必由之路[J]. 中国科学基金, 2015, 29(5): 337-342.
13	GUI Weihua, WANG Chenghong, XIE Yongfang, et al. The necessary way to realize great-leap-forward development of process industries[J]. Bulletin of National Natural Science Foundation of China, 2015, 29(5): 337-342.
14	李静海, 葛蔚. 过程工业中的多尺度效应及离散化单元模拟[J]. 化工进展, 1999, 18(5): 11-13.
14	LI Jinghai, GE Wei. Multi-scale effect and discrete element simulation in process industries[J]. Chemical Industry and Engineering Progress, 1999, 18(5): 11-13.
15	VILLERMAUX J. New horizons in chemical engineering[R]. Keynote/plenary address, in: 5th World Congress of Chemical Engineering, San Diego, USA: American Institute of Chemical Engineers, 1996-07-14.
16	汪伟, 苏瑶瑶, 刘壮, 等. 微流控法可控构建微尺度功能材料[J]. 化工进展, 2019, 38(1): 428-440.
16	WANG Wei, SU Yaoyao, LIU Zhuang, et al. Controllable microfluidic fabrication of microscale functional materials[J]. Chemical Industry and Engineering Progress, 2019, 38(1): 428-440.
17	ZHOU Changan, HE Kaiwu, Wenyao Lü, et al. Energy and economic analysis for post-combustion CO₂ capture using amine-functionalized adsorbents in a temperature vacuum swing process[J]. Energy & Fuels, 2019, 33(3): 1774-1784.
18	WANG Wei, HE Xiaoheng, ZHANG Maojie, et al. Controllable microfluidic fabrication of microstructured materials from nonspherical particles to helices[J]. Macromolecular Rapid Communications, 2017, 38(23): 1700429.
19	王中杰, 谢璐璐. 信息物理融合系统研究综述[J]. 自动化学报, 2011, 37(10): 1157-1166.
19	WANG Zhongjie, XIE Lulu. Cyber-physical systems: a survey[J]. Acta Automatica Sinica, 2011, 37(10): 1157-1166.
20	LI Renfa, XIE Yong, LI Rui, et al. Survey of cyber-physical systems[J]. Journal of Computer Research and Development, 2012, 49(6): 1149-1161.
21	桂卫华, 陈晓方, 阳春华, 等. 知识自动化及工业应用[J]. 中国科学: 信息科学, 2016, 46(8): 1016-1034.
21	GUI Weihua, CHEN Xiaofang, YANG Chunhua, et al. Knowledge automation and its industrial application[J]. Scientia Sinica (Informationis), 2016, 46(8): 1016-1034.
22	李伯虎, 柴旭东, 张霖. 智慧云制造—— 一种互联网与制造业深度融合的新模式、新手段和新业态[J]. 中兴通讯技术, 2016, 22(5): 2-6.
22	LI Bohu, CHAI Xudong, ZHANG Lin. Smart cloud manufacturing — a new kind of manufacturing paradigm, approach and ecosystem of deep integration of the internet and the manufacturing industry[J]. ZTE Technology Journal, 2016, 22(5): 2-6.
23	QIU Xumeng, HE Ge, JI Xu. Cloud manufacturing model in polymer material industry[J]. The International Journal of Advanced Manufacturing Technology, 2016, 84(1/2/3/4): 239-248.
24	李向前, 杨海成, 敬石开, 等. 面向集团企业云制造的知识服务建模[J]. 计算机集成制造系统, 2012, 18(8): 1869-1880.
24	LI Xiangqian, YANG Haicheng, JING Shikai, et al. Knowledge service modeling approach for group enterprise cloud manufacturing[J]. Computer Integrated Manufacturing Systems, 2012, 18(8): 1869-1880.
25	QUE Yi, ZHONG Wei, CHEN Hailin, et al. Improved adaptive immune genetic algorithm for optimal QoS-aware service composition selection in cloud manufacturing[J]. International Journal of Advanced Manufacturing Technology, 2018, 96(10): 4455-4465.
26	李伯虎, 张霖, 任磊, 等. 云制造典型特征、关键技术与应用[J]. 计算机集成制造系统, 2012, 18(7): 1345-1356.
26	LI Bohu, ZHANG Lin, REN Lei, et al. Typical characteristics, technologies and applications of cloud manufacturing[J]. Computer Integrated Manufacturing Systems, 2012, 18(7): 1345-1356.
27	QIU Yue, MA Maode, CHEN Shuo. An anonymous authentication scheme for multi-domain machine-to-machine communication in cyber-physical systems[J]. Computer Networks, 2017, 129: 306-318.
28	王杭州, 邱彤, 陈丙珍, 等. 本质安全化的化工过程设计方法研究进展[J]. 化学反应工程与工艺, 2014, 30(3): 254-261.
28	WANG Hangzhou, QIU Tong, CHEN Bingzhen, et al. Progress on inherently safer design methods in chemical process[J]. Chemical Reaction Engineering and Technology, 2014, 30(3): 254-261.
29	DAI Yiyang, WANG Hangzhou, KHAN F, et al. Abnormal situation management for smart chemical process operation[J]. Current Opinion in Chemical Engineering, 2016, 14: 49-55.
30	CHOSNEK J. Managing management of change[J]. Process Safety Progress, 2010, 29(4): 384-386.
31	FERNáNDEZ-CARAMéS T M, FRAGA-LAMAS P. A review on the use of blockchain for the internet of things[J]. IEEE Access, 2018, 6: 32979-33001.
32	CHEN Min, WAN Jiafu, LI Fang. Machine-to-machine communications: architectures, standards and applications[J]. KSII Transactions on Internet & Information Systems, 2012, 6(2): 480-497.
33	SIKORSKI J J, HAUGHTON J, KRAFT M. Blockchain technology in the chemical industry: machine-to-machine electricity market[J]. Applied Energy, 2017, 195: 234-246.

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