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Engineering >> 2017, Volume 3, Issue 2 doi: 10.1016/J.ENG.2017.02.011

Fundamental Theories and Key Technologies for Smart and Optimal Manufacturing in the Process Industry

Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

Received:2016-02-28 Revised:2017-03-03 Accepted: 2017-03-06 Available online:2017-04-05

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Given the significant requirements for transforming and promoting the process industry, we present the major limitations of current petrochemical enterprises, including limitations in decision-making, production operation, efficiency and security, information integration, and so forth. To promote a vision of the process industry with efficient, green, and smart production, modern information technology should be utilized throughout the entire optimization process for production, management, and marketing. To focus on smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of the manufacturing process, operating mode, and supply chain management, we put forward several key scientific problems in engineering in a demand-driven and application-oriented manner, namely: ① intelligent sensing and integration of all process information, including production and management information; ② collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; ③ cooperative control and optimization of plant-wide production processes via human-cyber-physical interaction; and ④ life-cycle assessments for safety and environmental footprint monitoring, in addition to tracing analysis and risk control. In order to solve these limitations and core scientific problems, we further present fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Although this paper discusses the process industry in China, the conclusions in this paper can be extended to the process industry around the world.


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[ 1 ] Williams E. Environmental effects of information and communications technologies. Nature 2011;479(7373):354–8 link1

[ 2 ] Smart Manufacturing Leadership Coalition. Implementing 21st century smart manufacturing [Internet]. Washington, DC: Smart Manufacturing Leadership Coalition. 2011 Jun 24 [cited 2016 Oct 15]. Available from:

[ 3 ] Federal Ministry of Education and Research (Germany). The CAE Centre for Strategic Studies, trans. Grasp the future of German manufacturing industry: Recommendations for implementing the strategic initiative “Industry 4.0”. Final report. Bonn: Federal Ministry of Education and Research (Germany); 2013 Sep. Chinese.

[ 4 ] State Council of the People’s Republic of China. Made in China 2025 strategy [Internet]. Beijing: State Council of the People’s Republic of China. 2015 May 8 [cited 2016 Oct 15]. Available from: Chinese.

[ 5 ] Li K. Report on the work of the government in 2016 [Internet]. Beijing: State Council of the People’s Republic of China. 2016 Mar 5 [cited 2016 Oct 15]. Available from: Chinese.

[ 6 ] Sendler U (Germany). Deng M, Li X, trans. Industry 4.0: The forthcoming Fourth Industrial Revolution. Beijing: China Machine Press; 2014 Jul. Chinese.

[ 7 ] Chai T. Industrial process control systems: Research status and development direction. Sci Sinica Inf 2016;46(8):1003–15. Chinese.

[ 8 ] Cassandras CG. Smart cities as cyber-physical social systems. Engineering 2016;2(2):156–8 link1

[ 9 ] Rajkumar R. A cyber-physical future. P IEEE 2012;100(Special Centennial Issue):1309–12. link1

[10] Sztipanovits J, Koutsoukos X, Karsai G, Kottenstette N, Antsaklis P, Gupta V, et al.Toward a science of cyber-physical system integration. P IEEE 2012;100(1):29–44 link1

[11] O’Rourke D. The science of sustainable supply chains. Science 2014;344(6188):1124–7 link1

[12] Dooley KJ. The whole chain. Science 2014;344(6188):1108 link1

[13] Hellweg S, Milà i Canals L. Emerging approaches, challenges and opportunities in life cycle assessment. Science 2014;344(6188):1109–13 link1

[14] Hoekstra AY, Wiedmann TO. Humanity’s unsustainable environmental footprint. Science 2014;344(6188):1114–7 link1

[15] Tang Y, Qian F, Gao H, Kurths J. Synchronization in complex networks and its application—A survey of recent advances and challenges. Annu Rev Contr 2014;38(2):184–98 link1

[16] Cernansky R. Chemistry: Green refill. Nature 2015;519(7543):379–80 link1

[17] Wallace JM, Held IM, Thompson DWJ, Trenberth KE, Walsh JE. Global warming and winter weather. Science 2014;343(6172):729–30 link1

[18] Marx V. Biology: The big challenges of big data. Nature 2013;498(7453):255–60 link1

[19] Bergamaschi S, Carlini E, Ceci M, Furletti B, Giannotti F, Malerba D, et al.Big data research in Italy: A perspective. Engineering 2016;2(2):163–70 link1

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