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《工程(英文)》 >> 2017年 第3卷 第2期 doi: 10.1016/J.ENG.2017.02.003

流程工业智能制造展望:过程系统工程师面临的挑战

Center for Process Systems Engineering, Department of Chemical Engineering, University College London, London WC1E 7JE, UK

收稿日期: 2016-11-24 修回日期: 2017-01-16 录用日期: 2017-01-17 发布日期: 2017-03-16

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摘要

本文讨论了流程工业智能制造对过程系统工程(PSE) 研究人员提出的挑战。现有的研究在实现全厂和全站点优化方面已经取得了很大进展,进行基准化测试能够增加说服力。本文进一步讨论了过程系统工程师在开发可用工具和技术时遇到的技术性挑战,包括灵活性和不确定性,响应性和敏捷性,鲁棒性和安全性,混合物性质和功能的预测,以及新的建模和数学范式。利用大数据进行智能化开发来驱动系统灵活性需要面对新的挑战,例如,如何在漫长又复杂的供应链中确保数据的一致性和机密性。建模方面也存在很多挑战,涉及如何对所有的关键技术进行恰当的建模,特别是健康、安全和环境方面,需要在特定地点对微小却关键的量进行准确预测。对环境方面的关注要求我们紧密跟踪所有的分子种类,以便于它们能被最佳地用于创造可持续的解决方案。而源自于新型个性化产品的破坏性商业模式对环境的影响则难以预测。

参考文献

[ 1 ] Davis J, Edgar T, Porter J, Bernaden J, Sarli M. Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Comput Chem Eng 2012;47:145–56 链接1

[ 2 ] Kumar A, Baldea M, Edgar TF, Ezekoye OA. Smart manufacturing approach for efficient operation of industrial steam-methane reformers. Ind Eng Chem Res 2015;54(16):4360–70 链接1

[ 3 ] Li D. Perspective for smart factory in petrochemical industry. Comput Chem Eng 2016;91:136–48 链接1

[ 4 ] Grossmann IE, Doherty MF, Harold MP. A tribute to Roger Sargent. AIChE J 2016;62(9):2950 链接1

[ 5 ] Smith R. Chemical process: Design and integration. Chichester: John Wiley & Sons, Ltd.; 2005.

[ 6 ] Douglas JM. Conceptual design of chemical processes. New York: McGraw-Hill Book Company; 1988.

[ 7 ] Biegler LT, Grossmann IE, Westerberg AW. Systematic methods of chemical process design. Englewood Cliffs: Prentice-Hall; 1997.

[ 8 ] Jaksland CA, Gani R, Lien KM. Separation process design and synthesis based on thermodynamic insights. Chem Eng Sci 1995;50(3):511–30 链接1

[ 9 ] Dijkema GPJ, Basson L. Complexity and industrial ecology: Foundations for a transformation from analysis to action. J Ind Ecol 2009;13(2):157–64 链接1

[10] Hebert D. Real-time optimization with MPC. Control [Internet]. 2013 Sep 12 [cited 2016 Oct 20]. Available from: http://www.controlglobal.com/articles/2013/real-time-optimization-with-mpc/.

[11] He X, Hayya JC. The Impact of just-in-time production on food quality. Total Qual Manage 2002;13(5):651–70 链接1

[12] Cao C, Gu X, Xin Z. A data-driven rolling-horizon online scheduling model for diesel production of a real-world refinery. AIChE J 2013;59(4):1160–74 链接1

[13] Grossmann IE, Sargent RWH. Optimum design of chemical plants with uncertain parameters. AIChE J 1978;24(6):1021–8 链接1

[14] Halemane KP, Grossmann IE. Optimal process design under uncertainty. AIChE J. 1983;29(3):425–33 链接1

[15] Steimel J, Harrmann M, Schembecker G, Engell S. A framework for the modeling and optimization of process superstructures under uncertainty. Chem Eng Sci 2014;115:225–37 链接1

[16] Steimel J, Engell S. Optimization-based support for process design under uncertainty: A case study. AIChE J 2016;62(9):3404–19 链接1

[17] Mohideen MJ, Perkins JD, Pistikopoulos EN. Optimal design of dynamic systems under uncertainty. AIChE J 1996;42(8):2251–72 链接1

[18] Washington ID, Swartz CLE. Design under uncertainty using parallel multiperiod dynamic optimization. AIChE J 2014;60(9):3151–68 链接1

[19] Wang S, Baldea M. Identification-based optimization of dynamical systems under uncertainty. Comput Chem Eng 2014;64:138–52 链接1

[20] Sahinidis NV. Optimization under uncertainty: State-of-the-art and opportunities. Comput Chem Eng 2004;28(6–7):971–83 链接1

[21] Yuan Z, Chen B, Zhao J. An overview on controllability analysis of chemical processes. AIChE J 2011;57(5):1185–201 链接1

[22] Sharifzadeh M. Integration of process design and control: A review. Chem Eng Res Des 2013;91(12):2515–49 链接1

[23] Ellis M, Durand H, Christofides PD. A tutorial review of economic model predictive control methods. J Process Contr 2014;24(8):1156–78 链接1

[24] Youssef MA, Youssef EM. The synergistic impact of time-based technologies on manufacturing competitive priorities. Int J Technol Manage 2015;67(2–4):245–68 链接1

[25] Sousa RT, Shah N, Papageorgiou LG. Supply chains of high-value low-volume products. In: Pistikopoulos EN, Georgiadis MC, Dua V, Papageorgiou LG, editors Process systems engineering: Supply chain optimization, volume 4. Weinheim: Wiley-VCH Verlag GmbH & Co. KGaA; 2008. p. 1–27.

[26] Li J, Xiao X, Boukouvala F, Floudas CA, Zhao B, Du G, et al.Data-driven mathematical modeling and global optimization framework for entire petrochemical planning operation. AIChE J 2016;62(9):3020–40 链接1

[27] Sahay N, Ierapetritou M. Multienterprise supply chain: Simulation and optimization. AIChE J 2016;62(9):3392–403 链接1

[28] Venkatasubramanian V, Rengaswamy R, Yin K, Kavuri SN. A review of process fault detection and diagnosis: Part I: Quantitative model-based methods. Comput Chem Eng 2003;27(3):293–311 链接1

[29] Zhang L, Babi DK, Gani R. New vistas in chemical product and process design. Annu Rev Chem Biomol 2016;7:557–82 链接1

[30] Jonuzaj S, Akula PT, Kleniati PM, Adjiman CS. The formulation of optimal mixtures with generalized disjunctive programming: A solvent design case study. AIChE J 2016;62(5):1616–33 链接1

[31] Bogle IDL. Recent developments in process systems engineering as applied to medicine. Curr Opin Chem Eng 2012;1(4):453–8 链接1

[32] Ashworth W, Perez-Galvan C, Davies N, Bogle IDL. Liver function as an engineering system. AIChE J 2016;62(9):3285–97 链接1

[33] Duran MA, Grossmann IE. An outer-approximation algorithm for a class of mixed-integer nonlinear programs. Math Program 1986;36(3):307–39 链接1

[34] Ruiz JP, Grossmann IE. Global optimization of non-convex generalized disjunctive programs: A review on reformulations and relaxation techniques. J Global Optim 2017;67(1–2):43–58 链接1

[35] Floudas CA, Pardalos PM. State of the art in global optimization: Computational methods and applications. Dordrecht: Kluwer Academic Publishers; 2012.

[36] Brandt SC, Morbach J, Miatidis M, Thei?en M, Jarke M, Marquardt W. An ontology-based approach to knowledge management in design processes. Comput Chem Eng 2008;32(1–2):320–42 链接1

[37] Zhao Y, Jiang C, Yang A. Towards computer-aided multiscale modelling: An overarching methodology and support of conceptual modelling. Comput Chem Eng 2012;36:10–21 链接1

[38] Lopez Flores R, Belaud JP, Negny S, Le Lann JM. Open computer aided innovation to promote innovation in process engineering. Chem Eng Res Des 2015;103:90–107 链接1

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