Skip to main content
SpringerLink
Log in

The Current State of Analysis, Synthesis, and Optimal Functioning of Multiproduct Digital Chemical Plants: Analytical Review

  • Published:
Theoretical Foundations of Chemical Engineering Aims and scope Submit manuscript

Abstract

An analytical review of the state of multiproduct chemical plants has been proposed. A comprehensive analysis is made of works of Russian and international scientists on the subject of flexibility of designing multiproduct chemical engineering systems under uncertainty. Works on planning and scheduling multiproduct chemical plants are considered. The formulations of mixed-integer linear and nonlinear programming problems and the methods and software to solve them are discussed. A brief overview is provided of Russian information systems and databases of technologies, equipment, manufacturers, consumers, and products of fine and specialty chemicals. Modern trends in creating intelligent systems of design and optimal functioning of flexible automated multiproduct chemical plants based on the main concepts of Industry 4.0 are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.

Similar content being viewed by others

REFERENCES

  1. The Official Website of the Russian Government, Plan of measures (the road map) on the development of production in the field of small-tonnage chemistry in the Russian Federation for the period until 2030. http://static.government.ru/media/files/BXMyJhAEHhaR9pbRmu4rQxY2ZAz7P7GF.pdf. Accessed July 27, 2020.

  2. Russian Chemical Complex, Development of small-tonnage chemistry in Russia. http://chemcomplex.ru/мaлo. Accessed July 28, 2020.

  3. Kalyuzhnyi, S.V., Small rain lays great dust, Khim. Zhizn, 2018, no. 6.

  4. Klepikov, D.N., Vygolov, N.V., and Il’inykh, L.V., Priority directions of the development of small-tonnage chemistry in the Russian Federation, Vestn. Khim. Prom-sti., 2016, no. 5 (92), p. 18.

  5. Klevtsov, A.A., Trokhin, V.E., Bessarabov, A.M., and Stoyanov, O.V., Development of the strategy of coordinating authorities for efficient production management in the field of small-tonnage chemistry in the Russian Federation, Vestn. Tekhnol. Univ., 2019, vol. 22, no. 11, p. 141.

    Google Scholar 

  6. Mokrozub, V.G. and Malygin, E.N., Development of decision-making support systems to design chemical process equipment for batch production, Adv. Mater. Technol., 2019, no. 2, p. 48.

  7. Mokrozub, V., Malygin, E., and Nemtinov, V., Information models for problems solving of hardware design of multi-range chemical industries, MATEC Web Conf., 2018, vol. 224, article no. 02060. https://doi.org/10.1051/matecconf/201822402060

  8. Bogomolov, B.B., Boldyrev, V.S., Zubarev, A.M., Meshalkin, V.P., and Men’shikov, V.V., Intelligent logical information algorithm for choosing energy- and resource-efficient chemical technologies, Theor. Found. Chem. Eng., 2019, vol. 53, no. 5, pp. 709–718. https://doi.org/10.1134/S0040579519050270

    Article  CAS  Google Scholar 

  9. Morary, M., Flexibility and resiliency of process systems, Comput. Chem. Eng., 1983, vol. 7, no. 4, p. 423.

    Article  Google Scholar 

  10. Grossmann, I.E., Mixed-integer programming approach for the synthesis of integrated process flowsheets, Comput. Chem. Eng., 1985, vol. 9, p. 463.

    Article  CAS  Google Scholar 

  11. Grossmann, I.E. and Floudas, C.A., Active constraint strategy for flexibility analysis in chemical processes, Comput. Chem. Eng., 1987, vol. 11, p. 675.

    Article  CAS  Google Scholar 

  12. Rippin, D.W.T., Design and operation of multiproduct and multipurpose batch chemical plants. — An analysis of problem structure, Comput. Chem. Eng,1983, vol. 7, p. 463. https://doi.org/10.1016/0098-1354(83)80023-4

    Article  CAS  Google Scholar 

  13. Rippin, D.W.T., Simulation of single and multiproduct batch chemical plants for optimal design and operation, Comput. Chem. Eng., 1983, vol. 7, no. 3, p. 137.

    Article  CAS  Google Scholar 

  14. Suhami, I. and Mah, R.S.H., Optimal design of multipurpose batch plants, Ind. Eng. Chem. Process Des. Dev., 1982, vol. 21, no. 1, p. 94.

    Article  CAS  Google Scholar 

  15. Karimi, I.A. and Reklaitis, G.V., Intermediate storage in noncontinuous processes involving stage of parallel units, AIChE J., 1985, vol. 31, no. 1, p. 44.

    Article  CAS  Google Scholar 

  16. Swaney, R.E. and Grossmann, I.E., An index for operational flexibility in chemical process design. Part II: Computational algorithms, AIChE J., 1985, vol. 31, no. 4, p. 631.

    Article  CAS  Google Scholar 

  17. Sparrow, R.E., Forder, G.J., and Rippin, D.W.T., The choice of equipment sizes for multiproduct batch plants. Heuristics vs. branch and bound, Ind. Eng. Chem. Process Des. Dev., 1975, vol. 14, no. 3, p. 197.

    Article  CAS  Google Scholar 

  18. Grossmann, I.E. and Sargent, R.W., Optimum design of multipurpose chemical plants, Ind. Eng. Chem. Process Des. Dev., 1979, vol. 18, no. 2, p. 343.

    Article  CAS  Google Scholar 

  19. Grossmann, I.E., Halemane, K.P., and Swaney, R.E., Optimization strategies for flexible chemical processes, Comput. Chem. Eng., 1983, vol. 7, no. 4, p. 439.

    Article  CAS  Google Scholar 

  20. Grossmann, I.E. and Halemann, K.P., A decomposition strategy for designing flexible chemical plants, AIChE J., 1982, vol. 28, no. 4, p. 686.

    Article  CAS  Google Scholar 

  21. Floudas, C.A. and Grossmann, I.E., Synthesis of flexible heat exchanger networks with uncertain flowrates and temperatures, Comput. Chem. Eng., 1987, vol. 11, no. 4, p. 319.

    Article  CAS  Google Scholar 

  22. A special issue devoted to flexible automated systems in small-tonnage chemistry, Zh. Vses. Khim. O-va. im. D. I. Mendeleeva, 1987, vol. 32, no. 3.

  23. Kafarov, V.V., Makarov, V.V., and Egorov, A.F., Flexible automated manufacturing systems in the chemical and related industries, Itogi Nauki Tekh., Ser.: Protsessy Appar. Khim. Tekhnol., Moscow: VINITI, 1988, vol. 16, p. 92.

    Google Scholar 

  24. Kafarov, V.V., Flexible automated manufacturing systems in the chemical industry, Zh. Vses. Khim. O-va. im. D. I. Mendeleeva, 1987, vol. 32, no. 3, p. 252.

    CAS  Google Scholar 

  25. Kafarov, V.V., Perov, V.L., and Meshalkin, V.P., Printsipy matematicheskogo modelirovaniya khimiko-tekhnologicheskikh sistem (Principles of Mathematical Modeling of Chemical Process Systems), Moscow: Khimiya, 1974.

  26. Kafarov, V.V., Meshalkin, V.P., and Perov, V.L., Matematicheskie osnovy avtomatizirovannogo proektirovaniya khimicheskikh proizvodstv (Mathematical Fundamentals of Computer-Aided Design of Chemical Production Processes), Moscow: Khimiya, 1979.

  27. Kafarov, V.V. and Makarov, V.V., Gibkie avtomatizirovannye proizvodstvennye sistemy v khimicheskoi promyshlennosti (Flexible Automated Manufacturing Systems in the Chemical Industry), Moscow: Khimiya, 1990.

  28. Kafarov, V.V. and Meshalkin, V.P., Analiz i sintez khimiko-tekhnologicheskikh sistem. Uchebnik dlya vuzov (Analysis and Synthesis of Chemical Process Systems: A Textbook for Institutions of Higher Education), Moscow: Khimiya, 1991.

  29. Perov, V.L. and Egorov, A.F., The use of adaptation principles in the design of flexible automated manufacturing systems, Zh. Vses. Khim. O-va. im. D. I. Mendeleeva, 1987, vol. 32, no. 3, p. 322.

    Google Scholar 

  30. Perov, V.L. and Egorov, A.F., A strategy for flexible control of multiproduct chemical plants under uncertainty, Teor. Osn. Khim. Tekhnol., 1994, vol. 28, no. 5, p. 519.

    CAS  Google Scholar 

  31. Perov, V.L., Bel’kov, V.P., and Savitskaya, T.V., Theoretical and practical aspects of the flexibility of multiproduct plants, Izv. Vyssh. Uchebn. Zaved., Khim. Khim. Tekhnol., 1991, no. 12, p. 98.

  32. Makarov, V.V. and Tarasova, E.C., A model and an algorithm for the synthesis of a flexible chemical process system in a multiproduct plant, in Printsipy kiberneticheskoi organizatsii khimicheskikh proizvodstv. Trudy MKhTI im. D.I. Mendeleeva (Principles of Cybernetic Organization of Chemical Plants: Transactions of the Mendeleev Moscow Institute of Chemical Technology), Moscow: Mosk. Khim.-Tekhnol. Inst. im. D.I. Mendeleeva, 1988, vol. 152, p. 81.

  33. Kafarov, V.V., Bodrov, V.I., Dvoretsky, S.I., et al., A new generation of flexible automated chemical plants, Teor. Osn. Khim. Tekhnol., 1993, vol. 27, no. 2, p. 254.

    Google Scholar 

  34. Bodrov, V.I., Dvoretsky, S.I., and Matveikin, V.G., Control problems in new-generation multiproduct flexible automated manufacturing systems, Teor. Osn. Khim. Tekhnol., 1994, vol. 28, no. 5, p. 537.

    CAS  Google Scholar 

  35. Dvoretsky, S.I., Synthesis of flexible automated small-tonnage chemical plants, Doctoral (Eng.) Dissertation, Tambov: Tambov Inst. of Chemical Engineering, 1991.

  36. Malygin, E.N. and Mishchenko, S.V., Design of flexible manufacturing systems in chemical engineering, Zh. Vses. Khim. O-va. im. D. I. Mendeleeva, 1987, vol. 32, no. 3, p. 280.

    CAS  Google Scholar 

  37. Malygin, A.N., Methods for computer-aided synthesis of multiproduct chemical plants, Doctoral (Eng.) Dissertation, Tambov: Tambov Inst. of Chemical Engineering, 1986.

  38. Malygin, E.N. and Frolova, T.A., Optimal scheduling of flexible chemical process flow diagrams, Khim. Prom-st., 1992, no. 6, p. 55.

  39. Ryabenko, E.A., Malyshev, R.M., and Bessarabov, A.M., Flexible multiproduct chemical process systems in the technology of chemical reagents and high-purity substances, Teor. Osn. Khim. Tekhnol., 1996, vol. 30, no. 1, p. 104.

    Google Scholar 

  40. Bessarabov, A.M., Synthesis of optimal chemical process systems for the production of high-purity oxide materials, Doctoral (Eng.) Dissertation, Moscow: Mendeleev Univ. of Chemical Technology of Russia, 1991.

  41. Egorov, A.F., Principles and strategy for flexible control of multiproduct chemical plants under uncertainty, Doctoral (Eng.) Dissertation, Moscow: Mendeleev Univ. of Chemical Technology of Russia, 1996.

  42. Ostrovsky, G.M., Volin, Y.M., and Senyavin, M.M., About one approach solving two stage optimization problem under uncertainty, Comput. Chem. Eng., 1997, vol. 21, no. 3, p. 317.

    Article  CAS  Google Scholar 

  43. Ostrovsky, G.M., Volin, Yu.M., Senyavin, M.M., and Berezhinskii, T.A., On the flexibility of chemical manufacturing processes, Teor. Osn. Khim. Tekhnol., 1994, vol. 28, no. 1, p. 54.

    Google Scholar 

  44. Zadorskii, V.M., Rusalin, S.M., Fokin, A.P., and Zhidenko, V.F., Engineering support of the flexibility of chemical process systems, Zh. Vses. Khim. O-va. im. D. I. Mendeleeva, 1987, vol. 32, no. 3, p. 273.

    CAS  Google Scholar 

  45. Lysenko, A.Yu., Modeling and optimization in the redesign of operating multiproduct plants, Cand. Sci. (Eng.) Dissertation, Moscow: Mendeleev Moscow Inst. of Chemical Technology, 1988.

  46. Kadosova, E.S., Synthesis of modular chemical process systems in the synthetic dye industry, Cand. Sci. (Eng.) Dissertation, Moscow: Mendeleev Moscow Inst. of Chemical Technology, 1990.

  47. Savitskaya, T.V., The use of a modular approach in the design of flexible manufacturing systems in the medical industry, Doctoral (Eng.) Dissertation, Moscow: Mendeleev Univ. of Chemical Technology of Russia, 1992.

  48. Perov, V.L., Bel’kov, V.P., and Savitskaya, T.V., Design of multiproduct chemical process systems taking into account flexibility: Part I. Theoretical fundamentals of the assessment of flexibility, Izv. Vyssh. Uchebn. Zaved., Khim. Khim. Tekhnol., 2000, vol. 43, no. 6, p. 81.

    CAS  Google Scholar 

  49. Verdiyan, M.A., Egorov, A.F., Savitskaya, T.V., and Tyurina, N.S., Flexible low-waste technologies in the field of functional powdered materials, Khim. Tekhnol., 2003, no. 11, p. 38.

  50. Egorov, A.F., Savitskaya, T.V., and Pugacheva, V.S., Design of flexible process flow diagrams for pharmaceutical production and wastewater treatment, in Sbornik nauchnykh statei “Matematicheskoe modelirovanie, resursosberezhenie i ekologicheskaya bezopasnost' tekhnologii” (Mathematical Modeling, Resource Saving, and Environmental Safety of Technologies: A Collection of Scientific Works), Moscow: Mosk. Gos. Univ. Inzh. Ekol., 1998, p. 49.

  51. Becker, T., Lier, S., and Werners, B., Value of modular production concepts in future chemical industry production networks, Eur. J. Oper. Res., 2019, vol. 276, no. 3, p. 957.

    Article  Google Scholar 

  52. Friedrich, J., Scheifele, S., Verl, A., and Lechler, A., Flexible and modular control and manufacturing system, Procedia CIRP, 2015, vol. 33, p. 115.

    Article  Google Scholar 

  53. Reuter, A., Kircher, C., and Verl, A., Manufacturer-independent mechatronic information model for control systems, Prod. Eng., 2010, vol. 4, p. 165.

    Article  Google Scholar 

  54. Wang, W. and Koren, Y., Scalability planning for reconfigurable manufacturing systems, J. Manuf. Syst., 2012, vol. 31, no. 2, p. 83.

    Article  Google Scholar 

  55. Mass Customization und Kundenintegration. Neue Wege zum innovativen Produkt, Piller, F.T. and Stotko, C.M., Eds., Düsseldorf: Symposion, 2003.

    Google Scholar 

  56. Business-wissen.de – Werkzeuge für Organisation und Management, Mass Customization – Mit individualisierten Standardprodukten zum Erfolg. http://www.business-wissen.de/artikel/mass-customization-mit-individualisierten-standardprodukten-zum-erfolg. Accessed July 24, 2020.

  57. Pistikopoulos, E.N. and Grossmann, I.E., Optimal design of flexibility in linear systems, Comput. Chem. Eng., 1988, vol. 12, no. 5, p. 383.

    Google Scholar 

  58. Straub, D.A. and Grossmann, I.E., Evaluation and optimization of stochastic flexibility in multiproduct batch plants, Comput. Chem. Eng., 1992, vol. 16, no. 2, p. 69.

    Article  CAS  Google Scholar 

  59. Pistikopoulos, E.N. and Grossmann, I.E., Evaluation and redesign for improving flexibility in linear system with infeasible nominal parameters, Comput. Chem. Eng., 1988, vol. 12, no. 12, p. 841.

    Article  CAS  Google Scholar 

  60. Pistikopoulos, E.N. and Grossmann, I.E., Optimal retrofit design for improving process flexibility in nonlinear systems. Part I: Fixed degree of flexibility. Part II: Optimal degree of flexibility, Comput. Chem. Eng., 1988, vol. 12, no. 12, p. 719.

    Article  CAS  Google Scholar 

  61. Perov, V.L., Bel’kov, V.P., and Savitskaya, T.V., Design of multiproduct chemical process systems taking into account flexibility: Part II. Practical use of the flexibility criterion, Izv. Vyssh. Uchebn. Zaved., Khim. Khim. Tekhnol., 2001, vol. 44, no. 4, p. 93.

    CAS  Google Scholar 

  62. Ostrovsky, G.M., Lapteva, T.V., and Ziyatdinov, N.N., Optimal design of chemical processes under uncertainty, Theor. Found. Chem. Eng., 2014, vol. 48, no. 5, pp. 583–593. https://doi.org/10.1134/S0040579514050212

    Article  CAS  Google Scholar 

  63. Halemane, K.P. and Grossmann, I.E., Optimal process design under uncertainty, AIChE J., 1983, vol. 29, p. 425.

    Article  CAS  Google Scholar 

  64. Wendt, M., Li, P., and Wozny, G., Nonlinear chance-constrained process optimization under uncertainty, Ind. Eng. Chem. Res., 2002, vol. 41, p. 3621.

    Article  CAS  Google Scholar 

  65. Grossmann, I.E., Apap, R.M., Calfa, B.A., Garcia-Herreros, P., and Zhang, Q., Mathematical programming techniques for optimization under uncertainty and their application in process systems engineering, Theor. Found. Chem. Eng., 2017, vol. 51, no. 6, pp. 893–909. https://doi.org/10.1134/S0040579517060057

    Article  CAS  Google Scholar 

  66. Ostrovsky, G.M., Lapteva, T.V., Ziyatdinov, N.N., and Silvestrova, A.S., Design of chemical engineering systems with chance constraints, Theor. Found. Chem. Eng., 2017, vol. 51, no. 6, pp. 961–971. https://doi.org/10.1134/S0040579517060136

    Article  CAS  Google Scholar 

  67. Grossmann, I.E. and Straub, D.A., Recent developments in the evaluation and optimization of flexible chemical processes, Proc. COPE-91, Puigjaner, L. and Espuna, A., Eds., Barcelona, 1991, p. 49.

  68. Ostrovskii, G.M., Ziyatdinov, N.N., Lapteva, T.V., and Pervukhin, I.D., Flexibility analysis of chemical technology systems, Theor. Found. Chem. Eng., 2007, vol. 41, no. 3, p. 235. https://doi.org/10.1134/S0040579507030025

    Article  CAS  Google Scholar 

  69. Li, C. and Grossmann, I.E., An improved L-shaped method for two-stage convex 0-1 mixed integer nonlinear stochastic programs, Comput. Chem. Eng., 2018, vol. 112, p. 165.

    Article  CAS  Google Scholar 

  70. Grossmann, I.E., Calfa, B.A., and Garcia-Herreros, P., Evolution of concepts and models for quantifying resiliency and flexibility of chemical processes, Comput. Chem. Eng., 2014, vol. 70, p. 22.

    Article  CAS  Google Scholar 

  71. Long, F., Zeiler, P., and Bertsche, B., Modelling the flexibility of production systems in Industry 4.0 for analysing their productivity and availability with high-level Petri nets, IFAC-PapersOnLine, 2017, vol. 50, no. 1, p. 5680.

    Article  Google Scholar 

  72. De Meyer, A., Nakane, J., Miller, J.G., and Ferdows, K., Flexibility: The next competitive battle the manufacturing futures survey, Strategic Manage. J., 1989, vol. 10, no. 2, p. 135.

    Article  Google Scholar 

  73. Sethi, A.K. and Sethi, S.P., Flexibility in manufacturing: A survey, Int. J. Flexible Manuf. Syst., 1990, vol. 2, no. 4, p. 289.

    Article  Google Scholar 

  74. Gupta, Y.P. and Somers, T.M., The measurement of manufacturing flexibility, Eur. J. Oper. Res., 1992, vol. 60, no. 2, p. 166.

    Article  Google Scholar 

  75. Gerwin, D. and Tarondeau, J.C., Consequences of programmable automation for French and American automobile factories: An international case study, Production Management: Methods and Studies, Ed. Lev B., Ed., Amsterdam: North-Holland, 1986, p. 85.

    Google Scholar 

  76. Alanche, P., Benzakour, K., Dolle, F., Gillet, P., Rodrigues, P., and Valette, R., PSI: A Petri net based simulator for flexible manufacturing systems, Advances in Petri Nets 1984, Rosenberg, G., Ed., Berlin: Springer, 1985, vol. 188, p. 1.

    Google Scholar 

  77. Narahari, Y. and Viswanadham, N., A Petri net approach to the modelling and analysis of flexible manufacturing systems, Ann. Oper. Res., 1985, vol. 3, no. 8, p. 449.

    Article  Google Scholar 

  78. El-Sayed, H.M., Younis, M.A., and Mahmoud, M.S., Modelling and simulation of a flexible manufacturing system with variable production ratios, Appl. Math. Modell., 1989, vol. 13, no. 7, p. 397.

    Article  Google Scholar 

  79. Boualem, M., Cherfaou, M., Bouchentouf, A.A., and Aissani, D., Modeling, simulation and performance analysis of a flexible production system, Eur. J. Pure Appl. Math., 2015, vol. 8, no. 1, p. 26.

    Google Scholar 

  80. Saren, S.K. and Tiberiu, V., Review of flexible manufacturing system based on modeling and simulation, Ann. Univ. Oradea, Fasc. Manage. Technol. Eng., 2016, vol. 25 (15), no. 1, p. 113.

  81. Floudas, C.A. and Lin, X., Continuous-time versus discrete-time approaches for scheduling of chemical processes: A review, Comput. Chem. Eng., 2004, vol. 28, no. 11, p. 2109.

    Article  CAS  Google Scholar 

  82. Makarov, V.V., Optimal organization of multiproduct chemical plants, Khim. Prom-st. Segodnya, 2008, no. 1, p. 29.

  83. Bel'kov, V.P., Development of methods for analysis and synthesis of flexible multiproduct batch chemical plants, Doctoral (Eng.) Dissertation, Moscow: Mendeleev Univ. of Chemical Technology of Russia, 2004.

  84. Vaselenak, A., Grossmann, I.E., and Westeberg, W., An embedding formulation for the optimal scheduling and design of multipurpose batch plants, Ind. Eng. Chem. Res., 1987, vol. 26, no. 1, p. 139.

    Article  CAS  Google Scholar 

  85. Egorov, A.F., Bel’kov, V.P., Komissarov, Yu.A., and Savitskaya, T.V., Simultaneous synthesis and scheduling of multiproduct chemical plants, Izv. Vyssh. Uchebn. Zaved., Khim. Khim. Tekhnol., 2004, vol. 47, no. 10, p. 93.

    CAS  Google Scholar 

  86. Bansal, V., Sakizlis, V., Ross, R., Perkins, J.D., and Pistikopoulos, E.N., New algorithms for mixed-integer dynamic optimization, Comput. Chem. Eng., 2003, vol. 27, no. 5, p. 647.

    Article  CAS  Google Scholar 

  87. Shimizu, Y. and Takamatsy, T., Application of mixed-integer linear programming in multiterm expansion planning under multi-objectives, Comput. Chem. Eng., 1985, vol. 9, no. 4, p. 367.

    Article  CAS  Google Scholar 

  88. Birewar, D.B. and Grossmann, I.E., Efficient optimization algorithms for zero-wait scheduling of multiproduct batch plants, Ind. Eng. Chem. Res., 1989, vol. 28, no. 9, p. 1333.

    Article  CAS  Google Scholar 

  89. Roman, R. and Grossmann, I.E., Relation between MILP modelling and logical inference for chemical process synthesis, Comput. Chem. Eng., 1991, vol. 15, no. 2, p. 73.

    Article  Google Scholar 

  90. Sahinidis, N.V. and Grossmann, I.E., Reformulation of multi-period MILP model for planning and scheduling of chemical processes, Comput. Chem. Eng., 1991, vol. 15, no. 3, p. 255.

    Article  CAS  Google Scholar 

  91. Orçun, S., Altinel, I.K., and Hortaçsu, Ö., General continuous time models for production planning and scheduling of batch processing plants: Mixed integer linear program formulations and computational issues, Comput. Chem. Eng., 2001, vol. 25, nos. 2–3, p. 371.

    Article  Google Scholar 

  92. Kocis, G.R. and Grossmann, I.E., Global optimization of noncovex mixed-integer nonlinear programming (MINLP) problems in process synthesis, Ind. Eng. Chem. Res., 1988, vol. 27, no. 8, p. 1407.

    Article  CAS  Google Scholar 

  93. Viswanathan, J. and Grossmann, I.E., A combined penalty function and outes-approximation method for MINLP optimization, Comput. Chem. Eng., 1991, vol. 15, no. 11, p. 769.

    Google Scholar 

  94. Türkay, M. and Grossmann, I.E., Logic-based MINLP algorithms for the optimal synthesis of process networks, Comput. Chem. Eng., 1996, vol. 20, no. 8, p. 959.

    Article  Google Scholar 

  95. Su, L.J., Tang, L.X., and Grossmann, I.E., Computational strategies for improved MINLP algorithms, Comput. Chem. Eng., 2015, vol. 75, p. 40.

    Article  CAS  Google Scholar 

  96. Karpushkin, S.V., A methodology for the design of multiproduct chemical plants, Extended Abstract of Doctoral (Eng.) Dissertation, Tambov: Tambov State Technical Univ., 2007.

  97. Egorov, A.F., Bel’kov, V.P., and Tyurina, N.S., Optimal selection of standard equipment in the design of multiproduct chemical plants, Khim. Prom-st., 2001, no. 2, p. 40.

  98. Borisenko, A.B. and Gorlatch, S., Parallel hybrid methaheuristics approach for optimal selection of production equipment, Vestn. Tambov. Gos. Tekh. Univ., 2018, vol. 24, no. 2, p. 228.

  99. Golubchikov, M.A. and Makarov, V.V., Modeling of discrete interactive and competitive processes in batch chemical plants, Usp. Khim. Khim. Tekhnol., 2012, vol. 26, no. 1 (130), p. 18.

  100. Ziyatdinov, N.N., Modeling and optimization of chemical engineering processes and systems, Theor. Found. Chem. Eng., 2017, vol. 51, no. 6, pp. 889–892. https://doi.org/10.1134/S0040579517060197

    Article  CAS  Google Scholar 

  101. Dvoretsky, D.S. and Dvoretsky, S.I., Integrated design of flexible chemical processes, devices, and control systems, Theor. Found. Chem. Eng., 2014, vol. 48, no. 5, pp. 614–621. https://doi.org/10.1134/S0040579514050169

    Article  CAS  Google Scholar 

  102. Biegler, L.T., Integrated optimization strategies for dynamic process operations, Theor. Found. Chem. Eng., 2017, vol. 51, no. 6, p. 910.

    Article  CAS  Google Scholar 

  103. Trespalacios, F. and Grossmann, I.E., Review of mixed-integer nonlinear and generalized disjunctive programming methods, Chem. Ing. Tech., 2014, vol. 86, no. 7, pp. 991–1012. https://doi.org/10.1002/cite.201400037

    Article  CAS  Google Scholar 

  104. Lee, S. and Grossmann, I.E., New algorithms for nonlinear generalized disjunctive programming, Comput. Chem. Eng., 2000, vol. 24, p. 2125.

    Article  CAS  Google Scholar 

  105. Floudas, C.A., Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications, Oxford: Oxford Univ. Press, 1995.

    Book  Google Scholar 

  106. Javid, N., Khalili-Damghani, K., Makui, A., and Abdi, F., Multi-objective flexibility-complexity trade-off problem in batch production systems using fuzzy goal programming, Expert Syst. Appl., 2020, vol. 148, p. 113266.

    Article  Google Scholar 

  107. Marques, A.F., Alves, A.C., and Sousa, J.P., An approach for integrated design of flexible production systems, Procedia CIRP, 2013, vol. 7, p. 586.

    Article  Google Scholar 

  108. Meshalkin, V.P., Panchenko, S.V., Dli, M.I., and Panchenko, D.S., Analysis of the thermophysical processes and operating modes of electrothermic reactor using a computer model, Theor. Found. Chem. Eng., 2018, vol. 52, no. 2, pp. 166–174. https://doi.org/10.1134/S0040579518020124

    Article  CAS  Google Scholar 

  109. Tsay, C. and Baldea, M., 110th Anniversary: Using data to bridge the time and length scales of process systems, Ind. Eng. Chem. Res., 2019, vol. 58, no. 36, p. 16696.

    Article  CAS  Google Scholar 

  110. Hadidi, L.A., Al-Turki, U.M., Rahim, A., et al., Integrated models in production planning and scheduling, maintenance and quality: A review, Int. J. Ind. Syst. Eng., 2012, vol. 10, no. 1, p. 21.

    Google Scholar 

  111. Pistikopoulos, E.N., Vassiliadis, C.G., Arvela, J., and Papageorgiou, L.G., Interactions of maintenance and production planning for multipurpose process plants: A system effectiveness approach, Ind. Eng. Chem. Res., 2001, vol. 40, p. 3195.

    Article  CAS  Google Scholar 

  112. Yildirim, M.B. and Nezami, F.G., Integrated maintenance and production planning with energy consumption and minimal repair, Int. J. Adv. Manuf. Technol., 2014, vol. 74, p. 1419.

    Article  Google Scholar 

  113. Liu, S., Yahia, A., and Papageorgiou, L.G., Optimal production and maintenance planning of biopharmaceutical manufacturing under performance decay, Ind. Eng. Chem. Res., 2014, vol. 53, p. 17075.

    Article  CAS  Google Scholar 

  114. Meeker, W.Q. and Hong, Y., Reliability meets big data: Opportunities and challenges, Qual. Eng., 2014, vol. 26, p. 102.

    Article  Google Scholar 

  115. Yildirim, M., Sun, X.A., and Gebraeel, N.Z., Sensor-driven condition-based generator maintenance scheduling—Part I: Maintenance problem, IEEE Trans. Power Syst., 2016, vol. 31, no. 6, p. 4253.

    Article  Google Scholar 

  116. Yildirim, M., Sun, X.A., and Gebraeel, N.Z., Sensor-driven condition-based generator maintenance scheduling—Part II: Incorporating operations, IEEE Trans. Power Syst., 2016, vol. 31, no. 6, p. 4263.

    Article  Google Scholar 

  117. Wu, O., Ave, G.D., Harjunkoski, I., Bouaswaig, A., Schneider, S.M., Roth, M., and Imsland, L., Optimal production and maintenance scheduling for a multiproduct batch plant considering degradation, Comput. Chem. Eng., 2020, vol. 135, p. 106734.

    Article  CAS  Google Scholar 

  118. Verderame, P.M., Elia, J.A., Li, J., et al., Planning and scheduling under uncertainty: A review across multiple sectors, Ind. Eng. Chem. Res., 2010, vol. 49, no. 9, p. 3993.

    Article  CAS  Google Scholar 

  119. Petkov, S.B. and Maranas, C.D., Multiperiod planning and scheduling of multiproduct batch plants under demand uncertainty, Ind. Eng. Chem. Res., 1997, vol. 36, no. 11, p. 4864.

    Article  CAS  Google Scholar 

  120. Balasubramanian, J. and Grossmann, I.E., Approximation to multistage stochastic optimization in multiperiod batch plant scheduling under demand uncertainty, Ind. Eng. Chem. Res., 2004, vol. 43, no. 14, p. 3695.

    Article  CAS  Google Scholar 

  121. Verderame, P.M. and Floudas, C.A., Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty. I. Robust optimization framework, Ind. Eng. Chem. Res., 2009, vol. 48, no. 15, p. 7214.

    Article  CAS  Google Scholar 

  122. Verderame, P.M. and Floudas, C.A., Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty: II. Conditional value-at-risk framework, Ind. Eng. Chem. Res., 2014, vol. 48, no. 15, p. 7214.

    Article  CAS  Google Scholar 

  123. De Mirandaa, J.L. and Casquilhob, M., Design and scheduling of chemical batch processes: Generalizing a deterministic to a stochastic model, Theor. Appl. Math. Comput. Sci., 2011, vol. 1, no. 2, p. 71.

    Google Scholar 

  124. Charitopoulos, V.M., Papageorgiou, L.G., and Dua, V., Multi-parametric mixed integer linear programming under global uncertainty, Comput. Chem. Eng., 2018, vol. 116, p. 279.

    Article  CAS  Google Scholar 

  125. Brunaud, B., Amaran, S., Bury, S., Wassick, J., and Grossmann, I.E., Novel approaches for the integration of planning and scheduling, Ind. Eng. Chem. Res., 2019, vol. 58, no. 43, p. 19973.

    Article  CAS  Google Scholar 

  126. Castro, P.M., Grossmann, I.E., and Zhang, Q., Expanding scope and computational challenges in process scheduling, Comput. Chem. Eng., 2018, vol. 114, p. 14.

    Article  CAS  Google Scholar 

  127. Erdirik-Dogan, M. and Grossmann, I.E., Planning models for parallel batch reactors with sequence-dependent changeovers, AIChE J., 2007, vol. 53, p. 2284.

    Article  CAS  Google Scholar 

  128. Erdirik-Dogan, M. and Grossmann, I.E., Slot-based formulation for the short-term scheduling of multistage, multiproduct batch plants with sequence-dependent changeovers, Ind. Eng. Chem. Res., 2008, vol. 47, p. 1159.

    Article  CAS  Google Scholar 

  129. Sung, C. and Maravelias, C.T., A projection-based method for production planning of multiproduct facilities, AIChE J., 2009, vol. 55, p. 2614.

    Article  CAS  Google Scholar 

  130. Terrazas-Moreno, S. and Grossmann, I.E., A multiscale decomposition method for the optimal planning and scheduling of multisite continuous multiproduct plants, Chem. Eng. Sci., 2011, vol. 66, p. 4307.

    Article  CAS  Google Scholar 

  131. Calfa, B.A., Agarwal, A., Grossmann, I.E., and Wassick, J.M., Hybrid Bilevel-Lagrangean decomposition scheme for the integration of planning and scheduling of a network of batch plants, Ind. Eng. Chem. Res., 2013, vol. 52, pp. 2152–2167. https://doi.org/10.1021/ie302788g

    Article  CAS  Google Scholar 

  132. Charitopoulos, V.M., Papageorgiou, L.G., and Dua, V., Closed-loop integration of planning, scheduling and multi-parametric nonlinear control, Comput. Chem. Eng., 2019, vol. 122, p. 172.

    Article  CAS  Google Scholar 

  133. Grossmann, I.E., Advances in mathematical programming models for enterprise-wide optimization, Comput. Chem. Eng., 2012, vol. 47, p. 2.

    Article  CAS  Google Scholar 

  134. Chu, Y. and You, F., Model-based integration of control and operations: Overview, challenges, advances, and opportunities, Comput. Chem. Eng., 2015, vol. 83, p. 2.

    Article  CAS  Google Scholar 

  135. Dias, L.S. and Ierapetritou, M.G., Integration of scheduling and control under uncertainties: Review and challenges, Chem. Eng. Res. Des., 2016, vol. 116, p. 98.

    Article  CAS  Google Scholar 

  136. Chu, Y. and You, F., Integration of scheduling and control with online closed-loop implementation: Fast computational strategy and large-scale global optimization algorithm, Comput. Chem. Eng., 2012, vol. 47, p. 248.

    Article  CAS  Google Scholar 

  137. Zhuge, J. and Ierapetritou, M.G., Integration of scheduling and control for batch processes using multi-parametric model predictive control, AIChE J., 2014, vol. 60, no. 9, p. 3169.

    Article  CAS  Google Scholar 

  138. Zhuge, J. and Ierapetritou, M.G., An integrated framework for scheduling and control using fast model predictive control, AIChE J., 2015, vol. 61, no. 10, p. 3304.

    Article  CAS  Google Scholar 

  139. GAMS Development Corp. and GAMS Software GmbH, System overview. https://www.gams.com/ products/gams/gams-language. Accessed July 25, 2020.

  140. Kronqvist, J., Bernal, D.E., Lundell, A., and Grossmann, I.E., A review and comparison of solvers for convex MINLP, Optim. Eng., 2019, vol. 20, p. 397.

    Article  Google Scholar 

  141. Schweiger, C. and Floudas, C.A., The MINOPT modeling language, Modeling Languages in Mathematical Optimization, Series in Applied Optimization, vol. 88, Kallrath, J., Ed., Boston: Springer, 2004, p. 185.

    Google Scholar 

  142. Biegler, L.T., Nonlinear Programming: Concepts, Algorithms, and Applications to Chemical Processes, MOS-SIAM Series on Optimization, Philadelphia: SIAM, 2010.

  143. Bussieck, M.R. and Vigerske, S., MINLP solver software, Wiley Encyclopedia of Operations Research and Management Science, Cochran, J.J., Cox, L.A., Jr., Keskinocak, P., Kharoufeh, J.P., and Smith, J.C., Eds., New York: Wiley, 2010.

    Google Scholar 

  144. Aspen Technology Inc, Aspen HYSYS. https://www.aspentech.com/en/products/engineering/ aspen-hysys. Accessed June 19, 2020.

  145. Aspen Technology Inc, Aspen Plus. https://www.aspentech.com/en/products/engineering/aspen-plus. Accessed June 19, 2020.

  146. Chemstations Inc., CHEMCAD: Chemical engineering simulation software. https://www.chemstations.com/CHEMCAD. Accessed June 19, 2020.

  147. Latyipov, R.M., Osipov, E.V., and Telyakov, E.Sh., Systems analysis of equipment and technology for glycols production, Theor. Found. Chem. Eng., 2017, vol. 51, no. 6, pp. 980–991. https://doi.org/10.1134/S0040579517060112

    Article  CAS  Google Scholar 

  148. Ziyatdinov, N.N., Lapteva, T.V., and Ryzhov, D.A., Matematicheskoe modelirovanie khimiko-tekhnologicheskikh sistem s ispol’zovaniem programmy CHEMCAD. Uchebno-metodicheskoe posobie (Mathematical Modeling of Chemical Engineering Systems Using the CHEMCAD Program: A Guidance Manual), Kazan: Kazan. Gos. Tekhnol. Univ., 2008.

  149. Borisenko, A.B., Haidl, M., and Gorlatch, S., Using parallel branch-and-bound algorithm on GPUs for optimal design of multi-product batch plants, Vestn. Tambov. Gos. Tekh. Univ., 2015, vol. 21, no. 3, p. 406.

  150. Gao, X., Wang, Y., Feng, Z., Huang, D., and Chen, T., Plant planning optimization under time-varying uncertainty: Case study on a poly(vinyl chloride), Ind. Eng. Chem. Res., 2018, vol. 57, no. 36, p. 12182.

    Article  CAS  Google Scholar 

  151. Tang, L. and Grossmann, I.E., Scheduling of cracking production process with feedstocks and energy constraints, Comput. Chem. Eng., 2016, vol. 94, p. 92.

    Article  CAS  Google Scholar 

  152. Sal’nikov, E.D. and Savitskaya, T.V., Certificate of the State Registration of a Computer Program no. 2017662859 RU, 2017.

  153. Savitskaya, T.V., Egorov, A.F., Mikhaylova, P.G., and Dementienko, A.V., Multilevel training of chemists and technologists in the interdisciplinary training system using distance educational technologies, Proc. 4th International Conference on Information Technologies in Engineering Education (Inforino 2018), Moscow, 2018. https://doi.org/10.1109/INFORINO.2018.8581753

  154. Sal’nikov, E.D. and Savitskaya, T.V., Certificate of the State Registration of a Computer Program no. 2017662858 RU, 2017.

  155. Sal’nikov, E.D. and Savitskaya, T.V., A program module for solving the problems of the synthesis of multiproduct chemical plants, Sbornik trudov. Informatizatsiya inzhenernogo obrazovaniya. Mezhdunarodnaya nauchno-prakticheskaya konferentsiya – INFORINO-2016 (Information Technologies in Engineering Education: Proc. International Research and Practice Conference – INFORINO-2016), Moscow: Nats. Issled. Univ. MEI, 2016, p. 429.

  156. Chernukhin, A.V., Sverchkov, A.M., and Savitskaya, T.V., Certificate of the State Registration of a Computer Program no. 2019665460 RU, 2019.

  157. Chernukhin, A.V., Savitskaya, T.V., Sverchkov, A.M., and Egorov, A.F., Software application for research on the organization of cyclic production of multi-assorted products, Proc. 5th International Conference on Information Technologies in Engineering Education (Inforino 2020), Moscow, 2020. https://doi.org/10.1109/Inforino48376.2020.9111749

  158. The Ministry of Industry and Trade of the Russian Federation, State Information System of Industry. https://gisp.gov.ru/gisplk. Accessed August 3, 2020.

  159. Bureau of Best Available Techniques, About us. http://burondt.ru/index/o-nas.html. Accessed August 1, 2020.

  160. Bureau of Best Available Techniques, Database “BAT Bureau”. http://burondt.ru/lpage/#base-buro. Accessed August 1, 2020.

  161. The Environmental Industrial Policy Centre (EIPC), Best available techniques. https://eipc.center/ndt. Accessed August 1, 2020.

  162. Bureau of Best Available Techniques, TK113. http://burondt.ru/informacziya/tk113/tk113.html. Accessed August 1, 2020.

  163. European Commission, Reference Documents, European IPPC Bureau. https://eippcb.jrc.ec.europa.eu/reference. Accessed August 1, 2020.

  164. Bessarabov, A.M., Kazakov, A.A., Trokhin, V.E., and Stoyanov, O.V., Application-oriented flexible CALS systems in multiproduct plants for the production of chemical reagents and high-purity substances, Vestn. Kazan. Tekhnol. Univ., 2014, vol. 17, no. 3, p. 292.

    Google Scholar 

  165. Razinov, A.L., Glushko, A.N., Bessarabov, A.M., Chigorina, E.A., Priorov, G.G., and Stoyanov, O.V., Development of a CALS-based technology for the modular production of impregnating compounds for roads, Vestn. Tekhnol. Univ., 2017, vol. 20, no. 14, p. 94.

    Google Scholar 

  166. Bessarabov, A.M., Trokhin, V.E., Filatova, L.N., Malyshev, R.M., Stoyanov, O.V., and Abzal’dinov, Kh.S., Developing a CALS-based technology for obtaining and analytically monitoring high-purity orthophosphoric acid, Vestn. Tekhnol. Univ., 2019, vol. 22, no. 11, p. 111.

    Google Scholar 

  167. Kazakov, A.A., Trokhin, V.E., Vendilo, A.G., and Bessarabov, A.M., CALS projects for equipment modules in the technology of high-purity substances, Usp. Khim. Khim. Tekhnol., 2012, vol. 26, no. 1 (130), p. 93.

  168. Trokhin, V.E., Bessarabov, A.M., Vendilo, A.G., and Stoyanov, O.V., Development of a CALS-based modular technology for the production of a range of high-purity trimethyl alkoxysilanes, Vestn. Tekhnol. Univ., 2016, vol. 19, no. 2, pp. 94–97.

    Google Scholar 

  169. Egorov, S.Ya., Sharonin, K.A., Andreev, G.I., and Nemtinov, K.V., A procedure for the development of electronic-graphical catalogs of multipurpose process equipment, Inf. Tekhnol. Proekt. Proizvod., 2011, no. 2, p. 67.

  170. Tambov State Technical University, Department of Computer Integrated Systems in Mechanical Engineering. http://www.apto.tstu.ru. Accessed August 31, 2020.

  171. Taptunov, V.N., An intelligent system for the information support of the selection of process flow diagrams for the production of solid pharmaceuticals, Extended Abstract of Cand. Sci. (Eng.) Dissertation, Ivanovo: Ivanovo State Univ. of Chemistry and Technology, 2012.

  172. Zhang, L., Mao, H., Liu, Q., and Gani, R., Chemical product design – Recent advances and perspectives, Curr. Opin. Chem. Eng., 2020, vol. 27, p. 22.

    Article  CAS  Google Scholar 

  173. Monostori, L., Kádár, B., Bauernhansl, T., et al., Cyber-physical systems in manufacturing, CIRP Ann., 2016, vol. 65, no. 2, p. 621.

    Article  Google Scholar 

  174. Bashir, M., Muhammad, B.B., and Li, Z., Minimal supervisory structure for flexible manufacturing systems using Petri nets, Proc. 2nd International Conference on Control, Automation and Robotics (ICCAR), 2016, p. 291.

  175. Hernández-Martínez, E.G., Puga-Velazquez, E.S., FoyoValdés, S.A., and Campaña, J.M., Task-based coordination of flexible manufacturing cells using Petri nets and ISA standards, IFAC-PapersOnLine, 2016, vol. 49, no. 12, p. 1008.

    Article  Google Scholar 

  176. Negri, E., Fumagalli, L., and Macchi, M.A., Review of the roles of digital twin in CPS-based production systems, Procedia Manuf., 2017, vol. 11, p. 939.

    Article  Google Scholar 

  177. Wenzelburger, P. and Allgower, F., A novel optimal online scheduling scheme for flexible manufacturing systems, IFAC-PapersOnLine, 2019, vol. 52, no. 10, p. 1.

    Article  Google Scholar 

  178. Wenzelburger, P. and Allgower, F., A Petri net modeling framework for the control of flexible manufacturing systems, IFAC-PapersOnLine, 2019, vol. 52, no. 13, p. 492.

    Article  Google Scholar 

  179. Holloway, L.E., Krogh, B.H., and Giua, A., A survey of Petri net methods for controlled discrete event systems, Discrete Event Dyn. Syst., 1997, vol. 7, no. 2, p. 151.

    Article  Google Scholar 

  180. Westkämper, E. and Löffler, C., Strategien der Produktion. Technologien, Konzepte und Wege in die Praxis, Berlin: Springer, 2016.

    Book  Google Scholar 

  181. Brettel, M., Friederichsen, N., Keller, M., and Rosenberg, M., How virtualization, decentralization and network building change the manufacturing landscape: An industry 4.0 perspective, Int. J. Mech. Ind. Sci. Eng., 2014, vol. 8, no. 1, p. 37.

    Google Scholar 

  182. Westerkamp, M., Friedhelm, V., and Küpper, A., Tracing manufacturing processes using blockchain-based token compositions, Digital Commun. Networks, 2020, vol. 6, no. 2, p. 167.

    Google Scholar 

  183. Kamalakkannan, S., Kulatunga, A.K., and Bandara, L.A.D.A.D., The conceptual framework of IoT based decision support system for life cycle management, Procedia Manuf., 2020, vol. 43, p. 423.

    Article  Google Scholar 

  184. Liu, Y. and Zhou, G., Key technologies and applications of Internet of Things, Proc. 2012 Fifth International Conference on Intelligent Computation Technology and Automation, Zhangjiajie, 2012, p. 197.

Download references

Funding

This work was supported by the Mendeleev University of Chemical Technology of Russia, Moscow, Russia.

Author information

Authors and Affiliations

  1. Mendeleev University of Chemical Technology of Russia, 125047, Moscow, Russia

    A. F. Egorov, T. V. Savitskaya & P. G. Mikhailova

Authors
  1. A. F. Egorov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. V. Savitskaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. P. G. Mikhailova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to A. F. Egorov, T. V. Savitskaya or P. G. Mikhailova.

Additional information

Translated by V. Glyanchenko

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Egorov, A.F., Savitskaya, T.V. & Mikhailova, P.G. The Current State of Analysis, Synthesis, and Optimal Functioning of Multiproduct Digital Chemical Plants: Analytical Review. Theor Found Chem Eng 55, 225–252 (2021). https://doi.org/10.1134/S0040579521010061

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0040579521010061

Keywords:

Search

Navigation