Multi-objective optimization of a fluid catalytic cracking unit using response surface methodology
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Anish Thomas
Abstract
In oil refineries, fluid catalytic cracking (FCC) is a major unit consisting of several process variables and multiple products. Since FCC units are given prime importance as they are contributing a large share in profits, the optimal operation of FCC is always desirable while considering the changing economic scenarios with respect to the products. However, optimization of FCC is quite challenging due to the complex nature of the process. In this work, using Aspen HYSYS V9® catcracker module, process data of FCC was obtained using central composite design (CCD). Second order regression equations for the selected responses were obtained using Analysis of variance (ANOVA) approach. The interaction effects of feed flow, feed temperature, feed pressure, air blower discharge temperature and catalyst circulation rate on responses (yield of products) were presented. Further, the optimization was performed based on a multi-response optimization technique in the Design expert software and the optimal values of the input variables were obtained for the chosen objectives (representing various operation scenarios). The optimal operation scenarios that were obtained for the objectives were validated successfully. This work highlights the use of statistics based soft computing techniques for the optimization of complex chemical engineering operations such as FCC.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Avidan, AA, Edwards, M, Owen, H. Fluid-catalytic cracking: past and future challenges. Rev Chem Eng 1990;6:1–72. https://doi.org/10.1515/revce.1990.6.1.1.Search in Google Scholar
2. Reza, S. Fluid catalytic cracking handbook. Waltham: Butterworth-Heinmann; 2012.Search in Google Scholar
3. Ali, H, Rohani, S, Corriou, JP. Modeling and control of a riser type fluid catalytic cracking (FCC) unit. Chem Eng Res Des 1997;75:401–12. https://doi.org/10.1205/026387697523868.Search in Google Scholar
4. Malay, P, Milne, BJ, Rohani, S. The modified dynamic model of a riser type fluid catalytic cracking unit. Can J Chem Eng 1999;77:169–79. https://doi.org/10.1002/cjce.5450770128.Search in Google Scholar
5. Han, IS, Chung, CB. Dynamic modeling and simulation of a fluidized catalytic cracking process. Part I: process modeling. Chem Eng Sci 2001;56:1951–71. https://doi.org/10.1016/s0009-2509(00)00493-0.Search in Google Scholar
6. Secchi, AR, Santos, MG, Neumann, GA, Trierweiler, JO. A dynamic model for a FCC UOP stacked converter unit. Comput Chem Eng 2001;25:851–8. https://doi.org/10.1016/s0098-1354(01)00659-7.Search in Google Scholar
7. Almeida, NtE, Secchi, AR. Dynamic optimization of a FCC converter unit: numerical analysis. Braz J Chem Eng 2011;28:117–36. https://doi.org/10.1590/s0104-66322011000100014.Search in Google Scholar
8. John, YM, Patel, R, Mujtaba, IM. Maximization of gasoline in an industrial fluidized catalytic cracking unit. Energy Fuel 2017;31:5645–61. https://doi.org/10.1021/acs.energyfuels.7b00071.Search in Google Scholar
9. Kasat, RB, Gupta, SK. Multi-objective optimization of an industrial fluidized-bed catalytic cracking unit (FCCU) using genetic algorithm (GA) with the jumping genes operator. Comput Chem Eng 2003;27:1785–800. https://doi.org/10.1016/s0098-1354(03)00153-4.Search in Google Scholar
10. Sankararao, B, Gupta, SK. Multi-objective optimization of an industrial fluidized-bed catalytic cracking unit (FCCU) using two jumping gene adaptations of simulated annealing. Comput Chem Eng 2007;31:1496–515. https://doi.org/10.1016/j.compchemeng.2006.12.012.Search in Google Scholar
11. Bohorquez, JFC, Tovar, LP, Maciel, MRW, Melo, DC, Filho, RM. Surrogate-model-based, particle swarm optimization, and genetic algorithm techniques applied to the multiobjective operational problem of the fluid catalytic cracking process. Chem Eng Commun 2019;207:612–31.10.1080/00986445.2019.1613230Search in Google Scholar
12. Cuadros, JF, Melo, DC, Filho, RM, Maciel, MRW. Fluid catalytic cracking optimisation using factorial design and genetic algorithm techniques. Can J Chem Eng 2013;91:279–90. https://doi.org/10.1002/cjce.21700.Search in Google Scholar
13. Ridzuan, N, Adam, F, Yaacob, Z. Screening of factor influencing wax deposition using full factorial experimental design. Petrol Sci Technol 2016;34:84–90. https://doi.org/10.1080/10916466.2015.1122625.Search in Google Scholar
14. Bhran, AA, Shoaib, AM, Umana, B. Optimization of crude oil hydrotreating process as a function of operating conditions: application of response surface methodology. Comput Chem Eng 2016;89:158–65. https://doi.org/10.1016/j.compchemeng.2016.03.026.Search in Google Scholar
15. Das, S, Mishra, S. Box-Behnken statistical design to optimize preparation of activated carbon from Limonia acidissima shell with desirability approach. J Environ Eng 2017;5:588–600. https://doi.org/10.1016/j.jece.2016.12.034.Search in Google Scholar
16. Wang, ZM, Lee, JS, Park, J. Optimization of biodiesel production from trap grease via acid catalysis. Kor J Chem Eng 2008;25:670–4. https://doi.org/10.1007/s11814-008-0110-6.Search in Google Scholar
17. Bas, D, Boyaci, IH. Modeling and optimization I: usability of response surface methodology. J Food Eng 2007;78:836–45.10.1016/j.jfoodeng.2005.11.024Search in Google Scholar
18. Han, IS, Chung, CB. Dynamic modeling and simulation of a fluidized catalytic cracking process. Part II: property estimation and simulation. Chem Eng Sci 2001;56:1973–90. https://doi.org/10.1016/s0009-2509(00)00494-2.Search in Google Scholar
19. Khuri, AI. Response surface methodology and related topics. Toh Tuck Link: World Scientific; 2006.10.1142/5915Search in Google Scholar
20. Cavazzuti, M. Optimization methods: from theory to design. Springer-Verlag Berlin Heidelberg; 2013.10.1007/978-3-642-31187-1Search in Google Scholar
21. Souza, AS, dos Santos, WNL, Ferreira, SLC. Application of Box–Behnken design in the optimization of an on-line pre-concentration system using knotted reactor for cadmium determination by flame atomic absorption spectrometry. Spectrochim Acta B 2005;609:737–42. https://doi.org/10.1016/j.sab.2005.02.007.Search in Google Scholar
22. Massart, DL, Vandeginste, BGM, Buydens, LMC, Jong, SD, Lewi, PJ, Smeyers, JV. Handbook of chemometrics and qualimetrics part A. Amsterdam: Elsevier Science B.V.; 1997.Search in Google Scholar
23. Gilani, HG, Samper, KG, Haghi, RK. Advanced process control and simulation for chemical engineers. Oakville: Apple Academic Press; 2013.Search in Google Scholar
24. Myers, RH, Montgomery, DC. Response surface methodology: process and product optimization using designed experiments. Hoboken: John Wiley & Sons; 1995.Search in Google Scholar
25. Rakic, T, Kasagic-Vujanovic, I, Jovanovic, M, Jancic-Stojanovic, B, Ivanovic, D. Comparison of full factorial design, central composite design and box–behnken design in chromatographic method development for the determination of fluconazole and its impurities. Anal Lett 2014;47:1334–47.10.1080/00032719.2013.867503Search in Google Scholar
26. Biswas, J, Maxwell, IE. Octane enhancement in fluid catalytic cracking II. Operation in the overcracking regime. Appl Catal, A 1990;58:19–27. https://doi.org/10.1016/s0166-9834(00)82275-7.Search in Google Scholar
27. Thomas, A, Kumar, MVP. Comparison of the steady-state performances of 2x2 regulatory control structures for fluid catalytic cracking unit. Arabian J Sci Eng 2019;44:5475–87. https://doi.org/10.1007/s13369-019-03782-1.Search in Google Scholar
28. Occelli, ML. Advances in fluid catalytic cracking: testing, characterization, and environmental regulations. Boca Raton: CRC Press; 2010.10.1201/b10380Search in Google Scholar
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cppm-2022-0018).
© 2022 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Frontmatter
- Research Articles
- Two-stage adsorber optimization of NaOH-prewashed oil palm empty fruit bunch activated carbon for methylene blue removal
- Response surface methodology (RSM) and artificial neural network (ANN) approach to optimize the photocatalytic conversion of rice straw hydrolysis residue (RSHR) into vanillin and 4-hydroxybenzaldehyde
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- Optimal sequencing of conventional distillation column train for multicomponent separation system by evolutionary algorithm
- Enhanced design of PID controller and noise filter for second order stable and unstable processes with time delay
- Removal of glycerol from biodiesel using multi-stage microfiltration membrane system: industrial scale process simulation
- Multi-objective optimization of a fluid catalytic cracking unit using response surface methodology
- Effect of pipe rotation on heat transfer to laminar non-Newtonian nanofluid flowing through a pipe: a CFD analysis
- Statistical modeling and optimization of the bleachability of regenerated spent bleaching earth using response surface methodology and artificial neural networks with genetic algorithm
- Short Communication
- A comparative study: conventional and modified serpentine micromixers
