Machine Learning-assisted Prediction and Optimization of Exergy Efficiency and Destruction of Cumene Plant under Uncertainty
Received: 21 November 2023 | Revised: 17 December 2023 | Accepted: 19 December2023 | Online: 3 January 2024
Corresponding author: Farooq Ahmad
Abstract
Machine Learning (ML)'s growing role in process industries during the digitalization era is notable. This study combines Artificial Neural Networks (ANNs) and Aspen Plus to predict exergy efficiency, exergy destruction, and potential improvements in a cumene plant under uncertain process conditions. An optimization framework, using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), was developed to enhance exergy efficiency amid uncertainty. Initially, a steady-state Aspen model evaluates exergy efficiency, irreversibility, and potential improvements. The proposed model is transitioned to a dynamic mode, introducing artificial uncertainties into key variables. An ANN model predicts exergy efficiency and exergy destruction under uncertainty. The PSO and GA-based optimization methods improve exergy efficiency and reduce exergy destruction. This work demonstrates the potential real-time application of intelligent methods in plant analysis.
Keywords:
exergy analysis, digitalization, industry 4.0, machine learning, process uncertaintiesDownloads
References
K. R. Ramazanov, "Increase of efficiency of cumene process of receiving phenol and acetone," in European Science and Technology, 2013, pp. 775–786.
N. Ahmad, E. Fouad, and F. Ahmad, "Effect of Shear Flow on Crystallization of Sydiotactic Polypropylene/Clay Composites," Engineering, Technology & Applied Science Research, vol. 8, no. 4, pp. 3108–3112, Aug. 2018.
N. Ahmad, F. Ahmad, and I. Alenezi, "Influence of Starch Content on the Thermal and Viscoelastic Properties of Syndiotactic Polypropylene/Starch Composites," Engineering, Technology & Applied Science Research, vol. 11, no. 3, pp. 7228–7232, Jun. 2021.
A. Z. Al-Khazaal and N. Ahmad, "A Study of the Impact of Iron Content on the Thermal Response of the sPP/Fe Composites," Engineering, Technology & Applied Science Research, vol. 12, no. 3, pp. 8555–8558, Jun. 2022.
A. S. Pathak, S. Agarwal, V. Gera, and N. Kaistha, "Design and Control of a Vapor-Phase Conventional Process and Reactive Distillation Process for Cumene Production," Industrial & Engineering Chemistry Research, vol. 50, no. 6, pp. 3312–3326, Mar. 2011.
H. R. Norouzi, M. A. Hasani, B. Haddadi-Sisakht, and N. Mostoufi, "Economic Design and Optimization of Zeolite-Based Cumene Production Plant," Chemical Engineering Communications, vol. 201, no. 10, pp. 1270–1293, Oct. 2014.
J. Zhai, Y. Liu, L. Li, Y. Zhu, W. Zhong, and L. Sun, "Applications of dividing wall column technology to industrial-scale cumene production," Chemical Engineering Research and Design, vol. 102, pp. 138–149, Oct. 2015.
H. R. Norouzi and S. Fatemi, "Economic Optimization of the Cumene Production Process Using Response Surface Methodology," Chemical Engineering Communications, vol. 199, no. 11, pp. 1375–1393, Nov. 2012.
A. Chudinova, A. Salischeva, E. Ivashkina, O. Moizes, and A. Gavrikov, "Application of Cumene Technology Mathematical Model," Procedia Chemistry, vol. 15, pp. 326–334, Jan. 2015.
F. Mahmoudian, A. H. Moghaddam, and S. M. Davachi, "Genetic-based multi-objective optimization of alkylation process by a hybrid model of statistical and artificial intelligence approaches," The Canadian Journal of Chemical Engineering, vol. 100, no. 1, pp. 90–102, 2022.
W. L. Luyben, "Design and Control of the Cumene Process," Industrial & Engineering Chemistry Research, vol. 49, no. 2, pp. 719–734, Jan. 2010.
D. Maity, R. Jagtap, and N. Kaistha, "Systematic top-down economic plantwide control of the cumene process," Journal of Process Control, vol. 23, no. 10, pp. 1426–1440, Nov. 2013.
V. Gera, M. Panahi, S. Skogestad, and N. Kaistha, "Economic Plantwide Control of the Cumene Process," Industrial & Engineering Chemistry Research, vol. 52, no. 2, pp. 830–846, Jan. 2013.
S. Sharma, Z. Chao Lim, and G. P. Rangaiah, "Process Design for Economic, Environmental and Safety Objectives with an Application to the Cumene Process," in Multi-Objective Optimization in Chemical Engineering, John Wiley & Sons, Ltd, 2013, pp. 449–477.
F. Flegiel, S. Sharma, and G. P. Rangaiah, "Development and Multiobjective Optimization of Improved Cumene Production Processes," Materials and Manufacturing Processes, vol. 30, no. 4, pp. 444–457, Apr. 2015.
M. Carlos, B. Fatine, O.-M. Nelly, and G. Nadine, "Deviation propagation analysis along a cumene process by using dynamic simulations," Computers & Chemical Engineering, vol. 117, pp. 331–350, Sep. 2018.
P. G. Junqueira, P. V. Mangili, R. O. Santos, L. S. Santos, and D. M. Prata, "Economic and environmental analysis of the cumene production process using computational simulation," Chemical Engineering and Processing - Process Intensification, vol. 130, pp. 309–325, Aug. 2018.
J. Mustafa, I. Ahmad, M. Ahsan, and M. Kano, "Computational fluid dynamics based model development and exergy analysis of naphtha reforming reactors," International Journal of Exergy, vol. 24, no. 2–4, pp. 344–363, Jan. 2017.
P. Luis and B. Van der Bruggen, "Exergy analysis of energy-intensive production processes: advancing towards a sustainable chemical industry," Journal of Chemical Technology & Biotechnology, vol. 89, no. 9, pp. 1288–1303, 2014.
E. S. Dogbe, M. A. Mandegari, and J. F. Görgens, "Exergetic diagnosis and performance analysis of a typical sugar mill based on Aspen Plus® simulation of the process," Energy, vol. 145, pp. 614–625, Feb. 2018.
N. A. Madlool, R. Saidur, N. A. Rahim, and M. Kamalisarvestani, "An overview of energy savings measures for cement industries," Renewable and Sustainable Energy Reviews, vol. 19, pp. 18–29, Mar. 2013.
M. S. Arif and I. Ahmad, "Artificial Intelligence Based Prediction of Exergetic Efficiency of a Blast Furnace," in 31st European Symposium on Computer Aided Process Engineering, Jan. 2021, vol. 50, pp. 1047–1052.
Z. ur Rahman, I. Ahmad, M. Kano, and J. Mustafa, "Model Development and Exergy Analysis of a Microreactor for the Steam Methane Reforming Process in a CFD Environment," Entropy, vol. 21, no. 4, Apr. 2019, Art. no. 399.
A. Samad, I. Ahmad, M. Kano, and H. Caliskan, "Prediction and optimization of exergetic efficiency of reactive units of a petroleum refinery under uncertainty through artificial neural network-based surrogate modeling," Process Safety and Environmental Protection, vol. 177, pp. 1403–1414, Sep. 2023.
M. Khan, I. Ahmad, M. Ahsan, M. Kano, and H. Caliskan, "Prediction of optimum operating conditions of a furnace under uncertainty: An integrated framework of artificial neural network and genetic algorithm," Fuel, vol. 330, Dec. 2022, Art. no. 125563.
S. Kurban, G. K. Kaya, and S. Yaman, "Exergy Analysis of Vacuum Distillation Unit," in 31st European Symposium on Computer Aided Process Engineering, Jan. 2021, vol. 50, pp. 63–68.
A. Ullah, I. Ahmad, A. Chughtai, and M. Kano, "Exergy Analysis and Optimization of Naphtha Reforming Process with Uncertainty," International Journal of Exergy, vol. 26, no. 3, Mar. 2018, Art. no. 247.
Downloads
How to Cite
License
Copyright (c) 2024 Farooq Ahmad, Naveed Ahmad, Abdul Aal Zuhayr Al-Khazaal
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
