OPTIMIZATION OF DIFFERENT CHEMICAL PROCESSES USING RESPONSE SURFACE METHODOLOGY- A REVIEW

Response Surface Methodology

Authors

  • Hiba Zaid Chemical Engineering Department, College of Engineering, University of Al-Qadisiyah, Diwaniya, Iraq
  • Zainab Al-sharify Chemical Engineering Department, Birmingham University, Birmingham, UK https://orcid.org/0000-0002-3870-3815
  • Muhammad Hazwan Hamzah Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia. https://orcid.org/0000-0001-7684-0370
  • Salih Rushdi Chemical Engineering Department, College of Engineering, University of Al-Qadisiyah, Diwaniya, Iraq.

DOI:

https://doi.org/10.31272/jeasd.26.6.1

Keywords:

Response surface methodology, optimization, extraction, microwave, olive oil, palm oil

Abstract

Several chemical and biological processes have been investigated and predicted using Response Surface Methodology (RSM) models. Response Surfaces Methodology is a useful instrument for designing laboratory-scale experiments that optimize and support the research outcomes with statistical analysis. It is a powerful statistical technique for complex variable study systems. The standard optimization (one component at a time) strategy is well-studied. However, it has significant drawbacks, such as requiring more experimental runs and time and failing to reveal the synergistic impact of processing parameters. It is a valuable instrument for process improvement. Recent research has shown, for instance, that RSM successfully optimizes biodiesel in fats and oils generated from diverse feedstocks. According to this study, Response Surface Methodology is the best cost-effective technique for maximizing environmentally friendly and sustainable methods applied to different experimental procedures. The current review reported RSM's application, theory, methodology, advantages, and limitations for different processes using different oil sources.

Author Biographies

Hiba Zaid, Chemical Engineering Department, College of Engineering, University of Al-Qadisiyah, Diwaniya, Iraq

Master student, Chemical Engineering Department, College of Engineering, University of Al-Qadisiyah, Diwaniya, Iraq

Muhammad Hazwan Hamzah, Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.

Associated Professor, Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.

Smart Farming Technology Research Centre, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.

Salih Rushdi, Chemical Engineering Department, College of Engineering, University of Al-Qadisiyah, Diwaniya, Iraq.

Professor, Chemical Engineering Department, College of Engineering, University of Al-Qadisiyah, Diwaniya, Iraq.

References

Zhang, D., et al., (2022). Chapter 6 - Analysis of universality and diversity of biological surface/interface energy field effect, in Micro- and Nano-Bionic Surfaces, D. Zhang, et al., Editors, Elsevier. p. 127-150. https://doi.org/10.1016/B978-0-12-824502-6.00010-7.

Manzella, G.M.R., et al., (2022). Chapter One - A narrative of historical, methodological, and technological observations in marine science, in Ocean Science Data, G. Manzella and A. Novellino, Editors, Elsevier. p. 3-64. https://doi.org/10.1016/B978-0-12-823427-3.00004-9.

García-López, E.I. and Marcì, G., (2021). Chapter 3 - Preparation of photocatalysts by physical methodologies, in Materials Science in Photocatalysis, E.I. García-López and L. Palmisano, Editors, Elsevier. p. 37-62. https://doi.org/10.1016/B978-0-12-821859-4.00007-6.

Eren Şenaras, A., (2019). Chapter 8 - Parameter optimization using the surface response technique in automated guided vehicles, in Sustainable Engineering Products and Manufacturing Technologies, K. Kumar, D. Zindani, and P. Davim, Editors, Academic Press. p. 187-197. https://doi.org/10.1016/B978-0-12-816564-5.00008-6.

Myers, R.H., Montgomery, D.C., and Anderson-Cook, C.M., (1995). Response surface methodology: process and product optimization using designed experiments. 4th ed. 1995, New York: John Wiley & Sons. ISBN: 1118916034.

Zhang, L.Z., et al., (2022). Optimization of a variable-temperature heat pump drying process of shiitake mushrooms using response surface methodology. Renewable Energy. Vol. 1981267-1278. https://doi.org/10.1016/j.renene.2022.08.094.

Elkelawy, M., et al., (2022). A comprehensive review on the effects of diesel/biofuel blends with nanofluid additives on compression ignition engine by response surface methodology. Energy Conversion and Management: X. Vol. 14100177. https://doi.org/10.1016/j.ecmx.2021.100177.

Bhavani, Y., Chitti Babu, N., and Uday Kumar, K., (2022). Decolorisation of Congo red synthetic solution using Fe doped ZnO nano particles and optimization using response surface methodology. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2022.07.049.

Wu, J., He, J., and Christakos, G., (2022). Chapter 3 - CTDA methodology, in Quantitative Analysis and Modeling of Earth and Environmental Data, J. Wu, J. He, and G. Christakos, Editors, Elsevier. p. 57-100. https://doi.org/10.1016/B978-0-12-816341-2.00010-1.

Baş, D. and Boyacı, İ.H., (2007). Modeling and optimization I: Usability of response surface methodology. Journal of Food Engineering. Vol. 78, Issue 3, pp. 836-845. https://doi.org/10.1016/j.jfoodeng.2005.11.024.

Farooq Anjum, M., Tasadduq, I., and Al-Sultan, K., (1997). Response surface methodology: A neural network approach. European Journal of Operational Research. Vol. 101, Issue 1, pp. 65-73. https://doi.org/10.1016/S0377-2217(96)00232-9.

Ong, T.H., Hamzah, M.H., and Che Man, H., (2021). Optimization of palm oil extraction from decanter cake using soxhlet extraction and effects of microwaves pre-treatment on extraction yield and physicochemical properties of palm oil. Food Research. Vol. 525-32. https://doi.org/10.26656/fr.2017.5(S1).008.

Myers, R.H., et al., (2004). Response Surface Methodology: A Retrospective and Literature Survey. Journal of Quality Technology. Vol. 36, Issue 1, pp. 53-77. https://doi.org/10.1080/00224065.2004.11980252.

Box, G.E.P. and Wilson, K.B., (1992). On the Experimental Attainment of Optimum Conditions, in Breakthroughs in Statistics: Methodology and Distribution, S. Kotz and N.L. Johnson, Editors, Springer New York: New York, NY. p. 270-310. https://doi.org/10.1007/978-1-4612-4380-9_23.

Myers, R.H. and Montgomery, D.C., (2002). Response surface methodology: Process and product optimization using designed experiments. 2nd ed. 2002, New York: John Wiley & Sons Inc.

Cacace, J.E. and Mazza, G., (2003). Mass transfer process during extraction of phenolic compounds from milled berries. Journal of Food Engineering. Vol. 59, Issue 4, pp. 379-389. https://doi.org/10.1016/S0260-8774(02)00497-1.

Wettasinghe, M. and Shahidi, F., (1999). Evening Primrose Meal: A Source of Natural Antioxidants and Scavenger of Hydrogen Peroxide and Oxygen-Derived Free Radicals. Journal of Agricultural and Food Chemistry. Vol. 47, Issue 5, pp. 1801-1812. https://doi.org/10.1021/jf9810416.

Cacace, J.E. and Mazza, G., (2003). Optimization of Extraction of Anthocyanins from Black Currants with Aqueous Ethanol. Journal of Food Science. Vol. 68, Issue 1, pp. 240-248. https://doi.org/10.1111/j.1365-2621.2003.tb14146.x.

GAO, L. and MAZZA, G., (1996). Extraction of Anthocyanin Pigments from Purple Sunflower Hulls. Journal of Food Science. Vol. 61, Issue 3, pp. 600-603. https://doi.org/10.1111/j.1365-2621.1996.tb13167.x.

Ge, Y., et al., (2002). Optimization of the Supercritical Fluid Extraction of Natural Vitamin E from Wheat Germ Using Response Surface Methodology. Journal of Food Science. Vol. 67, Issue 1, pp. 239-243. https://doi.org/10.1111/j.1365-2621.2002.tb11391.x.

Anupam, K., Yadav, V., and Karri, R.R., (2021). Chapter5 - Entropy and MTOPSIS assisted central composite design for preparing activated carbon toward adsorptive defluoridation of wastewater, in Green Technologies for the Defluoridation of Water, M. Hadi Dehghani, R. Karri, and E. Lima, Editors, Elsevier. p. 119-140. https://doi.org/10.1016/B978-0-323-85768-0.00020-8.

Rana, D.S., et al., (2003). Stability and kinetics of β-1,3-glucanse from Trichoderma harzianum. Process Biochemistry. Vol. 39, Issue 2, pp. 149-155. https://doi.org/10.1016/S0032-9592(02)00323-0.

Jones, M.D., Khalid, G.A., and Prabhu, R.K., (2022). Chapter 11 - Development of a coupled physical–computational methodology for the investigation of infant head injury, in Multiscale Biomechanical Modeling of the Brain, R. Prabhu, and M. Horstemeyer, Editors, Academic Press. p. 177-192. DOI: 10.1016/B978-0-12-818144-7.00011-6.

Wang, Z., et al., (2022). Optimization and mechanism of Tetrabromobisphenol A removal by dithionite under anaerobic conditions: Response surface methodology and degradation pathway. Journal of Environmental Management. Vol. 321116034. https://doi.org/10.1016/j.jenvman.2022.116034.

Chen, J., et al., (2022). Optimized luminescent intensity of Ca2MgWO6:Er3+,Yb3+ up-conversion phosphors by uniform design and response surface methodology. Journal of Luminescence. Vol. 248118958. https://doi.org/10.1016/j.jlumin.2022.118958.

Sinha, A.S.K., Jazie, A.A., and Pramanik, H., (2012). Optimization of biodiesel production from peanut and rapeseed oils using response surface methodology. International Journal of Biomass and Renewables. Vol. 1, Issue 2, pp. 9-18V 1.

Chalermsinsuwan, B., Li, Y.-H., and Manatura, K., (2023). Optimization of gasification process parameters for COVID-19 medical masks using response surface methodology. Alexandria Engineering Journal. Vol. 62335-347. https://doi.org/10.1016/j.jobe.2022.104827.

Sasidharan, R. and Kumar, A., (2022). Response surface methodology for optimization of heavy metal removal by magnetic biosorbent made from anaerobic sludge. Journal of the Indian Chemical Society. Vol. 99, Issue 9, pp. 100638. https://doi.org/10.1016/j.jics.2022.100638.

Iliyasu, I., et al., (2022). Response surface methodology for the optimization of the effect of fibre parameters on the physical and mechanical properties of deleb palm fibre reinforced epoxy composites. Scientific African. Vol. 16e01269. https://doi.org/10.1016/j.sciaf.2022.e01269.

Dutta, P., et al., (2022). Chapter 13 - Response surface methodology-based optimization of parameters for biodiesel production, in Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies, K. Kumar, et al., Editors, Elsevier. p. 321-339. https://doi.org/10.1016/j.sciaf.2022.e01269.

Singhal, A., et al., (2022). Optimizing cellulase production from Aspergillus flavus using response surface methodology and machine learning models. Environmental Technology & Innovation. Vol. 27102805. https://doi.org/10.1016/j.sciaf.2022.e01269.

Kaliyavaradhan, S.K., Li, L., and Ling, T.-C., (2022). Response surface methodology for the optimization of CO2 uptake using waste concrete powder. Construction and Building Materials. Vol. 340127758. https://doi.org/10.1016/j.conbuildmat.2022.127758.

Milchert, E., Smagowicz, A., and Lewandowski, G., (2010). Optimization of the reaction parameters of epoxidation of rapeseed oil with peracetic acid. Journal of Chemical Technology & Biotechnology. Vol. 85, Issue 8, pp. 1099-1107. https://doi.org/10.1002/jctb.2405.

Olga, G., et al., (2018). Optimization of the epoxidation of linseed oil using response surface methodology. Chemical Industry and Chemical Engineering Quarterly. Vol. 24, Issue 4, pp. 357-368. https://doi.org/10.2298/CICEQ171012008G.

Kazemian, M.E., Gandjalikhan Nassab, S.A., and Jahanshahi Javaran, E., (2022). Comparative techno-economic investigation of CCHP combined by GSHP based on response surface methodology. Thermal Science and Engineering Progress. Vol. 34101386. https://doi.org/10.1016/j.tsep.2022.101386.

Díaz, L., et al., (2022). Response surface methodology for continuous biodiesel production from Jatropha curcas oil using Li/pumice as catalyst in a packed-bed reactor assisted with diethyl ether as cosolvent. Chemical Engineering and Processing - Process Intensification. Vol. 179109065. https://doi.org/10.1016/j.tsep.2022.101386.

Song, Q., et al., (2022). Study on the recycling of ceramic polishing slag in autoclaved aerated foam concrete by response surface methodology. Journal of Building Engineering. Vol. 56104827. https://doi.org/10.1016/j.jobe.2022.104827.

Fernández Valdivia, D.G., Espínola Lozano, F., and Moya Vilar, M., (2008). The influence of different technological co-adjuvants on the quality and yield of virgin olive oil using response surfaces methodology. Grasas y Aceites. Vol. 59, Issue 1, pp. 39-44. https://doi.org/10.3989/gya.2008.v59.i1.488.

Delil, S.O.S., ÖZKAN, G., and KARACABEY, E., (2022). A Comprehensive Study on Phenolic Transition to Olive Oil from Fruits Depending on Malaxation Conditions and Ripening Degree. Food Analytical Methods. Vol. X, Issue X, pp. XX. https://doi.org/10.21203/rs.3.rs-1485913/v1.

Naveenkumar, R. and Baskar, G., (2022). Ultrasonic assisted extraction of oil from castor seeds: optimization using response surface methodology, extraction kinetics and characterization. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. Vol. 44, Issue 1, pp. 2497-2508. https://doi.org/10.1080/15567036.2019.1650136.

Lo, C.-F., et al., (2012). Optimization of Lipase Production by Burkholderia sp. Using Response Surface Methodology. International Journal of Molecular Sciences. Vol. 13, Issue 11, pp. 14889-14897. https://doi.org/10.3390/ijms131114889.

Ghadge, S.V. and Raheman, H., (2006). Process optimization for biodiesel production from mahua (Madhuca indica) oil using response surface methodology. Bioresource Technology. Vol. 97, Issue 3, pp. 379-384. https://doi.org/10.1016/j.biortech.2005.03.014.

Miladi, M., et al., (2021). Optimization of Ultrasound-Assisted Extraction of Spent Coffee Grounds Oil Using Response Surface Methodology. Processes. Vol. 9, Issue 11, pp. 2085. https://doi.org/10.3390/pr9112085.

Mohammed, I.A., et al.(2014). Optimization of Transesterification of Nigerian Jatropha Curcas oil Using Response Surface Methodology. in 6th International Conference on Economics, Humanities, Bio-Technology and Environment Engineering (ICEHBEE 2014), Planetary Scientific Research Center,PSRC. Cape Town (SA)

Goren, A.Y., Recepoğlu, Y.K., and Khataee, A., (2022). Chapter 4 - Language of response surface methodology as an experimental strategy for electrochemical wastewater treatment process optimization, in Artificial Intelligence and Data Science in Environmental Sensing, M. Asadnia, A. Razmjou, and A. Beheshti, Editors, Academic Press. p. 57-92. https://doi.org/10.1016/B978-0-323-90508-4.00009-5.

Motta, I.L., et al., (2020). Optimization of Biomass Circulating Fluidized Bed Gasifier for Synthesis Applications using Simulation and Response Surface Methodology, in Computer Aided Chemical Engineering, S. Pierucci, et al., Editors, Elsevier. p. 1585-1590. https://doi.org/10.1016/B978-0-12-823377-1.50265-2.

Karchiyappan, T. and Karri, R.R., (2021). Chapter 21 - Process Optimization and Modeling of Hydraulic Fracturing Process Wastewater Treatment Using Aerobic Mixed Microbial Reactor via Response Surface Methodology, in Soft Computing Techniques in Solid Waste and Wastewater Management, R.R. Karri, G. Ravindran, and M.H. Dehghani, Editors, Elsevier. p. 351-363. https://doi.org/10.1016/B978-0-12-824463-0.00023-9.

Yim, S.C., et al., (2019). Chapter 15 - Supercritical Extraction of Value-Added Compounds From Empty Fruit Bunch: An Optimization Study by Response Surface Methodology, in Advances in Feedstock Conversion Technologies for Alternative Fuels and Bioproducts, M. Hosseini, Editor, Woodhead Publishing. p. 281-298. https://doi.org/10.1016/B978-0-12-824463-0.00023-9.

Rezaei, S., et al., (2022). Dimensional optimization of a two-body Wave energy converter using response surface methodology. Ocean Engineering. Vol. 261112186. https://doi.org/10.1016/j.oceaneng.2022.112186.

Perez, C., Lors, C., and Erable, B., (2022). Methodological approaches for the structural, chemical, and microbial analysis of microbial biofilms developed on the surface of cementitious materials: Overview and future prospects. International Biodeterioration & Biodegradation. Vol. 175105485. https://doi.org/10.1016/j.ibiod.2022.105485.

Belwal, T., et al., (2020). Chapter Ten - Optimization of extraction methodologies and purification technologies to recover phytonutrients from food, in Phytonutrients in Food, S.M. Nabavi, et al., Editors, Woodhead Publishing. p. 217-235. https://doi.org/10.1016/B978-0-12-815354-3.00007-1.

Chakraborty, D. and Mondal, N.K., (2022). Chapter 8 - Optimization of rural indoor kitchen structure and minimizing the pollution load: a sustainable environmental modeling approach, in Cognitive Data Models for Sustainable Environment, S. Bhattacharyya, et al., Editors, Academic Press. p. 181-202. https://doi.org/10.1016/B978-0-12-824038-0.00011-0.

Liu, G., et al., (2009). Supercritical CO2 extraction optimization of pomegranate (Punica granatum L.) seed oil using response surface methodology. LWT - Food Science and Technology. Vol. 42, Issue 9, pp. 1491-1495. https://doi.org/10.1016/j.lwt.2009.04.011.

Yu, M., et al., (2022). Design and multi-objective optimization of a new annular constructal bifurcation Stirling regenerator using response surface methodology. International Journal of Heat and Mass Transfer. Vol. 195123129. https://doi.org/10.1016/j.ijheatmasstransfer.2022.123129.

Dave, S., et al., (2021). 22 - Mathematical modeling and surface response curves for green synthesized nanomaterials and their application in dye degradation, in Photocatalytic Degradation of Dyes, M. Shah, S. Dave, and J. Das, Editors, Elsevier. p. 571-591. https://doi.org/10.1016/B978-0-12-823876-9.00027-5.

Alfarge, D., Wei, M., and Bai, B., (2020). Chapter 12 - Comparative and optimization of CO2 and natural gas EOR methods, in Developments in Petroleum Science, D. Alfarge, et al., Editors, Elsevier. p. 245-265. https://doi.org/10.1016/B978-0-12-818343-4.00012-7.

Beg, Q.K., Sahai, V., and Gupta, R., (2003). Statistical media optimization and alkaline protease production from Bacillus mojavensis in a bioreactor. Process Biochemistry. Vol. 39, Issue 2, pp. 203-209. https://doi.org/10.1016/S0032-9592(03)00064-5.

Taoufik, N., et al., (2021). Comparative analysis study by response surface methodology and artificial neural network on salicylic acid adsorption optimization using activated carbon. Environmental Nanotechnology, Monitoring & Management. Vol. 15100448. https://doi.org/10.1016/j.enmm.2021.100448.

Manojkumar, N., Muthukumaran, C., and Sharmila, G., (2022). A comprehensive review on the application of response surface methodology for optimization of biodiesel production using different oil sources. Journal of King Saud University - Engineering Sciences. Vol. 34, Issue 3, pp. 198-208. https://doi.org/10.1016/j.jksues.2020.09.012.

Namal Senanayake, S.P.J. and Shahidi, F., (2002). Lipase-catalyzed incorporation of docosahexaenoic acid (DHA) into borage oil: optimization using response surface methodology. Food Chemistry. Vol. 77, Issue 1, pp. 115-123. https://doi.org/10.1016/S0308-8146(01)00311-9.

Pereira, L.M.S., Milan, T.M., and Tapia-Blácido, D.R., (2021). Using Response Surface Methodology (RSM) to optimize 2G bioethanol production: A review. Biomass and Bioenergy. Vol. 151106166. https://doi.org/10.1016/j.biombioe.2021.106166.

Downloads

Published

2022-11-04

How to Cite

Zaid, H., Al-sharify, Z., Hamzah, M. H., & Rushdi, S. . (2022). OPTIMIZATION OF DIFFERENT CHEMICAL PROCESSES USING RESPONSE SURFACE METHODOLOGY- A REVIEW: Response Surface Methodology . Journal of Engineering and Sustainable Development, 26(6), 1–12. https://doi.org/10.31272/jeasd.26.6.1