Expert opinion-based multi objective optimization: an application in plasma coating technology

Keywords: multi objective optimization, weight method, FUCOM method, plasma coating process

Abstract

Multi-objective optimization is a very important activity which is applied in many different fields. When solving this problem, it is important to determine weights for criteria. If the weight of criteria is determined according to dry mathematical formulas, the opinion of researchers will be ruined. On the contrary, if the weight of criteria is determined according to the subjective opinion of researchers, it is also easy to make mistakes. This study applies a method of determining the weight of criteria based on experts' opinions and conditions must be also strictly satisfied, thereby both of the above limitations have been remedied. Such method is known as FUCOM (FUll COonsistency Method). An application example was carried out for multi-objective optimization in the plasma coating process. Plasma coating is a modern coating technology. This method is increasingly used in many different fields. However, determining the value of technological parameters to ensure the quality of high-quality products is a very complicated job. In order to ensure many requirements of the product, it is necessary to determine the optimal value of the technological parameters. Four criteria to evaluate a coating process include the adhesion strength of the coating, the shear strength of the coating, the tensile strength of the coating, and the porosity of the coating. The task of multi-objective optimization in this study is to determine the values of three input parameters (including: spray current intensity, powder feed flow, and spray distance) to ensure that the desired values of the four criteria are simultaneously achieved. After the weight of criteria is determined by the FUCOM method, the multi-objective optimization problem has been solved. Experiments to verify the optimal results were also conducted, thereby demonstrating the correctness of the methodology. The optimal values of the technology parameters (spray current intensity, powder feed flow, and spray distance) have been determined to be 568.69 A, 31.87 g/min, and 170.19 mm, respectively

Downloads

Download data is not yet available.

Author Biographies

Vu Duong, Duy Tan University

School of Engineering Technology

Nguyen Van Cuong, University of Transport and Communications

Faculty of Mechanical Engineering

References

Prabhakaran, V. V., Singh, A. (2019). Enhancing Power Quality in PV-SOFC Microgrids Using Improved Particle Swarm Optimization. Engineering, Technology & Applied Science Research, 9 (5), 4616–4622. doi: https://doi.org/10.48084/etasr.2963

Chang, K.-H. (2015). Multiobjective Optimization and Advanced Topics. Design Theory and Methods Using CAD/CAE, 325–406. doi: https://doi.org/10.1016/b978-0-12-398512-5.00005-0

Zopounidis, C., Doumpos, M. (Eds.) (2017). Multiple Criteria Decision Making. Applications in Management and Engineering. Springer, 211. doi: https://doi.org/10.1007/978-3-319-39292-9

Dawes, R. M., Corrigan, B. (1974). Linear models in decision making. Psychological Bulletin, 81 (2), 95–106. doi: https://doi.org/10.1037/h0037613

Do, T. (2021). Application of TOPSIS an PIV Methods for Multi - Criteria Decision Making in Hard Turning Process. Journal of Machine Engineering, 21 (4), 57–71. doi: https://doi.org/10.36897/jme/142599

Einhorn, H. J., McCoach, W. (1977). A simple multiattribute utility procedure for evaluation. Behavioral Science, 22 (4), 270–282. doi: https://doi.org/10.1002/bs.3830220405

Duc Trung, D. (2022). Multi-criteria decision making under the MARCOS method and the weighting methods: applied to milling, grinding and turning processes. Manufacturing Review, 9, 3. doi: https://doi.org/10.1051/mfreview/2022003

Zhu, Y., Tian, D., Yan, F. (2020). Effectiveness of Entropy Weight Method in Decision-Making. Mathematical Problems in Engineering, 2020, 1–5. doi: https://doi.org/10.1155/2020/3564835

Duc Trung, D. (2021). A combination method for multi-criteria decision making problem in turning process. Manufacturing Review, 8, 26. doi: https://doi.org/10.1051/mfreview/2021024

Saleh, E. S., Kimiagari, A. M. (2017). Ranking Tehran’s Stock Exchange Top Fifty Stocks Using Fundamental Indexes and Fuzzy TOPSIS. Engineering, Technology & Applied Science Research, 7 (4), 1863–1869. doi: https://doi.org/10.48084/etasr.1252

Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. (2021). Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC). Symmetry, 13 (4), 525. doi: https://doi.org/10.3390/sym13040525

Trung, D. D., Thinh, H. X. (2021). A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study. Advances in Production Engineering & Management, 16 (4), 443–456. doi: https://doi.org/10.14743/apem2021.4.412

Liu, S., Cai, H., Cao, Y., Yang, Y. (2011). Advance in grey incidence analysis modelling. 2011 IEEE International Conference on Systems, Man, and Cybernetics. doi: https://doi.org/10.1109/icsmc.2011.6083947

Benmoussa, N., Elyamami, A., Mansouri, K., Qbadou, M., Illoussamen, E. (2019). A Multi-Criteria Decision Making Approach for Enhancing University Accreditation Process. Engineering, Technology & Applied Science Research, 9 (1), 3726–3733. doi: https://doi.org/10.48084/etasr.2352

Pamučar, D., Stević, Ž., Sremac, S. (2018). A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM). Symmetry, 10 (9), 393. doi: https://doi.org/10.3390/sym10090393

Haqbin, A. (2022). Comparing best-worst method and full consistency method in a fuzzy environment. Decision Science Letters, 11 (2), 181–192. doi: https://doi.org/10.5267/j.dsl.2021.11.002

Durmić, E. (2019). The Evaluation of the Criteria for Sustainable Supplier Selection by Using the FUCOM Method. Operational Research in Engineering Sciences: Theory and Applications, 2 (1). doi: https://doi.org/10.31181/oresta1901085d

Ali, Y., Mehmood, B., Huzaifa, M., Yasir, U., Khan, A. U. (2020). Development of a new hybrid multi criteria decision-making method for a car selection scenario. Facta Universitatis, Series: Mechanical Engineering, 18 (3), 357. doi: https://doi.org/10.22190/fume200305031a

Kuma, B. S., Subbaiah, K. V. (2022). Application of the Fucom Method Accompained by SAW-WASPAS Method for the Selection for the Pump. International Journal of Engineering Research & Technology, 11 (3), 99–106. Available at: https://www.ijert.org/research/application-of-the-fucom-method-accompained-by-saw-waspas-method-for-the-selection-for-the-pump-IJERTV11IS030074.pdf

Stevic, Z. (2021). Decision-making in transport and logistics using integrated models. The Eighth International Conference Transport and Logistics, UNIVERSITY OF NIS FACULTY OF MECHANICAL ENGINEERING, 21–26. Available at: http://til.masfak.ni.ac.rs/images/til-pedja/til2021_Proceedings_3.pdf

Popović, V., Pamučar, D., Stević, Ž., Lukovac, V., Jovković, S. (2022). Multicriteria Optimization of Logistics Processes Using a Grey FUCOM-SWOT Model. Symmetry, 14 (4), 794. doi: https://doi.org/10.3390/sym14040794

Demir, G., Damjanović, M., Matović, B., Vujadinović, R. (2022). Toward Sustainable Urban Mobility by Using Fuzzy-FUCOM and Fuzzy-CoCoSo Methods: The Case of the SUMP Podgorica. Sustainability, 14 (9), 4972. doi: https://doi.org/10.3390/su14094972

Got, H. V., Trung, D. D. (2012). Research on the application of spray coating technology by experimental methods. Ha Noi: Science and technics publishing House.

Tung, H. (2006). Spray coating technology and application. Ha Noi: Science and technics publishing House.

Electric Arc Spray. Available at: https://www.asbindustries.com/electric-arc-spray

Fauchais, P. L., Heberlein, J. V. R., Boulos, M. I. (2014). Thermal Spray Fundamentals. Springer, 1566. doi: https://doi.org/10.1007/978-0-387-68991-3

Bauer, J. T., Montero, X., Galetz, M. C. (2020). Fast heat treatment methods for al slurry diffusion coatings on alloy 800 prepared in air. Surface and Coatings Technology, 381, 125140. doi: https://doi.org/10.1016/j.surfcoat.2019.125140

Tapphorn, R. M., Gabel, H. (1998). The solid-state spray forming of low-oxide titanium components. JOM, 50 (9), 45–47. doi: https://doi.org/10.1007/s11837-998-0414-3

Stokes, J. (2008). The Theory and Application of the HVOF Thermal Spray Process. Dublin City University.

Drexler, J. M., Gledhill, A. D., Shinoda, K., Vasiliev, A. L., Reddy, K. M., Sampath, S., Padture, N. P. (2011). Jet Engine Coatings for Resisting Volcanic Ash Damage. Advanced Materials, 23 (21), 2419–2424. doi: https://doi.org/10.1002/adma.201004783

Kim, K., Li, W., Guo, X. (2015). Detection of oxygen at the interface and its effect on strain, stress, and temperature at the interface between cold sprayed aluminum and steel substrate. Applied Surface Science, 357, 1720–1726. doi: https://doi.org/10.1016/j.apsusc.2015.10.022

Thao, D. X. (2021). Research on chromium-based alloy plasma spray technology, applied in flue propeller recovery in thermal power plants. Hanoi University of Industry.

Mariaux, G., Vardelle, A. (2005). 3-D time-dependent modelling of the plasma spray process. Part 1: flow modelling. International Journal of Thermal Sciences, 44 (4), 357–366. doi: https://doi.org/10.1016/j.ijthermalsci.2004.07.006

Nogues, E., Vardelle, M., Fauchais, P., Granger, P. (2008). Arc voltage fluctuations: Comparison between two plasma torch types. Surface and Coatings Technology, 202 (18), 4387–4393. doi: https://doi.org/10.1016/j.surfcoat.2008.04.014

Alaya, M., Chazelas, C., Vardelle, A. (2015). Parametric Study of Plasma Torch Operation Using a MHD Model Coupling the Arc and Electrodes. Journal of Thermal Spray Technology, 25 (1-2), 36–43. doi: https://doi.org/10.1007/s11666-015-0330-3

Thao, D. X., Got, H. V., Cuong, P. D. (2022). Optimization of Plasma Spraying Parameters with Respect to Shear Adhesion Strength of Cr3C2-NiCr Coating on 16Mn Steel. Tribology in Industry, 44 (1), 221–229. doi: https://doi.org/10.24874/ti.1101.04.21.09

Thao, D. X., Duc, C. P. (2022). A study on the effects of plasma spraying parameters on the adhesion strength of Cr3C2-NiCr coating on 16Mn steel. EUREKA: Physics and Engineering, 2, 91–100. doi: https://doi.org/10.21303/2461-4262.2022.001827

Yusoff, N. H. N., Ghazali, M. J., Isa, M. C., Daud, A. R., Muchtar, A., Forghani, S. M. (2012). Optimization of plasma spray parameters on the mechanical properties of agglomerated Al2O3–13%TiO2 coated mild steel. Materials & Design, 39, 504–508. doi: https://doi.org/10.1016/j.matdes.2012.03.019

Ramachandran, C. S., Balasubramanian, V., Ananthapadmanabhan, P. V. (2010). Multiobjective Optimization of Atmospheric Plasma Spray Process Parameters to Deposit Yttria-Stabilized Zirconia Coatings Using Response Surface Methodology. Journal of Thermal Spray Technology, 20 (3), 590–607. doi: https://doi.org/10.1007/s11666-010-9604-y

Manjunath Patel, G. C., Pradeep, N. B., Girisha, L., Harsha, H. M., Shettigar, A. K. (2020). Experimental analysis and optimization of plasma spray parameters on microhardness and wear loss of Mo-Ni-Cr coated super duplex stainless steel. Australian Journal of Mechanical Engineering, 20 (5), 1426–1438. doi: https://doi.org/10.1080/14484846.2020.1808760

Du, N. V., Binh, N. D. (2011). Design of experiment techniques. Ha Noi: Science and technics publishing House.

Dean, A., Voss, D., Draguljić, D. (2017). Design and Analysis of Experiments. Springer, 840. doi: https://doi.org/10.1007/978-3-319-52250-0

Expert opinion-based multi objective optimization: an application in plasma coating technology

👁 223
⬇ 207
Published
2022-11-29
How to Cite
Duong, V., & Van Cuong, N. (2022). Expert opinion-based multi objective optimization: an application in plasma coating technology. EUREKA: Physics and Engineering, (6), 175-184. https://doi.org/10.21303/2461-4262.2022.002535
Section
Mathematics