APPLICATION OF FUZZY MCDM IN SELECTING ECO-FRIENDLY MATERIALS FOR ELECTRIC VEHICLE INTERIORS
Abstract
The growing demand for sustainable solutions in the automotive industry has led to a significant focus on eco-friendly materials for electric vehicle (EV) interiors. This research paper explores the application of Fuzzy Multi-Criteria Decision-Making (MCDM) in selecting optimal eco-friendly materials for EV interiors. Fuzzy MCDM provides a robust framework to handle the inherent uncertainty and subjectivity in evaluating multiple criteria such as recyclability, durability, strength, comfort, aesthetic appeal, carbon footprint, price, energy requirements, and complexity in manufacturing. By employing a combination of Fuzzy-Entropy and Fuzzy-TOPSIS, this study aims to prioritize materials that offer the best balance of environmental sustainability and performance. Entropy is employed to evaluate the criteria weights, whereas TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is applied to select the ideal sustainable materials for EV interiors and to rate the alternatives. The final result reveals that Polyethylene Terephthalate is the most suitable material alternative for EV interiors, significantly enhancing the sustainability of the automotive industry. In contrast, Bamboo Fiber Composite ranks the lowest among the alternatives, indicating it is the least favorable option in the group. The final outcomes from the fuzzy-entropy-TOPSIS model are also compared to six others solo MCDM models and the ranking stability is also verified through sensitivity analysis.
References
Eti, S., Dinçer, H., Yüksel, S., & Gökalp, Y. (2025). A New Fuzzy Decision-Making Model for Enhancing Electric Vehicle Charging Infrastructure. Spectrum of Decision Making and Applications, 2(1), 94-99. https://doi.org/10.31181/sdmap21202513
Yardım, M. F., Yüksel, S., & Dinçer, H. (2025). Development of Optimal Investment Strategies for Electric Vehicle Charging Stations with a Novel Decision-Making Technique. Journal of Operations Intelligence, 3(1), 67-73. https://doi.org/10.31181/jopi31202534
Sarfraz, M., & Gul, R. (2025). An Aczel-Alsina T-Spherical Fuzzy Framework for the Electric Vehicle Selection. Spectrum of Engineering and Management Sciences, 3(1), 158-174. https://doi.org/10.31181/sems31202543s
Jameel, T., Yasin, Y., & Riaz, M. (2025). An Integrated Hybrid MCDM Framework for Renewable Energy Prioritization in Sustainable Development. Spectrum of Decision Making and Applications, 3(1), 124-150. https://doi.org/10.31181/sdmap31202640
Guliyev, J., Güneri, B., Konur, M., Duymaz, Şeyma, & Türk, A. (2025). Offshore Wind Power Site Selection in Türkiye Using q-Rung Orthopair Fuzzy Sets and the COPRAS Method. Journal of Operations Intelligence, 3(1), 278-302. https://doi.org/10.31181/jopi31202551
Zahoor, A., Zhang, J., Wu, D., Chen, J. L., Nihed, B., Sen, T., Yu, Y., Mao, G., Yang, P. (2024). A systematic study involving patent analysis and theoretical modeling of eco-friendly technologies for electric vehicles and power batteries to ease carbon emission from the transportation industry. Energy Conversion and Management, 321, 118996. https://doi.org/10.1016/j.enconman.2024.118996
Mumani, A., Maghableh, G. (2022). An integrated ANP-ELECTRE III decision model applied to eco-friendly car selection. Journal of Engineering Research, 10(3A). https://doi.org/10.36909/jer.11207
Ghosh, A., Dey, M., Mondal, S. P., Shaikh, A., Sarkar, A., Chatterjee, B. (2021). Selection of best E-Rickshaw-A green energy game changer: an application of AHP and TOPSIS method. Journal of Intelligent & Fuzzy Systems, 40(6), 11217-11230. https://doi.org/10.3233/JIFS-202406
Kapilan, N. (2021). Impact of Carbon Nano Tubes on the Performance and Emissions of a Diesel Engine Fuelled with Pongamia Oil Biodiesel. Jordan Journal of Mechanical & Industrial Engineering, 15(3). https://jjmie.hu.edu.jo/V15-3/05-jjmie_108_20.pdf
Mhana, K. H., Awad, H. A. (2024). An ideal location selection of electric vehicle charging stations: Employment of integrated analytical hierarchy process with geographical information system. Sustainable Cities and Society, 107, 105456. https://doi.org/10.1016/j.scs.2024.105456
Petchimuthu, S., Banu M, F., Mahendiran, C., & Premala, T. (2025). Power and Energy Transformation: Multi-Criteria Decision-Making Utilizing Complex q-Rung Picture Fuzzy Generalized Power Prioritized Yager Operators. Spectrum of Operational Research, 2(1), 219-258. https://doi.org/10.31181/sor21202525
Yu, Z., Jia, H., Huang, X. (2021). Design of the Lower Control Arm of an Electric SUV Front Suspension Based on Multi-Disciplinary Optimization Technology. Jordan Journal of Mechanical & Industrial Engineering, 15(1). https://jjmie.hu.edu.jo/v15-1/02-ET574.pdf
Kurniadi, K. A., Ryu, K. (2021). Development of multi-disciplinary green-BOM to maintain sustainability in reconfigurable manufacturing systems. Sustainability, 13(17), 9533. https://doi.org/10.3390/su13179533
Jeyanthi, S., Nivedhitha, D. M., Thiagamani, S. M. K., Ansari, M., Nainar, M., Viswapriyan, A. S., Nishaanth, S. G., Manoranjith, S. (2023). A comparative analysis of flexible polymer-based poly (vinylidene) fluoride (PVDF) films for pressure sensing applications. Jordan Journal of Mechanical & Industrial Engineering, 17(3). https://jjmie.hu.edu.jo/vol17/vol17-3/06-JJMIE-154-23.pdf
Mishra, A. R., & Rani, P. (2025). Evaluating and Prioritizing Blockchain Networks using Intuitionistic Fuzzy Multi-Criteria Decision-Making Method. Spectrum of Mechanical Engineering and Operational Research, 2(1), 78-92. https://doi.org/10.31181/smeor21202527
Soni, A., Das, P. K., Gupta, S. K., Saha, A., Rajendran, S., Kamyab, H., Yusuf, M. (2024). An overview of recent trends and future prospects of sustainable natural fiber-reinforced polymeric composites for tribological applications. Industrial Crops and Products, 222, 119501. https://doi.org/10.1016/j.indcrop.2024.119501
Hussain, A., & Ullah, K. (2024). An Intelligent Decision Support System for Spherical Fuzzy Sugeno-Weber Aggregation Operators and Real-Life Applications. Spectrum of Mechanical Engineering and Operational Research, 1(1), 177-188. https://doi.org/10.31181/smeor11202415
Ikram, M., Ferasso, M., Sroufe, R., Zhang, Q. (2021). Assessing green technology indicators for cleaner production and sustainable investments in a developing country context. Journal of Cleaner Production, 322, 129090. https://doi.org/10.1016/j.jclepro.2021.129090
Kenger, Z. D., Kenger, Ö. N., Özceylan, E. (2023). Analytic hierarchy process for urban transportation: a bibliometric and social network analysis. Central European Journal of Operations Research, 1-20. https://doi.org/10.1007/s10100-023-00869-x
Ullah, I., Ali, F., Khan, H., Khan, F., Bai, X. (2024). Ubiquitous computation in internet of vehicles for human-centric transport systems. Computers in Human Behavior, 161, 108394. https://doi.org/10.1016/j.chb.2024.108394
Skosana, S. J., Khoathane, C., Malwela, T. (2025). Driving towards sustainability: A review of natural fiber reinforced polymer composites for eco-friendly automotive light-weighting. Journal of Thermoplastic Composite Materials, 38(2), 754-780. https://doi.org/10.1177/08927057241254324
Biswas, A., Gazi, K. H., Sankar, P. M., & Ghosh, A. (2025). A Decision-Making Framework for Sustainable Highway Restaurant Site Selection: AHP-TOPSIS Approach based on the Fuzzy Numbers. Spectrum of Operational Research, 2(1), 1-26. https://doi.org/10.31181/sor2120256
Narang, M., Kumar, A., & Dhawan, R. (2023). A fuzzy extension of MEREC method using parabolic measure and its applications. Journal of Decision Analytics and Intelligent Computing, 3(1), 33–46. https://doi.org/10.31181/jdaic10020042023n
Qian, S., Qiu, Y., Bouraima, M. B., Badi, I., & Chusi, T. N. (2024). Assessing the Challenges to Leverage Carbon Markets for Renewable Energy in Developing Countries: A Multi-Criteria Decision-Making Approach. Spectrum of Engineering and Management Sciences, 2(1), 151-160. https://doi.org/10.31181/sems21202412s
Agarwal, J., Sahoo, S., Mohanty, S., Nayak, S. K. (2020). Progress of novel techniques for lightweight automobile applications through innovative eco-friendly composite materials: a review. Journal of Thermoplastic Composite Materials, 33(7), 978-1013. https://doi.org/10.1177/0892705718815530
Goswami, S. S., Behera, D. K. (2021). Implementation of ENTROPY-ARAS decision making methodology in the selection of best engineering materials. Materials Today: Proceedings, 38, 2256-2262. https://doi.org/10.1016/j.matpr.2020.06.320
Zhang, Q., Lu, Z., Wang, Y., Lin, W. (2020). Driving Pattern Recognition of Hybrid Electric Vehicles Based on Multi-hierarchical Fuzzy Comprehensive Evaluation. Jordan Journal of Mechanical & Industrial Engineering, 14(1). https://jjmie.hu.edu.jo/VOL-14-1/18-jjmie-2304-01.pdf
Özdağoğlu, A., Keleş, M. K., & Şenefe, M. (2024). Evaluation of banks in terms of customer preferences with fuzzy SWARA and fuzzy MOORA integrated approach. Journal of Decision Analytics and Intelligent Computing, 4(1), 216–232. https://doi.org/10.31181/jdaic10007122024o
Ghalme, S. G. (2021). Improving Mechanical Properties of Rice Husk and Straw Fiber Reinforced Polymer Composite through Reinforcement Optimization. Jordan Journal of Mechanical & Industrial Engineering, 15(5). https://jjmie.hu.edu.jo/vol15-5/01-jjmie_27_21.pdf
Babar, A. H. K., Ali, Y., Khan, A. U. (2021). Moving toward green mobility: overview and analysis of electric vehicle selection, Pakistan a case in point. Environment, Development and Sustainability, 23, 10994-11011. https://doi.org/10.1007/s10668-020-01101-5
Lo, H.-W., Wang, L.-Y., Weng, A. K.-W., & Lin, S.-W. (2024). Assessing Supplier Disruption Risks Using a Modified Pythagorean Fuzzy SWARA–TOPSIS Approach. Journal of Soft Computing and Decision Analytics, 2(1), 169-187. https://doi.org/10.31181/jscda21202440
Wang, H., Zhao, W., & Zheng, J. (2024). Improved q-Rung Orthopair Fuzzy WASPAS Method Based on Softmax Function and Frank operations for Investment Decision of Community Group-Buying Platform. Journal of Soft Computing and Decision Analytics, 2(1), 188-212. https://doi.org/10.31181/jscda21202442
