APPLICATION OF FUZZY MCDM IN SELECTING ECO-FRIENDLY MATERIALS FOR ELECTRIC VEHICLE INTERIORS - Goswami, Shankha Shubhra; Pamučar, Dragan S. (Journal of Applied Engineering Science, 2025)
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.