Integrated AHP–TOPSIS and genetic algorithm based optimization of sustainable sisal/carbon hybrid composite leaf springs with FEA validation

This research investigates sisal fiber composites as a sustainable alternative for vehicle leaf springs. Sisal provides environmental benefits and weight reduction potential, improving fuel efficiency and ride quality. However, its limitations in strength and water resistance restrict its application. To address these challenges, hybridization and an integrated Analytic Hierarchy Process (AHP)–Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)–Genetic Algorithm (GA) approach were employed. Unidirectional glass and carbon fibers, along with glass and carbon fillers, were incorporated into the sisal/polyester composite to enhance material performance for leaf spring applications. AHP was used to determine the relative importance of selection criteria, while TOPSIS facilitated multi-criteria decision-making. Twenty-seven hybrid composite laminates were evaluated, and the C–S–C–S–C (carbon–sisal–carbon–sisal–carbon) stacking sequence was identified as the most suitable material configuration. A GA optimized the hybrid composite leaf spring design to minimize weight while satisfying strength requirements based on the Tsai–Wu failure criterion. The optimized design was validated through Finite Element Analysis (FEA) using Abaqus, based on Classical Laminate Theory (CLT). The proposed sisal/carbon hybrid composite leaf spring demonstrated an 80% weight reduction compared to conventional steel leaf springs. Additionally, the optimized design incorporates 37.3% sisal fibers, enhancing sustainability and supporting economic opportunities for local communities.