Optimization of tribo-mechanical properties of kenaf/jute-SiC hybrid composites using integrated grey-fuzzy approach

An increasing need for wear-resistant hybrid materials has prompted researchers to develop alternative materials that comprise different reinforcements and fillers. In recent studies, the combination of natural fibers and ceramic fillers has resulted in hybrid composites with improved tribological characteristics for automotive and aircraft applications. Even though natural fibers have some disadvantages, the combined effect of natural fibers and ceramics with suitable multi-response optimization techniques can overcome the limitations and provide a composite with enhanced mechanical and tribological properties at minimal cost. This paper explores the wear behavior of silicon carbide (SiC) filled kenaf/jute-based hybrid composite. In addition, a multi-response optimization technique combining the fuzzy model interference system and grey relation analysis (GRA) is adopted in the current work. Design of experiments was carried out with the Taguchi L27 orthogonal array (OA) to yield the minimum wear rate and coefficient of friction (COF). This study demonstrated that the highest gray relational grade (GRG) and gray fuzzy grade (GFG) value of 0.804 and 0.801, respectively to obtain the optimal operating parameters of 1 wt% SiC, 30 wt% reinforcement, 1500 m sliding distance, 1.5 m/s sliding speed, and 15 N load. Scanning electron microscope (SEM) revealed worn-out surface mechanisms, fine debris, and the ploughing effect, which play a significant role in begetting the desired wear characteristics. Furthermore, the best combination of particulate hybrid composite was tested for mechanical characteristics in dry and wet conditions.