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Natural fiber composites have garnered considerable interest in recent years as sustainable substitutes for synthetic materials, owing to their environmental advantages, including renewability, biodegradability, and cost-effectiveness. Notwithstanding these benefits, there is a vital need to improve the mechanical and tribological characteristics of these composites for applications involving significant wear. This work used compression molding to make hybrid composites with natural fibers (NFs) and nano silicon dioxide (nSiO2) filler. The matrix material was epoxy, and the natural reinforcements were Enset ventricosum (EV) and Terminalia arjuna (TA) fibers. Tensile (TS), flexural (FS), and impact (IS) characteristics improved using 1:1 SiO2filler and EV/TA fiber reinforcement. The combination of 6 wt% SiO2and 45 wt% EV/TA improved mechanical performance. A high SiO2filler (6 wt%) in polymer-based composites decreased Specific Wear Rate (SWR), according to Taguchi optimization. A better fiber-matrix interaction improves the mechanical characteristics of materials with fillers. This study optimized several responses using the new combined compromise solution (CoCoSo) method. Multi-criteria decision making is used here. This study introduces Method based on the Removal Effects of Criteria (MEREC) to determine objective criteria weights. Conclusions from experiments show ideal results. CoCoSo's optimization study showed that Enset ventricosum and Terminalia arjuna fiber (EV/TA) hybridization affected composites' tribological behavior.This hybrid fiber combination carried the most influence, followed by fillers. The optimal results were obtained with 6 wt% SiO2/25 wt% EV/TA Hybrid fiber, 1000 m Sliding distance (SD), 2 m/s Sliding speed (SS), and 10 N axial load (AL).

This study investigates the wear and temperature performance of injection-molded polymer gears composed of Polylactic acid (PLA) and Thermoplastic polyurethane, enhanced with 2% silica-coated TiO2nanoparticles (PLA/TPU/2%S-TiO2) gears, they surpass Nylon 66's torque resistance by 23.07%, enduring 13 Nm torque in step loading conditions. Enhanced hardness and glass transition temperature, attributed to TPU and S-TiO2reinforcement, result in reduced wear at pitch and flank areas compared to Nylon 66 under various torques. Scanning Electron Microscopy (SEM) analysis reveals a transition from adhesive interactions to abrasion mechanisms, intricately linked to applied torque fluctuations. The study employs an integrated approach, combining experimental monitoring, Short-Time Fourier Transform, and Convolutional Neural Network, achieving a noteworthy 92.5% accuracy in detecting gearbox faults. These findings hold promise for enhancing machinery reliability and maintenance efficiency in industrial applications.

The current study presents a methodology for examining the effect of solutionizing and aging parameters on the wear and corrosion behaviour of ZA27/SiC/TiB2, a Hybrid Metal Matrix Composite(HMMC). ZA27 alloy is widely used in applications where high bearing resistance and wear resistance properties are desired. However, its usability is limited to temperatures less than 1000C as its properties exhibit a declining trend. The addition of SiC and TiB2were found to contribute in circumventing this lacuna. Furthermore, no studies were reported on the process of augmenting the corrosion and wear resistance of this hybrid composite. This research gap is specifically addressed in this work. The chosen Hybrid Composite consisting of 15% of reinforcing elements(SiC + TiB2) proportioned equally among them along with 85% of ZA27 alloy matrix is produced by Mechanical Stir casting method. The experimental work has been broadly divided into two major spectrums. The first part consisting of analysing the change in properties being studied before and after heat treatment. Besides, this part of the work also involved the study of the variation in artificial aging temperature on the properties under consideration. The Potentiodynamic Polarisation tests showed that the solution heat treatment produces a significant decline in corrosion rate. Further, aging at a temperature of 1800C has also evidently improved the properties of corrosion and wear resistance. However, results also depicted that over aging would deteriorate these properties. The final and subsequent part was completely devoted to identifying the best and optimised heat treatment parameters viz., solutionising time, aging temperature and time. Further, Taguchi L9 orthogonal array is taken to design the experiments in the second phase. Regression Equations were developed from the observations of this set of experiments. These equations were later subjected to Multi-Objective Genetic Algorithm (MOGA) which produces a pareto set of optimal solutions. The Pareto frontier was then analysed using Multi criteria decision making approaches viz., VIKOR, LINMAP and TOPSIS to arrive at the most optimal solution. This approach has culminated in an optimal solution of corrosion and Wear rates of 2.27mpy, 2.75 ˟10-3mm3/m and coefficient of friction as 0.271 at the input variables of solutionizing time −5 h, aging temperature-1890C and aging time-2 h.