S. Arivazhagan’s research while affiliated with KPR Institute of Engineering and Technology and other places

In this research, a novel cellulosic fiber from the Cannonball tree was extracted and alkalized. The alkalisation was done for 45 min using a 5% NaOH solution. The cellulose percentage of the alkalized fiber was elevated to 69.23% from 54.96%. The increase in the crystallinity index (72.73% from 65.29%) of alkalized fiber was recognized via XRD analysis. Thermogravimetric analysis established that after alkalization maximal deterioration peak of (362.94 °C from 357.21 °C) and kinetic activation energy (67.5 kJ/mol from 60.33 kJ/mol) are enhanced. Lignin, wax, and impurity-free exterior layers are seen in the FE-SEM images of alkalized fiber. The absence of impurity elements in the EDX spectrum of alkalized CBFs indicated the abolishment of contaminants on the fibre’s exterior. After the NaOH treatment, CBF tensile strength (71.5 ± 25 Mpa from 42.2 ± 10.5), and tensile modulus (4.15 ± 1.572 GPa from 2.1 ± 789) were increased. All the above findings concluded that CBFs are potential materials for reinforcement in fiber-reinforced plastics.

Fused deposition modeling (FDM) is a contemporary approach that can produce simple and complex physical models, prototype tools, and functional components. However, the challenge is choosing the right parameters, which are essential to printing a high-quality Additive Manufactured (AM) structure with acceptable mechanical attributes, like mechanical strength. In the additive manufacturing technique, fabricating a lightweight structure without compromising the weight and shape is very difficult because the significant parameter is infill density (D) %, which is directly proportional to the strength and inversely proportional to the weight. In this research based on morphogenesis, the infill density is varied at different locations wherever it is needed to print a lightweight, high-strength structure. Parameters Layer Thickness (LT), Shell Thickness (ST), and D were chosen, and experiments were conducted as per Central Composite Design (CCD). Tensile Strength (TS) and Compression Strength (CS) samples were printed with PLA and tested. The results were used to develop a multi-objective function. To predict maximum TS and CS without compromising the weight, Particle Swarm Optimization (PSO) and Response Surface Methodology (RSM) techniques were used to solve the multi-objective function. PSO predicts that the optimum printing parameter values for achieving a lightweight, high-strength structure are LT of 0.17 mm, ST of 0.91 mm, and D of 11.3%. These predicted results were confirmed through experiments.

This study aimed to intensify the Tensile Strength (TSFSW) of dissimilar thermoplastic joints by utilizing a bio-inspired jig saw suture and optimizing the Friction Stir Welding (FSW) limits. Statistical analysis, Response Surface Methodology (RSM), and experimental validation were involved to attain the research objectives. The outcomes showed that the Traverse Speed (TS) and Plunge Depth (PD) parameters had a higher significance on Tensile Strength compared to Rotational Speed (RS). Increasing TS directly correlated with an increase in Tensile Strength, while excessive PD beyond a certain point had a negative impact. The RSM prediction results were validated through experiments, achieving a extreme TSFSW of 11.1 MPa with a low error percentage. The best values of the FSW limits were found to be RS of 1200 rpm, PD of 0.37 mm, and TS of 49.39 mm/min. The formulated model and RSM proved effective in predicting the optimal FSW limits and achieving superior TSFSW. These findings contribute to advanced FSW techniques for dissimilar thermoplastic joints, providing insights for industrial applications requiring strong and reliable joints.

High Chromium White Cast Iron (HCWCI) plays a major role in manufacturing of wear-resistant components. Due to unique wear resistance property, attribution to the additions of carbide forming elements, they have been used for mill liner applications. By varying the wt% of alloying elements such as Cr, Ti, and Mo, the wear resistance and impact strength of High Chromium Cast Iron (HCCI) can be increased. To enhance the wear resistance property according to Central Composite Design (CCD), 16 samples were fabricated by varying the wt% of alloying elements. To fabricate the samples, furan sand molds were prepared and used for the further casting process. The properties of Furan sand mold enhance the mechanical properties and reduce the mold rejection rate, production time, etc. To attain the optimum Wear Rate (WR) and Impact Strength (IS) value without dominance, optimization techniques such as Response Surface Methodological (RSM) and Particle swarm optimization (PSO) are employed to solve the multi-objective problem. The RSM and PSO predicted optimum solutions are compared by using the Weighted Aggregated Sum Product Assessment (WASPAS) ranking method. The WASPAS result revealed that when compared to the RSM result, the PSO predicted optimal wt% of chemical composition (22 wt % Cr, 3 wt % Ti, and 2.99 wt % Mo) gives the optimum WR value (53 mm ³ /min) and IS value (3.77 J). To validate the PSO result, experiments were carried out for the predicted wt% of alloying elements and tested. The difference between the PSO predicted result and experimental result is less than 5% error which clearly shows that PSO is an effective method to solve the multi-objective problem.

Friction stir welding (FSW) is presently a significant process still underway of research owing to its dynamic behavior of the process. The process is still in its developing stage for the reason that every change in tool dimensions can lead to a different result altogether. In this present work, one such attempt to redesign the tool geometry is experimented for joining AA7068-T6. The specimens were fabricated with the experimentation matrix developed, using a central composite design. The input parameters particularly Rotation Speed (RS), Transverse speed (TS), Pin Profile (PP) and Axial Load (AL) of the tool have been considered for experimentation. To enhance the mechanical properties of FSW joints regression equation is developed and Response Surface Methodology (RSM) is used to optimize the process parameters. A total of 30 sets of experimental runs and three confirmatory experiments were conducted for prediction and validation purposes. The experimental results illustrated that to improve the tensile and hardness property of the joint, the optimum values of process parameters should be fixed at 1515 rpm, 57.3 mm min⁻¹, 10.4 kN, and the welding to be carried out with a tool straight pentagon. The statistical analysis showed that, as compared with the geometry of the tool profile and TS, the parameters RS and the AL influence the tensile and Hardness of FSW joints. A joint efficiency of 88% was found to be achievable when the right combination of process parameters is applied.