The dry sliding wear behaviour of LM 24 aluminum alloy composites reinforced with garnet particles was evaluated. Stir casting technique was used to fabricate the composites. A pin-on-disc wear-testing machine was used to evaluate the wear rate, in which an EN 24 steel disc was used as the counterface. Results indicated that the wear rates of the composites were lower than that of the matrix alloy and further decreased with the increase in garnet content. However, in both unreinforced and reinforced composites, the wear rate increased with the increase in load and the sliding speed. Increase in the applied load increased the wear severity by changing the wear mechanism from abrasion to particle cracking-induced delamination wear. It was found that with the increase in garnet content, the wear resistance increased monotonically. The observations have been explained using scanning electron microscopy analysis of the worn surfaces and the subsurface of the composites. In this work, the most influencing input and output parameters have been performed and the process parameters have been prioritized using genetic algorithm. Genetic algorithm is used to optimize the most influencing input as well as output process parameters. The practical significance of applying genetic algorithm to dry sliding wear behavior process has been validated by means of computing the deviation between predicted and experimentally obtained wear behavior of metal matrix composite.

In this research work, an experimental investigation of Friction Welding of Tube to Tube Plate with External Tool (FWTPET) has been carried out using backing block arrangement with interference fit. The Materials have been used in this research of SA213 tube and SA387 tube plate. The results of the experimental investigation revealed that by employing backing block, FWTPET is capable of producing defect free welds. The Welding sample has been conducted several characteristics such as Compression test, radiographic test and Microscopic Test. Further Taguchi L₉ orthogonal array was utilized to find the most significant control factors which will yield better joint strength. Besides, the contribution of each process parameter has been determined using statistical analysis of variance (ANOVA). The Input and Output values are 1320 rpm Speed, 0 mm projection, 0.1 mm Depth of cut and 3086.90 MPa optimal joint strength respectively.