Current work attempts to fabricate aluminium alloy AA2219 metal matrix composite (AMC) reinforced with natural bio-based sea shell powder (SSP) which is a ceramic material, in view of improving the mechanical and tribological properties. SSP was characterized by X-Ray Diffraction (XRD) to assess its chemical constituents and particle size. Stir casting route was adopted for fabricating AMCs reinforced with 1, 2 and 3 wt. % of SSP. Energy Dispersive X-ray Spectroscopy (EDS) was used to analyse the formation of secondary elements during casting and scanning electron microscopy (SEM) was used analyze the surface morphology of the composite specimen before and after tribological tests. Hardness, Compressive strength and tribological properties were evaluated using appropriate tests and corresponding ASTM standards. Characterization methods revealed that the formation of secondary elements was very low at 3 wt. % of SSP when compared with other compositions. Hardness and compressive strength was found to be maximum for 3 wt. % of SSP while the specific wear rate and coefficient of friction values were found to be lesser for the same composite when compared with the unreinforced alloy and were on par with the AA2219 composites containing synthetic reinforcements.

The dry sliding wear behavior of heat-treated super duplex stainless steel AISI 2507 was examined by taking pin-on-disc type of wear-test

rig. Independent parameters, namely applied load, sliding distance, and sliding speed, influence mainly the wear rate of super duplex

stainless steel. The said material was heat treated to a temperature of 850°C for 1 hour followed by water quenching. The heat treatment

was carried out to precipitate the secondary sigma phase formation. Experiments were conducted to study the influence of independent

parameters set at three factor levels using the L27 orthogonal array of the Taguchi experimental design on the wear rate. Statistical

significance of both individual and combined factor effects was determined for specific wear rate. Surface plots were drawn to explain the

behavior of independent variables on the measured wear rate. Statistically, the models were validated using the analysis of variance test.

Multiple non-linear regression equations were derived for wear rate expressed as non-linear functions of independent variables. Further,

the prediction accuracy of the developed regression equation was tested with the actual experiments. The independent parameters

responsible for the desired minimum wear rate were determined by using the desirability function approach. The worn-out surface

characteristics obtained for the minimum wear rate was examined using the scanning electron microscope. The desired smooth surface was

obtained for the determined optimal condition by desirability function approach.