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The present research work involves the study of AA 7075-TiB2-Gr in situ composite through stir casting route. This in situ method involves formation of reinforcements within the matrix by the chemical reaction of two or more compounds which also produces some changes in the matrix material within the vicinity. Titanium Diboride (TiB2) and graphite were the reinforcement in a matrix of AA 7075 alloy. The composite was prepared with the formation of the reinforcement inside the molten matrix by adding salts of Potassium Tetrafluoroborate (KBF4) and Potassium Hexafluorotitanate (K2TiF6). The samples were taken under casted condition and the properties of the composite were tested by conducting characterization using X-ray diffraction (XRD), hardness test, flexural strength by using three-point bend test, scanning electron microscope (SEM), optical microstructure, grain size analysis, and surface roughness. It was found that good/excellent mechanical properties were obtained in AA 7075-TiB2-Gr reinforced in situ hybrid composite compared to alloy due to particulate strengthening of ceramic particles of TiB2 in the matrix. Further, Al 7075-3% TiB2-1% Gr hybrid in situ composite exhibited improved machinability over the alloy and composites due to self-lubricating property given by the Gr particles in the materials. [ABSTRACT FROM AUTHOR]

Dual heat treatment (DHT) effect is analyzed using the machining of Al6061-T6 alloy, a readily available material for quickly finding the machining properties. The heat treatments are conducted twice over the specimen by the furnace heating before processing through CNC machining. The HSS and WC milling cutters are preferred for the diameter of 10 mm for the reviewed rotational speeds of 2000 rpm and 4000 rpm, and the constant depth of cut of 0.5 mm is chosen based on various reviews. Worthy roughness could be provided mostly by the influence of feed rates preferred here as 0.05 mm/rev and 0.1 mm/rev. The influencing factors are identified by the Taguchi, genetic algorithm (GA), and Artificial Neural Network (ANN) techniques and compared within it. The simulation finding also helps to clarify the relationship between influenced machining constraints and roughness outcomes of this project. The average values of heat treated and nonheat treated Al6061-T6 are compared and it is to be evaluated that 41% improvement is obtained with the lower surface roughness of 1.78975 µm and it shows good surface finish with the help of dual heat treatment process. [ABSTRACT FROM AUTHOR]