No abstract

The demand for materials arises to improve the effi ciency of the structural, aerospace and automotive components. It induces to identifi cation and production of composite materials. Amongst the varieties, Aluminium Metal Matrix Composite is widely used in automotive and aerospace industries because if inheriting wide range of acceptable mechanical and tribological properties besides being constructive by holding high strength to weight ratio. Herein, ED machining properties of cryogenic treated AA7075-B4C composites were analysed. B4C particles reinforced Aluminium metal matrix composites were prepared by using one of the liquid metrological method viz. stir casting. The samples were cryogenically treated at various soaking time periods (12, 24 & 36 hours). In ED Machining, material removal (MR) rate, tool wear (TW) rate and surface roughness (Ra) parameters were analysed depending upon the inputs viz. soaking time (SoT), electrode gap (Gap), current, Pon (pulse ON time), Poff (pulse OFF time). Experimentation remarks that current be one of the mostly infl uencing parameter towards ED machining than any other considerations in this part of research.

The present research pacts with fabrication of Cu – HEA surface MMC through solid state Friction Stir process (FSP) and analysis of wear characteristics. AlCoCrCuFe HEA with higher hardness values vacillated up in the level of 770HV is selected as reinforcement. The wear test is performed for 16 parameter combinations based on Taguchi method with the aid of Pin-on-Disc apparatus. The input parameters considered are HEA percentage, applied load, sliding velocity and distance whereas wear rate and coeffi cient of friction are chosen as response. WR signifi cantly decreases with HEA additions and increases with increase in load, sliding velocity and sliding distance. The consequence of HEA addition on CoF during dry sliding wear test is contradictory to its effect over WR. ANOVA results confi rmed the signifi cant effect of reinforced HEA over wear characteristics of copper composite. TOPSIS methodology is followed to fi nd the best possible parameter combination that yields better wear rate and coeffi cient of friction.