Experimental analysis and characterization of SiC and RE oxides reinforced Al-6063 alloy based hybrid composites

• Published in: International journal of advanced manufacturing technology 2020-05, Vol.108 (4), p.1173-1187
• Main Authors: Sharma, Vipin Kumar, Kumar, Vinod, Joshi, Ravinder Singh, Sharma, Deepak
• Format: Article
• Language: English
• Subjects: Aluminum base alloys; CAE) and Design; Cerium oxides; Computer-Aided Engineering (CAD; Electron backscatter diffraction; Engineering; Hybrid composites; Impact strength; Industrial and Production Engineering; Lanthanum oxides; Mechanical Engineering; Mechanical properties; Media Management; Microhardness; Original Article; Regression analysis; Rockwell hardness; Scanning electron microscopy; Silicon carbide; Software; Tensile strength
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-020-05228-7

The current paper investigates the mechanical behavior of Al-6063 hybrid composites reinforced with silicon carbide (SiC) and rare earth (RE) oxides. Hybrid composites containing wt% of SiC as 3, 6 and 9% and (CeO 2  + La 2 O 3 ) mixture as RE oxides as 1,2 and 3 wt% were fabricated using stir casting technique. The scanning electron microscopy (SEM), X-Ray diffraction (XRD), electron backscattered diffraction (EBSD) and energy dispersive spectroscopy (EDS) analysis were used to characterize the prepared samples of hybrid composites. The mechanical characterization including Rockwell hardness, Vicker’s microhardness, impact strength and tensile strength were tested as per ASM standards. The fractured samples of different hybrid composites were studied using SEM. The highest value of Rockwell hardness was observed as 69 HRB in composite sample with 6 wt% of SiC and 2 wt% of RE mixture. For the same sample, highest value of Vicker’s microhardness was found to be 114.24 HV. Furthermore, highest value of tensile strength and impact strength was observed to be 91 MPa and 56 J for the same sample. The obtained data were analyzed on Design Expert software Version 6.0.8 using two level factorial designs afterward. The regression equations obtained from the software is validated using diagnosis plots and the optimized values of reinforcements are obtained using desirability analysis.