Several components are made from Al-Mg-based composites. MoS2 is used to increase the composite’s machinability. Different weight percent (3, 4, and 5) of MoS2 are added as reinforcement to explore the machinability properties of Al-Mg-reinforced composites. The wire cut electrical discharge machining (WEDM) process is used to study the machinability characteristics of the fabricated Al-Mg-MoS2 composite. The machined surface’s roughness and overcut under different process conditions are discussed. The evaluation-based distance from average solution (EDAS) method is used to identify the optimal setting to get the desired surface roughness and overcut. The following WEDM process parameters are taken to determine the impact of peak current, pulse on time, and gap voltage on surface roughness, and overcut. The WEDM tests were carried out on three different reinforced samples to determine the impact of reinforcement on surface roughness and overcut. The surface roughness and overcut increase as the reinforcement level increases, but the optimal parameters for all three composites are the same. According to EDAS analysis, I3, Ton2, and V1 are the best conditions. Furthermore, peak current and pulse on-time significantly influence surface roughness and overcut.
This work presents the application of hybrid approach for optimizing the dry sliding wear behavior of red mud based aluminum metal matrix composites (MMCs). The essential input parameters are identified as applied load, sliding velocity, wt.% of reinforcement, and hardness of the counterpart material, whereas the output responses are specific wear rate and Coefficient of Friction (COF). The Grey Relational Analysis (GRA) is performed to optimize the multiple performance characteristics simultaneously. The Principle Component Analysis (PCA) and entropy methods are applied to evaluate the values of weights corresponding to each output response. The experimental result shows that the wt.% of reinforcements (Q=34.9%) followed by the sliding velocity (Q=34.5%) contributed more to affecting the dry sliding wear behavior. The optimized conditions are verified through the confirmation test, which exhibited an improvement in the grey relational grade of specific wear rate and COF by 0.3 and 0.034, respectively.
Aerospace alloys with reduced wall thickness but possessing higher hardness, good tensile strength and reasonable corrosion resistance are essential in manufacturing of structures such as fuselage. In this work, friction stir welding has been carried out on such an aerospace aluminum alloy AA8090 T87 which contains 2.3% lithium. Tool rotational speed of 900 rpm and traverse speeds of 90 mm/min., 110 mm/min. are the welding parameters. Hardness analysis, surface roughness analysis and corrosion analysis are conducted to analyze the suitability of the joint for the intended application. The samples were corrosion tested in acid alkali solution and they resulted in the formation of pits of varying levels which indicate the extent of surface degradation. Hardness of the samples was measured after corrosion analysis to observe the changes. The analysis suggests that the change in tool traverse speed transformed the corrosion behavior of the joint and affected both the hardness and surface roughness which mitigated the quality of the joint.
The manuscript discusses the abrasive water jet machining (AWJM) of Al-NiTi and Al-NiTi-nano SiC composites to understand the influences and the effect of each parameter and to indentify optimal combination of AWJM parameters. The experiments are planned and conducted based on L27 orthogonal array. Pressure, standoff distance, and transverse feed rate are considered as input parameters; surface roughness and kerf angle are considered as output parameters. Gravitational search algorithm (GSA) is employed to identify the best possible combination of AWJM parameters. Regression model is used to develop the surface roughness and kerf angle model for Al-NiTi and Al-NiTi-nano SiC composites. The developed mathematical model is used as fitness function in GSA. It is found from the result of GSA that the optimal value for surface roughness of Al-NiTi composite is set at pressure 176 kPa, standoff distance 1 mm, and transverse feed 20 mm/min and for Al-NiTi-nano SiC composite is set at pressure 180 kPa, standoff distance 1.1 mm, and transverse feed 20 mm/min. Similarly, for kerf angle, the optimal value for Al-NiTi composite is set at pressure 260, standoff distance 1 mm, and transverse feed 20 mm/min and for Al-NiTi-nano SiC composite is set at pressure 255 kPa, standoff distance 1 mm, and transverse feed 20 mm/min. Analysis of variance is also performed to understand the effect of each input parameter on output response.
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