Experimental Investigation of Tool Wear Rate (TWR) During the EDM of Hybrid Aluminum Metal Matrix Composite Reinforced with SiCp and Grp

2021 ◽  
pp. 409-419
Author(s):  
Mandeep Singh ◽  
Pardeep Kumar Mishra ◽  
Pragyan Parimita Mohaty ◽  
Rasmeet Singh
Keyword(s):  
Experimental Investigation ◽  
Wear Rate ◽  
Tool Wear ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Metal Matrix ◽  
Tool Wear Rate ◽  
Aluminum Metal ◽  
Aluminum Metal Matrix Composite

scholarly journals Drilling studies on the prepared aluminum metal matrix composite from wet grinder stone dust particles

2018 ◽  
Vol 25 (3) ◽  
pp. 473-487
Author(s):  
L. Francis Xavier ◽  
Paramasivam Suresh
Keyword(s):  
Composite Materials ◽  
Tool Wear ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Metal Matrix ◽  
Thrust Force ◽  
Dominant Factor ◽  
Aluminum Metal ◽  
Aluminum Metal Matrix Composite ◽  
Stone Dust

AbstractThe demand for high-performance and cost-effective composite materials is gaining attention in today’s competitive world. In this work, an attempt has been made to prepare low-cost reinforced aluminum metal matrix composite by reinforcing 10% and 20% weight fractions of wet grinder stone dust (WSD) particles, an industrial waste produced during stone dressing operation in the wet grinder manufacturing industry. As drilling is one of the major machining operations carried out in industries, the prepared composite materials are subjected to drilling studies using carbide, TiN-coated carbide, and HSS drills of 5 mm diameter under dry conditions. The major concern with the machining of composites is the extreme tool wear. Tool wear is a very important and challenging task for manufacturing engineers because it has adverse affects on the product quality and increases the production cost. Hence, there is a need to identify the factors that have most significant influence on the tool wear. In this work, the Taguchi-based design of experiments and analysis of variance were used to determine the optimal cutting parameters and to analyze their effects on thrust force, torque, and tool wear. Multivariable linear regression analysis was also employed to determine the correlations between the factors and the response, namely, thrust force, torque, and tool wear. Finally, a confirmation test was conducted to validate the Taguchi optimization method. From the experimental results, feed rate was identified as the dominant factor influencing the thrust force and spindle speed was identified as the significant factor influencing the torque. Thrust force, torque, and tool wear were found to increase with the increase in the reinforcement content irrespective of the drill used for the investigation.

On the impacts of cutting parameters on surface roughness, tool wear mode and size in slot milling of A356 metal matrix composites reinforced with silicon carbide elements

2020 ◽  
pp. 095440542093750
Author(s):  
Masoud Saberi ◽  
Seyed Ali Niknam ◽  
Ramin Hashemi
Keyword(s):  
Surface Roughness ◽  
Silicon Carbide ◽  
Tool Wear ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Metal Matrix ◽  
Minimum Quantity Lubrication ◽  
Average Surface Roughness ◽  
Aluminum Metal ◽  
Aluminum Metal Matrix Composite

Metal matrix composite is made of non-metallic reinforcements (usually ceramic) in metal matrices that are widely used in various industries, including aerospace and automotive. Two main components of metal matrix composite are the matrix (base metal) and the reinforcing particles that tend to increase the hardness of the workpart. The production and machining of such materials are hard and costly. However, due to their excellent mechanical properties such as high strength to weight ratio, high hardness and rigidity, corrosion resistance, abrasion resistance, and low thermal coefficient, their applications are still growing in various aspects. One major division of metal matrix composite is aluminum metal matrix composite with ceramics particulate reinforcement such as silicon carbide and alumina. According to review of literature, a low volume of information was found in terms of machinability of specific grades of aluminum composite (A356-10% silicon carbide) under various lubrication modes. Therefore, in the course of this study, several blocks of aluminum metal matrix composite (A356) reinforced with 10% silicon carbide elements were used under dry, minimum quantity lubrication and wet milling operation. The maximum flank wear, tool wear modes, as well as the average surface roughness were recorded and were subsequently studied as the machining performance attributes. The use of lubricants in both minimum quantity lubrication and wet modes led to reduced tool wear as compared with readings made under dry mode. However, under similar experimental conditions, no significant improvement was observed on the average surface roughness values.

Multi-scale modeling of thermal conductivity of SiC-reinforced aluminum metal matrix composite

2017 ◽  
Vol 51 (28) ◽  
pp. 3941-3953 ◽  
Author(s):  
Xiangyang Dong ◽  
Yung C Shin
Keyword(s):  
Thermal Conductivity ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Metal Matrix ◽  
Scale Model ◽  
Electronic Effects ◽  
Multi Scale ◽  
Aluminum Metal ◽  
Aluminum Metal Matrix Composite ◽  
Sic Particle

High thermal conductivity is one important factor in the selection or development of ceramics or composite materials. Predicting the thermal conductivity would be useful to the design and application of such materials. In this paper, a multi-scale model is developed to predict the effective thermal conductivity in SiC particle-reinforced aluminum metal matrix composite. A coupled two-temperature molecular dynamics model is used to calculate the thermal conductivity of the Al/SiC interface. The electronic effects on the interfacial thermal conductivity are studied. A homogenized finite element model with embedded thin interfacial elements is used to predict the properties of bulk materials, considering the microstructure. The effects of temperatures, SiC particle sizes, and volume fractions on the thermal conductivity are also studied. A good agreement is found between prediction results and experimental measurements. The successful prediction of thermal conductivity could help a better understanding and an improvement of thermal transport within composites and ceramics.

Sign in / Sign up

Export Citation Format

Share Document