Machining parameters optimization during machining of Al/5 wt% alumina metal matrix composite by fiber laser

2017 ◽  
Author(s):  
Arindam Ghosal ◽  
Pravin Patil
Keyword(s):  
Fiber Laser ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Metal Matrix ◽  
Parameters Optimization ◽  
Machining Parameters ◽  
Machining Parameters Optimization

scholarly journals Analysis, predictive modelling and multi-response optimization in electrical discharge machining of Al-22%SiC metal matrix composite for minimization of surface roughness and hole overcut

2020 ◽  
Vol 7 ◽  
pp. 20 ◽  
Author(s):  
Subhashree Naik ◽  
Sudhansu Ranjan Das ◽  
Debabrata Dhupal
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Discharge Current ◽  
Metal Matrix ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Parameters ◽  
Response Optimization ◽  
Pulse On Time

Due to the widespread engineering applications of metal matrix composites especially in automotive, aerospace, military, and electricity industries; the achievement of desired shape and contour of the machined end product with intricate geometry and dimensions that are very challenging task. This experimental investigation deals with electrical discharge machining of newly engineered metal matrix composite of aluminum reinforced with 22 wt.% of silicon carbide particles (Al-22%SiC MMC) using a brass electrode to analyze the machined part quality concerning surface roughness and overcut. Forty-six sets of experimental trials are conducted by considering five machining parameters (discharge current, gap voltage, pulse-on-time, pulse-off-time and flushing pressure) based on Box-Behnken's design of experiments (BBDOEs). This article demonstrates the methodology for predictive modeling and multi-response optimization of machining accuracy and surface quality to enhance the hole quality in Al-SiC based MMC, employing response surface methodology (RSM) and desirability function approach (DFA). Finally, a novel approach has been proposed for economic analysis which estimated the total machining cost per part of rupees 211.08 during EDM of Al-SiC MMC under optimum machining conditions. Thereafter, under the influence of discharge current several observations are performed on machined surface morphology and hole characteristics by scanning electron microscope to establish the process. The result shows that discharge current has the significant contribution (38.16% for Ra, 37.12% in case of OC) in degradation of surface finish as well as the dimensional deviation of hole diameter, especially overcut. The machining data generated for the Al-SiC MMC will be useful for the industry.

scholarly journals Optimization of end milling on Al–SiC-fly ash metal matrix composite using Topsis and fuzzy logic

2019 ◽  
Vol 1 (10) ◽  
Author(s):  
N. Tamiloli ◽  
J. Venkatesan ◽  
G. Murali ◽  
Shyam Prasad Kodali ◽  
T. Sampath Kumar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fly Ash ◽  
Metal Matrix Composite ◽  
Metal Matrix Composites ◽  
Matrix Composite ◽  
Metal Matrix ◽  
End Milling ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Optimal Cutting Parameters

Abstract Metal matrix composites are extensively used in aerospace, automobile and other engineering applications as an alternative to a wide range of elements. High strength–weight ratio, durability and high corrosion resistance are benefits of metal matrix composites. The study that exhibits adopts optimal cutting parameters (speed, feed and depth of cut). The initial study is to explore end milling process of alumina (AA6082 with SiC 3% and fly ash 2%) molted metal matrix composite. The technique for order preference by similarity to ideal solution and fuzzy logic for optimizing the cutting parameter values has been utilized in the MMC. The response surface methodology is being used to develop the numerical model between output responses and machining parameters. The second-order regression models are studied through analysis of variance. The experimental investigation exhibits that feed rate is the important factor on response variables.

Optimization of Machining Parameters on Turning of Hybrid Metal Matrix Composite

2013 ◽  
Vol 315 ◽  
pp. 113-116 ◽  
Author(s):  
T.S. Mahesh Babu ◽  
P.S. Ramkumar ◽  
Nambi Muthukrishnan
Keyword(s):  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Surface Finish ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Ratio Method ◽  
Depth Of Cut ◽  
Mechanical And Thermal Properties ◽  
Machining Parameters ◽  
Hybrid Metal Matrix Composite

Hybrid metal matrix composite constitutes a tough metal matrix with reinforcement of at least two ceramic particulates and exhibit superior mechanical and thermal properties. The difficulties in machining metal matrix composites are obtaining good surface finish, consumption of more electrical power, involving excessive cutting forces and greater tool wear as it contain very hard ceramic particulates. This factor restrict the wide spread application of these kind of materials. Hence the study of machining characteristics and the optimization of the cutting parameters are prime importance. In this paper aluminium alloy is taken as metal matrix and the silicon carbide (SiC 10% by wt.) and boron carbide (B4C 5% by wt.) taken as ceramic reinforcement. This material is fabricated in the form of cylindrical rod using stir casting method. Turning operations are carried out in medium duty lathe using poly crystalline diamond (PCD) cutting tool insert. Taguchis design of L09orthogonal array is followed selecting three machining factors namely cutting speed, feed and depth of cut at three levels. Optimal cutting conditions are arrived by Signal-Noise ratio method with respect to surface roughness. The results are validated by (ANOVA) analysis of variance and the percentage of contribution of cutting speed, feed rate and depth of cut for better surface finish are determined and it is found that the vital parameter is feed followed by cutting speed and then by depth of cut.

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