Investigation of the effect of process parameters on the formation and characteristics of recast layer in wire-EDM of Inconel 718

2009 ◽  
Vol 513-514 ◽  
pp. 208-215 ◽  
Author(s):  
Thomas R. Newton ◽  
Shreyes N. Melkote ◽  
Thomas R. Watkins ◽  
Rosa M. Trejo ◽  
Laura Reister
2015 ◽  
Vol 772 ◽  
pp. 245-249
Author(s):  
A. Ramamurthy ◽  
R. Sivaramakrishnan ◽  
S. Venugopal ◽  
T. Muthuramalingam

It is very important and complexity to find the optimum values of wire EDM process parameters and contribution of each parameter to attain the better performance characteristics. In this study, an attempt has been made to optimize those parameters while machining the titanium alloy. Since the process involves more one than one response parameter, it is essential to carry out the multi-response optimization methodology .The experiments have been conducted with different levels of input factors such as pulse on time,pulse off time and wire tension based on Taguchi L9 orthogonal table.Wire EDM optimal process parameter has been identified using grey relational analysis and significant parameter has been determined by analysis of variance. Experimental results have indicated that the multi-response characteristic such as material removal rate and surface roughness can be improved effectively through grey relational analysis.


Author(s):  
C. Divya ◽  
L. Suvarna Raju ◽  
B. Singaravel

Turning process is a primary process in engineering industries and optimization of process parameters enhance the machining performance. Inconel 718 is a nickel-based superalloy, widely found applications in the manufacturing of blades, sheets and discs in aircraft engines and rocket engines. It provides toughness at low temperature, with stand high mechanical stresses at elevated temperature and creep resistance. In this work, turning process is carried out on Inconel 718 with micro whole textured cutting inserts filled with solid lubricants. Three different solid lubricants are used namely molybdenum-di-sulfide (MoS2), tungsten-di-sulfide (WS2) and calcium-di-fluoride (CaF2). Experiments are performed as per L9 orthogonal array. Statistical approaches such as orthogonal array, Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) are used to find the importance and effects of machining parameters. In this study, input parameters included are feed, cutting speed and depth of cut and output parameter includes surface roughness. Optimization of process parameters is carried out and the significance is estimated. The result suggested that WS2 followed by MoS2 and CaF2 given good surface finish value. Also, solid lubricant in machining enhances the sustainability in manufacturing.


2018 ◽  
Vol 7 (2.8) ◽  
pp. 10
Author(s):  
A VS Ram Prasad ◽  
Koona Ramji ◽  
B Raghu Kumar

Machining of Titanium alloys is difficult due to their chemical and physical properties namely excellent strength, chemical reactivity and low thermal conductivity. Traditional machining of such materials leads to formation of continuous chips and tool bits are subjected to chatter which leads to formation of poor surface on machined surface. In this study, Wire-EDM one of the most popular unconventional machining process which was used to machine such difficult-to-cut materials. Effect of Wire-EDM process parameters namely peak current, pulse-on- time, pulse-off-time, servo voltage on MRRand SR was investigated by Taguchi method. 0.25 mm brass wire was used in this process as electrode material. A surface roughness tester (Surftest 301) was used to measure surface roughness value of the machined work surface. A multi-response optimization technique was then utilized to optimize Wire-EDM process parameters for achieving maximum MRR and minimum SR simultaneously.


Mechanika ◽  
2020 ◽  
Vol 26 (6) ◽  
pp. 540-544
Author(s):  
Jayaraj JEEVAMALAR ◽  
Sundaresan RAMABALAN ◽  
Chinnamuthu SENTHILKUMAR

Modelling is used for correlating the relationship between the input process parameters and the output responses during the machining process. To characterize real-world systems of considerable complexity, an Artificial Neural Network (ANN) model is regularly used to replace the mathematical approximation of the relationship. This paper explains the methodological procedure and the outcome of the ANN modeling process for Electrical Discharge Drilling of Inconel 718 superalloy and hollow tubular copper as tool electrode. The most important process parameters in this work are peak current, pulse on time and pulse off time with machining performances of material removal rate and surface roughness. The experiments were performed by L20 Orthogonal Array. In such conditions, an Artificial Neural Network model is developed using MATLAB programming on the Feed Forward Back Propagation technique was used to predict the responses. The experimental data were separated into three parts to train, test the network and validate the model. The developed model has been confirmed experimentally for training and testing in considering the number of iterations and mean square error convergence criteria. The developed model results are to approximate the responses fairly exactly. The model has the mean correlation coefficient of 0.96558. Results revealed that the proposed model can be used for the prediction of the complex EDM drilling process.


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