Modelling of Surface Roughness in Coated Wire Electric Discharge Machining through Response Surface Methodology

2015 ◽  
Vol 2 (4-5) ◽  
pp. 3520-3526 ◽  
Author(s):  
Dain Thomas ◽  
Rajeev Kumar ◽  
G.K. Singh ◽  
Prashant Sinha ◽  
Sachin Mishra
2021 ◽  
Vol 1026 ◽  
pp. 28-38
Author(s):  
I. Vishal Manoj ◽  
S. Narendranath ◽  
Alokesh Pramanik

Wire electric discharge machining non-contact machining process based on spark erosion technique. It can machine difficult-to-cut materials with excellent precision. In this paper Alloy-X, a nickel-based superalloy was machined at different machining parameters. Input parameters like pulse on time, pulse off time, servo voltage and wire feed were employed for the machining. Response parameters like cutting speed and surface roughness were analyzed from the L25 orthogonal experiments. It was noted that the pulse on time and servo voltage were the most influential parameters. Both cutting speed and surface roughness increased on increase in pulse on time and decrease in servo voltage. Grey relation analysis was performed to get the optimal parametric setting. Response surface method and artificial neural network predictors were used in the prediction of cutting speed and surface roughness. It was found that among the two predictors artificial neural network was accurate than response surface method.


Author(s):  
Bikash Choudhuri ◽  
Ruma Sen ◽  
Subrata Kumar Ghosh ◽  
Subhash Chandra Saha

Wire electric discharge machining is a non-conventional machining wherein the quality and cost of machining are influenced by the process parameters. This investigation focuses on finding the optimal level of process parameters, which is for better surface finish, material removal rate and lower wire consumption for machining stainless steel-316 using the grey–fuzzy algorithm. Grey relational technique is applied to find the grey coefficient of each performance, and fuzzy evaluates the multiple performance characteristics index according to the grey relational coefficient of each response. Response surface methodology and the analysis of variance were used for modelling and analysis of responses to predict and find the influence of machining parameters and their proportion of contribution on the individual and overall responses. The measured values from confirmation experiments were compared with the predicted values, which indicate that the proposed models can be effectively used to predict the responses in the wire electrical discharge machining of AISI stainless steel-316. It is found that servo gap set voltage is the most influential factor for this particular steel followed by pulse off time, pulse on time and wire feed rate.


2012 ◽  
Vol 622-623 ◽  
pp. 1280-1284 ◽  
Author(s):  
Pragya Shandilya ◽  
P.K. Jain ◽  
N.K. Jain

Wire electric discharge machining (WEDM) is one of the most popular non-conventional machining processes for machining metal matrix composites (MMCs). The present research work deals the parametric optimization of the input process parameters for response parameter during WEDM of SiCp/6061 Al metal matrix composite (MMC). Response surface methodology (RSM) and genetic algorithm (GA) integrated with each other to optimize the process parameters. RSM has been used to plan and analyze the experiments. Four WEDM parameters namely servo voltage, pulse-on time, pulse-off time and wire feed rate were varied to study their effect on the quality of cut in SiCp/6061 Al MMC using cutting width (kerf) as response parameter. The relationship between kerf and machining parameters has been developed by using RSM. The mathematical model thus than developed was then employed on GA to optimized the process parameters.


2019 ◽  
Vol XVI (4) ◽  
pp. 81-93
Author(s):  
Muhammad Hanif ◽  
Wasim Ahmad ◽  
Salman Hussain ◽  
Mirza Jahanzaib

This paper presents a study on optimisation of process parameters of die-sinking electric discharge machining. The influence of dielectric type, electrode polarity, discharge current and gap on the material removal rate (MRR) and surface roughness for machining of AISI D2 steel have been studied. Response surface methodology suggested in the existing literature was employed for conducting the experiments. Kerosene and transformer oils were found as the best dielectric for MRR and surface roughness, respectively. It was also found that electrode with positive polarity offers high MRR while negative polarity ensures best surface finish. ANOVA results indicated that discharge current was the most influencing factor affecting the performance measures, MRR and surface roughness. Although discharge gap showed low effect on MRR and surface roughness, it was effective for debris removal. Empirical models were developed to optimise the results of MRR and surface roughness.


Author(s):  
Divyanshu Bhartiya ◽  
Pinal Rana ◽  
Meinam Annebushan Singh ◽  
Deepak Marla

Abstract Recent investigations on the fabrication of ultra-thin silicon (Si) wafers using wire-electric discharge machining (wire-EDM) were observed to possess some inherent limitations. These include thermal damage (TD), kerf-loss (KL), and low slicing rate (SR), which constraints its industrial use. The extent of TD, KL, and SR largely depends on the process parameters such as open voltage (OV), servo voltage (SV), and pulse on-time (Ton). Therefore, optimizing the parameters that pertain to minimum TD and KL while maintaining a higher SR is the key to improvement in the fabrication of Si wafers using wire-EDM. Thus, the present study is an effort to analyze and identify the optimal parameters that relate to the most effective Si slicing in wire-EDM. A central composite design-based response surface methodology was used for optimizing the process parameters. The capability to slice Si wafers in wire-EDM was observed to be influenced by the discharge energy, which significantly impacted the overall responses. The severities of thermal damages were observed to be mainly dominated by the variation in OV and Ton due to the diffusion of thermal energy into the workpiece, leading to melting and subsequent re-solidification. For high productivity, the optimized parameters resulted in a slicing rate of 0.72 mm/min, thermal damage of 17.44 µm, and a kerf loss of about 280 µm.


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