Multi-Objective Optimization of Wire-Electric Discharge Machined Ultra-Thin Silicon Wafers Using Response Surface Methodology for Solar Cell Applications

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.

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

Abstract Recent investigations on the fabrication of ultra-thin silicon (Si) wafers using wire-electrical discharge machining (wire-EDM) were observed to possess some inherent limitations. This includes severe thermal damage, kerf-loss, and low slicing rate, which could be detrimental towards realizing actual practical applications. The extent of thermal damage, kerf-loss, and slicing rate largely depends on the process parameters such as open voltage (OV), servo voltage (SV), and pulse on-time (Ton). Therefore, choosing the optimal parameters that pertain to minimum thermal damage and kerf-loss while maintaining a higher slicing rate is the key to further excel in the fabrication of Si wafers using wire-EDM. Therefore, 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 (CCD) based response surface methodology (RSM) was used for optimizing the process parameters. The capability to slice Si wafers in wire-EDM was observed to be highly influenced by the discharge energy, which had a positive impact on the overall responses. The severity of thermal damages was observed to be mainly dominated by the variation in open voltage and Ton due to the high diffusion of thermal energy into the workpiece, which led to intense melting and subsequent re-solidification. The parametric optimization resulted in OV = 84.32 V, SV = 42.98 V and Ton = 0.62 μs as the most feasible parameter that relates to comparatively high slicing rate (0.65 mm/min), low kerf-loss (280 μm) and thermal damage (18 μm) for a given machine. In general, with a decrease in spark energy slicing rate and thermal damage decreases whereas, kerf-loss increases. When spark energy decreases by 83%, there is a nearly 55% decrease in slicing rate and thermal damage and a 10% increase in kerf-loss.


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.


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.


2021 ◽  
Vol 49 (3) ◽  
pp. 756-763
Author(s):  
Kapil Gupta

This work presents the wire-EDM of WC-Co composite and optimization of process parameters using an integrated technique of response surface methodology (RSM), Vise Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and artificial bee colony (ABC) algorithm to obtain the best set of machinability indicators. Wire feed (WF), servo voltage (SV), pulse off-time (Pon) and pulse on-time (Poff) are the variable process parameters, whereas root mean square roughness (Rq), average surface roughness (Ra) and material removal rate (MRR) are the machinability indicators considered in the present work. A total of twenty nine experiments have been conducted based on Box Behnken design (BBD) technique of response surface methodology. VIKOR has been used for normalization of responses and followed by solving empirical models using ABC algorithm to obtain optimized process parameters setting. WF-12 m/min, SV-65V, Pon-116 µs, Poff-20 µs are the optimum wire-EDM parameters obtained by intelligent RSM-VIKOR-ABC technique that produced best values of Ra-4.51 µm, Rq-5.64 µm, MRR-0.061 mm3 /min simultaneously. The validation test confirmed an improvement up to 15% in the response characteristics which proved the effectiveness of this novel hybrid technique for optimization. The optimum parameter setting is for ready industrial reference to attain best surface quality and process productivity for WC-Co composite machining by wire-EDM.


2011 ◽  
Vol 110-116 ◽  
pp. 847-855
Author(s):  
Gyanendra Kumar Singh ◽  
Vinod Yadava ◽  
Raghuvir Kumar

The present study investigates the relationship of process parameters in electro-discharge diamond face grinding (EDDFG) of tungsten carbide and cobalt composite (WC-Co). The central composite rotatable design had been utilized to plan the experiments and response surface methodology (RSM) was employed for developing experimental models. Analysis on machining characteristics of EDDFG was made based on the developed models. In this study, wheel RPM, current, pulse on-time, and duty factor are considered as input process parameters. The process performances such as material removal rate (MRR) and average surface roughness (Ra) were evaluated. Analysis of variance test had also been carried out to check the adequacy of the developed regression models. The observed optimal process parameter settings are wheel RPM of 1500, current of 6.9029 A, pulse on-time of 137. 8208 µs, and duty factor of 0.79 for achieving maximum MRR and minimum Ra; finally, the results were experimentally verified. A good agreement is observed between the results based on the RSM model and the actual experimental observations. The error between experimental and predicted values at the optimal combination of parameter settings for MRR and Ra lie within 6.18% and 12.33%, respectively.


2014 ◽  
Vol 550 ◽  
pp. 53-61
Author(s):  
R.Arun Bharathi ◽  
P.Ashoka Varthanan ◽  
K. Manoj Mathew

The objective of the present work is to predict the optimal set of process parameters such as peak current (IP), pulse on/off time (TON/TOFF) and spark gap voltage (SV) to achieve minimum Surface roughness (Ra), wire consumption rate (WCR) and maximum material removal rate (MRR). In this work, experiments were carried out by pulse arc discharges generated between ZnO coated brass wire and specimen (IS2062 steel) suspended in deionized water dielectric. The experiments were designed based on the above mentioned four factors, each having three levels. Custom design based Response Surface Methodology (RSM) is used in this research. 21 runs of experiments were constructed based on custom design procedure and results of the experimentation were analyzed analytically as well as graphically. Moreover the surface roughness after machining was measured by Taylor Hobson Surtronic device. Second order regression model has been developed for predicting Ra, WCR and MRR in terms of interactive and higher order machining parameters through RSM, utilizing relevant experimental data as obtained through experimentation. The research outcome identifies significant parametersand their effect on process performance on IS2062 steel. The results revealed that peak current, pulse on-time and their interactions have significant effects on Ra, whereas pulse off time and peak current have significant effects on MRR and it is also observed that peak current and interaction between peak current and pulse off time have significant effects on WCR. The adequacy of the above proposed models has been tested through the analysis of variance (ANOVA).


Author(s):  
P. Bharathi ◽  
G. Srinivasarao ◽  
P. Gopalakrishnaiah

In this work, an attempt has been made for optimization of process parameters in Wire Electric Discharge Machining (WEDM) of Ti–6Al–4V while producing square and circular profiles. The input parameters, namely pulse on time, pulse off time, peak current and servo voltage, were considered to study the responses cutting speed (CS) and surface roughness (SR). Each input parameter was set at three levels. Experiments were conducted as per central composite face (CCF) centered design. Based upon the experimental data, Gray relational analysis (GRA), a multi-objective optimization technique has been employed to find the best level of process parameters to optimize the machining profiles. Analysis of variance (ANOVA) has been conducted for investigating the effect of process parameters on overall machining performance. Finally, it was identified that the process parameters such as pulse on time, current and voltage have more impact on the square and circular profiles.


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