Multi-objective optimization of electrical discharge machining of PH17-4 stainless steel with surfactant-mixed and graphite powder–mixed dielectric using Taguchi-data envelopment analysis–based ranking method

Reddy, V. Vikram; Valli, P. Madar; Kumar, Adepu; Reddy, Ch. Sridhar

doi:10.1177/0954405414530904

Cited by 31 publications

(14 citation statements)

References 14 publications

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“…Recent studies have investigated successful combinations of the Taguchi method with other optimization techniques, therefore optimizing multiple characteristics of EDM, including a combination of MRR and SR, or even MRR, TWR, and SR. 16 The surface roughness and width of the cut are the two characteristics used to simultaneously optimize the machining processes for stainless steel SS304 with a wire EDM. 17 The optimal values were obtained with the current of 3 A, and the pulse-on time of 15 µs and pulse-off time of 4 µs. These results demonstrate that the pulse-on time includes the process parameters that strongly affect both of the indicators studied.…”

Section: Introductionmentioning

confidence: 99%

Characteristics optimization of powder mixed electric discharge machining using titanium powder for die steel materials

Banh

Huu

Cuong

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part E:

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In the present study, four quality characteristics of the electrical discharge are simultaneously presented and optimized using titanium powder mixed electric discharge machining. The Taguchi method and the grey relational analysis are applied to the processing parameters to investigate the following: workpiece material, tool material, polarity, pulse-on time, current, pulse-off time, and powder concentration. The combination of the Taguchi method and grey relational analysis is applied to optimize simultaneously four quality characteristics of powder mixed electric discharge machining, including material removal rate, tool wear rate, surface roughness, and microhardness surface. Optimal results by the Taguchi-grey relational analysis show that both surface roughness and tool wear rate decrease, while both material removal rate and microhardness surface increase, respectively. This approach proves effective in terms of improving the processing efficiency of the study parameters. The results from both optimization calculations and experimentation demonstrate high accuracy and efficiency. Furthermore, powder mixed electric discharge machining has improved significantly. The concentration of titanium powder is the processing parameter with the strongest influence on the efficiency of powder mixed electric discharge machining.

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Section: Introductionmentioning

confidence: 99%

Characteristics optimization of powder mixed electric discharge machining using titanium powder for die steel materials

Banh

Huu

Cuong

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part E:

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show abstract

“…The genetic algorithm concept was used to optimize the weighting factors of the network [12]. Investigated the effect of surfactant and graphite powder mixed dielectric on EDM performance characteristics such as MRR, SR, white layer thickness and surface crack density [16]. The significance of surfactant and graphite powder mixed dielectric on MRR, TWR and SR have reported and also process parameters were optimized using Taguchi-DEAR multi response optimization method [17].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Process Parameters of Surfactant and Graphite Powder Mixed Dielectric EDM through Taguchi-Grey Relational Analysis

Reddy¹,

Reddy²,

Valli³

2015

BIJIEMS

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This paper presents an optimization of process parameters of Electrical Discharge Machining (EDM) process with surfactant and graphite powder mixed dielectric using multi-response optimization Grey Relational Analysis (GRA) method instead of single response optimization. These parameters were optimized based on Taguchi orthogonal array (OA) combined with Grey Relational Analysis. A grey relational grade (GRG) was calculated based on Grey Relational Analysis. A grey relational grade is used to optimize the EDM process with multiple performance characteristics. Taguchi L9 orthogonal array was used to design the experiments. The machining parameters such as peak current, surfactant concentration, and graphite powder concentration were chosen for experimentation. The performance characteristics chosen for this study are material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR). Experiments were conducted using electrolyte copper as the tool and PH17-4 stainless steel as the work piece. Results revealed that machining performance has been improved considerably using this approach. The confirmation experiments were conducted at optimum parametric setting and it was found that the predicted values of responses at optimal combination of parameters are in good agreement with the results of confirmation experiments.

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“…Reddy et al [24] investigated the performance of an EDM process while machining PH17-4 stainless steel material using graphite powder-mixed and surfactantmixed dielectric fluids. An integrated Taguchi-data envelopment analysis-based multi-response optimization technique was applied while choosing peak current, surfactant concentration and graphite powder concentration as the three important process parameters, and MRR, Ra and TWR as the responses.…”

Section: Literature Reviewmentioning

confidence: 99%

Parametric optimization of non-traditional machining processes using Taguchi method and super ranking concept

Protim

Chakraborty

2019

YUGOSLAV J OPERATION

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In order to achieve higher dimensional accuracy along with better surface quality, the conventional machining processes have now-a-days being replaced by nontraditional machining (NTM) processes, because of their ability to generate intricate shape geometries on various advanced engineering materials. In order to exploit their fullest machining potential, it is often recommended to operate those NTM processes at their optimal parametric settings. Several optimization tools and techniques are now available which can be effectively applied to obtain the optimal parametric conditions of those processes. In this paper, Taguchi method and super ranking concept are integrated together to present an efficient optimization technique for simultaneous optimization of three NTM processes, i.e. electro-discharge machining process, wire electro-discharge machining process and electro-chemical discharge drilling process. The derived results are validated with the help of developed regression equations, which show that the proposed approach outperforms the other popular multi-response optimization techniques. Analysis of variance is also performed to identify the most influencing control parameters for the considered NTM processes. The developed response surface plots further help the process engineers in identifying the effects of various NTM process parameters on the calculated sum of squared rank values.

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Multi-objective optimization of electrical discharge machining of PH17-4 stainless steel with surfactant-mixed and graphite powder–mixed dielectric using Taguchi-data envelopment analysis–based ranking method

Cited by 31 publications

References 14 publications

Characteristics optimization of powder mixed electric discharge machining using titanium powder for die steel materials

Characteristics optimization of powder mixed electric discharge machining using titanium powder for die steel materials

Optimization of Process Parameters of Surfactant and Graphite Powder Mixed Dielectric EDM through Taguchi-Grey Relational Analysis

Parametric optimization of non-traditional machining processes using Taguchi method and super ranking concept

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