Taguchi analysis of surface modification technique using W-Cu powder metallurgy sintered tools in EDM and characterization of the deposited layer

Patowari, Promod Kumar; Saha, Partha; Mishra, P. K.

doi:10.1007/s00170-010-2966-y

Cited by 66 publications

(35 citation statements)

References 16 publications

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“…And similar methodology was also utilized by [28][29][30] in EDM. To analyze the effect of key process parameters on MRR and Ra and to optimize these parameters for machining process, Taguchi method was used in the experimental researches by many researchers [31][32][33][34][35]. Joshi et al [16] and Wang et al [36] performed a hybrid approach for modeling and optimization of EDM process using ANN to obtain optimal process parameters.…”

Section: Femmentioning

confidence: 99%

A hybrid process model for EDM based on finite-element method and Gaussian process regression

Ming

Zhang

et al. 2014

Int J Adv Manuf Technol

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This paper proposed a hybrid intelligent process model, based on finite-element method (FEM) and Gaussian process regression (GPR), for electrical discharge machining (EDM) process. A model of single-spark EDM process has been constructed based on FEM method, considering the latent heat, variable heat distribution coefficient of cathode (f c ), and plasma flushing efficiency (PFE), to predict material removal rate (MRR) and surface roughness (Ra). This model was validated using reported analytical and experimental results. Then, a GPR model was proposed to establish relationship between input process parameters (pulse current, pulse duration, and discharge voltage) and the process responses (MRR and Ra) for EDM process. The GPR model was trained, tested, and tuned using the

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Section: Femmentioning

confidence: 99%

A hybrid process model for EDM based on finite-element method and Gaussian process regression

Ming

Zhang

et al. 2014

Int J Adv Manuf Technol

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“…The Taguchi's robust design approach was proposed for the WEDM operation in order to optimize the MRR and Ra [14,15]. Mohammadi and Aminollah also used the Taguchi's method analysis of variance (ANOVA) to study the relationship between WEDM input and output measures [15,16], and other scholars also used this method to investigate surface modification in EDM [17]. The artificial neural network was utilized to establish a mathematical relationship between the cutting parameters and output measures [18,19].…”

Section: Introductionmentioning

confidence: 99%

“…The artificial neural network was utilized to establish a mathematical relationship between the cutting parameters and output measures [18,19]. It can be seen from above that the MRR and Ra are the most widely characteristics that are used to describe WEDM cutting conditions [6][7][8][9][10][11][12][13][15][16][17][18]. In terms of workpiece material, tool steel YG15 was used because of its wide application in cutting tools and mold industry.…”

Section: Introductionmentioning

confidence: 99%

Optimization of cutting conditions of YG15 on rough and finish cutting in WEDM based on statistical analyses

Huang

Ming

Guo

et al. 2013

Int J Adv Manuf Technol

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In this paper, the effects and the optimization of cutting parameters on surface roughness (Ra) and material removal rate (MRR) in the wire electrical discharge machining (WEDM) of high hardness tool steel YG15 are analyzed. In the WEDM process, the key process parameters, such as pulse-on time, pulse-off time, power, cutting feed rate, wire tension, wire speed, and water pressure, are optimized. Experimental data were initially collected based on the Taguchi method of experimental design, which are L 18 2 1 × 3 5 and L 18 2 1 × 3 4 Taguchi standard orthogonal array on rough and finish cutting experiments, respectively. The level of importance of the cutting parameters on the Ra and MRR was determined on both finish and rough cutting by using statistical analyses; average gap voltage is discussed in order to balance cutting efficiency and stability on both finish and rough cutting. In addition, comparative analysis of finish and rough cutting is drawn to analyze the difference between rough cutting and finish cutting. Then, regression models and signal-to-noise ratio are used to obtain the optimum cutting parameter combination. Finally, the results present the optimized MRR and Ra of the rough and finish process, respectively, and confirm the efficiency and abilities of the model.

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“…For proper material transfer, the tool material must be loosely bonded together to be able to get eroded sufficiently by thermoelectric energy of the discharge. This type of special tool can be made by P/M compact, either in green or semi sintered state [3]. The intentional transfer of tool material is done to modify the mechanical properties such as strength, toughness, hardness along with surface properties such as wear resistance and abrasion resistance with good surface finish.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Surface Roughness Parameters of Al-6351 Alloy in EDC Process: A Taguchi Coupled Fuzzy Logic Approach

Kar

Chakraborty

Dey

et al. 2016

J. Inst. Eng. India Ser. C

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This paper investigates the application of Taguchi method with fuzzy logic for multi objective optimization of roughness parameters in electro discharge coating process of Al-6351 alloy with powder metallurgical compacted SiC/Cu tool. A Taguchi L16 orthogonal array was employed to investigate the roughness parameters by varying tool parameters like composition and compaction load and electro discharge machining parameters like pulse-on time and peak current. Crucial roughness parameters like Centre line average roughness, Average maximum height of the profile and Mean spacing of local peaks of the profile were measured on the coated specimen. The signal to noise ratios were fuzzified to optimize the roughness parameters through a single comprehensive output measure (COM). Best COM obtained with lower values of compaction load, pulse-on time and current and 30:70 (SiC:Cu) composition of tool. Analysis of variance is carried out and a significant COM model is observed with peak current yielding highest contribution followed by pulse-on time, compaction load and composition. The deposited layer is characterised by X-Ray Diffraction analysis which confirmed the presence of tool materials on the work piece surface.

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Taguchi analysis of surface modification technique using W-Cu powder metallurgy sintered tools in EDM and characterization of the deposited layer

Cited by 66 publications

References 16 publications

A hybrid process model for EDM based on finite-element method and Gaussian process regression

A hybrid process model for EDM based on finite-element method and Gaussian process regression

Optimization of cutting conditions of YG15 on rough and finish cutting in WEDM based on statistical analyses

Optimization of Surface Roughness Parameters of Al-6351 Alloy in EDC Process: A Taguchi Coupled Fuzzy Logic Approach

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