Experimental comparison of near-dry and cryogenically cooled near-dry machining in wire-cut electrical discharge machining processes

Myilsamy, Sureshkumar; Boopathi, Sampath

doi:10.1088/2051-672x/ac15e0

Cited by 51 publications

(10 citation statements)

References 42 publications

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“…For all analyses, the confidence interval is set at 0.95 with a margin of error of 5%. The degree of freedom (DM), the sequential sum of the square (SSQ), the adjusted sequential sum of the square (ASSQ), the variance (VE), the F-value, and the percentage of contribution (POC) have been determined based on the standard procedures of the Taguchi technique [31,32]. The residual error for all response parameters has been determined to be less than 5% by Taguchi's analysis.…”

Section: Resultsmentioning

confidence: 99%

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool

Paul,

Thilagham,

K G

et al. 2024

Eng. Res. Express

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The boron carbide (B4C) reinforced AA5052-H32 aluminium composite has been initially fabricated by stir casting method. Friction stir welding (FSW) is used to join two similar AA5052-H32/B4C plates using a titanium nitride (TiN)-coated square tool. The tool wear loss, microhardness, and tensile strength of FSW joints have been investigated by the Taguchi technique. Welding parameters consist of TiN coating thickness, tool rotational speed, welding speed, and axial thrust. Taguchi analysis is used to determine the influences, contributions, and best values of welding parameters to meet optimal welding attributes. The maximum tensile strength (140.134 MPa) has been obtained by increasing the TiN coating thickness, tool's rotational speed, axial thrust, and welding speed. At the highest tool speed and axial trust, the maximum microhardness (158.3 HV) has been attained. The minimum tool wear loss (9.023 %) has been obtained by welding at a moderate speed with maximum rotational speed, axial thrust, and TiN coating thickness. Fractography and SEM analysis have been used to analyze the microstructural behaviour of welded aluminium composite materials and worn-out tool surfaces. The Additive Ratio Assessment (ARAS) multi-criteria optimization technique has been applied to predict the best welding parameters to attain the optimal welding characteristics. The 40 µm TiN coating thickness, 1200 rpm tool rotation, 20 mm/min welding speed, and 6000N axial force are predicted to achieve 108.6 MPa tensile strength, 110 HV microhardness, and 9.37% tool wear loss.

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Section: Resultsmentioning

confidence: 99%

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool

Paul,

Thilagham,

K G

et al. 2024

Eng. Res. Express

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“…While increasing the gap voltage, MH and SR are improved and slightly reduced if the voltage is further increased. However, discharge current increases the MH, WLT, and SR due to increasing heat in the machining zone [55,57]. However, it is possible to make the short-circuit problem worse during the high temperature duration [58].…”

Section: Machining Mechanism Of Graphite Powder-argon Gas Assisted De...mentioning

confidence: 99%

Experimental investigation on microhardness, surface roughness, and white layer thickness of dry EDM

Janardhana

Anushkannan²,

Dinakaran

et al. 2023

Eng. Res. Express

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In this research, the environment-friendly dry electrical discharge machining (EDM) process is investigated to improve the microhardness, surface finish, and white layer thickness of the machined surfaces using graphite-argon gas as a dielectric medium. The graphite powder, mixed with compressed argon gas, has been used to replace the existing dielectric medium in the EDM process. Gas pressure, discharge current, pulse width, and gap voltage were working as input parameters to reduce surface roughness and enhance the microhardness and white layer thickness. The Taguchi L16 orthogonal array is applied to the design and analysis of the experimental results. The minimum surface roughness (2.23 µm) of the HN31 steel has been attained by increasing the gas pressure up to 1.0 MPa and the minimum values of pulse width (40 µs), gap voltage (40 V), and discharge current (6 A). The maximum microhardness (501.04 HV) has been obtained at 1.2 MPa of gas pressure, 120 µs of pulse width, 60 V of gap voltage, and 18 A of discharge current. The maximum white layer thickness (16.24 µm) is achieved by the maximum values of gas pressure (1.2 MPa), pulse width (160 µs), gap voltage (70 V) and discharge current (18 A). The SEM analysis had been done to reveal the white recast layer thickness and surface roughness of the machined surfaces of the dry EDM process. The SR is increased by the recast layer, pores, and microcracks on the machined surfaces. Finally, the multi-criteria optimization technique: Weight Product Method (WPM) is applied to predict optimum process parameter settings: GP: 1.2 MPa, PW: 120 µs, GV: 50 V, and DC: 18 A to meet the best machining performances (MH=493.32 HV, WLT= 14.28 µm, and SR= 3.82 µm). The validation tests were done to confirm the predicted results obtained by both the Taguchi and WSM methods.

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“…It was found that the effects of interaction parameters were not significantly contributed on both responses than individual parameters. The equations ( 3)-( 7) are used for Taguchi analysis as follows [25][26][27]. The total sum of square:…”

Section: Experimentationsmentioning

confidence: 99%

Experimental investigation on abrasive water jet machining of neem wood plastic composite

Boopathi¹,

Thillaivanan²,

Azeem³

et al. 2022

Funct. Compos. Struct.

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In this article, the neem wood plastic composite material (NWPC) has been fabricated by mixing neem wood saw powder with polypropylene (PP) matrix by injection molding method to study the machining characteristics of the abrasive water jet machining (AWJM) process. The volume percentage of neem wood saw powder(NW), the volume percentage of additive agent talc mixed with polypropylene matrix(A), table traveling speed(Ts), and water-jet pressure (Wp) have been considered as process parameters. The experiments were conducted and analyzed to predict the optimum parameters setting for surface roughness(SR) and kerf angle(KA) using the Taguchi method. It was observed that KA and SR have been greatly impacted by the percentage of neem wood saw powder, table traveling speed, and water-jet pressure. The SR and KA were minimized by reducing the percentage of neem wood powder, table traveling speed, and water-jet pressure. The surface roughness has been decreased by adding talc agent, conversely, the kerf angle has been increased. The concurrent optimum process parameters setting to minimize both SR and KA had been estimated by the weighted product method (WPM). The predicted results from Taguchi and WPM had been verified by microscopic analysis and confirmation experiments.

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Experimental comparison of near-dry and cryogenically cooled near-dry machining in wire-cut electrical discharge machining processes

Cited by 51 publications

References 42 publications

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool

Experimental investigation on microhardness, surface roughness, and white layer thickness of dry EDM

Experimental investigation on abrasive water jet machining of neem wood plastic composite

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Experimental comparison of near-dry and cryogenically cooled near-dry machining in wire-cut electrical discharge machining processes

Cited by 51 publications

References 42 publications

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B4C) using titanium nitride coated tool

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B4C) using titanium nitride coated tool

Experimental investigation on microhardness, surface roughness, and white layer thickness of dry EDM

Experimental investigation on abrasive water jet machining of neem wood plastic composite

Contact Info

Product

Resources

About

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool