Investigation of surface roughness and material removal rate of WEDM of SS304 using ANOVA and regression models

Srinivasan, D.; Ganesh, Nakkala; D, Jafrey Daniel James; Ramakrishnan, H.; Balasundaram, R.; Sanjeevi, R; Pandiyan, G. Karthik; G, Sathisk Kumar; Mohanraj, C

doi:10.1088/2051-672x/ac6c9e

Cited by 13 publications

(7 citation statements)

References 29 publications

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“…1, 2, and 5, the SR of the samples increased with an increase in T on and V. When T on increased to 6.5 μs, the SR increased significantly from 3.694 μm to 5.111 μm. Because of the larger T on , the higher the discharge energy, the higher the pulse energy that corrodes the workpiece surface to form deeper discharge craters [36]. Although the IP of experiment No.…”

Section: Analysis Of Surface Roughness (Ra)mentioning

confidence: 97%

Research on microstructure evolution and surface quality of WEDM for magnetic refrigerant rare-earth gadolinium

Sun,

Shi,

et al. 2024

Surf. Topogr.: Metrol. Prop.

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Rare-earth gadolinium (Gd) is preferable for manufacturing regenerators of the core components of room-temperature magnetic refrigeration owing to its unique magnetocaloric and mechanical properties. However, the surface quality of the regenerator plays a crucial role in the heat transfer effect and service life of magnetocaloric systems during wire electrical discharge machining (WEDM) when fabricating rare-earth Gd array microstructure regenerators. In this study, different process parameters were used to conduct a process experiment of the WEDM of rare-earth Gd. First, the evolution of the surface microstructure and its causes were analyzed using a single-factor experiment, while a corrosion test was conducted on the samples. The analysis showed that the pulse-on time and open voltage considerably affected the surface quality of the processed samples, while the samples with better surfaces exhibited good corrosion resistance. Additionally, a Taguchi experiment was designed, and a regression analysis used to establish regression models between the process parameters (pulse-on time, pulse-off time, peak current, open voltage, and water pressure) and both surface roughness (SR) and material removal rate (MRR). The results showed that the average prediction errors of SR and MRR were only 5.34 % and 5.48 %, respectively.

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Section: Analysis Of Surface Roughness (Ra)mentioning

confidence: 97%

Research on microstructure evolution and surface quality of WEDM for magnetic refrigerant rare-earth gadolinium

Sun,

Shi,

et al. 2024

Surf. Topogr.: Metrol. Prop.

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“…It classifies the different input factors according to their effect on the output parameter and also, plots the 3D response surfaces of the studied parameters. 41 In this case the confidence interval is assumed to be 95%, or alpha = 0.05. A statistical parameter called ''p-value'' is considered in this study to assess the effect of cutting parameters on responses.…”

Section: Ecs J=mmmentioning

confidence: 99%

Experimental investigation on the performance of ceramics and CBN cutting materials during dry machining of cast iron: Modeling and optimization study using RSM, ANN, and GA

Gasmi,

Yallese,

Boucherit

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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This study focuses on the performance evaluation of CBN and ceramic tools in dry machining of gray cast iron EN GJL-350. The machining factors taken into account during turning are: cutting speed ( Vc), feed rate ( f), depth of cut ( ap), and cutting tool material (CBN, white ceramic, mixed ceramic, and silicon nitride). The first part of this investigation concerns the evaluation of the four cutting materials performance used in terms of tool wear evolutions, 2D and 3D surface roughness and cutting forces variation according to working parameters. The second part exposes the results according to L32 Taguchi design of experiment. Statistical treatment by ANOVA allowed to quantify the impact of the input factors on the performance parameters, namely the surface roughness ( Ra), the cutting force ( Fz), the cutting power ( Pc), and the specific cutting energy ( Ecs). The response surface methodology (RSM), and the artificial neural network (ANN) approach were adopted to develop mathematical models for predicting the different output parameters. The results of the two methods were compared and discussed. A multi-criteria optimization was performed using the desirability function (DF) approach. The genetic algorithm (GA) was also applied to find pareto fronts. The results found show that CBN is the most efficient material in terms of lower tool wear, surface roughness and cutting forces. The DF method allowed to find an optimal combination ( Vc = 660 m/min, f = 0.13 mm/rev, ap = 0.232 mm, and the CBN material) leading to a compromise between the minimization of ( Ra, Fz, Pc, and Ecs) and the maximization of (MRR). The Pareto fronts found by the (GA) method make it possible to propose a multitude of solutions according to the desired objectives.

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“…At a higher level of gap voltage, the liberation of energy was more, resulting in a void on the surface and a lower MRR. When IP and Ton are combined, the enhancement of MRR is accomplished by enhancing the IP and Ton [34]. MRR ampli ed as IP was increased where V and IP were combined.…”

Section: Microstructure Examinationmentioning

confidence: 99%

Machinability analysis and optimisation of EDM in AA6082/3 wt% BN/1 wt% MoS2 hybrid composites using entropy method weights integrated with complex proportional assessment (COPRAS) method

Ganesan¹,

Dhilip²,

Sivalingam

et al. 2022

Int J Adv Manuf Technol

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An investigation was made on composites containing AA6082 as matrix and boron nitride/molybdenum disulphide (BN/MoS 2 ) used as reinforcement, which was 3 wt. % of BN and 1% MoS 2 hybrid composite materials were fabricated by stir casting methodology. Using electrical discharge machining (EDM) equipment, machinability studies were examined to achieve an optimal condition of process parameters. Taguchi (L27 orthogonal array) based design of experiments was employed for experiments to examine the in uence of process parameters like pulse on time (Ton), peak current (IP) and gap voltage (V) on material removal rate (MRR), circularity (CIRC), electrode wear rate (EWR), and cylindricity (CYLD) were investigated. Multi Criteria Decision Making (MCDM) methodology was employed for the process parameters while machining AA6082/ 3 wt. % BN/1% MoS 2 hybrid composites. An entropy-based objective weights method was integrated with the complex proportional assessment (COPRAS) approach to assess the most excellent optimal level of process parameters. The entropy (W j ) weights were 0.1285, 0.1002, 0.5707 and 0.2005 for MRR, EWR, CIRC, and CYLD. The optimal conditions are obtained from the COPRAS method of relative signi cance score, and quantitative utility assessment score in the nineteenth experiment having the 15 A, 50 µs and 30 V with the relative signi cance score of 0.0735 with a higher quantitative utility score of 100% is achieved. Using an SEM, the machined surface is analysed for the micro-structural examination. At higher peak current (IP), micro-voids and craters with poor surface nish were achieved.

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Investigation of surface roughness and material removal rate of WEDM of SS304 using ANOVA and regression models

Cited by 13 publications

References 29 publications

Research on microstructure evolution and surface quality of WEDM for magnetic refrigerant rare-earth gadolinium

Research on microstructure evolution and surface quality of WEDM for magnetic refrigerant rare-earth gadolinium

Experimental investigation on the performance of ceramics and CBN cutting materials during dry machining of cast iron: Modeling and optimization study using RSM, ANN, and GA

Machinability analysis and optimisation of EDM in AA6082/3 wt% BN/1 wt% MoS2 hybrid composites using entropy method weights integrated with complex proportional assessment (COPRAS) method

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