A study on machinability evaluation of Al-Gr-B&lt;SUB align="right"&gt;4C MMC using response surface methodology-based desirability analysis and artificial neural network technique

Ponnuvel, S.; Senthilkumar, N.

doi:10.1504/ijrapidm.2019.10017666

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…such as machining polarity, peak current, pulse duration, among others, on the wire-cut electrical discharge machining (WEDM) characteristics such as material removal rate, surface roughness [12] and [13]. Tsoukalas [14] and Hsu and Do [15] used an L 27 orthogonal array of Taguchi method to determine the optimum conditions leading to minimum porosity in aluminium alloy die castings.…”

Section: Cutting Forces and Surface Roughness In Face-milling Of Skd6mentioning

confidence: 99%

Cutting Forces and Surface Roughness in Face-Milling of SKD61 Hard Steel

Hoang¹,

Nguyen²,

Tran³

et al. 2019

SV-JME

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This experimental study investigated the effects of milling conditions on cutting forces and finished surface roughness. The face-milling processes were performed using heat-treated SKD61 steel at a hardness of 46 HRC. With three controllable factors/levels (cutting speed, axial depth of cut, and feed rate), the most suitable orthogonal array L 27 was performed with four performance measurements that are amplitudes of cutting forces in three directions (feed, normal, and axial) and surface roughness. With ANOVA analysis, the effect of cutting conditions on the amplitudes of cutting forces and surface roughness were analysed and modelled. The most suitable regression of the cutting force's amplitudes and surface roughness was a quadratic regression with the confidence level is more than 93.74 %, and they were successfully verified via experimental results with very promising results. The relationship between cutting force and surface roughness was also investigated. Furthermore, using the Taguchi and ANOVA methods, the optimization process of surface roughness was performed with very close results (different of surface roughness about 4.58 %). The approach method of the present study can be applied in industrial machining to improve the surface quality in finish face-milling the SKD61 hard steel.

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Section: Cutting Forces and Surface Roughness In Face-milling Of Skd6mentioning

confidence: 99%

Cutting Forces and Surface Roughness in Face-Milling of SKD61 Hard Steel

Hoang¹,

Nguyen²,

Tran³

et al. 2019

SV-JME

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“…The significance of the model formulated was verified with the help of Analysis of variance (ANOVA) technique as well as response surface model fitting [16,17]. ANOVA for final Ra and MRR are given in Table 4 and 5 respectively.…”

Section: Design Of Experiments and Observationsmentioning

confidence: 99%

Multi-Objective Optimization of Magneto Rheological Abrasive Flow Nano Finishing Process on AISI Stainless Steel 316L

Kathiresan

Mohan

2020

JNanoR

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In this experimental work, Magneto rheological abrasive flow nano finishing processes were conducted on AISI Stainless steel 316L work pieces that are widely used in medical implants. The focus of the present study is to assess the effect of input variables namely the volume percentage of iron (Fe) particles, silicon carbide (SiC) abrasive particles in the Magneto rheological abrasive fluid and number of cycles on the final surface roughness at nano level as well as the material removal rate. The volume % of Fe particles were taken as 20, 25 and 30 and the volume % of SiC particles were taken as 10, 15 and 20. The different number of cycles considered for the study is 100,200 and 300. There are 20 different set of experiments with different combinations of input variables mentioned have been carried out based on the experimental design derived through central composite design technique. The minimum surface roughness observed is 23.34 nanometer (nm) from the initial surface roughness of 1.92 micro meter (µm). Towards optimizing the input process variables, a multi objective optimization was carried out by using response surface methodology.

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“…From the evaluated results they have concluded that Al6061 aluminum series shows good drilling performance when compared with the other series. 15 From the literature survey, it was concluded that there was a lack of study on influence of hot extrusion process on the mechanical and machinability of the composites. In this experimental work, various weight proportions of B 4 C ceramic particles were added into the Al6061 alloy matrix.…”

Section: Introductionmentioning

confidence: 99%

“…From the evaluated results they have concluded that Al6061 aluminum series shows good drilling performance when compared with the other series. 15…”

Section: Introductionmentioning

confidence: 99%

Performance analysis on mechanical and machinability attributes of Al6061-B₄C-T6 composites processed via hot extrusion

Tinga,

Karakoç,

Yağmur

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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In this study, composite materials with Al6061 alloy matrix and B4C particles reinforcement were produced by hot extrusion process. Fabricated composites were examined for the mechanical and machinability attributes. Al6061 alloy powders (<100 µm) and B4C particles (<10 µm) were mixed with the different weight fraction of B4C (3%, 6%, and 9% by weight) of and then cold pressed under 200 MPa pressure. The cold pressed powder metal block was extruded hot after preheating at 550°C for 1 h. Further, the composites were subjected to T6 aging heat treatment after hot extrusion. Microstructure, density, hardness, tensile strength, and wear properties were examined. The effects of cutting speed and cutting force on the machinability were also investigated. In addition, surface roughness and chips formation were examined. High density (99.6%) values were achieved with the extrusion process. With increasing B4C particles ratio, the hardness and tensile values were increased which was substantiated by the fracture morphology of the tensile specimens. It has been observed that tool smearing was high in the machining of the low-reinforced (3% B4C) composite. The highest cutting force was measured as 236 N at a feed rate of 0.27 mm/rev and a cutting speed of 250 m/min. It has also been observed that the average surface roughness decreased with increasing cutting speed and it increased with increasing feed rate.

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A study on machinability evaluation of Al-Gr-B<SUB align="right">4C MMC using response surface methodology-based desirability analysis and artificial neural network technique

Cited by 11 publications

References 12 publications

Cutting Forces and Surface Roughness in Face-Milling of SKD61 Hard Steel

Cutting Forces and Surface Roughness in Face-Milling of SKD61 Hard Steel

Multi-Objective Optimization of Magneto Rheological Abrasive Flow Nano Finishing Process on AISI Stainless Steel 316L

Performance analysis on mechanical and machinability attributes of Al6061-B₄C-T6 composites processed via hot extrusion

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A study on machinability evaluation of Al-Gr-B<SUB align="right">4C MMC using response surface methodology-based desirability analysis and artificial neural network technique

Cited by 11 publications

References 12 publications

Cutting Forces and Surface Roughness in Face-Milling of SKD61 Hard Steel

Cutting Forces and Surface Roughness in Face-Milling of SKD61 Hard Steel

Multi-Objective Optimization of Magneto Rheological Abrasive Flow Nano Finishing Process on AISI Stainless Steel 316L

Performance analysis on mechanical and machinability attributes of Al6061-B4C-T6 composites processed via hot extrusion

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Performance analysis on mechanical and machinability attributes of Al6061-B₄C-T6 composites processed via hot extrusion