Hybrid Reinforced Magnesium Matrix Composites (Mg/Sic/GNPs): Drilling Investigation

Abdulgadir, Mustafa M.; Demir, Bilge; Turan, Muhammet Emre

doi:10.3390/met8040215

Cited by 19 publications

(10 citation statements)

References 19 publications

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“…They found that weight fraction, and GNPs average size affect the output responses. Abdulgadir et al [ 25 ] reported an experimental study on the drilling of the Mg-nanocomposite reinforced by 10 wt.% SiC and 0.25 wt.% GNPs. They found that the presence of the GNPs in Mg-nanocomposite reduces the friction between the cutting tool and nanocomposite due to the lubricant effect of graphene resulting in decreasing cutting force.…”

Section: Introductionmentioning

confidence: 99%

Milling of Graphene Reinforced Ti6Al4V Nanocomposites: An Artificial Intelligence Based Industry 4.0 Approach

et al. 2020

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The studies about the effect of the graphene reinforcement ratio and machining parameters to improve the machining performance of Ti6Al4V alloy are still rare and incomplete to meet the Industry 4.0 manufacturing criteria. In this study, a hybrid adaptive neuro-fuzzy inference system (ANFIS) with a multi-objective particle swarm optimization method is developed to obtain the optimal combination of milling parameters and reinforcement ratio that lead to minimize the feed force, depth force, and surface roughness. For achieving this, Ti6Al4V matrix nanocomposites reinforced with 0 wt.%, 0.6 wt.%, and 1.2 wt.% graphene nanoplatelets (GNPs) are produced. Afterward, a full factorial approach was used to design experiments to investigate the effect of cutting speed, feed rate, and graphene nanoplatelets ratio on machining behaviour. After that, artificial intelligence based on ANFIS is used to develop prediction models as the fitness function of the multi-objective particle swarm optimization method. The experimental results showed that the developed models can obtain an accurate estimation of depth force, feed force, and surface roughness with a mean absolute percentage error of 3.87%, 8.56%, and 2.21%, respectively, as compared with experimentally measured outputs. In addition, the developed artificial intelligence models showed 361.24%, 35.05%, and 276.47% less errors for depth force, feed force, and surface roughness, respectively, as compared with the traditional mathematical models. The multi-objective optimization results from the new approach indicated that a cutting speed of 62 m/min, feed rate of 139 mm/min, and GNPs reinforcement ratio of 1.145 wt.% lead to the improved machining characteristics of GNPs reinforced Ti6Al4V matrix nanocomposites. Henceforth, the hybrid method as a novel artificial intelligent method can be used for optimizing the machining processes with complex relationships between the output responses.

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Section: Introductionmentioning

confidence: 99%

Milling of Graphene Reinforced Ti6Al4V Nanocomposites: An Artificial Intelligence Based Industry 4.0 Approach

et al. 2020

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“…This environmentally friendly procedure can be contrasted evaluating the main variables of drilling under specific cutting conditions. Variables such as thrust forces should be low to improve process stability, at least in drilling operations; the literature shows that a homogeneous variation of thrust forces does not exist with respect to cutting conditions, at least in different types of composites such as glass fiber reinforced PEEK [16], fibre metal laminates [17], magnesium matrix based silicon carbide and graphene nanoplatelets (Mg/SiC/GNPs), hybrid magnesium matrix composite [18] or wood-based composite of medium density fiberboard [19]. Nevertheless, the energy consumed during the process could be a key factor to stablish the most sustainable procedure, and also the material removed rate (MRR) in order to evaluate the process efficiency.…”

Section: Introductionmentioning

confidence: 99%

Study of Drilling Process by Cooling Compressed Air in Reinforced Polyether-Ether-Ketone

2020

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This study is focused on the application of a cooling compressed air system in drilling processes; this environmentally friendly technique allows removing material at very low temperatures, approximately up to −22 °C in the cutting area. The main goals are to find the most improve cutting conditions with less energy consumption, for the drilling of reinforced polyether-ether-ketone with glass fiber at 30% (PEEK-GF30) with cooling compressed air by a Ranque-Hilsch vortex tube, and to find a balance between environmental conditions and adequate process performance. Drilling tests were carried out on plates of PEEK-GF30 to analyze the influence of cutting parameters and environmental temperature (–22, 0 and 22 °C) on variables such as thrust forces, energy and material removed rate by the use of statistical methods; analysis of variance, analysis of means, response surface, and desirability function were employed to identify the optimum region that provides the most improved values of the aforementioned variables. Drill bit diameter was also analyzed to determine the quality of drilled holes. During the drilling processes, force signals were detected by a piezoelectric dynamometer connected to multichannel amplifier and a pyrometer was used to control the temperature. The diameters of the drilled holes were measured by a coordinate measuring machine. Cooling compressed air can be considered an adequate technique to improve the results from an environmental and efficient perspective; in particular, the maximum desirability function was found at a spindle speed of 7000 rpm, a feedrate of 1 mm/rev and a temperature close to −22 °C.

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“…Chip morphology is reported to be more dominant on cutting speed compared to tool rake angle, volume fraction, and the average size of silicon carbide [ 18 ]. Mustafa et al [ 19 ] conducted drilling studies on graphene nanoplatelet, and silicon carbide reinforced in a hybrid magnesium matrix composite, which was manufactured through the powder metallurgy method. The results of their study showed that lower thrust forces could be achieved using the physical vapor deposition (PVD) coated tool and drilling at a cutting speed of 50 m/min and a feed rate of 0.10 mm/rev.…”

Section: Introductionmentioning

confidence: 99%

“…The results of their study showed that lower thrust forces could be achieved using the physical vapor deposition (PVD) coated tool and drilling at a cutting speed of 50 m/min and a feed rate of 0.10 mm/rev. Their study shows that lower feed rates are preferred while drilling hybrid magnesium metal matrix composites primarily due to the achievement of good surface finish and lower thrust forces [ 19 ]. Dry microdrilling tests were carried out on pure magnesium reinforced with the varying volume fraction of nanoparticles of SiO 2 [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Cryogenic Drilling of AZ31 Magnesium Syntactic Foams

et al. 2020

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Machined surface quality and integrity affect the corrosion performance of AZ31 magnesium composites. These novel materials are preferred for temporary orthopedic and vascular implants. In this paper, the drilling performance of AZ31-magnesium reinforced with hollow alumina microsphere syntactic foam under LN2 cryogenic, dry, and Almag® Oil is presented. Cutting tests were conducted using TiAlN physical vapor deposition (PVD) coated multilayer carbide and K10 uncoated carbide twist drills. AZ31 magnesium matrices were reinforced with hollow alumina ceramic microspheres with varying volume fractions (5%, 10%, 15%) and average bubble sizes. Experimental results showed that the drilling thrust forces increased by 250% with increasing feed rate (0.05 to 0.6 mm/tooth) and 46% with the increasing volume fraction of alumina microspheres (5% to 15%). Cryogenic machining generated 45% higher thrust forces compared to dry and wet machining. The higher the volume fraction and the finer the average size of hollow microspheres, the higher were the thrust forces. Cryogenic machining (0.42 µm) produced a 75% improvement in surface roughness (Ra) values compared to wet machining (1.84 µm) with minimal subsurface machining-induced defects. Surface quality deteriorated by 129% with an increasing volume fraction of alumina microspheres (0.61 µm to 1.4 µm). Burr height reduction of 53% was achieved with cryogenic machining (60 µm) compared to dry machining (130 µm). Overall, compared to dry and wet machining methods, cryogenic drilling can be employed for the machining of AZ31 magnesium syntactic foams to achieve good surface quality and integrity.

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Hybrid Reinforced Magnesium Matrix Composites (Mg/Sic/GNPs): Drilling Investigation

Cited by 19 publications

References 19 publications

Milling of Graphene Reinforced Ti6Al4V Nanocomposites: An Artificial Intelligence Based Industry 4.0 Approach

Milling of Graphene Reinforced Ti6Al4V Nanocomposites: An Artificial Intelligence Based Industry 4.0 Approach

Study of Drilling Process by Cooling Compressed Air in Reinforced Polyether-Ether-Ketone

Cryogenic Drilling of AZ31 Magnesium Syntactic Foams

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