“…14 For calculation of MRR, the initial weight and final weight are obtained through digital weighing balance, as displayed in Figure 3(b). The MRR was computed by applying the expression 15 :where:wi,wf = Initial and final weight of the machined sampleρ = Density of the prepared sample (1.31 g/cm3)tm = Machining timeFigure 3.(a) Digital balancing meter and (b) cutting force measurement setup.…”
The machining behavior of polymers is substantially different from metal and their alloys due to non-homogeneity and anisotropy. This article describes a hybrid optimization method during machining (milling) of epoxy nanocomposites reinforced by graphene oxide/carbon fiber (G/CF). The milling experimentation was staged according to the L9 orthogonal array of the Taguchi theory. The control of process constraints, namely, cutting speed (Vc), feed (F), depth of cut (D), and G weight % (G) have been appraised to acquired the desired machining response such as material removal rate (MRR), cutting force ( F c), and surface roughness ( R a). Grey-coupled principal component analysis (grey-PCA) effectively tackled the response priority weight during aggregation of conflicting responses. The optimal condition secured by the grey-PCA module are found as Vc = 25.12 m/min, F = 240 mm/min, D = 0.5 mm, and G = 1 %. The supplement of graphene enhances the machining characteristics of the nanocomposites, which in turn, minimizes the damages that occur during the milling process. Scanning electron microscopy (SEM) analysis was conducted for microstructure investigation of the machined component. The findings of confirmatory experiments show good agreement with the actual ones. The preferred solution values of grey-PCA are observed as 1.027, which confirms the proposed technique’s higher practicability.
“…14 For calculation of MRR, the initial weight and final weight are obtained through digital weighing balance, as displayed in Figure 3(b). The MRR was computed by applying the expression 15 :where:wi,wf = Initial and final weight of the machined sampleρ = Density of the prepared sample (1.31 g/cm3)tm = Machining timeFigure 3.(a) Digital balancing meter and (b) cutting force measurement setup.…”
The machining behavior of polymers is substantially different from metal and their alloys due to non-homogeneity and anisotropy. This article describes a hybrid optimization method during machining (milling) of epoxy nanocomposites reinforced by graphene oxide/carbon fiber (G/CF). The milling experimentation was staged according to the L9 orthogonal array of the Taguchi theory. The control of process constraints, namely, cutting speed (Vc), feed (F), depth of cut (D), and G weight % (G) have been appraised to acquired the desired machining response such as material removal rate (MRR), cutting force ( F c), and surface roughness ( R a). Grey-coupled principal component analysis (grey-PCA) effectively tackled the response priority weight during aggregation of conflicting responses. The optimal condition secured by the grey-PCA module are found as Vc = 25.12 m/min, F = 240 mm/min, D = 0.5 mm, and G = 1 %. The supplement of graphene enhances the machining characteristics of the nanocomposites, which in turn, minimizes the damages that occur during the milling process. Scanning electron microscopy (SEM) analysis was conducted for microstructure investigation of the machined component. The findings of confirmatory experiments show good agreement with the actual ones. The preferred solution values of grey-PCA are observed as 1.027, which confirms the proposed technique’s higher practicability.
“…AM application reduces the surplus expenditures in product development and can generate parts with high strength to weight ratio. AM is widely used in industrial applications including aerospace, automobile, construction, prototyping, and casting [10] . Ability to tackle variability, volume and delivery time constraints in the best possible manner, especially on-demand production scenario, makes this technology the best candidate to tackle the challenges emerged from the current scenario.…”
“…Application areas of EDM include electronic industries, semi-conductor manufacturing industries, and mold and die industries [ 8 , 9 ]. In the mold and die industries, 25–40% of the total cost is incurred in the EDM of the workpiece, and 50% of EDM cost is spent in the design and production of the electrode, respectively [ 10 ]. The complexity of the cavity required to be machined further increases the cost of electrode production.…”
Section: Introductionmentioning
confidence: 99%
“…The complexity of the cavity required to be machined further increases the cost of electrode production. Additive manufacturing (AM) comprises of processes that mainly use plastic-based polymers for the manufacturing of complex products, and recently, it has opened a new gateway for use of these products in novel applications such as mold and die making, electronics [ 10 ], medical uses [ 11 , 12 , 13 ], jewelry [ 14 ], and aerospace and automotive industries [ 15 ]. AM technology can be used to produce plastic-based low-cost complex-shaped EDM electrodes.…”
Section: Introductionmentioning
confidence: 99%
“…They are light in weight and possess characteristics such as water-resistance, corrosion resistance, and plasticity, etc. [ 10 ]. They are used in various applications ranging from household items such as buckets and bottles to engineering applications in automobiles, electronics, and textiles.…”
In the present study, cylindrical ABS P400 polymer parts (diameter 6.5 mm) to be used as die-sinking EDM (electric discharge machining) novel electrodes were fabricated using a fused deposition modeling (FDM) process. To meet the conductivity requirement in EDM, ABS parts were metallized using an innovative method that comprised putting aluminum–charcoal (Al–C) on them followed by their copper electroplating. Real-time EDM of the mild steel workpiece was performed using novel electrodes, and machining performance of the electrodes, measured in terms of dimensional accuracy, i.e., change in diameter (ΔD) and change in depth (ΔH) of the cavity, under varying levels of three EDM factors, i.e., current (I), pulse on time (Ton), and pulse off time (Toff), was investigated. Machining results were analyzed using analysis of variance (ANOVA), perturbation graphs, and 3D surface plots. The optimal setting of the EDM parameters for minimizing ΔD and ΔH was determined using the desirability function approach. The suitability of the novel electrodes for EDM was ascertained by comparing their machining results with those of solid copper (SC) electrodes and electrodes fabricated by FDM and metallized using the electro-deposition method (FDM-EM), already reported in the literature, under similar machining conditions. From the results, it was found that ΔD and ΔH were less when EDM was performed using novel electrodes.
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