Optimisation of Drilling Parameters of Metal Matrix Composites using Genetic Algorithm in the Taguchi Method

Rao, Ch. V. S. Parameswara; Rao, Yue; Marimuthu, P.; Jeyapaul, R.; Chakravarthy, Niranjan; Murugesan, Pradeep Kumar

doi:10.1088/1757-899x/1126/1/012035

Cited by 6 publications

(3 citation statements)

References 9 publications

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“…It was noticed that minimum wear rate for alumina composite could be achieved at 5 wt% reinforcement. Rao et al [18] applied GA and Taguchi methodology to optimize the drilling parameters for AlSiC MMC. Bongale et al [19] attempted to minimize wear on Al/SiCnp/E-glass fiber MMC while adopting Taguchi methodology and GA technique.…”

Section: Introductionmentioning

confidence: 99%

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Kalita

Kumar

Chakraborty

2023

Multiscale and Multidiscip. Model. Exp. and Des.

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Machining of metal matrix composites (MMCs) has now become an essential task in shaping them to their final usable forms for various industrial applications. These machining operations may range from drilling of simple through holes to cutting and shaping the composites into complex shapes.Determination of the optimal process parameters during their machining presents a combinatorial optimization problem, which may turn out to be more complex due to involvement of various material dependent parameters of the MMCs, like particle size, reinforcement percentage etc. The importance of optimization increases manifold due to conflicting settings of different process parameters for attaining the desired quality characteristics. In this paper, two nature-inspired optimization algorithms, i.e. multi-objective antlion optimization (MOALO) and multi-objective dragonfly algorithm (MODA) are applied for multi-objective optimization of various process parameters during machining of MMCs. To mitigate uncertainties in global optimality of the predicted Pareto optimal fronts arising due to stochastic nature of the metaheuristics, an ensemble approach integrating MOALO and MODA techniques is proposed here. It is demonstrated with the help of two case studies that MOALO-MODA ensemble is far superior to its individual counterparts and thus, can be employed for development of robust and reliable Pareto optimal fronts.

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Section: Introductionmentioning

confidence: 99%

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Kalita

Kumar

Chakraborty

2023

Multiscale and Multidiscip. Model. Exp. and Des.

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“…However, statistical or mathematical methods may be used to predict the Ra. Subba Rao et al applied Taguchi method for determining the appropriate parameter setting on Ra for MMC during drilling tests and they concluded that the point angle and feed have most noteworthy factors for Ra [10]. Jayaganth et al carried out the drilling experiments using various 'v', 'f' and cutting fluids as per Taguchi's orthogonal array.…”

Section: Introductionmentioning

confidence: 99%

Optimization of machining parameters in drilling of aluminium matrix composite (Al7050-12wt.% ZrO2) using Taguchi technique

Kumar¹,

Alagarsamy

Hossain³

et al. 2023

Preprint

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This study focused on optimizing the drilling variables for minimizing the surface roughness (Ra) of Al7050 alloy based composite using Taguchi technique. The stir casting route was adopted to synthesis the Al7050 matrix composite with addition of 12 wt. % ZrO2 particles as reinforcement. The different process parameters such as spindle speed (v), feed (f), and depth of cut (d) were chosen as the input parameters, while the Ra was considered as the output response. Based on the parameters selection, the drilling process was carried out on Taguchi L16 orthogonal design. The SN (signal-to-noise) ratio and ANOVA (analysis of variance) were applied to yield the optimal setting of parameters and their impact contribution on Ra for the drilled composite. The SN ratio results identified that the minimum value of Ra was achieved at 1600 rpm of spindle speed, 0.12 mm/rev of feed and 1.0 mm of depth of cut. ANOVA result observed that the most noteworthy parameter for Ra was feed (62.24%), followed by spindle speed (26.24%). The contour graphs revealed that the Ra value drastically reduced when an increase in depth of cut (d) and decrease in feed (f). The regression model has been formulated to establishing the relationship of drilling parameters on Ra.

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“…Cutting force is a key part of the machining process. It can directly affect how well the material is machined and how well it is processed [ 7 ]. So, looking at the milling force of SiCp/Al composites can help us figure out how milling works and improve the accuracy of machining.…”

Section: Introductionmentioning

confidence: 99%

Force Prediction and Material Removal Mechanism Analysis of Milling SiCp/2009Al

et al. 2022

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In recent years, medium- and low-volume fraction silicon carbide particle-reinforced aluminum matrix composites (SiCp/Al) have increasingly become a key material in the aerospace industry. Force prediction and material removal mechanism analysis of milling SiCp/Al are necessary to improve the surface integrity of products. An orthogonal experiment of SiCp/2009Al with a volume fraction of 20% was carried out, and the effect of the milling parameters on milling force was studied with the input parameters of milling speed, feed rate, and milling depth. Thereby, the empirical force model of milling SiCp/2009Al is established by fitting the experiential data based on the multiple linear regression analysis methods. Moreover, the effects of the milling parameters on the force were analyzed. Finally, the material removal mechanism of milling SiCp/Al is analyzed based on dislocation theory. The analyzed results reveal that the removal mechanism of the SiCp/Al composites includes plastic deformation of the aluminum matrix, cutting of particles, fragmentation, and deboning. Based on dislocation theory and maximum undeformed thickness theory, the effect of cutting parameters on the form of material removal was analyzed, which serves as a guide for selecting appropriate machining parameters to obtain improved machining quality of SiCp/Al composites.

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Optimisation of Drilling Parameters of Metal Matrix Composites using Genetic Algorithm in the Taguchi Method

Cited by 6 publications

References 9 publications

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Optimization of machining parameters in drilling of aluminium matrix composite (Al7050-12wt.% ZrO2) using Taguchi technique

Force Prediction and Material Removal Mechanism Analysis of Milling SiCp/2009Al

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