Investigating the Material Removal Rate Parameters in ECM for Al 5086 Alloy‐Reinforced Silicon Carbide/Flyash Hybrid Composites by Using Minitab‐18

Gugulothu, Bhiksha; Kumar, P. S. Satheesh; Srinivas, B.; Ramakrishna, A.; Vijayakumar, S.

doi:10.1155/2021/2079811

Cited by 33 publications

(15 citation statements)

References 18 publications

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“…In [14], authors introduced the aluminium alloy (AA6061) matrix composite. The stir casting technique is used to create the hybrid aluminum-based MMNC samples as the process of carrying out the reinforcing element progresses.…”

Section: Related Workmentioning

confidence: 99%

Experimental Investigation on Metal Matrix Nanocomposite: Aluminium Alloy 6061 and 7075 with SiC and Fly Ash

Kotteda¹,

Eshwar²,

Balakrishna

et al. 2022

Journal of Nanomaterials

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Aluminium metal matrix nanocomposites (AMMNCs) have been recognized as a promising material with excellent structural and functional characteristics that can be suggestively personalized to satisfy industrial demands as well as design requirements for a wide range of applications, including those in defense, marine, automobiles, and aerospace. Particularly, these industries are using an increasing number of components manufactured by AMMNCs. When compared to monolithic materials, components manufactured from aluminium-based composites have better qualities such as tribological behaviors, hardness, stiffness, strength, and higher strength to weight ratio. Therefore, this article addresses the experimental investigation on aluminium-based metal matrix nanocomposites (MMNCs) with silicon carbide (SiC) and fly ash (FA) as a reinforcement material with distinct ratios. Here aluminium alloy 6061 and 7075, hereafter referred as AA6061 and AA7075, are considered as base material. The final workpieces obtained using the process of stir casting and machining are tested to compute the output response parameters like yield strength (YS), wear rate (WR), hardness, impact strength (IS), and ultimate tensile strength (UTS). In addition, the scanning electron microscopy (SEM) images also studied for examining the distribution of reinforcement material particles in base metal.

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Section: Related Workmentioning

confidence: 99%

Experimental Investigation on Metal Matrix Nanocomposite: Aluminium Alloy 6061 and 7075 with SiC and Fly Ash

Kotteda¹,

Eshwar²,

Balakrishna

et al. 2022

Journal of Nanomaterials

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“…Tis is due to the increase in electrode feed, which makes good contact with composite to remove material. Whenever parameters of electrolyte concentration, voltage, and MRR values are increasing, it is due to extra energy for oxidation that provides more anodic dissolution, more heat, and a good chemical reaction between the electrolyte and Al composite [22].…”

Section: Resultsmentioning

confidence: 99%

Experimental Investigation of Material Removal Rate Parameters in ECM for Aluminum Hybrid Matrix Composites Using the RSM Technique

Sri

Anusha

Krishnajirao³

et al. 2023

Advances in Materials Science and Engineering

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In the present work, the preparation of AA-6082/ZrSiO4/TiC hybrid composite is studied along with an analysis of the effects of electrochemical machining parameters such as feed rate of electrode (FE), voltage (VO), electrolyte concentration (EL), and electrolyte discharge (ED) rate on the output responses of the material removal rate (MRR) and surface roughness (SR) for Al hybrid composites. The experiments are carried out based on the Taguchi L16 orthogonal array and the important process parameters are found for MRR and SR. Each parameter contains four different levels that are FE (0.10, 0.15, 0.20, and 0.25 mm/min), VO (10, 15, 20, and 25 V), EL (15, 20, 25, and 30 g/lit), and ED (1.5, 2, 2.5, and 3 lit/min).The optimization software, namely, Minitab-17 version helps to find the contribution of each parameter on MRR and SR. The ANOVA result reveals that the feed rate of electrode is the highest contributing parameter, trailed by the electrolyte discharge rate and other process parameters for MRR and SR. A linear model of regression and interaction plots is also included to show the relationship between the parameters. From the observational results, the highest MRR (0.00953 mg/min) is attained by the parameter combination level of the feed rate of electrode of 0.20 mm/min, voltage of 25 V, electrolyte concentration of 20 g/lit, and electrolyte discharge rate of 1.5 g/, whereas the lowest MRR is found at FE of 0.10 mm/min, VO of 10 V EL-15 g/lit and ED of 2.5 g/litre. For SR, the maximum and minimum are recognized at FE2-VO4-EL3-ED2 (0.15 mm/min, 25 V, 25 g/lit, and 2 lit/min) and FE1-VO1-EL1-ED1 (0.10 mm/min, 10 V, 15 g/lit, and 1.5 lit/min), respectively. Finally, the increment of MRR and SR values is mostly dependent on the feed rate of the electrode.

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“…e defects on prepared specimens can be found by conducting nondestructive testing [18]. e radiography test is a kind of NDT used for analysing defects present on welding plates of SS304 [19]. e EDs test is also utilized to check microstructure and chemical composition of objects [20,21].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Wear Behaviour of AA5052 Alloy Composites by Addition Alumina with Zirconium Dioxide Using the Taguchi-Grey Relational Method

Gugulothu

Sankar

Vijayakumar³

et al. 2022

Advances in Materials Science and Engineering

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The present study deals with preparation of Al hybrid metal matrix composites by the stir casting technique. In this work, Al5052 alloy was selected as the main metal which reinforces with zirconium dioxide and aluminium oxide. The wear test has been conducted on the POD apparatus. 9 specimens are produced by varying reinforcements’ percentage for conduction of tests. The amount of ZrO2 reinforcement is fixed to 8wt%, while the concentration of Al2O3 varied from 5wt% to 10wt%. The parametric optimization of wear behaviour is done through the Taguchi method with L9 orthogonal array. Minitab statistical software helped to find SN ratio and ANOVA reading for each parameter: load (N), sliding speed (rpm), and wt% of reinforcements. From the ANOVA outcome, the load parameter is the highest influencing element that improves wear resistance of made samples around 46%, followed by weight% of reinforcement 29% and sliding speed 26% as second and third influenced parameters, respectively.

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Investigating the Material Removal Rate Parameters in ECM for Al 5086 Alloy‐Reinforced Silicon Carbide/Flyash Hybrid Composites by Using Minitab‐18

Cited by 33 publications

References 18 publications

Experimental Investigation on Metal Matrix Nanocomposite: Aluminium Alloy 6061 and 7075 with SiC and Fly Ash

Experimental Investigation on Metal Matrix Nanocomposite: Aluminium Alloy 6061 and 7075 with SiC and Fly Ash

Experimental Investigation of Material Removal Rate Parameters in ECM for Aluminum Hybrid Matrix Composites Using the RSM Technique

Analysis of Wear Behaviour of AA5052 Alloy Composites by Addition Alumina with Zirconium Dioxide Using the Taguchi-Grey Relational Method

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