Study of Cutting force and Surface Roughness in machining of Al alloy Hybrid Composite and Optimized using Response Surface Methodology

Venkatesan, K.; Ramanujam, R.; Joel, J.; Jeyapandiarajan, P.; Vignesh, M.; Tolia, Darsh Jiten; Krishna, Raji

doi:10.1016/j.proeng.2014.12.297

Cited by 52 publications

(22 citation statements)

References 22 publications

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“…Since TiAlN/TiCN coated tool performs better in coating point of view, the ANOVA values of this particular coated tool could be considered for tool wear evaluation. Hence from this result, feed rate is found to be the more influential factor in deciding tool wear criterion [28,29]. The lower tool wear obtained during machining of custom450 alloy was 136.6 µm for TiAlN/TiCN coated tool.…”

Section: Tool Wear Analysismentioning

confidence: 74%

Machinability Investigations on Aerospace Custom 450 Alloy Using TiAlN/TiCN, TiCN/TiAlN Coated and Uncoated Carbide Tools

Kumar¹,

Margabandu²,

Radhakrishnan³

et al. 2021

JESA

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In this present research, the machinability studies of TiAlN/TiCN, TiCN/TiAlN coated and uncoated inserts were investigated on machining custom 450 alloy. The machining input parameters such as feed rate (f), cutting speed (V) and depth of cut (d) are set using orthogonal array. The machining output parameters such as surface roughness, tool wear and cutting forces were studied for its parametric contribution and it was analyzed using Analysis of Variance (ANOVA). Further, the tool wear obtained was studied using scanning electron microscopic images and energy dispersive spectroscopy analysis was conducted to check the addition of work material elements to the coated tool surface. The results show that, the feed rate is the most contributing factor in deciding resultant forces, surface roughness and tool wear respectively. TiAlN/TiCN coated carbide tool has obtained improved machinability, when compared to TiCN/TiAlN coated carbide and uncoated carbide inserts. To obtain one optimal level for all three responses of three types of tools, multi criteria decision making approach, named utility concept approach is selected. Based on the MCDM analysis, it is found that trial number 4 gives better experimental output of improved surface integrity, lower resultant force and less tool wear for all types of tools.

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Section: Tool Wear Analysismentioning

confidence: 74%

Machinability Investigations on Aerospace Custom 450 Alloy Using TiAlN/TiCN, TiCN/TiAlN Coated and Uncoated Carbide Tools

Kumar¹,

Margabandu²,

Radhakrishnan³

et al. 2021

JESA

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show abstract

“…If the expected response E(y) is = f(x 1 , x 2 , x 3 , ., x k ) = h, then the response surface is the surface represented by h. 21 To find an approximation to the relation between y and x's, a low-order polynomial is usually used. In the context of surface roughness optimization, a second-order model in the form of equation 2is usually applied [22][23][24]…”

Section: Methodsmentioning

confidence: 99%

Effect of equal-channel angular pressing on the surface roughness of commercial purity aluminum during turning operation

Abbas

Ragab

El‐Danaf

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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Aluminum has been increasingly used in automotive and aerospace applications due to its beneficial specific strength and chemical properties. Due to its extensive use, machining of aluminum parts has become specifically significant in recent years. One important aspect of machining is the surface quality represented by the surface roughness values. In this article, the effect of equal-channel angular pressing on the surface roughness (R a , R q , R t and R z) of commercial purity aluminum machined by turning was studied. Five starting material conditions, defined as the annealed and equal-channel angular pressing processed up to four passes, were investigated. The independent variables were the cutting speed, depth of cut and feed rate. The fourth parameter (number of equal-channel angular pressing passes) was considered as categorical factor and, hence, was not included in the mathematical model. A full central composite circumscribed design matrix was built to allow the optimization of surface roughness using response surface methodology. The significance of process parameters and their interactions in estimating surface roughness was investigated using analysis of variance. The two parameters, with significant effect on surface roughness, were found to be the feed rate and number of equalchannel angular pressing passes. Minimum depth of cut (0.15 mm) and minimum feed rate (0.05 mm/rev) are needed to achieve minimum surface roughness parameters: R a (0.06 mm), R q (0.057 mm) and R z (0.71 mm) and R t (1.2 mm). The cutting speed, for these optimum roughness values, ranged from 207.5 m/min for R a to 193 m/min for R z. The optimum roughness values were generally achieved with the higher strength materials. Optimum values for R a , R q and R z happened at the four equal-channel angular pressing passes-processed material, while the optimum value of R t happened at the three equal-channel angular pressing passes-processed material.

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“…Venkatesan et al [13], have presented the results of experimental investigation on machinability properties of Silicon Carbide and Boron Carbide reinforced Aluminum 356 hybrid metal matrix composite. Face centered central composite experimental design coupled with RSM was used for modeling.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology

Patole

Kulkarni

2018

Manufacturing Rev.

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This paper presents an investigation into the minimum quantity lubrication mode with nano fluid during turning of alloy steel AISI 4340 work piece material with the objective of experimental model in order to predict surface roughness and cutting force and analyze effect of process parameters on machinability. Full factorial design matrix was used for experimental plan. According to design of experiment surface roughness and cutting force were measured. The relationship between the response variables and the process parameters is determined through the response surface methodology, using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed. The values predicted from the model and experimental values are very close to each other.

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Study of Cutting force and Surface Roughness in machining of Al alloy Hybrid Composite and Optimized using Response Surface Methodology

Cited by 52 publications

References 22 publications

Machinability Investigations on Aerospace Custom 450 Alloy Using TiAlN/TiCN, TiCN/TiAlN Coated and Uncoated Carbide Tools

Machinability Investigations on Aerospace Custom 450 Alloy Using TiAlN/TiCN, TiCN/TiAlN Coated and Uncoated Carbide Tools

Effect of equal-channel angular pressing on the surface roughness of commercial purity aluminum during turning operation

Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology

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