Modeling and Optimization of Turning Parameters during Machining of AA6061 composite using RSM Box-Behnken Design

Kumar, Vidyanand; Kharub, Manjeet; Sinha, Animesh

doi:10.1088/1757-899x/1057/1/012058

Cited by 12 publications

(5 citation statements)

References 12 publications

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“…Singh et al [13] focused on the reducing the usage of cutting fluids, an effort has been made to present an overview of the various cutting fluid types, cooling techniques, and important alternatives, such as dry machining, cryogenic cooling, minimal amount lubrication, and hybrid cooling. Kumar et al [14] investigated the RSM Box-Behnken Design, modelling and optimisation of turning parameters during machining of AA6061 composite. They also found that feed had the most influence on surface roughness, whereas depth of cut has a big impact on material removal.…”

Section: Introductionmentioning

confidence: 99%

Optimizing turning parameters for improved surface quality and productivity of Al-MMC under dry, wet, and MQL conditions

Khandey,

Chandra,

Arya

et al. 2023

Eng. Res. Express

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The machining of Aluminum-based Metal Matrix Composites (Al-MMCs) is challenging due to their inhomogeneity, anisotropic nature, and dynamic cutting forces. In this paper, the effect of machining parameters, including cutting speed, feed rate, and depth of cut, on surface quality (Ra) and main (Normal) cutting forces (Fc) during turning of Al-MMCs under different cutting conditions (DRY, WET, and MQL) was investigated. Statistical analysis tools were used to analyze the experimental results, and ANOVA and RSM techniques were used to model the relationships between machining parameters and responses. The results showed that feed rate significantly affected both Ra and Fc for all machining conditions. The DRY machining mode was optimal for surface finish, and the MQL mode was effective in reducing cutting forces due to its cooling and lubrication properties. A feed rate of 0.03 mm rev−1 was found to be the most favourable for all cutting environments as it resulted in lower Ra and Fc values. Turning in the WET condition also produced lower Ra due to the effective flushing of chips and cleaning of the cutting zone. In contrast, turning in the MQL condition reduced cutting forces by 17% and 50% as compared with dry and Wet conditions respectively under optimal conditions. Similarly, surface roughness improves under dry conditions by 33% and 3% compared to Wet and MQL conditions.

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Section: Introductionmentioning

confidence: 99%

Optimizing turning parameters for improved surface quality and productivity of Al-MMC under dry, wet, and MQL conditions

Khandey,

Chandra,

Arya

et al. 2023

Eng. Res. Express

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“…Response surface methodology is used to reduce MRR and surface smoothness. The author found that the multiple responses desirability strategy improved the result [ 11 ]. Taguchi’s L27 orthogonal array technique investigates Al-15%–SiCp metal matrix composite.…”

Section: Introductionmentioning

confidence: 99%

Temperature Optimization by Using Response Surface Methodology and Desirability Analysis of Aluminium 6061

2022

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Because aluminium is a lightweight and low-density material, its alloys, such as Al 6061 alloy, are extensively used in numerous automobile, defense, and aviation components. This study aims to develop a predictive model to investigate the impact of tool nose radius on the CNC turning process of Al 6061 alloy and better recognize the implications of operating machining considering cutting speed, rate of feed, cutting depth, and tool nose radius. The trials were carried out by using the response surface methodology (RSM), with an Al2O3 coated carbide tool as the cutter and an Al 6061 workpiece as the material. A mathematical model of the second-order was created. The analysis of variance (ANOVA) approach was used to analyze the performance characteristics of the turning operation. Individual desirability values from the desirability function analysis for the multi-responses are used to construct a composite desirability value. The ideal parameter levels were determined by using the composite desirability value, and the significant impact of parameters was assessed by using the analysis of variance. The minimum temperature attained at the machining parameters are 98.0 m/min cutting speed, 0.26 mm/rev rate of feed, 0.893 mm cutting depth, and 0.84 mm tool nose radius. The best total desirability value is 23.615 °C, indicating that the experimental results are close to the predicted values.

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“…Furthermore, the author in [ 11 ] optimized surface quality using the RSM and DFA of aluminum alloys. The RSM and DFA were also used to maximize aluminum alloy energy utilization, surface waviness, and material removal rate (MRR) by taking the cutting depth, the rate of feed, and the cutting speed into account [ 1 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Minimization of Surface Roughness and Temperature during Turning of Aluminum 6061 Using Response Surface Methodology and Desirability Function Analysis

2022

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Aluminum alloy is the second most abundant metal on Earth, known for its wide range of utilization in commercial goods due to its heat capacity and tensile strength. This study examines the effect of nose radius on the turning process. Further, it explores the implications of cutting parameters such as the cutting speed, the rate of feed, the cutting depth, and the nose radius of the tool. The trials were carried out with an Al 6061 workpiece and an Al2O3-coated carbide tool as the cutter, utilizing the response surface methodology. A mathematical model was developed to investigate the performance characteristics of the turning operation using the analysis of variance method. The multi-response desirability function analysis combines individual desirability values to create a composite desirability value. The ideal parameter levels were determined using the composite desirability value, and the significant influence of parameters was assessed. The obtained optimum surface roughness and temperature parameters are at a cutting speed of 116.37 m/min, a rate of feed of 0.408 mm/rev, a cutting depth of 0.538 mm, and a tool nose radius of 0.20 mm. The related ideal surface roughness and temperature values are 0.374 µm and 27.439 °C. The optimal overall desirability value is 0.829, close to the target response.

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Modeling and Optimization of Turning Parameters during Machining of AA6061 composite using RSM Box-Behnken Design

Cited by 12 publications

References 12 publications

Optimizing turning parameters for improved surface quality and productivity of Al-MMC under dry, wet, and MQL conditions

Optimizing turning parameters for improved surface quality and productivity of Al-MMC under dry, wet, and MQL conditions

Temperature Optimization by Using Response Surface Methodology and Desirability Analysis of Aluminium 6061

Minimization of Surface Roughness and Temperature during Turning of Aluminum 6061 Using Response Surface Methodology and Desirability Function Analysis

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