Optimization of material removal rate in CNC turning of AA2024 via Taguchi technique

Kumar, M. Vinoth; Meignanamoorthy, M.; Sakthivelu, S.; Kumar, Sudhir; Chanakyan, C.; Alagarsamy, S.V.

doi:10.1016/j.matpr.2020.02.045

Cited by 9 publications

(2 citation statements)

References 6 publications

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“…Vinoth Kumar et al reported that speed is the utmost prompting parameter for higher material removal trailed by speed and cutting depth. The optimum values of speed is 55 rpm, feed is 50 mm/min [11]. Sunil and Deepak established that the MRR is greatly inclined by depth of cut than the feed and speed.…”

Section: Introductionmentioning

confidence: 99%

Material Removal Rate Study on Turning of Al Alloy

Yau¹,

Chockalingam²

2022

Proceedings of the Multimedia University Engineering Conference (MECON 2022)

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Material removal rate (MRR) can indicate how efficiently the lathe machine is cutting the workpiece, and surface roughness can indicate the quality of the machined part. In this study, the material removal rate (MRR) and surface roughness (Ra) of the turning of aluminium alloy were investigated using turning process parameters such as depth of cut, spindle speed, and feed to find the optimum combinations of parameters. An experiment has been designed with factorial design and the use of an L27 orthogonal array. This work uses a CNC lathe machine to cut the workpieces to a constant length while varying the three parameters: spindle speed, feed, and depth of cut. Then the surface roughness was measured with the surface roughness tester and material removal rate was calculated with turning parameters. The results are used to proceed to find out which is the most influential factor among the three parameters using statistical software and full factorial analysis. The results showed that spindle speed influences both MRR and Ra the most. The best Ra will be produced because the experimental value of 1.932 μm is within the 95% prediction interval. Due to experiment error for MRR, we could not accept the optimum parameters of 1000 rpm spindle speed, 100 mm/min feed and 0.6 mm depth of cut as the experiment MRR value of 2789.76 cm 3 /min does not fall within the 95% confidence interval (CI) or 95% prediction interval (PI).

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Section: Introductionmentioning

confidence: 99%

Material Removal Rate Study on Turning of Al Alloy

Yau¹,

Chockalingam²

2022

Proceedings of the Multimedia University Engineering Conference (MECON 2022)

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“…Other important cutting parameters are depth of cut, workpiece material, material hardness, cutting tool geometry, cutting tool tip angle, cutting tool coating, workpiece length, cooling type etc. [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Experimental and Statistical (Respond Surface Method and Grey Relational Analysis) of Surface Roughness, Vibration and Enerrgy consumption Values of Titanium Alloy During Machining

Akkuş

2021

Scientia Iranica

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This study aims to explain the interaction between the results measured in the turning operation. For this purpose, Ti 6Al-4V alloy workpiece was machined on CNC lathe. Surface roughness (Ra), vibration and energy consumption values were determined by turning. Experimental results were analyzed statistically.Response surface method (RSM) and grey relational analysis were used statistical analysis. In RSM analysis, regression equations, ANOVA, contour graphs, pertubation graphs, real and prediction graphs, % contribution graphs, most significant factor, optimum parameters, it is determined that the effective parameter in surface roughness, vibration and energy consumption is feed rate. Grey relational analysis steps and results are examined.

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