Analysis of tool wear and surface finish in hard turning

Tamizharasan, T.; Selvaraj, T.; Haq, A. Noorul

doi:10.1007/s00170-004-2411-1

Cited by 82 publications

(38 citation statements)

References 18 publications

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“…Researchers have used the Taguchi parameter design method for the purpose of optimizing turning parameters for minimizing surface roughness and to obtain dimensional accuracy and long life of the cutting tool [13][14][15][16][17] and some success has been reached [18][19][20][21][22]. Across these studies, it was Tamizharasan et al [23] who presented a rather skeptical finding that the depth of cut and the feed rate have negligible and little respective effect on the surface finish, which presents an opportunity for a reassessment of this finding.…”

Section: Brief Review Of the Machining Studies Using Taguchi Methodsmentioning

confidence: 99%

Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)

Rashid

Goel

Davim

et al. 2015

Int J Adv Manuf Technol

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Abstract:Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was developed using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a welldesigned full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method. Furthermore, Signal-to-noise (S/N) ratio analysis, Analysis of variance (ANOVA), and Multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02mm/rev), it could alone be most significant (99.16%) parameter in influencing the machined surface roughness (Ra). This has, however also been shown that low feed rate results in high tool wear, so the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations.

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Section: Brief Review Of the Machining Studies Using Taguchi Methodsmentioning

confidence: 99%

Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)

Rashid

Goel

Davim

et al. 2015

Int J Adv Manuf Technol

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“…The authors also have detected significance of radial force and feed rate in this paper. Tamizharasan et al (2006) proposed that as an alternative to grinding, the hard turning produced better surface finish, lower flank wear rate and high material removal on the selected crank pin material by low content CBN tool. concluded that the surface roughness was low by CBN at high cutting speed but the flank wear was high during machining stainless steel (45-55 HRC).…”

Section: Review Of Literature and Objectivesmentioning

confidence: 99%

A response surface methodology and desirability approach for predictive modeling and optimization of cutting temperature in machining hardened steel

Sahoo¹,

Mishra²

2014

10.5267/j.ijiec

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This paper presents an experimental investigation on cutting temperature during hard turning of EN 24 steel (50 HRC) using TiN coated carbide insert under dry environment. The prediction model is developed using response surface methodology and optimization of process parameter is performed by desirability approach. A stiff rise in cutting temperature is noticed when feed and cutting speed are elevated. The effect of depth of cut on cutting temperature is not that much significant compared with cutting speed and feed as observed from main effects plot. The response surface second order model presented high correlation coefficient (R 2 = 0.992) explaining 99.2 % of the variability in the cutting temperature which indicates the goodness of fit for the model to the actual data and high statistical significance of the model. The experimental and predicted values are very close to each other. The calculated error for cutting temperature lies between 1.88-3.19 % during confirmation trial. Therefore, the developed second order model correlates the relationship of the cutting temperature with the process parameters with good degree of approximation. The optimal combination for process parameter is depth of cut at 0.2mm, feed of 0.1597 mm/rev and cutting speed of 70m/min. Based on these combination, the value of cutting temperature is 302.95 0 C whose desirability is one.

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“…Several experimental studies have been performed to investigate the influence of cutting parameters (cutting speed, feed and depth of cut), machining time, tool geometry, workpiece hardness, tool materials, different coatings on machinability characteristics like surface roughness, cutting forces and tool flank wear with various workpiece materials (MDN 250, AISI 4340, 4140, 52100, 6150, D2, D3, H10, H11 and H13 die steel) in hard turning for process optimization and machining performance prediction through experimental methods (Tamizharasan et al 2006;Lalwani et al 2008;Hosseini et al 2016;Das et al 2016), mathematical models (Singh & Rao 2007;Al-Ahmari 2007;Ozel et al 2007;Sieben et al 2010;Asiltürk & Çunkaş 2011) and statistical analysis Caydas 2010;Bouacha et al 2010;Nabil et al 2012). Aslan et al (2007) conducted an optimization study by machining a hardened AISI 4140 grade (63 HRC) steel with Al 2 O 3 + TiCN mixed ceramic inserts in order to analyze the effect of cutting parameters (cutting speed, feed rate and depth of cut) on surface roughness and flank wear by employing Taguchi technique, ANOVA and regression analysis.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation of surface roughness, flank wear, chip morphology and cost estimation during machining of hardened AISI 4340 steel with coated carbide insert

Das

Panda

Dhupal

2017

Mech Adv Mater Mod Process

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Background: Now-a-days, newer hardened steel materials are coming rapidly into the market due to its wide applications in various fields of engineering. So the machinability investigation of these steel materials is one of the prime concern for practicing engineers, prior to actual machining. Methods: The present study addresses surface roughness, flank wear and chip morphology during dry hard turning of AISI 4340 steel (49 HRC) using CVD (TiN/TiCN/Al 2 O 3 /TiN) multilayer coated carbide tool. Three factors (cutting speed, feed and depth of cut) and three-level factorial experiment designs with Taguchi's L 9 Orthogonal array (OA) and statistical analysis of variance (ANOVA) were performed to investigate the consequent effect of these cutting parameters on the tool and workpiece in terms of flank wear and surface roughness. For better understanding of the cutting process, surface topography of machined workpieces, wear mechanisms of worn coated carbide tool and chip morphology of generated chips were observed by scanning electron microscope (SEM). Consequently, multiple regression analysis was adopted to develop mathematical model for each response, along with various diagnostic tests were performed to check the validity and efficacy of the proposed model. Finally, to justify the economical feasibility of coated carbide tool in hard turning application, a cost analysis was performed based on Gilbert's approach by evaluating the tool life under optimized cutting condition (suggested by response optimization technique).

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Analysis of tool wear and surface finish in hard turning

Cited by 82 publications

References 18 publications

Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)

Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)

A response surface methodology and desirability approach for predictive modeling and optimization of cutting temperature in machining hardened steel

Experimental investigation of surface roughness, flank wear, chip morphology and cost estimation during machining of hardened AISI 4340 steel with coated carbide insert

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