High speed turning for hard material with PCBN inserts: tool wear analysis

Mahfoudi, F. F.; List, Gautier; Molinari, A.; Moufki, Abdelhadi; Boulanouar, Lakhdar

doi:10.1504/ijmmm.2008.017625

Cited by 15 publications

(19 citation statements)

References 29 publications

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“…Ozel and Karpat (2005) observed that low CBN content insert with honed edge geometry performed better in terms of surface roughness and tool wear in finish hard turning of AISI H13 steel. Mahfoudi et al (2008) found that high speed machining (300 and 400 m/min) of a 50 HRC hardened steel (AISI 4140/ 42CrMo4) with a PCBN tool could be acceptable for industrial application providing very good surface roughness with significant tool life. Derakhshan and Akbari (2009) obtained best surface quality in hard turning of AISI 4140 steel (45-65 HRC) with CBN tool with Ra being 0.175 μm.…”

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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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

View full text Add to dashboard Cite

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“…Especially, at the tool rake face, high pressure and high temperature lead to the formation of an important crater. 21 Crater wear can severe change the cutting edge geometry in the cutting zone. 16 When looked closely at the surface of crater, it can be seen that abrasion marks were formed in the chip flow direction.…”

Section: Tool Wear Analysismentioning

confidence: 99%

Application of grey relational analysis in high-speed machining of hardened AISI D6 steel

Yıldırım

2012

Proceedings of the Institution of Mechanical Engineers, Part C:

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This study reports an optimization of finish turning of hardened AISI D6 (60 HRC) cold work tool steel with ceramic and cubic boron nitride cutting tools using grey relational analysis. Optimization of the process parameters was performed using quality characteristics, i.e. tool wear, surface roughness, machining force and specific cutting force. Analysis of variance was used for observing the most influencing machining parameters on the quality characteristics. Evaluation of tool wear type and wear mechanism was done by tool makers' microscope and scanning electron microscope analysis. The optimal process parameters were calculated using grey relation grade and confirmation test was performed. Based on analysis of variance results, the feed rate is the most significant controllable machining factor for the finish hard turning of AISI D6 according to the quality characteristics. Flank and crater wears were the prominent wear types on the ceramic and cubic boron nitride inserts. Grey relational analysis was successfully applied on optimization of high-speed finish hard turning of hardened AISI D6 using multi-performance characteristics.

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“…PCBN wiper inserts yields better surface roughness and elevated compressive residual stresses correlate to conventional cutting tool in machining. Mahfoudi et al [11] studied turning of AISI 4140/ 42CrMo4 grade steel (50 HRC) with PCBN insert at higher cutting speeds (300 and 400 m/min). Better surface finish with significant tool life is calculated which shows its application in industrial applications.…”

Section: Introductionmentioning

confidence: 99%

Investigating Machinability in Hard Turning of AISI 52100 Bearing Steel Through Performance Measurement: QR, ANN and GRA Study

Panda¹,

Sahoo²,

Panigrahi³

et al. 2018

INT. J. AUTOMOT. MECH. ENG.

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The existing endeavor investigates on machinability characteristics through performance measurement of flank wear, surface quality and chip morphology during finish turning of AISI 52100 bearing steel (55 ± 1 HRC) under dry environment employing carbide insert coated along with various layers (TiN/TiCN/Al2O3). Secondly the influence of machining variables viz. cutting speed, feed rate and depth of cut on responses are assessed by ANOVA and modeled through quadratic regression and artificial neural network. Multiparametric optimization of cutting conditions has been obtained through Taguchi based grey relational analysis. Finally, tool life at ideal conditions has been evaluated through experiment. Based on the study, it is disclosed that coated carbide with multilayer insert outperformed during hard machining as wear at the flank surface and surface quality are within the benchmark cap of 0.3 mm and 1.6 microns respectively. From the chip morphology analysis, multilayer coated carbide insert generates lower temperature and maintains cutting edge sharpness and delays the growth of tool wear. ANN model using multilayered feed forward network yields accurate prediction of responses with minimum error percentage compared to QR model. The optimal parametric combination through GRA approach is found to be d1 (0.1 mm)-f1 (0.04 mm/rev)-v2 (110 m/min) and is greatly improved. Feed is the compelling aspect for multi-responses pursued by cutting speed. The tool life at optimized cutting condition is found to be approximately 19 minutes.

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High speed turning for hard material with PCBN inserts: tool wear analysis

Cited by 15 publications

References 29 publications

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

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

Application of grey relational analysis in high-speed machining of hardened AISI D6 steel

Investigating Machinability in Hard Turning of AISI 52100 Bearing Steel Through Performance Measurement: QR, ANN and GRA Study

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