Performance of coated and uncoated mixed ceramic tools in hard turning process

Bensouilah, Hamza; Aouici, Hamdi; Meddour, Ikhlas; Yallese, Mohamed Athmane; Mabrouki, Tarek; Girardin, François

doi:10.1016/j.measurement.2015.11.042

Cited by 115 publications

(59 citation statements)

References 24 publications

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“…Out of the cutting parameters taken into account the effect of feed (F = 42.81) is most significant on the output response surface roughness (Ra), followed by cutting speed (F = 13.37), as its F calculated value is more than Ftable value (9.0) and probability (P) value is less than 0.1 at 90% confidence level. This results is in concordance with those published in Bensouilah et al (2016), Bouzid et al (2014a), and Hessainia et al (2013). The feed and cutting speed factors affect the surface roughness by 70.22% and 21.93% respectively.…”

Section: Surface Roughness Analysissupporting

confidence: 93%

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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Section: Surface Roughness Analysissupporting

confidence: 93%

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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“…Therefore, the uncoated ceramic insert (CC650) has the better performance compared with coated ceramic insert (CC6050) in terms of surface roughness of the workpiece. Similar results were found by Bensouilah et al [5] when turning AISI D3 steel. Dividing the BAC into subsections could help interpret the results of surface roughness.…”

Section: D and 3d Surface Topographysupporting

confidence: 90%

Comparative assessment of two ceramic cutting tools on surface roughness in hard turning of AISI H11 steel: including 2D and 3D surface topography

Khellaf

Aouici

Smaiah

et al. 2016

Int J Adv Manuf Technol

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This paper presents a comparison of surface roughness between both ceramic cutting tools namely, TiN coated mixed ceramic CC6050 and uncoated mixed ceramic CC650 when machining hardened hot work steel X38CrMoV5-1 [AISI H11] treated at 50 HRC. A mathematical model, relating surface roughness criteria and main factors such as cutting radius, cutting speed, feed rate, and depth of cut, was developed using response surface methodology (RSM) and its adequacy was checked by regression analysis. The effect of cutting parameters on surface roughness is evaluated and the optimum cutting conditions to minimize the surface roughness are determined. A multiple linear models have been established between the cutting parameters and the surface roughness using response surface methodology. The experimental results reveal that the most significant machining parameter for surface roughness is the feed followed by cutting radius. Also the determined optimal conditions really reduce the surface roughness on the machining of AISI H11 steels within the ranges of parameters studied. In addition, excellent surface roughness was obtained in hard turning using CC650 tools. The coated ceramic tools had no advantage over CC650 from the point of view of surface roughness. Keywords Hard turning . AISI H11 steel . Ceramic . Surface roughness . ANOVA . RSM Nomenclature Vc Cutting speed (m/min) HRC Rockwell hardness f Feed rate (mm/rev) ANOVA Analysis of variance ap Depth of cut (mm) RSM Response surface methodology r Cutting radius (mm) DF Degrees of freedom Ra Arithmetic mean roughness (μm) Seq SS Sequential sum of squares Rt Total roughness (μm) Adj MS Adjusted mean squares Fc Tangential force (N) Cont. % Contribution ratio (%) HT Hard turning R² Coefficient of determination (%).

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“…Better surface finish with significant tool life is calculated which shows its application in industrial applications. Bensouilah et al [12] worked on the impact of machining factors on surface quality and cutting force while turning of AISI D3 hardened steel using mixed ceramic cutting tools through Taguchi approach. Coated CC6050 ceramic insert induced better surface quality i.e.…”

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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Performance of coated and uncoated mixed ceramic tools in hard turning process

Cited by 115 publications

References 24 publications

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

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

Comparative assessment of two ceramic cutting tools on surface roughness in hard turning of AISI H11 steel: including 2D and 3D surface topography

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

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