Comparative investigation towards machinability improvement in hard turning using coated and uncoated carbide inserts: part I experimental investigation

Kumar, Ramanuj; Sahoo, Ashok Kumar; Mishra, Purna Chandra; Das, Rabin Kumar

doi:10.1007/s40436-018-0215-z

Cited by 69 publications

(30 citation statements)

References 42 publications

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“…Crater wear is affected by the temperature at the tool-chip interface and the chemical affinity between the tool and the workpiece material. Diffusion, adhesion and, to a lesser extent, abrasion contribute to cratering [1,9,10].…”

Section: Introductionmentioning

confidence: 99%

New Observations on High-Speed Machining of Hardened AISI 4340 Steel Using Alumina-Based Ceramic Tools

Shalaby

Veldhuis

2018

JMMP

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High-speed machining (HSM) is used in industry to improve the productivity and quality of the cutting operations. In this investigation, pure alumina ceramics with the addition of ZrO 2 , and mixed alumina (Al 2 O 3 + TiC) tools were used in the dry hard turning of AISI 4340 (52 HRC) at different high cutting speeds of 150, 250, 700 and 1000 m/min. It was observed that at cutting speeds of 150 and 250 m/min, pure alumina ceramic tools had better wear resistance than mixed alumina ones. However, upon increasing the cutting speed from 700 to 1000 m/min, mixed alumina ceramic tools outperformed pure ceramic ones. Scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) were used to investigate the worn cutting edges and analyze the obtained results. It was found that the tribo-films formed at the cutting zone during machining affected the wear resistances of the tools and influenced the coefficient of friction at the tool-chip interface. These observations were confirmed by the chip compression ratio results at different cutting conditions. Raising cutting speed to 1000 m/min corresponded to a remarkable decrease in cutting force components in the dry hard turning of AISI 4340 steel.

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Section: Introductionmentioning

confidence: 99%

New Observations on High-Speed Machining of Hardened AISI 4340 Steel Using Alumina-Based Ceramic Tools

Shalaby

Veldhuis

2018

JMMP

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“…Ribbon type of chips is bonded types of a structure where chips are bonded together and form a long and continuous strip. The bottom portion of chips has steps marks due to intermittent slip while the outside portion is smooth and shining as shown in (Figure 6 Figure 6(c) were produced at more feed and highest depth of cut condition which attributes the relatively rough surface and not favourable for hard turning concern [10]. In the entire set of experiments, the colours of chips are metallic which indicates the optimum amount of heat generation during the process.…”

Section: Chip Morphology and Chip Reduction Coefficientmentioning

confidence: 93%

“…The mechanism like micro-chipping, abrasion, adhesive, oxidation, and severe notching are dominant under dry cutting condition. Kumar et al [10] stated that the diffusion and abrasion wear approach was dominant in dry cutting of D2 hard steel. Diffusion mechanism is the key agent for catastrophic breakage of uncoated carbide insert.…”

Section: Introductionmentioning

confidence: 99%

Hard Turning on JIS S45C Structural Steel: An Experimental, Modelling and Optimisation Approach

Kumar¹,

Modi²,

Panda³

et al. 2019

IJAME

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The present research is performed while turning of JIS S45C hardened structural steel with the multilayered (TiN-TiCN-Al2O3-TiN) CVD coated carbide insert by experimental, modelling and optimisation approach. Herein, cutting speed, feed rate, and depth of cut are regarded as input process factors whereas flank wear, surface roughness, chip morphology are considered to be measured responses. Abrasion and built up-edge are the more dominant mode of tool-wear at low and moderate cutting speed while the catastrophic failure of tool-tip is identified at higher cutting speed condition. Moreover, three different Modelling approaches namely regression, BNN, and RNN are implemented to predict the response variables. A Back-propagation neural network with a 3-8-1 network architecture model is more appropriate to predict the measured output responses compared to Elman recurrent neural network and regression model. The minimum mean absolute error for VBc, Ra and CRC is observed to be as 1.36% (BNN with 3- 8-1 structure), 1.11% (BNN with 3-8-1 structure) and 0.251 % (RNN with 3-8-1 structure). A multi-performance Optimisation approach is performed by employing the weighted principal component analysis. The optimal parametric combination is found as the depth of cut at level 2 (0.3 mm)-feed at level 1 (0.05 mm/rev) – cutting speed at level 2 (120 m/min) considered as favourable outcomes. The predicted results were validated through a confirmatory trial providing the process efficiency. The significant improvement for S/N ratio of CQL is observed to be 9.3586 indicating that the process is well suited to predict the machining performances. In conclusion, this analysis opens an avenue in the machining of medium carbon low alloy steel to enhance the machining performance of multi-layered coated carbide tool more effectively and efficiently.

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“…The dry hard turning tests were experimented by means of Taguchi L16 orthogonal array (OA) design which comprises of total 16 experimental runs of different combinations of process inputs such as cutting speed (v), feed (f) and depth of cut (d) respectively each at four levels [26,27,28,29]. The levels of depth of cut vary from 0.…”

Section: Cutting Parametersmentioning

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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Comparative investigation towards machinability improvement in hard turning using coated and uncoated carbide inserts: part I experimental investigation

Cited by 69 publications

References 42 publications

New Observations on High-Speed Machining of Hardened AISI 4340 Steel Using Alumina-Based Ceramic Tools

New Observations on High-Speed Machining of Hardened AISI 4340 Steel Using Alumina-Based Ceramic Tools

Hard Turning on JIS S45C Structural Steel: An Experimental, Modelling and Optimisation Approach

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

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