Predictive modeling of surface roughness in high speed machining of AISI 4340 steel using yttria stabilized zirconia toughened alumina turning insert

Mandal, Nilrudra; Doloi, B.; Mondal, Bittagopal

doi:10.1016/j.ijrmhm.2012.12.007

Cited by 56 publications

(22 citation statements)

References 23 publications

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“…The lower surface roughness value indicates that the machining forces are lesser during the trials and the smooth machining of EN24 alloy steel workpiece is obtained. 24,25 Surface¯nish is a signi¯cant index of machinability. The surface conditions of the machined component depend on its service life.…”

Section: Surface Roughness Analysismentioning

confidence: 99%

Comparative Evaluation of Performances of TiAlN-, AlCrN- and AlCrN/TiAlN-Coated Carbide Cutting Tools and Uncoated Carbide Cutting Tools on Turning EN24 Alloy Steel

Kumar

Prabu

Kumar³

2017

J. Adv. Manuf. Syst.

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In the present work, the performances of TiAlN-, AlCrN-and AlCrN/TiAlN-coated and uncoated tungsten carbide cutting tool inserts are evaluated from the turning studies conducted on EN24 alloy steel workpiece. The output parameters such as cutting forces, surface roughness and tool wear for TiAlN-, AlCrN-and AlCrN/TiAlN-coated carbide cutting tools are compared with uncoated carbide cutting tools (K10). The design of experiment based on Taguchi's approach is used to obtain the best turning parameters, namely cutting speed (V ), feed rate (f) and depth of cut (d), in order to have a better surface¯nish and minimum tool°ank wear. An orthogonal array (L 9 Þ was used to conduct the experiments. The results show that the AlCrN/ TiAlN-coated cutting tool provided a much better surface¯nish and minimum tool°ank wear. The minimum tool°ank wear and minimum surface roughness were obtained using AlCrN/ TiAlN-coated tools, when V ¼ 160 m/min, f ¼ 0:318 mm/rev and d ¼ 0:3 mm.

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Section: Surface Roughness Analysismentioning

confidence: 99%

Comparative Evaluation of Performances of TiAlN-, AlCrN- and AlCrN/TiAlN-Coated Carbide Cutting Tools and Uncoated Carbide Cutting Tools on Turning EN24 Alloy Steel

Kumar

Prabu

Kumar³

2017

J. Adv. Manuf. Syst.

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“…Response surface methodology (RSM) includes mathematical and statistical techniques for modeling and optimization of response variables which are influenced by several process variables [13]. Before applying RSM, it is required to check proper selection of process parameters and their ranges from previous studies and trial experiments for proper experimental design.…”

Section: A Construction Of Response Surface Methodology (Rsm) Modelmentioning

confidence: 99%

A Comparative Modeling and Multi- Objective Optimization in Wire EDM Process on H21 Tool Steel Using Intelligent Hybrid Approach

Choudhuri¹,

Sen²,

Ghosh³

et al. 2016

IJET

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H21 steel is one of the hot work tool steel, which exhibits superior red hardness, high mechanical strength and difficult-to-machine. Wire electrical discharge machining (WEDM) always demands high-speed and high-precision machining to fulfill productivity and accuracy of machining hard materials. Cutting speed determines the productivity of machining and the width of kerf determines the tolerance of finished product. Two methodologies viz. response surface method (RSM) and artificial neural network (ANN) are compared for their modeling, sensitivity analysis and optimization abilities. The predictability of ANN model is better than RSM which indicating the advantage of ANN in mapping the nonlinear behavior of the system. Finally, the ANN fitness function is integrated with particle swarm optimization (PSO) algorithm to optimize the process parameters of the WEDM process.

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“…Nilrudra Mandal et al studied the surface roughness produced during turning operation of 4340-grade steel using coated alumina tool. During experiment best surface finish was obtained at a machining parameter combination of machining speed 420 m/minute, depth of cut 0.5 millimetre and feed rate 0.24 mm/revolution [26]. Machining insert nose geometry along with feed rate was found to strongly affect the surface roughness values in the turning operation [27].…”

Section: Analysis Of Surface Roughnessmentioning

confidence: 97%

A Comprehensive Review on Machinability Aspects in Hard Turning of AISI 4340 Steel

Roy

Kumar

Das

et al. 2018

IOP Conf. Ser.: Mater. Sci. Eng.

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Predictive modeling of surface roughness in high speed machining of AISI 4340 steel using yttria stabilized zirconia toughened alumina turning insert

Cited by 56 publications

References 23 publications

Comparative Evaluation of Performances of TiAlN-, AlCrN- and AlCrN/TiAlN-Coated Carbide Cutting Tools and Uncoated Carbide Cutting Tools on Turning EN24 Alloy Steel

Comparative Evaluation of Performances of TiAlN-, AlCrN- and AlCrN/TiAlN-Coated Carbide Cutting Tools and Uncoated Carbide Cutting Tools on Turning EN24 Alloy Steel

A Comparative Modeling and Multi- Objective Optimization in Wire EDM Process on H21 Tool Steel Using Intelligent Hybrid Approach

A Comprehensive Review on Machinability Aspects in Hard Turning of AISI 4340 Steel

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