Modelling and experimental investigation of process parameters in WEDM of WC-5.3 % Co using response surface methodology

Jangra, Kamal Kumar; Grover, Sandeep

doi:10.5194/ms-3-63-2012

Cited by 18 publications

(6 citation statements)

References 22 publications

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“…The designs for fitting response surfaces are called response surface designs. The objective of RSM is to determine to determine a region of the factor space in which operating requirements are satisfied or the optimum operating conditions for the system (Datta and Mahapatra, 2010;Jangra and Grover, 2012;Aggarwal et al, 2015). Analysis of several responses is carried out in RSM.…”

Section: Response Surface Methodologymentioning

confidence: 99%

A study on machinability evaluation of Al-Gr-B<SUB align="right">4C MMC using response surface methodology-based desirability analysis and artificial neural network technique

Ponnuvel¹,

Senthilkumar²

2019

IJRAPIDM

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In this work, machinability behaviour of aluminium-graphite-boron carbide metal matrix composite is performed during wire-cut electrical discharge machining (WEDM) process. Experiments were designed using central composite-face centred design of response surface methodology (RSM) and with the application of desirability function multiple quality characteristics viz., kerf width, surface roughness and material removal rate (MRR) were optimised simultaneously. Input parameters gap voltage, pulse ON-time, pulse OFF-time and % reinforcement of boron carbide particles in the aluminium matrix are considered. The optimised machining condition obtained is a gap voltage of 150 V, pulse ON-time of 124.56 ms, pulse OFF-time of 48.03 ms and 2.5% reinforcement of boron carbide. From the experimental values, it is observed that better output responses are achieved with lower reinforcement of boron carbide. Second order regression models are developed individually for the output responses. An artificial neural network model is developed to predict the output responses, results obtained show that a better prediction can be achieved through artificial intelligent technique.

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Section: Response Surface Methodologymentioning

confidence: 99%

A study on machinability evaluation of Al-Gr-B<SUB align="right">4C MMC using response surface methodology-based desirability analysis and artificial neural network technique

Ponnuvel¹,

Senthilkumar²

2019

IJRAPIDM

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“…Response surface methodology (RSM) is a collection of mathematical and experimental techniques that requires sufficient number of experimental data to analyse the engineering problem and to develop mathematical models for several input variables and output performance characteristics (Myers & Montgomery, 1995;Jangra & Grover, 2012). By using the design of experiments and applying regression analysis, the modelling of the desired response ( ) to several independent input variables (xi) can be gained.…”

Section: Response Surface Methodology and Experimental Designmentioning

confidence: 99%

An experimental investigation and statistical modelling for trim cutting operation in WEDM of Nimonic-90

Kumar¹,

Kumar²,

Jangra³

2015

10.5267/j.ijiec

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Trim cutting operation in wire electrical discharge machining (WEDM) is considered as a probable solution to improve surface characteristics and geometrical accuracy by removing very small amount of work materials from the surface obtained after a rough cutting operation. In this study, an attempt has been made to model the surface roughness and dimensional shift in trim cutting operations in WEDM process through response surface methodology (RSM). Four process parameters; namely pulse-on time (Ton), servo voltage (SV), wire depth (Wd) and Dielectric flow rate (FR) have been considered as input parameters in trim cutting operations for modelling. Desirability function has been employed to optimize multi performance characteristics. Increasing the value of Ton, Wd and FR increases the surface roughness and dimensional shift but increasing SV decreases both surface roughness and dimensional shift. Quadratic models have been proposed for both the performance characteristics. In present experimentation, thickness of recast layer was observed in the range of 6μm to 12μm for low to high value of discharge parameters.

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“…Dielectric flow rate also increased the MRR initially, up to a certain limit and after that it was decreased because of pronounced cooling effect on the work material. Jangra K. and Grover S. [23] investigated the effect of process parameters (pulse-on-time, pulse offtime, servo voltage, wire feed rate) on cutting rate of WC-5.3%Co composite material during WEDM operation. Results showed that cutting speed increased with increment in pulse on-time and wire feed rate, and it got decreased with increasing pulse off-time and servo voltage.…”

Section: Cutting Ratementioning

confidence: 99%

Machining of WC-Co Composites - A Review

Kataria¹,

Kumar²

2014

MSF

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This article aims to present a review on the machining of tungsten carbide-cobalt composite material. WC-Co based materials are extensively used where the demand for high performance materials exists because these have the distinguished set of properties such as high hardness, superior wear resistance, high mechanical strength and good dimensional stability. Due to these excellent properties, it serves most applications in the field of tool and die making. Machining of the WC-Co materials is very difficult with conventional machining processes and results in poor surface finish, low material removal rate, high machining cost. Among all non-conventional machining processes, thermal energy based processes such as Electrical discharge machining, Wire EDM are most widely used to machine these materials. The machining of WC-Co is also affected by various factors such as the cobalt content and grain size and presence of other carbides. This paper attempts to critically review all these aspects of the machining of WC-CO composites.

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Modelling and experimental investigation of process parameters in WEDM of WC-5.3 % Co using response surface methodology

Cited by 18 publications

References 22 publications

A study on machinability evaluation of Al-Gr-B<SUB align="right">4C MMC using response surface methodology-based desirability analysis and artificial neural network technique

A study on machinability evaluation of Al-Gr-B<SUB align="right">4C MMC using response surface methodology-based desirability analysis and artificial neural network technique

An experimental investigation and statistical modelling for trim cutting operation in WEDM of Nimonic-90

Machining of WC-Co Composites - A Review

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