Experimental investigations and multi-response optimisation of wire electric discharge machining of hypereutectic Al-Si alloys

Babu, D. Mani; Kiran, S.; Vundavilli, Pandu R.; Mandal, A.

doi:10.1504/ijmr.2016.079460

Cited by 7 publications

(3 citation statements)

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“…From normalised values, GRC and GRG is calculated. Maximum GRG from all GRG values represents the desired value of the multi-response (Dieguez et al, 2007;Mohapatra et al, 2017;Babu et al, 2016). The procedures for solving GRA are as follows.…”

Section: Methodology Of Gramentioning

confidence: 99%

Experimental studies and multi-response optimisation of duplex turning parameters using grey relational analysis with entropy measurement

Kumar¹,

Yadav²,

Kumar³

2020

IJPTECH

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In present work, the effect of turning parameters like cutting velocity, feed rate, primary depth of cut (DOC) and secondary-DOC on responses like primary cutting force (Fp), secondary cutting force (Fs) and surface roughness (Ra) using duplex turning process are observed. The preliminary experiments and entropy-grey relational analysis (GRA) has been utilised to plan the experiment. Analysis of variance (ANOVA) analyses the influence of each parameter on the responses. It is observed that feed rate has more effect as compared to other parameters. The confirmation experiment at GRA optimal condition shows the improvement in all responses as Fp = 15.34%, Fs = 17.20% and Ra = 10.14% positively.

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Section: Methodology Of Gramentioning

confidence: 99%

Experimental studies and multi-response optimisation of duplex turning parameters using grey relational analysis with entropy measurement

Kumar¹,

Yadav²,

Kumar³

2020

IJPTECH

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“…The GRC is the ratio of referral and comparable sequence for each effort. The GRC is calculated by equation (4) and given in table 5. ζ=distinguishing coefficient, and taken as 0.50 in many metal cutting problems [29][30][31][32].…”

Section: Grey Relational Analyses (Gra) Analysismentioning

confidence: 99%

Multi-response optimization of duplex turning of Nickel alloy using grey relational analysis with entropy measurement

Kumar

Yadav

Kumar³

2019

Eng. Res. Express

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In this work, grey relational analysis (GRA) and entropy weight technique are used for optimizing the Duplex turning parameters of Nickel alloy for multi-performance measures. The Taguchi methodology and GRA are used for optimization of multi-responses like primary-cutting force (Fp), secondary-cutting force (Fs) and average surface roughness (Ra) positively. The factors like cutting speed, feed-rate, and primary depth-of-cut (DOC) and secondary-DOC are selected for experimentation. Analysis of variance technique is applied for investigating the factor effects on the responses. The optimal result shows improvement of 11.45%, 13.91% and 18.30% on responses F P , F S and Ra respectively.

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“…Rajyalakshmi and Venkata Ramaiah (2015) presented an application of Taguchi and GRA methods for optimization of WEDM process parameters (pulse-on time, pulse-off time, corner servo voltage, flushing pressure, wire feed, wire tension, servo feed and spark gap voltage). Babu et al (2016) applied two multi-objective optimization methodologies, i.e. GRA and PCA for determining the optimal settings of pulse-on time, pulse-off time, wire FR and variation of percentage of silicon in a WEDM process; and concluded that PCA would be a better optimization tool than GRA.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of grey-fuzzy logic technique for parametric optimization of non-traditional machining processes

Chakraborty

Das

Kumar

2018

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Purpose The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes. Design/methodology/approach In this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance. Findings The derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes. Practical implications This grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values. Originality/value The adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

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Experimental investigations and multi-response optimisation of wire electric discharge machining of hypereutectic Al-Si alloys

Cited by 7 publications

References 0 publications

Experimental studies and multi-response optimisation of duplex turning parameters using grey relational analysis with entropy measurement

Experimental studies and multi-response optimisation of duplex turning parameters using grey relational analysis with entropy measurement

Multi-response optimization of duplex turning of Nickel alloy using grey relational analysis with entropy measurement

Application of grey-fuzzy logic technique for parametric optimization of non-traditional machining processes

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