NSGA-II Approach for Multi- Objective Optimization of Wire Electrical Discharge Machining Process Parameter on Inconel 718

Kumar, Anshuman; Majumder, Himadri; Vivekananda, K.; Maity, Kalipada

doi:10.1016/j.matpr.2017.02.066

Cited by 26 publications

(7 citation statements)

References 11 publications

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“…A series of experimental runs following Taguchi's L 27 orthogonal array (OA) were conducted on ECOCUT, EIPULS 15 and manufactured by Electronica. Based on the available literature (Chalisgaonkar and Kumar, 2015;Gowd et al, 2014;Kumar et al, 2012a;Kumar et al, 2013;Kumar et al, 2017;Majumder and Maity, 2017;Mathew and Babu, 2014;Nayak and Mahapatra, 2016;Saha and Mondal, 2016b;Sharma et al, 2015b) and experience, different input parameters, such as pulse-on time, pulse-off time, wire feed and wire tension, were selected as machining parameters (Table I), whereas current and voltage were kept constant throughout the experimental runs. Brass wire, the most favorable and more economical electrode in industrial application (Majumder and Maity, 2018;Tiwary et al, 2014) having a diameter of 0.25 mm, was used as wire electrode and deionized water was used as dielectric fluid for WEDM machining.…”

Section: Methodsmentioning

confidence: 99%

Performance analysis in WEDM of titanium grade 6 through process capability index

Majumder

Maity

2020

WJE

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Purpose The purpose of this study aims to obtain excellent products, consistent investigation and manufacturing process control which are the preconditions that organizations have to consider. Nowadays, manufacturing industry apprise process capability index (Cpi) to evaluate the nature of their things with an expect to enhance quality and also to improve the productivity by cutting down the operating cost. In this paper, process capability analysis was applied during wire electrical discharge machining (WEDM) of titanium grade 6, to study the process performance within specific limits. Design/methodology/approach Four machine input parameters, namely, pulse ON time, pulse OFF time, wire feed and wire tension, were chosen for process capability study. Experiments were carried out according to Taguchi’s L27 orthogonal array. The value of Cpi was evaluated for two machining attributes, namely, average surface roughness and material removal rate (MRR). For these two machining qualities, single response optimization was executed to explore the input settings, which could optimize WEDM process ability. Findings Optimum parameter settings for average surface roughness and MRR were found to be TON: 115 µs, TOFF: 55 µs, WF: 4 m/min and WT: 6 kg−F and TON: 105 µs, TOFF: 60 µs, WF: 4 m/min and WT: 5 kg−F. Originality/value Process capability analysis constantly checks the process quality through the capability index keep in mind the end goal to guarantee that the items made are complying with the particulars, providing data for product plan and process quality enhancement for designer and engineers, giving the support to decrease the cost of item failures.

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Section: Methodsmentioning

confidence: 99%

Performance analysis in WEDM of titanium grade 6 through process capability index

Majumder

Maity

2020

WJE

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“…Literatures where MCDM techniques such as TOPSIS [18][19][20], VIKOR [21,22], MOORA [23][24][25], ARAS [26] and others [27][28][29] are used in selecting the best machining parameters. Meta-heuristic techniques such as non-dominated sorting algorithm-II [30][31][32], particle swarm optimization [33,34], teaching-learning based optimization [35], artificial bee colony algorithm [11] etc. to evaluate the optimal performance parameters by WEDM process.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling and optimizing performance parameters in the wire-electro discharge machining of Al5083/B4C composite by multi-objective response surface methodology

Singh

Hussain

Dash

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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Composite is an artificial multiphase material that constituent phases which are chemically dissimilar and separated by a distinct interface. As a result of such anisotropic and non-homogeneous formation machining of composites is a strenuous task. Therefore, the need arose for formulating a stable predictive model. The comprehensive intention of this study is to develop a highly robust and stable predictive soft-computing model for forecasting the machining performance of Al-5083 alloy reinforced with B 4 C particles (Al5083/B 4 C). The study mostly emphasize on selecting the best machining parameters among the conducted experiments and evaluating the optimal machining parameters for Al5083/B 4 C composite in wireelectro discharge machin. The paper is an integration of equally weighted experimental as well as computational study. In the experimental part of the study, 5 different specimen of Al5083/B 4 C is prepared by the ex situ technique through stir casting process. The experimental part includes design of experiment by Taguchi's method. The computational part of the study comprised of three different stages. The first stage involves the mathematical modelling of the performance measures and statistical scrutiny of the models. In the second stage, the best machining parameters are selected based on the fuzzy IFthen rules. The final stage of the manuscript is the trade-off analysis conducted to obtain the optimal machining parameters. In order to test the robustness of the formulated model an experimental validation is carried out at the optimal machining combination. The error calculated from the comparison is within the range of 2-5% which justifies the objective of the study.

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“…NSGA-II is widely used as an efficient algorithm, in which the Pareto frontier exhibits the characteristics of an actual optimal solution. The characteristic that accuracy of the Pareto frontier was secured by classifying the individual genetic algorithms using the non-dominated sorting method based on the concept of dominance [9][10][11][12][13]. The variance priority was applied through the crowding distance so that the Pareto frontier characteristics can be exhibited well.…”

Section: Non-dominated Sorting Genetic Algorithm-ii (Nsga-ii)mentioning

confidence: 99%

Study on Flow Pattern According to Rotor Design Parameter of Sewage Sludge Solid Fuel Crusher

Jeong

Lee

Lim³

et al. 2020

J. Electr. Eng. Technol.

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In coal-fired power plants, approximately 5% of sewage sludge solid fuel mixed with coal is used as power generation fuel for environmental protection and global warming prevention. The co-firing method needs a sewage sludge solid fuel crusher that can crush sewage sludge solid fuel to generate a fine powder. This study aims to determine the size of the rotor perpendicular plate hole that can minimize accumulation of the crushed fuel in the roller type sewage sludge solid fuel crusher to be used in the co-firing method. The range of the design parameters for optimization of the rotor perpendicular plate hole is selected and make an orthogonal array table according to design of experiments. The CFD is performed to analyze effect of design parameters according to an orthogonal array table. In addition, the dimension of the rotor perpendicular plate hole that can minimize accumulation of the fuel inside the crusher is drawn using the Multi-objective optimization method.

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NSGA-II Approach for Multi- Objective Optimization of Wire Electrical Discharge Machining Process Parameter on Inconel 718

Cited by 26 publications

References 11 publications

Performance analysis in WEDM of titanium grade 6 through process capability index

Performance analysis in WEDM of titanium grade 6 through process capability index

Modelling and optimizing performance parameters in the wire-electro discharge machining of Al5083/B4C composite by multi-objective response surface methodology

Study on Flow Pattern According to Rotor Design Parameter of Sewage Sludge Solid Fuel Crusher

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