Investigation for obtaining the optimal solution for improving the performance of WEDM of super alloy Udimet-L605 using particle swarm optimization

Nain, Somvir Singh; Garg, Dixit; Kumar, Sanjeev

doi:10.1016/j.jestch.2018.03.005

Cited by 31 publications

(12 citation statements)

References 18 publications

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“…Multi-response optimization is needed in contemporary manufacturing. Various methods such as gray relational analysis (GRA) [ 11 , 15 , 18 ], heat transfer search (HTS) algorithm [ 2 , 19 ], teacher learning-based algorithm [ 20 ], particle swarm algorithm [ 21 ], genetic algorithm [ 22 ], artificial neural networks [ 23 ], etc., have been attempted to check their feasibility in finding the tread-off solution in terms of optimized process parameters.…”

Section: Introductionmentioning

confidence: 99%

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM

et al. 2021

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Titanium and its alloys exhibit numerous uses in aerospace, automobile, biomedical and marine industries because of their enhanced mechanical properties. However, the machinability of titanium alloys can be cumbersome due to their lower density, high hardness, low thermal conductivity, and low elastic modulus. The wire electrical discharge machining (WEDM) process is an effective choice for machining titanium and its alloys due to its unique machining characteristics. The present work proposes multi-objective optimization of WEDM on Ti6Al4V alloy using a fuzzy integrated multi-criteria decision-making (MCDM) approach. The use of MCDM has become an active area of research due to its proven ability to solve complex problems. The novelty of the present work is to use integrated fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal situation (TOPSIS) to optimize the WEDM process. The experiments were systematically conducted adapting the face-centered central composite design approach of response surface methodology. Three independent factors—pulse-on time (Ton), pulse-off time (Toff), and current—were chosen, each having three levels to monitor the process response in terms of cutting speed (VC), material removal rate (MRR), and surface roughness (SR). To assess the relevance and significance of the models, an analysis of variance was carried out. The optimal process parameters after integrating fuzzy AHP coupled with fuzzy TOPSIS approach found were Ton = 40 µs, Toff = 15 µs, and current = 2A.

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Section: Introductionmentioning

confidence: 99%

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM

et al. 2021

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“…, 2020; Mech, 2021). Very little work has been reported on shape memory alloy and nickel-based superalloys (Nain et al. , 2018; Balasubramaniyan and Rajkumar, 2021).…”

Section: Introductionmentioning

confidence: 99%

A study of wire tool surface topography and optimization of wire electro-spark machined UNS N06690 using the federated mode of RSM-ANN

Raj

Misra

Khanduja

et al. 2021

IJSI

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PurposeThe purpose of this study is to examine the postprocessed wire tool surface using scanning electron microscopy and find out the streamlined conditions of input process variables using multi-objective optimization techniques to get minimum wire wear values.Design/methodology/approachA federated mode of response surface methodology (RSM) and artificial neural network (ANN) is used to optimize the process variables during the machining of a nickel-based superalloy.FindingsThe study explores that with the rise in spark-off time and spark gap voltage, the rate of wire tool consumption also escalates.Originality/valueMost of the researchers used the RSM technique for the optimization of process variables. The RSM generates a second-order regression model during the modeling and optimization of a manufacturing process whose major limitation is to fit the collected data to a second-order polynomial. The leading edge of ANN on the RSM is that it has comprehensive approximation capability, i.e. it can approximate virtually all types of nonlinear functions, including quadratic functions also.

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“…In recent years, most of the researchers have been developing various techniques to investigate the wire EDM performance on various materials using various modelling and new optimization techniques. The performance and surface characteristic of wire EDM has been investigated [15]. Artificial intelligence techniques, such as fuzzy logic and ANN, were successfully applied to various machining processes [16].…”

Section: Introductionmentioning

confidence: 99%

Influence of optimization techniques and nano surface coating materials on microstructure of iron-nickel-chromium alloy using wire EDM process

Selvabharathi¹,

Srinivasan

Sivaprakasam

2021

Materials Science-Poland

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This research proposes developing the new hybrid optimization techniques for getting optimized wire EDM machining parameters and analysing the performance and microstructure of hybrid treatment alloy 20 material (high-velocity oxygen fuel spraying and plasma nitriding on iron-nickel-chromium alloy) after machining in wire EDM. The devising optimization is carried out using back-propagation neural networks (BPNN) integrated with fuzzy logic techniques. Taguchi L27 method uses optimized parameters in 3 factors and 3 level methods to BPNN wire EDM processing parameters. Those processing parameter errors are controlled by applying fuzzy logic system in hybrid optimization techniques. The hybrid optimization provides best results (±5% error) while comparing other techniques. This proposal was started with research review of defined factors and BPNN parameters level for hidden layer number, learning algorithm, neurons numbers, and so on. The analysis of variance (ANOVA), analysis of means (ANOM) and signal to noise (S/N) ratio have been used to identify Taguchi results. The BPNN techniques have been employed significantly to tackle hidden layer's uncertain parameter structures. The fuzzy logic controllers in general have been designed engaging the relations between system performance and factor through error method calculation. The microstructure analysis showed that the no evidence was found of recast layer formation on hybrid treated material after machining in wire EDM due to compressive stress and compound layer on material surface.

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Investigation for obtaining the optimal solution for improving the performance of WEDM of super alloy Udimet-L605 using particle swarm optimization

Cited by 31 publications

References 18 publications

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM

A study of wire tool surface topography and optimization of wire electro-spark machined UNS N06690 using the federated mode of RSM-ANN

Influence of optimization techniques and nano surface coating materials on microstructure of iron-nickel-chromium alloy using wire EDM process

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