Study of Surface Characterization and Parametric Optimization during Wire Electric Discharge Machining for Inconel 625

This presented article focuses on surface characterization and assessing the satisfactory machining condition of WEDMed Inconel 625. This work material has been received remarkable attention to the industrial and academic organization for its end use applications. WEDM is well-known machining proces...

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Bibliographic Details
Published inMaterials science forum Vol. 978; pp. 97 - 105
Main Authors Kumar, Anshuman, Upadhyay, Chandramani, Kukkala, Vivekananda
Format Journal Article
LanguageEnglish
Published Pfaffikon Trans Tech Publications Ltd 01.02.2020
Subjects
Cutting parameters
Design of experiments
Electric discharge machining
Fuzzy systems
Genetic algorithms
Hard materials
Machine learning
Nickel base alloys
Optimization
Orthogonal arrays
Process parameters
Superalloys
Surface properties
Wire
Surface Characterization
TLBO
Inconel 625
Fuzzy
Wire Electric Discharge Machining (WEDM)
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Summary:This presented article focuses on surface characterization and assessing the satisfactory machining condition of WEDMed Inconel 625. This work material has been received remarkable attention to the industrial and academic organization for its end use applications. WEDM is well-known machining process for intricate shape cutting and machining hard materials. The experimental design was planned according to L27 orthogonal array (OA), by varying controllable process parameter (i.e. Wire-Tension, Wire-speed, Flushing-Pressure, Discharge-Current and Spark-on Time), each parameter varied at four discrete levels, within the selected parametric domain. WEDMed surfaces have been investigated with a focus to the surface characterization of selected machined surface through captured images from scanning electron microscope (SEM). Eventually, multi-response optimization of process parameters was sought by using a combination of nonlinear regression modelling, fuzzy inference system (FIS) with Teaching Learning-Based Optimization (TLBO) algorithm. The obtained TLBO result was compared with the Genetic algorithm (GA). The results show that optimization algorithms are effective tools for getting satisfactory optimal machining conditions during WEDM process of Inconel 625.
Bibliography:Selected, peer reviewed papers from the International Conference on Processing and Characterization of Materials (ICPCM 2018), 6-8 December, 2018, Odisha, India
ISSN:0255-5476
1662-9752
1662-9752
DOI:10.4028/www.scientific.net/MSF.978.97