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Optimization of Manufacturing ProcessesOptimization of Electric Discharge Machining Based Processes

Optimization of Manufacturing Processes: Optimization of Electric Discharge Machining Based... [The results of Electrical Discharge Machining (EDM)Electric discharge machining are characterized through many parameters. These include, material removal rateMaterial Removal Rate (MRR), surface finish, geometrical accuracy, tool wear, and kerf width. The three main types of EDM, wire, sinker, and micro EDM all have similar characteristics in relation to input parameters and their effects on the results. The typical EDM system is too complex to accurately model the effect of all the parameters together. Therefore, it is necessary to create an optimization algorithm to predict the results of specific input parameters. Various techniques such as TaguchiTaguchi robust design, grey relational analysisGrey relational analysis, desirabilityDesirability, genetic algorithmGenetic algorithm, and neural network etc. have been used for optimization of EDM based processes. This chapter first briefly introduces all the aforementioned optimization processes and comprehensively discusses their implementation and effect for optimization of EDM based processes.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Optimization of Manufacturing ProcessesOptimization of Electric Discharge Machining Based Processes

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Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2020
ISBN
978-3-030-19637-0
Pages
29 –63
DOI
10.1007/978-3-030-19638-7_2
Publisher site
See Chapter on Publisher Site

Abstract

[The results of Electrical Discharge Machining (EDM)Electric discharge machining are characterized through many parameters. These include, material removal rateMaterial Removal Rate (MRR), surface finish, geometrical accuracy, tool wear, and kerf width. The three main types of EDM, wire, sinker, and micro EDM all have similar characteristics in relation to input parameters and their effects on the results. The typical EDM system is too complex to accurately model the effect of all the parameters together. Therefore, it is necessary to create an optimization algorithm to predict the results of specific input parameters. Various techniques such as TaguchiTaguchi robust design, grey relational analysisGrey relational analysis, desirabilityDesirability, genetic algorithmGenetic algorithm, and neural network etc. have been used for optimization of EDM based processes. This chapter first briefly introduces all the aforementioned optimization processes and comprehensively discusses their implementation and effect for optimization of EDM based processes.]

Published: Jun 26, 2019

Keywords: EDM; Wire-EDM; Optimization; Design-of-experiment; Surface roughness; Material removal rate; Fuzzy

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