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2020 | OriginalPaper | Buchkapitel

Optimization of EDM Process Parameters Using Standard Deviation and Multi-objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA)

verfasst von : J. Anitha, Raja Das

Erschienen in: Intelligent Manufacturing and Energy Sustainability

Verlag: Springer Singapore

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Abstract

The process of decision making involves finding out all the attributes which are quite conflicting in nature and selecting the best alternative based on the choice of the decision maker. Multi-objective techniques can be used in the selection process. In this paper, a new multi-objective optimization method called multi-objective optimization on the basis of simple ratio analysis (MOOSRA) is used to find the best alternative. MOOSRA in combination with standard deviation is used as an improvement procedure. Standard deviation is applied to decide the weights that are used for normalizing the performance measures which are obtained from the experimental outcomes. Electric discharge machining (EDM) process has widely emerged as an outstanding method for cutting electrically conductive materials which are difficult to machine by any traditional machining process. Four EDM parameters, namely peak current (Ip), pulse on time (Ton), duty cycle (T) and voltage (V) were considered as input parameters, and material removal rate (MRR) and surface roughness (Ra) are the output parameters. MRR and surface finish are quite contradicting in nature. Higher values of MRR are required to acquire high productivity and lower values of surface roughness are required to achieve better surface quality. The objective is to maximize MRR and minimize surface roughness. The aim of the current study is to recommend optimized input parametric combination to enhance the productivity and the quality.

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Metadaten
Titel
Optimization of EDM Process Parameters Using Standard Deviation and Multi-objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA)
verfasst von
J. Anitha
Raja Das
Copyright-Jahr
2020
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-1616-0_63

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