A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process

Micro-electrical discharge machining (μ-EDM) has come up as an effective material removal process for the manufacturing of miniaturized components in modern industries. The performance and quality of the μ-EDM process mainly depend on the combination of process parameters selected. This paper attemp...

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Main Author: Partha Protim Das
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Engineering Proceedings
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Online Access:https://www.mdpi.com/2673-4591/59/1/112
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author Partha Protim Das
author_facet Partha Protim Das
author_sort Partha Protim Das
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description Micro-electrical discharge machining (μ-EDM) has come up as an effective material removal process for the manufacturing of miniaturized components in modern industries. The performance and quality of the μ-EDM process mainly depend on the combination of process parameters selected. This paper attempts to demonstrate the applicability of three well-known multi-criteria decision-making (MCDM) techniques, including the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), multi-attributive border approximation area comparison (MABAC), and complex proportional assessment (COPRAS) methods, separately hybridized with the grey wolf optimization (GWO) algorithm. The proposed hybrid optimization approaches are applied to find the optimal parametric setting of a μ-EDM process during machining on a stainless steel shim as the work material. Feed rate, capacitance, and voltage were selected as the machining control parameters, while material removal rate, surface roughness, and tool wear ratio were selected as the responses. The polynomial regression (PR) meta-models are observed as the inputs to these hybrid optimizers. The results obtained are further compared to the traditional weighted sum multi-objective optimization (WSMO) approach, which suggests that all the considered MCDM-PR-GWO approaches outperform traditional PR-WSMO-GWO approaches in obtaining better machining performance measures.
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spelling doaj-art-afd3d5ae3aa24fb388da69e5c3efc4b22025-08-20T03:43:21ZengMDPI AGEngineering Proceedings2673-45912023-12-0159111210.3390/engproc2023059112A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM ProcessPartha Protim Das0Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar 737136, IndiaMicro-electrical discharge machining (μ-EDM) has come up as an effective material removal process for the manufacturing of miniaturized components in modern industries. The performance and quality of the μ-EDM process mainly depend on the combination of process parameters selected. This paper attempts to demonstrate the applicability of three well-known multi-criteria decision-making (MCDM) techniques, including the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), multi-attributive border approximation area comparison (MABAC), and complex proportional assessment (COPRAS) methods, separately hybridized with the grey wolf optimization (GWO) algorithm. The proposed hybrid optimization approaches are applied to find the optimal parametric setting of a μ-EDM process during machining on a stainless steel shim as the work material. Feed rate, capacitance, and voltage were selected as the machining control parameters, while material removal rate, surface roughness, and tool wear ratio were selected as the responses. The polynomial regression (PR) meta-models are observed as the inputs to these hybrid optimizers. The results obtained are further compared to the traditional weighted sum multi-objective optimization (WSMO) approach, which suggests that all the considered MCDM-PR-GWO approaches outperform traditional PR-WSMO-GWO approaches in obtaining better machining performance measures.https://www.mdpi.com/2673-4591/59/1/112?-EDM processMCDMGWOmeta-modeloptimization
spellingShingle Partha Protim Das
A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process
Engineering Proceedings
?-EDM process
MCDM
GWO
meta-model
optimization
title A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process
title_full A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process
title_fullStr A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process
title_full_unstemmed A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process
title_short A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process
title_sort hybrid mcdm grey wolf optimizer approach for multi objective parametric optimization of μ edm process
topic ?-EDM process
MCDM
GWO
meta-model
optimization
url https://www.mdpi.com/2673-4591/59/1/112
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