Predictive modelling and optimization of WEDM parameter for Mg–Li alloy using ANN integrated CRITIC-WASPAS approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F24%3A00376389" target="_blank" >RIV/68407700:21220/24:00376389 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.heliyon.2024.e35194" target="_blank" >https://doi.org/10.1016/j.heliyon.2024.e35194</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.heliyon.2024.e35194" target="_blank" >10.1016/j.heliyon.2024.e35194</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Predictive modelling and optimization of WEDM parameter for Mg–Li alloy using ANN integrated CRITIC-WASPAS approach

Popis výsledku v původním jazyce

This work intended to improve the precision and machining efficiency of Magnesium alloy (Mg-Li-Sr) using Wire electrical discharge machining (WEDM). Mg-Li-Sr alloy is prepared through inert gas assisted stir casting route. Taguchi approach is used for experimental design for WEDM parameter such as pulse OFF time, pulse ON time, wire feed rate, servo voltage and current. L27 orthogonal array is considered to understand the influence of control parameter such as Kerf Width (KW), Roughness of the surface (Ra), Material Removal Rate (MRR). Integration of the CRITIC (Criteria Importance Through Intercriteria Correlation) -WASPAS (Weighted Aggregated Sum Product Assessment) multi-objective optimization method with Artificial Neural Network (ANN) modelling with different network structure for prediction and optimization is a novel approach that significantly improves prediction accuracy and machining outcomes. The developed ANN model with better R2 value of 99.9 % has better ability for prediction while correlated with formulated conventional regression equation. The error percentages identified through confirmation tests for regression and ANN models are Ra - 8.5 % and 3.4 %, MRR - 5.9 % and 2.8 %, KW - 6.7 % and 2.2 % respectively. Optimal output response attained by CRITICWASPAS approach yields surface roughness of 4.62 mu m, material removal rate of 0.073 g/min and kerf width of 0.388 mu m.

Název v anglickém jazyce

Predictive modelling and optimization of WEDM parameter for Mg–Li alloy using ANN integrated CRITIC-WASPAS approach

Popis výsledku anglicky

This work intended to improve the precision and machining efficiency of Magnesium alloy (Mg-Li-Sr) using Wire electrical discharge machining (WEDM). Mg-Li-Sr alloy is prepared through inert gas assisted stir casting route. Taguchi approach is used for experimental design for WEDM parameter such as pulse OFF time, pulse ON time, wire feed rate, servo voltage and current. L27 orthogonal array is considered to understand the influence of control parameter such as Kerf Width (KW), Roughness of the surface (Ra), Material Removal Rate (MRR). Integration of the CRITIC (Criteria Importance Through Intercriteria Correlation) -WASPAS (Weighted Aggregated Sum Product Assessment) multi-objective optimization method with Artificial Neural Network (ANN) modelling with different network structure for prediction and optimization is a novel approach that significantly improves prediction accuracy and machining outcomes. The developed ANN model with better R2 value of 99.9 % has better ability for prediction while correlated with formulated conventional regression equation. The error percentages identified through confirmation tests for regression and ANN models are Ra - 8.5 % and 3.4 %, MRR - 5.9 % and 2.8 %, KW - 6.7 % and 2.2 % respectively. Optimal output response attained by CRITICWASPAS approach yields surface roughness of 4.62 mu m, material removal rate of 0.073 g/min and kerf width of 0.388 mu m.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20501 - Materials engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Heliyon

ISSN

2405-8440

e-ISSN

2405-8440

Svazek periodika

10

Číslo periodika v rámci svazku

15

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

15

Strana od-do

1-15

Kód UT WoS článku

001285965600001

EID výsledku v databázi Scopus

2-s2.0-85199925406