ArticleScientific reports2024
Multi-objective optimization of wire electrical discharge machining process using multi-attribute decision making techniques and regression analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Experimental investigation and parametric optimization of machinability and surface characteristics in wire EDM of Inconel 718.Scientific reports · 2025Article
- Optimization of process parameter for green die sinking electrical discharge machining: a novel hybrid decision-making approach.Scientific reports · 2025Article
- Enhancing EDM Productivity for Plastic Injection Mold Manufacturing: An Experimental Optimization Study.Polymers · 2024Article
- Multi-objective optimization of an EDM process for Monel K-500 alloy using response surface methodology-multi-objective dragonfly algorithm.Scientific reports · 2024Article
- A profound study of damage behavior for Al 2024-T3 alloy worksheet produced by constrained groove pressing in the superior practical condition.Scientific reports · 2024Article
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Authors and funding
3 authors.
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Abstract
Wire electrical discharge machining (WEDM) is one of the most important non-traditional machining methods that is widely used in various industries. The present research work is concerned with the influences of process variables on quality of machined specimen obtained from WEDM process. The process parameters to manufacture mold structure included wire feed speed, wire tension and generator power, and in the current research, the effects of these variables on the aim factors, namely dimensional accuracy, hardness and roughness of product surface have been investigated, simultaneously. In order to obtain the optimal experiment, the multi-objective optimization with discrete solution area has been employed. Method based on the removal effects of criteria (MEREC) and weighted aggregates sum product assessment (WASPAS) techniques have been used with the aim of weighting the objective functions and discovering the best practical experiment. In the following, the regression analysis has been employed to study the effects of variables on response factors. A good correlation between the results gained from two analysis methods was observed. Based on MEREC-WASPAS hybrid technique, the weights of roughness, hardness and dimensional accuracy of machined part were calculated to about 89%, 9% and 2%, respectively. In the selected optimal experiment, the amount of wire feed speed, wire tension and generator power variables were considered to, in turn, 2 cm/s, 2.5 kg, and 10%.
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