Fuzzy logic approach to predict surface roughness in powder mixed electric discharge machining of titanium alloy

Dragan Rodić (Author), Marin Gostimirović (Author), Milenko Sekulić (Author), Borislav Savković (Author), Andjelko Aleksić (Author)

Abstract

This study deals with fuzzy logic based modeling and parametric analysis in powder mixed electrical discharge machining of titanium alloys. The central composition plan was used to design the experiments considering four parameters, namely discharge current, pulse duration, duty cycle as well as graphite powder concentration. All experiments were performed with different parameter combinations and the performance, i.e., surface roughness, was evaluated. The adaptive neuro-fuzzy inference system was used to understand and define the input-output relationship. The experimental results and the model results were compared and it was found that the results accurately predicted the reactions in the erosion of titanium alloys. In addition, the model was verified using data that had not participated in the training of the model, with an error of about 10%. In addition, a fuzzy plot was used to analyze the influence of input parameters on surface roughness. It was found that the discharge current was the most important influencing parameter. Additional experiments proved the positive effect of graphite powder, which reduced the surface roughness by 27 %.

Keywords

ANFIS;discharge current;pulse duration;duty cycle;graphite powder;

Data

Language:	English
Year of publishing:	2023
Typology:	1.01 - Original Scientific Article
Organization:	UL FS - Faculty of Mechanical Engineering
UDC:	621.3
COBISS:	168505859
ISSN:	0039-2480
Views:	12
Downloads:	0
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary title:	Uporaba mehke logike za napovedovanje površinske hrapavosti po elektroerozijski obdelavi titanove zlitine s primešanim prahom
Secondary keywords:	ANFIS;tok razelektritve;trajanje impulza;impulzni faktorji;grafitni prah;
Type (COBISS):	Article
Pages:	str. 376-387
Volume:	ǂVol. ǂ69
Issue:	ǂno. ǂ9/10
Chronology:	Sept./Oct. 2023
DOI:	10.5545/sv-jme.2023.561
ID:	20386139