Fuzzy Logic Approach to Modeling Weld Bead Geometry in ARC Welding

Weld joint quality depends on welding process settings. High-quality welds need controlled input settings. This study looks at four input settings: arc speed, wire feed to travel speed ratio, wire feed rate, and eccentricity. Tests used a full factorial design on a mild steel joint. Bead penetration, height, and width were measured. Fuzzy logic created models for these output measures. This fuzzy model predicts the output settings. Also, weld shape accuracy was checked. The inaccuracy is below 20% for bead penetration. Bead height and width inaccuracy is usually less than 10%.

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Publication Details

Published
2025-05-07
DOI
https://doi.org/10.38124/ijisrt/25apr1183
Primary Topic
Welding Techniques and Residual Stresses
Type
article
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article

Fuzzy Logic Approach to Modeling Weld Bead Geometry in ARC Welding

Penta. Shreenivasarao, U. Sathish Rao, V. Chiranjeevi, Prabhat Kumar et al.
Welding Techniques and Residual Stresses
article

Fuzzy Logic Approach to Modeling Weld Bead Geometry in ARC Welding

Penta. Shreenivasarao, U. Sathish Rao, V. Chiranjeevi, Prabhat Kumar, G. Phanindra
article en

Abstract

Weld joint quality depends on welding process settings. High-quality welds need controlled input settings. This study looks at four input settings: arc speed, wire feed to travel speed ratio, wire feed rate, and eccentricity. Tests used a full factorial design on a mild steel joint. Bead penetration, height, and width were measured. Fuzzy logic created models for these output measures. This fuzzy model predicts the output settings. Also, weld shape accuracy was checked. The inaccuracy is below 20% for bead penetration. Bead height and width inaccuracy is usually less than 10%.

Openalex Percentile: Top 91%
Welding Techniques and Residual Stresses
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