Tensile shear strength and elongation of FSW parts predicted by Taguchi-based fuzzy logic

Mustafa Kemal Kulekci; Ugur Esme; Seref Ocalir; Deniz Ustun; Yigit Kazancoglu

doi:10.3139/120.110856

Published by De Gruyter March 29, 2016

Tensile shear strength and elongation of FSW parts predicted by Taguchi-based fuzzy logic

Zugscherfestigkeit und Verlängerung von rührreibgeschweißten Teilen vorhergesagt mittels Taguchi-basierter Fuzzy-Logik

Mustafa Kemal Kulekci , Ugur Esme , Seref Ocalir , Deniz Ustun and Yigit Kazancoglu

From the journal Materials Testing

https://doi.org/10.3139/120.110856

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Abstract

This paper represents the fuzzy logic model for modeling and prediction of tensile shear strength and percent elongation of parts produced by the friction stir welding (FSW) process. A Taguchi L₁₆ orthogonal array is used to plan and select the parameters and their levels. Weld travel speed, pin diameter and tool rotation are used as input variables. Therefore, a three-input and two-output fuzzy model is used to correlate these variables to the responses of tensile shear strength and percent elongation using the fuzzy rules generated based on experimental results. Close agreement is obtained between the fuzzy predicted and experimental results with the correlation coefficients of 0.931 and 0.895 for tensile shear strength and elongation, respectively.

Kurzfassung

In dem vorliegenden Beitrag wird ein Modell basierend auf Fuzzy-Logik vorgestellt, mit dem die Scherzugfestigkeit und die prozentuale Verlängerung von Teilen modelliert und vorhergesagt werden kann, die mit dem Rührreibschweißprozess (Friction Stir Welding (FSW)) hergestellt wurden. Hierzu wurde ein L₁₆ orthogonales Taguchi-Array verwendet, um die Parameter und ihre Werte zu planen und auszuwählen. Die Schweißgeschwindigkeit, der Pin-Durchmesser und die Werkzeugrotation wurden als Inputvariablen ausgewählt. Daher wurde ein Fuzzy-Modell mit drei Input-Parametern und drei Output-Parametern und ihren entsprechenden Werten verwendet, um diese Variablen mit den Antworten der Scherzugfestigkeit und der prozentualen Verlängerungen zu korrelieren, wobei die Fuzzy-Regeln verwendet wurden, die basierend auf experimentellen Ergebnissen ermittelt wurden. Es ergab sich eine enge Übereinstimmung der mit Fuzzy-Logik vorhergesagten mit den experimentellen Ergebnissen mit den Korrelationskoeffizienten von 0.931 für die Scherzugfestigkeit bzw. 0.895 für die Verlängerung.

*Correspondence Address, Associate Prof. Dr. Ugur Esme, Department of Manufacturing Engineering, Engineering Faculty, Mersin University, Institute of Natural and Applied Sciences, 33400, Tarsus-Mersin/Turkey. E-mail: uguresme@gmail.com

Mustafa Kemal Kulekci is Professor in the Department of Mechanical Education, Faculty of Tarsus Technical Education, Mersin University, Turkey. He obtained his PhD degree from Gazi University, Ankara, Turkey in 2000. His research interests include CAD/CAM, friction stir welding, machinability of materials and water-jet cutting applications.

Assoc. Prof. Dr. Ugur Esme is working at Mersin University, Tarsus Technical Education Faculty, Turkey. He obtained his PhD degree from the Department of Mechanical Engineering of Cukurova University, Turkey, in 2006. His research areas include CAD/CAM technology, welding, modeling, designing and water jet cutting applications.

Seref Ocalir, born in 1982, works as a research assistant at the Graduate School of Natural and Applied Sciences, Mersin University, Turkey. He obtained his BSc degree and MSc degree from Mersin University, Turkey, in 2006 and in 2009, respectively. His research interests include friction stir welding, machinability of materials, design and corrosion.

Deniz Ustun has completed his BS degree in the Department of Computer Science Engineering of Istanbul University, Turkey in 2001. He received his MSc degree in Electrical and Electronics Engineering from Mersin University, Turkey in 2009. Since 2010, he has been working on his PhD degree in the same department. His current research interests are artificial neural networks and computer modeling of heuristic optimization algorithms.

Yigit Kazancoglu is Associate Professor İn the Department of Business Administration, Izmir University of Economics, Turkey. He received his BS degree from the Industrial Engineering Department of Eastern Mediterranean University, Famagusta, North Cyprus, Turkey, his MBA degree from Coventry Univertsity, UK, and Izmir University of Economics, Turkey, and PhD degree in Operations Management from Ege University, Izmir, Turkey. His work at the university involves giving courses and conducting research in the areas of production planning, operations management and operations research. He is the author of a number of international publications on these subjects.

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Published Online: 2016-03-29

Published in Print: 2016-04-04

Tensile shear strength and elongation of FSW parts predicted by Taguchi-based fuzzy logic

Abstract

Kurzfassung

References

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