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Licensed Unlicensed Requires Authentication Published by De Gruyter July 3, 2015

Grey-based fuzzy algorithm for the optimization of the ball burnishing process

Ein Grey-basierter Fuzzy-Algorithmus zur Optimierung des Kugelpolierprozesses
  • Ugur Esme , Mustafa Kemal Kulekci , Deniz Ustun , Funda Kahraman and Yigit Kazancoglu
From the journal Materials Testing


In the present study, Grey based fuzzy algorithm was used for the optimization of complex multiple performance characteristics of the ball burnishing process. Experiments have been planned according to Taguchi's L16 orthogonal design matrix. Burnishing force, number of passes, feed rate and burnishing speed were selected as input parameters, whereas surface roughness and microhardness were selected as output responses. Using Grey relation analysis (GRA), Grey relational coefficient (GRC) and Grey relation grade (GRG) were obtained. Then, Grey-based fuzzy algorithm was applied to obtain Grey fuzzy reasoning grade (GFRG). Analysis of variance (ANOVA) was carried out to find the significance and contribution of parameters on multiple performance characteristics. Finally, a confirmation test was applied at the optimum level of GFRG to validate the results. The results also show the feasibility of the Grey-based fuzzy algorithm for continuous improvement in product quality in complex manufacturing processes.


In der diesem Beitrag zugrunde liegenden Studie wurde ein Grey-basierter Fuzzy-Algorithmus eingesetzt, um die komplexen Performanzeigenschaften des Kugelpolierprozesses zu optimieren. Die Experimente wurden mittels der Taguchi-Methode entsprechend mit Hilfe von einer L16 orthogonaler Designmatrix geplant. Die Polierkraft, die Anzahl der Durchgänge, die Vorschubrate und die Poliergeschwindigkeit wurden als Inputparameter ausgewählt, wobei die Oberflächenhärte und die Mikrohärte als Output-Antworten ausgesucht wurden. Unter Verwendung der Grey-Relations-Analyse (Grey Relation Analysis – GRA), wurden der Grey Relationskoeffizient (Grey Relational Coefficient – GRC) und der Grey Relationsgrad (Grey Relation Grade – GRG) ermittelt. Daraufhin wurde der Grey-basierte Fuzzy-Algorithmus angewendet, um den Grey Fuzzy Reasoning Grade (GFRG) zu ermitteln. Es wurde eine Varianzanalyse (ANOVA) durchgeführt, um die Signifikanz und den Beitrag der Parameter hinsichtlich der vielfachen Performanzcharakteristik herauszufinden. Schließlich wurde ein Bestätigungstest auf dem optimalen GFRG-Niveau durchgeführt, um die Ergebnisse zu validieren. Die Ergebnisse zeigen auch, dass die Anwendung des Grey-basierten Fuzzy-Algorithmus für eine kontinuierliche Produktoptimierung in komplexen Produktionsprozessen möglich ist.

§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:

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

Mustafa Kemal Kulekci is Professor in the Faculty of Tarsus Technology Engineering, Department of Automotive Engineering, Mersin University, Mersin, 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.

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 network and computer modeling of heuristic optimization algorithms.

Funda Kahraman is Associate Professor at Mersin University, Tarsus Technology Faculty, Department of Mechatronic Engineering. She received her BS and MBA degrees from İstanbul Technical University, Engineering Faculty, Department of Metallurgical Engineering, Turkey, PhD degree from Cukurova University, Engineering and Architecture Faculty, Department of Mechanical Engineering, Turkey. Her research areas include metallurgy, welding and design. She is the author of a number of publications on these subjects.

Yigit Kazancoglu is Associate Professor at Izmir University of Economics, Department of Business Administration, Turkey. He received his BS degree from the Industrial Engineering Department of Eastern Mediterranean University, Cyprus, MBA degree from Coventry University, UK, and Izmir University of Economics, Turkey, and PhD degree from Ege University, Izmir, Turkey in Operations Management. 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: 2015-07-03
Published in Print: 2015-07-15

© 2015, Carl Hanser Verlag, München

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