Accessible Requires Authentication Published by De Gruyter November 15, 2018

Performance of coated and uncoated carbide/cermet cutting tools during turning

Verhalten von beschichteten und unbeschichteten Karbid/Cermet- Schneidwerkzeugen beim Drehen
Hasan Basri Ulas, Musa Bilgin, Huseyin Kursad Sezer and Murat Tolga Ozkan
From the journal Materials Testing

Abstract

Historically, cutting force and surface roughness are known to be important performance indicators in conventional machining operations and are mainly affected by material type and the choice of cutting tool. One well-known method to improve cutting tool performance is covering these tools with durable ceramic coatings to protect them from wear and thermal degradation. This work elucidates the advantage of Al2O3 and TiN coatings and presents important performance improvements in turning operation. Process parameters such as cutting speed, feed rate, cutting depth and tip radius were taken into consideration in a total of 540 experiments. The design of the experiment and a statistical analysis were performed to reveal significant process parameters. A special experimental setup was designed to measure in-situ cutting forces. The surface roughness of the machined surfaces was measured. An artificial neural network model was developed to predict optimum performance parameters.

Kurzfassung

Die Schnittkräfte und die Oberflächenrauheit stellen seit jeher wichtige Indikatoren für das werkstoffverhalten bei konventionellen maschinellen Bearbeitungsprozessen dar. Sie werden hauptsächlich durch den Materialtyp und die Auswahl des Schneidwerkzeuges beeinflusst. Ein bekanntes Verfahren zur Verbesserung des verhaltens von Schneidwerkzeugen besteht darin, sie mit haltbaren Keramikbeschichtungen zu versehen, um sie vor Verschleiß und thermischer Degradation zu schützen. Die diesem Beitrag zugrunde liegende Arbeit zeigt den Vorteil von Al2O3- und TiN-Beschichtungen und stellt eine wichtige Verbesserung des Verhaltens bei Drehprozessen dar. Es wurden die Prozessparamter, wie die Drehgeschwindigkeit, die Vorschubrate, die Schnitttiefe und der Spitzenradius in insgesamt 540 Versuchen berücksichtigt. Es wurde ein experimentelles Design und eine statistische Analyse durchgeführt, um signifikante Prozessparameter zu ermitteln. Ein besonderer Versuchsaufbau wurde gewählt, um die Schnittkräfte in-situ zu messen. Die Oberflächenrauheit der maschinell bearbeiteten Oberflächen wurde gemessen. Es wurde ein Modell auf der Basis eines neuronalen Netzes entwickelt um die optimalen Parameter vorherzusagen.


*Correspondence Address, Assoc. Prof. Dr. Murat Tolga Ozkan, Industrial Design Engineering Department, Faculty of Technology, Gazi University, 06500 Ankara, Turkey, E-mail: ;

Asistant Prof. Dr. Hasan Basri Ulas, born in 1971, studied Manufacturing at the Faculty of Technical Education, Department of Machine Engineering, University of Gazi, Ankara, Turkey and completed his MSc and PhD at the same university. Currently, he is employed as Assistant Professor in the Department of Manufacturing Engineering. His main fields of interest are manufacturing, system modeling, experimental techniques.

Lecturer Musa Bilgin, born in 1985, is employed at the Ankara Chamber of Industry First Organized Industrial Zone Vocational School of Hacettepe University, Ankara, Turkey. He received his M.Sc. in Mechanical Education from the University of Gazi, Ankara, Turkey in 2012. He is currently a Ph. D. student in Manufacturing Engineering from the same university. His main fields of interest are manufacturing, mechanical design and welding.

Assistant Prof. Dr. Huseyin Kursad Sezer, born in 1979, studied Mechanical Engineering at the Faculty of Engineering, University of Erciyes, Kayseri, Turkey and completed his MPhil followed by PhD at the University of Manchester, UK. Currently, he is employed as Assistant Professor in the Department of Industrial Design Engineering, Faculty of Technology, University of Gazi, Ankara. His main fields of interest are product design, manufacturing processes, finite element/volume modelling, laser processing and reverse engineering and additive manufacturing.

Associate Prof. Dr. Murat Tolga Ozkan, born in 1971, studied Manufacturing at the Faculty of Technical Education, Department of Machine, University of Gazi, Ankara, Turkey and completed his MSc and PhD at the same university. Currently, he is employed as Associate Professor in the Department of Industrial Design Engineering, Faculty of Technology, University of Gazi, Ankara. His main fields of interest are manufacturing, machine design, finite element method, artificial neural network, mechanisms and biomechanics.


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Published Online: 2018-11-15
Published in Print: 2018-09-30

© 2018, Carl Hanser Verlag, München