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Licensed Unlicensed Requires Authentication Published by De Gruyter March 7, 2022

Investigation of deep-drilled micro-hole profiles in Hadfield steel

Untersuchung von tiefgebohrten Mikrolochprofilen in einem Hadfield-Stahl
  • Volkan Yılmaz

    Dr. Volkan Yılmaz, born in 1983, studied at the Kazan Vocational High School at Gazi University, Ankara, Turkey, and received his PhD from the Department of Mechanical Education, Gazi University, in 2013. His research areas include CAD/CAM technology, manufacturing technology, optimization, modeling, design, conventional and alternative cutting applications.

    , Murat Sarıkaya

    Assist. Prof. Dr. Murat Sarıkaya, born in 1984, is a lecturer in the Department of Mechanical Engineering, Faculty of Engineering and Architecture, Sinop University, in Sinop, Turkey. He received his PhD degree from the Department of Mechanical Education, Gazi University, Ankara, Turkey in 2014. His areas of interest include manufacturing technologies, machinability of materials, design of experiments, optimization and modeling.

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    and Hakan Dilipak

    Assoc. Prof. Dr. Hakan Dilipak, born in 1971, is Associate Professor at University of Gazi in Ankara, Turkey. He received his PhD degree from the Department of Mechanical Education of Gazi University in 2001. His areas of interest include CNC, CAD/CAM, machinability of materials, sheet metal molding, casting, process planning and computer-aided programming.

From the journal Materials Testing

Abstract

Hadfield steel, due to its high manganese content, is difficult to drill and work-hardens very quickly. In this study, Hadfield steel material was drilled with micro-size deep holes using the electrical discharge machining (EDM) technique, and hole diameter values were examined for specific machining parameters. Experiments were carried out with three different discharge currents (6, 12 and 24 A), three different electrode rotational speeds (200, 400 and 600 rev × min-1), three different pulse durations (12, 50 and 100 µs), a fixed dielectric spray pressure (40 bars) and a fixed pulse interval (3 µs). It was determined that the hole profiles obtained following the tests are directly related to the machining parameters, and that the resulting average overcut (AOC) and taper (Tp) values increased with discharge current, electrode rotational speed and pulse duration. Analysis of variance (ANOVA) conducted demonstrates that pulse duration is the dominant parameter affecting AOC, whereas pulse duration has the highest effect on Tp. When determination coefficients and normal probability plots were compared for the mathematical models obtained from analyses conducted for the prediction of test values, it was observed that the models obtained by quadratic regression analysis exhibited a better performance than the models produced by linear regression analysis.

Abstract

Aufgrund seines hohen Mangangehalts ist Hadfield-Stahl schwer zu bohren und verfestigt sich sehr schnell. In der diesem Beitrag zugrunde liegenden Studie wurden in einen Hadfield-Stahl tiefe Mikrolöcher mittels Funkenerosion bei verschiedenen Bearbeitungsparametern gebohrt, wobei die entsprechenden Veränderungen der Lochgeometrie untersucht wurden. Innerhalb dieses Rahmens wurden Versuche mit drei verschiedenen Entladungsstromstärken (6, 12 und 24 A), drei verschiedenen Elektrodenrotationsgeschwindigkeiten (200, 400 und 600 U × min-1), drei verschiedenen Pulsdauern (12, 50 und 100 µs), einem stabilen Sprühdruck des Dielektrikums (40 bar) und einem stabilen Pulsinterval (3 µs) durchgeführt. Es wurde festgestellt, dass die Lochprofile, die nach den Versuchen erhalten wurden, in direktem Bezug zu den Bearbeitungsparametern stehen und dass der durchschnittliche radiale Overcut (AOC) sowie der Dimensionsfehler (Tp) mit der Entladungsstromstärke, der Elektrodenrotationsgeschwindigkeit und der Pulsdauer zunahmen. Entsprechend der durchgeführten ANOVA-Analyse zeigte sich, dass die Pulsdauer der einflussreichste Parameter bezüglich des durchschnittlichen radialen Overcuts ist. Wohingegen die Pulsdauer der effektivste Parameter bezüglich des Dimensionsfehlers ist. Die mathematischen Modelle aus der quadratischen Regressionsanalyse zeigten eine bessere Performance als ein lineares Regressionsmodell bei der Vorhersage der Testwerte der Bestimmungskoeffizienten und der Normalverteilungsdiagramme der Residuen.


Assistant Prof. Dr. Murat Sarıkaya Department of Mechanical Engineering Sinop University 57030 Sinop, Turkey

About the authors

Dr. Volkan Yılmaz

Dr. Volkan Yılmaz, born in 1983, studied at the Kazan Vocational High School at Gazi University, Ankara, Turkey, and received his PhD from the Department of Mechanical Education, Gazi University, in 2013. His research areas include CAD/CAM technology, manufacturing technology, optimization, modeling, design, conventional and alternative cutting applications.

Assist. Prof. Dr. Murat Sarıkaya

Assist. Prof. Dr. Murat Sarıkaya, born in 1984, is a lecturer in the Department of Mechanical Engineering, Faculty of Engineering and Architecture, Sinop University, in Sinop, Turkey. He received his PhD degree from the Department of Mechanical Education, Gazi University, Ankara, Turkey in 2014. His areas of interest include manufacturing technologies, machinability of materials, design of experiments, optimization and modeling.

Assoc. Prof. Dr. Hakan Dilipak

Assoc. Prof. Dr. Hakan Dilipak, born in 1971, is Associate Professor at University of Gazi in Ankara, Turkey. He received his PhD degree from the Department of Mechanical Education of Gazi University in 2001. His areas of interest include CNC, CAD/CAM, machinability of materials, sheet metal molding, casting, process planning and computer-aided programming.

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Published Online: 2022-03-07

© 2016 Carl Hanser Verlag, München

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