Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2022Dry Wear Behaviour of the New ZK60/AlN/SiC Particle Reinforced Composites8citations
  • 2021Statistical and Experimental Investigation of Hardened AISI H11 Steel in CNC Turning with Alternative Measurement Methods3citations
  • 2021Statistical and Experimental Investigation of Hardened AISI H11 Steel in CNC Turning with Alternative Measurement Methods3citations

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Ahlatci, Hayrettin
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Turen, Yunus
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Şahin, Emrah
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2022
2021

Co-Authors (by relevance)

  • Ahlatci, Hayrettin
  • Turen, Yunus
  • Şahin, Emrah
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article

Statistical and Experimental Investigation of Hardened AISI H11 Steel in CNC Turning with Alternative Measurement Methods

  • Esen, İsmail
Abstract

<jats:p>In recent years, hard turning, an alternative to grinding, which provides low cost and good surface quality, has become an attractive method to the manufacturers. In this experimental study, AISI H11 hot work tool steel that has been hardened up to 50 HRC was subjected to hard turning tests with coated carbide tooling. The analyses were carried out by applying response surface methodology with the analysis of variance method. A total of 27 experiments were modeled utilizing <jats:inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"><msup><mrow><mn>3</mn></mrow><mrow><mn>3</mn></mrow></msup></math></jats:inline-formula> full factorial design and were carried out using a CNC lathe. The effects of the cutting parameters on surface roughness, energy consumption, electric current value, and sound intensity level were investigated. Optimum cutting parameters and levels were determined according to these optimum values. The relationship between cutting parameters and output variables was analyzed with two-dimensional and three-dimensional graphics. The results show that while the most effective parameter on the surface roughness was the feed rate (88.62%), the most effective parameter on the sound intensity level was the cutting speed (44.92%). In addition, the cutting depth was the most effective parameter on both electric current (52.20%) and energy consumption (46.15%). Finally, regression coefficients were determined as a mathematical model, and it was observed that this estimated model gave results that were very similar to those achieved with real experiment (correlation values: 97.64% for surface roughness, 98.72% for energy consumption, 97.22% for electric current value, and 91.38% for sound intensity level).</jats:p>

Topics
  • surface
  • experiment
  • grinding
  • carbide
  • two-dimensional
  • hot-work steel