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 (1/1 displayed)

  • 2014Simultaneous optimization of multiple responses in turning operations7citations

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Subbaiah, K. Venkata
1 / 2 shared
Rao, Ch Srinivasa
1 / 2 shared
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2014

Co-Authors (by relevance)

  • Subbaiah, K. Venkata
  • Rao, Ch Srinivasa
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article

Simultaneous optimization of multiple responses in turning operations

  • Subbaiah, K. Venkata
  • Rao, Ch Srinivasa
  • Kaladhar, M.
Abstract

<jats:p> Making real-life decisions regarding selection of optimum parameters in machining of materials, especially when faced with conflicting objectives, is a tough task. Multi-objective methods are usually used to deal with such problems. This article applies grey relational analysis to the multi-responses that were obtained during turning of AISI 304 austenitic stainless steels on a computer numerical control lathe. The experiments were conducted using the Taguchi design of experiments technique. In grey relational theory, a grey relational grade is found such that it indicates an optimum level of machining parameters that produce smaller magnitudes of surface roughness, flank wear, tool vibrations and a higher magnitude of material removal rate. The combination of the following machining parameters produces a better turning performance: speed of 210 m/min, feed rate of 0.15 mm/rev, depth of cut of 1.0 mm and a nose radius of 0.4 mm. The significant factors affecting the overall responses of turning process were evaluated by analysis of variance. Thereafter, optimum values of overall responses were predicted. Finally, a second-order multi-objective model was developed, which relates the machining parameters to the grey relational grade using response surface methodology. </jats:p>

Topics
  • impedance spectroscopy
  • surface
  • stainless steel
  • theory
  • experiment