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 (2/2 displayed)

  • 2023Multi objective Optimizations of friction stir welding process parameters for reinforcement of copper particles in aluminum alloy using Taguchi based grey relational analysis (GRA) and ANOVA.3citations
  • 2023Novel Algebraic Matrix Method Used to Generate Linear Equation for Surface Roughness and Material Removal Rate during Wet/Dry Turning Operation on MMCs Al6061-T6/SiCcitations

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Unde, Sanket S.
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Sur, Anirban
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Jadhav, Pradeep
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Dhabale, Vrushali R.
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Dhabale, Rahul B.
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Shaikh, Sarfaraj
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Mate, Umesh G.
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2023

Co-Authors (by relevance)

  • Unde, Sanket S.
  • Sur, Anirban
  • Jadhav, Pradeep
  • Dhabale, Vrushali R.
  • Dhabale, Rahul B.
  • Shaikh, Sarfaraj
  • Mate, Umesh G.
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article

Novel Algebraic Matrix Method Used to Generate Linear Equation for Surface Roughness and Material Removal Rate during Wet/Dry Turning Operation on MMCs Al6061-T6/SiC

  • Unde, Sanket S.
  • Kurkute, Vijay K.
  • Shaikh, Sarfaraj
  • Mate, Umesh G.
  • Dhabale, Vrushali R.
  • Dhabale, Rahul B.
Abstract

<jats:title>Abstract</jats:title><jats:p>Stir casting process is well known for reinforcement of ceramic particle in aluminium. Due to improved properties of Al6061-T6/SiC particulate metal matrix composites have attracted by industry as well as received wider attention of material expertise. The purpose of this study is to evaluate the turning process parameters through algebraic matrix which is unique approach. Also studied effects of spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius on modifier element for instance surface roughness Ra and material removal rate MRR in both dry and wet condition. In addition to optimize the turning process parameters are on Al6061-T6/SiC 3% and 6% with a coated tungsten tool. The experimental runs are designed using the taguchi based multiple factorial design DOE and their outcomes are analyzed using Analysis of Variance ANOVA. Mathematical models are established using algebraic matrix to represent the relationship among turning process parameters as independent variables, surface roughness and material removal rate as dependent variables. For every experimental run, a same cutting insert was used to encourage accurate reporting of the surface roughness and material removal rate. The statistical variations revealed that the main effect of spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius are influenced the surface roughness and material removal rate. Moreover, Built-up-edge BUE formation was observed at every combinations of machining parameters such as spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius which affected the surface quality negatively. The proximity of predicted results and experimental results provide proof that the algebraic matrix – DOE method has successfully established the predictive models. It is strongly suggested SiC silicon carbide 3% and 6% are successfully reinforced in Al6061 as well as optimize turning process parameters in wet condition than dry condition. Mathematical models for surface roughness and material removal rate are found to be statistically significant in wet condition.</jats:p>

Topics
  • impedance spectroscopy
  • surface
  • aluminium
  • carbide
  • Silicon
  • casting
  • tungsten
  • metal-matrix composite