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)

  • 2024Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite16citations

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Akhai, Shalom
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Wadhwa, Amandeep Singh
1 / 1 shared
Kumar, Harmesh
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2024

Co-Authors (by relevance)

  • Akhai, Shalom
  • Wadhwa, Amandeep Singh
  • Kumar, Harmesh
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article

Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite

  • Akhai, Shalom
  • Wadhwa, Amandeep Singh
  • Kaushik, Arishu
  • Kumar, Harmesh
Abstract

<jats:title>Abstract</jats:title><jats:p>Optimizing electric discharge machining (EDM) for aluminum/SiC<jats:sub>p</jats:sub> metal matrix composites poses challenges due to intricate machine parameters and process complexity, impacting process economy and elevating product costs. The research aims to find the optimal combination of process parameters which include pulse on-time, pulse current, duty cycle (%), gap voltage, sensitivity and flushing pressure for EDM of Al/SiC<jats:sub>p</jats:sub>-MMC using a copper electrode for the selected response factors such as material erosion rate and surface roughness, R<jats:sub>a</jats:sub>. The experiments were designed using the central composite design of response surface methodology and an advanced optimization technique known as Teaching–learning-based optimization (TLBO), is applied to find the optimal combination of process parameters to obtain maximum material erosion rate subject to the desired range of surface roughness (SR), R<jats:sub>a</jats:sub>. The combination of the high pulse on-time (i.e. 150 <jats:italic>μ</jats:italic>s) and high pulse current (i.e. 12A) results in high material removal rate with deep craters on the machined surface clearly visible in SEM images contrasting the minimized surface roughness at lower values of pulse on-time (50 <jats:italic>μ</jats:italic>s) and the pulse current (4A). Pulse on - time (T<jats:sub>on</jats:sub>) is found to be the most significant factor for material erosion rate and surface roughness with percentage contribution of 70.86 and 54.9 respectively for optimization of the response. The regression models were developed at 95% confidence level for material removal rate and surface roughness with R<jats:sup>2</jats:sup> value of 0.93 and 0.95 respectively signifying high degree of accuracy in predicting the response. Confirmation tests conducted to check the adequacy of the established models revealed that the percentage error between the predicted and experimental responses is found to be within acceptable levels. Electron discharge machining of the aluminium metal matrix composite at the optimized conditions could provide economical aspect in the aerospace and automobile industry.</jats:p>

Topics
  • impedance spectroscopy
  • surface
  • scanning electron microscopy
  • experiment
  • aluminium
  • copper
  • metal-matrix composite