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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Materials Map under construction

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%

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Publications (1/1 displayed)

  • 2022RSM Modelling, and Multi-Object Optimization of Turning Parameters for Polyamide (PA66) Using PCA and PCA Coupled with TOPSIS7citations

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Belhadi, Salim
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Yallese, Mohamed Athmane
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Boucherit, Septi
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Zaidi, Ahmed
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2022

Co-Authors (by relevance)

  • Belhadi, Salim
  • Yallese, Mohamed Athmane
  • Boucherit, Septi
  • Zaidi, Ahmed
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article

RSM Modelling, and Multi-Object Optimization of Turning Parameters for Polyamide (PA66) Using PCA and PCA Coupled with TOPSIS

  • Belhadi, Salim
  • Kaddeche, Mounia
  • Yallese, Mohamed Athmane
  • Boucherit, Septi
  • Zaidi, Ahmed
Abstract

In this study, turning operations on polyamide PA66 with cemented carbide insert, were organized according to the L27 Taguchi design whose objective is the analysis of the cutting parameters on the output parameters (Surface roughness and cutting force), as well as on the calculated parameter (material removal rate (Q)). The results revealed that surface roughness is highly impacted by the feed rate, which accounts for more than 68% of the variance, followed by the cutting speed and finally the depth of cut. With respect to cutting force, depth of cut and feed rate have emerged as the most important terms.A mathematical model is then created to predict the surface roughness and cutting force. Finally, the optimal cutting regime leading to good surface quality with less cutting force and maximum productivity was examinedusing two multi criteria optimization methods namely PCA and PCA coupled with TOPSIS. The total desirability function was used as a decision criterion for evaluating the two optimization methods. The results demonstrate the potential superiority of the PCA-TOPSIS method over the PCA method.

Topics
  • impedance spectroscopy
  • surface
  • laser emission spectroscopy
  • carbide