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Prediction of the effect of vacuum sintering conditions on porosity and hardness of porous NiTi shape memory alloy using ANFIS

Authors
Journal
Computational Materials Science
0927-0256
Publisher
Elsevier
Publication Date
Volume
40
Issue
3
Identifiers
DOI: 10.1016/j.commatsci.2007.01.007
Keywords
  • Fuzzy Clustering
  • Anfis Method
  • Powder Metallurgy
  • Combustion Synthesis
  • Sintering
  • Niti
  • Sma

Abstract

Abstract A neuro-fuzzy model was utilized to predict the hardness and porosity of NiTi shape memory alloy produced by vacuum sintering of powder mixture. Compaction pressure, sintering time and sintering temperature were chosen as input nodes. This procedure allowed successful prediction of porosity and hardness of the NiTi SMA samples. Absolute relative errors were at most 6.3% for hardness and 4.8% for porosity. Mean relative values were 3.4% for hardness and 3.3% for porosity. Results showed that the increasing of the values of input parameters affected outputs, linearly. The most significant parameters influencing the porosity content and the hardness of the under-vacuum combustion-synthesized NiTi specimens were sintering temperature and compaction pressure.

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