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Design Optimization of Prosthesis Hip Joint using FEM and TAGUCHI - Om Shankar Prajapati - Bog

Bag om Design Optimization of Prosthesis Hip Joint using FEM and TAGUCHI

Using Taguchi method total experiments are required are L16 which are simulated in ANSYS FEM solver (Version-14.5). Proper FEM simulation techniques are applied for these simulation cases and the modeling steps are also developed for this research study. After proper simulation of these cases two responses are selected to optimize this base design for further study. The two response selected from this study is von-misses stress and body weight. In present study various type of analysis is performed both cases like signal to noise ratio analysis, analysis of variance analysis, model equation generation, optimization of this model equation for stress and body weight of hip joint. Visual analysis is also present in this research study. All these major outcomes are present in this research study. Rank identification of factors are also present in this study. The signal to noise ratio analysis for stress shows that the best factor is ball diameter whereas worst factor is neck length of hip joint.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9786200115409
  • Indbinding:
  • Paperback
  • Sideantal:
  • 116
  • Udgivet:
  • 27. maj 2019
  • Størrelse:
  • 229x152x7 mm.
  • Vægt:
  • 181 g.
  • 2-3 uger.
  • 11. december 2024

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Beskrivelse af Design Optimization of Prosthesis Hip Joint using FEM and TAGUCHI

Using Taguchi method total experiments are required are L16 which are simulated in ANSYS FEM solver (Version-14.5). Proper FEM simulation techniques are applied for these simulation cases and the modeling steps are also developed for this research study. After proper simulation of these cases two responses are selected to optimize this base design for further study. The two response selected from this study is von-misses stress and body weight. In present study various type of analysis is performed both cases like signal to noise ratio analysis, analysis of variance analysis, model equation generation, optimization of this model equation for stress and body weight of hip joint. Visual analysis is also present in this research study. All these major outcomes are present in this research study. Rank identification of factors are also present in this study. The signal to noise ratio analysis for stress shows that the best factor is ball diameter whereas worst factor is neck length of hip joint.

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