Modeling and Analysis of Process Parameters on State Variables in WEDM of TiB₂ Nanocomposite Ceramic

Abstract:

The main objective of the present research is to find the influence of process parameters on the state variables (i.e., surface roughness and material removal rate) in Wire Electrical Discharge Machining (WEDM) of Titanium Diboride (TiB2) nanocomposite ceramics. This work adopted an L32 orthogonal array based on Taguchi method for design of experiments. Statistically evaluating the obtained data is carried out by using the analysis of variance, signal to noise and artificial neural network techniques. Then, the effects of process parameters on the surface roughness and material removal rate are studied. Finally, the Multilayer Perceptron (MLP) neural network is used to model the WEDM of TiB2 nanocomposite ceramic. The obtained results have demonstrated very good modeling capacity of the proposed neural network. Furthermore, analyses have appropriately presented the influence of process parameters on state variables.

• Periodical: Applied Mechanics and Materials (Volumes 34-35)
• Pages: 631-635
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.34-35.631
• Online since: October 2010
• Authors: M. Reza, Soleymani Yazdi, Hoseyn Dehghan, Hoda Amini
• Keywords: Neural Network Modeling, Statistical Analysis, TiB₂, WEDM

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