Optimization of Green Sand Casting Process Parameters by Artificial Neural Network

Autores

  • Priyank V. Parekh Department of Mechanical Engineering, Shantilal Shah Government Engineering College, Bhavnagar, Gujarat, India
  • J. A Vadher Government Engineering College, Palanpur, Gujarat, India

Palavras-chave:

ANN, casting defects, NN tool, blow holes, porosity

Resumo

In this paper, artificial neural network (ANN) is used to train the network which can predict the casting defect. L27 orthogonal array is used as input matrix for training of neural network. NN tool is used to train the network for prediction of defects. Major defects observed on shop floor were; misrun, blowholes, inclusions and porosity. Moisture, permeability, LOI, compressive strength, volatile content, vent holes, pouring time, pouring temperature, mould hardness were the major process parameters identified. Back propagation neural network is used in this paper to train the network. The network is trained to prepare the model which forecast the casting defects.Cite this ArticleParekh Priyank V. Optimization of Green Sand Casting Process Parameters by Artificial Neural Network (ANN). Trends in Mechanical Engineering & Technology. 2016; 6(2): 75–80p.

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Publicado

2016-07-19

Edição

Vol. 6 N.º 2 (2016)

Secção

Research Articles

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