Modeling of grinding wheel sharpness by using neural network

  • Authors:

  • Hamid Baseri

  • Affiliations:

  • Babol University of Technology, Iran

  • Venue:
  • Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and Technologies
  • Year:
  • 2010

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Abstract

In this study, a feed-forward neural network was developed to estimate the skewness factor of an alumina grinding wheel that is a criterion for wheel sharpness. Some experimental samples have been firstly prepared to train the network to get it to estimate the wheel sharpness. Then network is tested using some experimental samples that have not been used in the training stage. The input parameters of the process are speed ratio, depth of dressing and cross-feed rate and the output parameter is the skewness factor of the grinding wheel. The predicted values of the neural network represented that this model has a good precision in estimation of wheel sharpness.