Abrasive waterjet (AWJ) machining is one of the recent non-traditional methods starting to be used widely in industry for material removal of different materials. The cutting performance of AWJ is achieved by a very high speed, small-scale erosion process. In this paper, a modified form of Finnie's
Modelling of abrasive flow machining process: a neural network approach
โ Scribed by R.K. Jain; V.K. Jain; P.K. Kalra
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 256 KB
- Volume
- 231
- Category
- Article
- ISSN
- 0043-1648
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โฆ Synopsis
A simple neural network model for abrasive flow machining process has been established. The effects of machining parameters on material removal rate and surface finish have been experimentally analysed. Based on this analysis, model inputs and outputs were chosen and off-line model training using back-propagation algorithm was carried out. Simulation results confirm the feasibility of this approach and show a good agreement with experimental and theoretical results for a wide range of machining conditions. Learning could remarkably be enhanced by training the network with noise injected inputs.
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