๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Modelling of abrasive flow machining process: a neural network approach

โœ 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

No coin nor oath required. For personal study only.

โœฆ 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.


๐Ÿ“œ SIMILAR VOLUMES


Modelling of Abrasive Waterjet Machining
โœ M. EITobgy; E-G. Ng; M.A. Elbestawi ๐Ÿ“‚ Article ๐Ÿ“… 2005 ๐Ÿ› International Academy for Production Engineering ๐ŸŒ English โš– 925 KB

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 hot strip rolling process u
โœ H.J. Kim; M. Mahfouf; Y.Y. Yang ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 931 KB

A neural network-based approach is developed to predict a mechanical property for the hot-rolled alloy strip. Using a data set containing critical information on the mechanical property which was obtained from a POSCO hot strip mill, a neural network-based model is elicited. A compact set of process

Run-to-run process control of a plasma e
โœ Jill P. Card; Mark Naimo; William Ziminsky ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 250 KB ๐Ÿ‘ 2 views

Run-to-run control of a plasma etch process for 8 inch diameter silicon wafers at Digital Semiconductor is determined by maintenance of targeted values of post-etch metrology variables. The post-etch quality variables are extremely sensitive to variation in the etch chamber conditions due to fluctua