Design of grinding process via inversion of neural nets

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

The design of a grinding process is a difficult task since there are so many characteristics to consider. In this paper, a generic scheme to establish the norm for automation of design by employing neural nets for a surface grinding process is proposed. Design of a grinding process is accomplished by initial determination of a set of optimal design variables in order to achieve a set of desired process variables. The design problem is reduced to the inversion of a set of nonlinear simultaneous equations. Two techniques of direct and indirect inversion are employed. Decomposition of NNs and Fuzzy Accelerator are used to speed up learning.

Original languageEnglish (US)
Pages715-720
Number of pages6
StatePublished - Dec 1 1993
EventProceedings of the 1993 Artificial Neural Networks in Engineering, ANNIE'93 - St.Louis, MO, USA
Duration: Nov 14 1993Nov 17 1993

Other

OtherProceedings of the 1993 Artificial Neural Networks in Engineering, ANNIE'93
CitySt.Louis, MO, USA
Period11/14/9311/17/93

All Science Journal Classification (ASJC) codes

  • Software

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