Computationally intelligent optimization of metal cutting regimes

Author:

Tanikić Dejan

Funder

Ministry of Education, Science and Technological Development

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference23 articles.

1. Parameter optimization of a multi-pass milling process using non-traditional optimization algorithms;Rao;Appl. Soft Comput.,2010

2. Metal cutting process parameters modeling: an artificial intelligence approach;Tanikić;J. Sci. Ind. Res India,2009

3. Modelling and optimization of the surface roughness in the dry turning of the cold rolled alloyed steel using regression analysis;Tanikić;J. Braz. Soc. Mech. Sci.,2012

4. Application of response surface methodology for determining cutting force model in turning of LM6/SiCP metal matrix composite;Joardar;Measurement,2014

5. Response surface methodology and genetic algorithm used to optimize the cutting condition for surface roughness parameters in CNC turning;Routara;Procedia Eng.,2012

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