Abstract

Due to the widespread use of highly automated machine tools, manufacturing requires reliable models and methods for the prediction of output performance of machining processes. The prediction of optimal machining conditions for good surface finish and dimensional accuracy plays a very important role in process planning. The present work deals with the study and development of a surface roughness prediction model for machining Al7075-T6, using Response Surface Methodology (RSM). Machining operations of work pieces made by Al7075-T6 covering a wide range of machining conditions have been carried out with by flat end mill with four teeth made by High Speed Steel. A RS model, in terms of machining parameters, was developed for surface roughness prediction using the Radial Basis Functions (RBF) technique. This model gives the process response sensitivity to the individual process parameters. An attempt has also been made to optimize the surface roughness prediction model using Genetic Algorithms (GA).

Autore Pugliese

• Del Prete Antonio , Anglani Alfredo

Tutti gli autori

• Del Prete A. , De Vitis A. , Anglani A. ,

Titolo volume/Rivista

INTERNATIONAL JOURNAL OF MATERIAL FORMING

Anno di pubblicazione

2010

ISSN

1960-6206

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

3

Ultimo Aggiornamento Citazioni

28/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile