EPrints@IIT Delhi >
Faculty Research Publicatons  >
Mechanical Engineering >

Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1044

Title: A genetic algorithmic approach for optimization of surface roughness prediction model
Authors: Suresh, P V S
Rao, P Venkateswara
Deshmukh, S G
Keywords: automated machine tools
dimensional accuracy
roughness prediction model
response surface methodology
TiN-coated tungsten carbide
machining parameters
genetic algorithms
optimal machining
Issue Date: 2002
Citation: International Journal of Machine Tools and Manufacture, 42(6), 675-680
Abstract: Due to the widespread use of highly automated machine tools in the industry, 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 mild steel, using Response Surface Methodology (RSM). The experimentation was carried out with TiN-coated tungsten carbide (CNMG) cutting tools, for machining mild steel work-pieces covering a wide range of machining conditions. A second order mathematical model, in terms of machining parameters, was developed for surface roughness prediction using RSM. This model gives the factor effects of the individual process parameters. An attempt has also been made to optimize the surface roughness prediction model using Genetic Algorithms (GA) to optimize the objective function. The GA program gives minimum and maximum values of surface roughness and their respective optimal machining conditions.
URI: http://eprint.iitd.ac.in/dspace/handle/2074/1044
Appears in Collections:Mechanical Engineering

Files in This Item:

File Description SizeFormat
sureshgen2002.pdf143.37 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback