Analysis and optimization of surface roughness in the ball burnishing process using response surface methodology and desirabilty function
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Date
2011
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Sci Ltd
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
In the present study, an optimization strategy based on desirability function approach (DFA) together with response surface methodology (RSM) has been used to optimize ball burnishing process of 7178 aluminium alloy. A quadratic regression model was developed to predict surface roughness using RSM with rotatable central composite design (CCD). In the development of predictive models, burnishing force, number of passes, feed rate and burnishing speed were considered as model variables. The results indicated that burnishing force and number of passes were the significant factors on the surface roughness. The predicted surface roughness values and the subsequent verification experiments under the optimal conditions were confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface roughness was calculated as 2.82%. (c) 2011 Elsevier Ltd. All rights reserved.
Description
Keywords
Burnishing, Surface roughness, Optimization, Response surface methodology, Desirability function approach, Central composite design, Parameters, Hardness, Finish, Steel, Force, Tool, Alloy
Journal or Series
Advances in Engineering Software
WoS Q Value
Q2
Scopus Q Value
Q1
Volume
42
Issue
11
