Call For Paper Volume:4 Issue:8 Aug'2017 |

PREDICTION AND OPTIMIZATION OF SURFACE ROUGHNESS IN TURNING BASED ON RESPONSE SURFACE METHODOLOGY

Publication Date : 28/02/2015



Author(s) :

Rajendra. K. Belkar , Raju. B. Tirpude , Sanjay.W. Rajurkar.


Volume/Issue :
Volume 2
,
Issue 2
(02 - 2015)



Abstract :

Surface roughness and tolerances are among the most critical quality measures in many mechanical products. Critical quality measure and surface roughness (Ra) in machined parts depends upon metal cutting parameters during the turning process. Researchers have predicted and developed various models for the optimum turning parameters for the desired surface roughness. Surface of a mechanical product can be created with a number of manufacturing processes. As competition grows closer, customers now have increasingly high demands on quality, making surface roughness become one of the most competitive dimensions in today’s metal cutting industry. This paper utilizes regression modeling in turning of Aluminum using response surface methodology (RSM) coupling with of factorial design. A linear and quadratic model will develop for the prediction and analysis of the relationship between the cutting conditions (variables) and surface roughness as well as to study the effect of cutting variables on surface roughness. In the development of predictive models, cutting parameters of cutting speed, feed rate and depth of cut will considered as model variables and surface roughness will considered as a response variables.


No. of Downloads :

18


Indexing

Web Design MymensinghPremium WordPress ThemesWeb Development

PREDICTION AND OPTIMIZATION OF SURFACE ROUGHNESS IN TURNING BASED ON RESPONSE SURFACE METHODOLOGY

February 24, 2015