Prediction of cutting power in end-milling operation of modified AISI P20 steel

The present paper discusses the development of the first and second order models for predicting the cutting power produced in end-milling operation of modified AISI P20 tool steel. The first and second order cutting force equations are developed using the response surface methodology (RSM) to study...

Full description

Saved in:
Bibliographic Details
Main Author: Mohd Yazid, Abu
Format: Undergraduates Project Papers
Language:English
Published: 2009
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/885/1/Mohd_Yazid_Abu.pdf
http://umpir.ump.edu.my/id/eprint/885/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Malaysia Pahang
Language: English
Description
Summary:The present paper discusses the development of the first and second order models for predicting the cutting power produced in end-milling operation of modified AISI P20 tool steel. The first and second order cutting force equations are developed using the response surface methodology (RSM) to study the effect of four input cutting parameters which is cutting speed, feed rate, radial depth and axial depth of cut on cutting power. The cutting power contours with respect to input parameters are presented and the predictive models analyses are performed with the aid of the statistical software package Minitab. The separate affect of individual input factors and the interaction between these factors are also investigated in this study. In first order model, the increase in the cutting speed, feed rate, axial and radial depths of cut will cause the cutting power to become larger. The received second order equation shows, based on the variance analysis, that the cutting power decreased when cutting speed, federate, axial and radial depth of cut is reduced. The predictive models in this study are believed to produce values of the longitudinal component of the cutting power close to those readings recorded experimentally with a 95% confident interval.