Paper Title:
Intelligent Monitoring and Estimation of Surface Roughness on CNC Turning
  Abstract

In order to realize an intelligent machine tool, an in-process monitoring system is developed to estimate the in-process surface roughness. The objective of this research is to propose a method to estimate the surface roughness during the in-process cutting by utilizing the in-process monitoring of cutting forces. The proposed in-process surface roughness model is developed based on the experimentally obtained results by employing the exponential function with five factors of the cutting speed, the feed rate, the tool nose radius, the depth of cut, and the cutting force ratio. The multiple regression analysis is utilized to calculate the regression coefficients with the use of the least square method. The prediction interval of the in-process surface roughness model has been also presented to monitor and control the in-process estimated surface roughness at 95% confident level. It is proved by the cutting tests that the proposed and developed in-process surface roughness model can be effectively used to monitor and estimate the in-process surface roughness by utilizing the cutting force ratio with the highly acceptable prediction accuracy achieved.

  Info
Periodical
Edited by
Jun Wang,Philip Mathew, Xiaoping Li, Chuanzhen Huang and Hongtao Zhu
Pages
376-381
DOI
10.4028/www.scientific.net/KEM.443.376
Citation
S. Tangjitsitcharoen, "Intelligent Monitoring and Estimation of Surface Roughness on CNC Turning ", Key Engineering Materials, Vol. 443, pp. 376-381, 2010
Online since
June 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Yuan Wei Wang, Song Zhang, Jian Feng Li, Tong Chao Ding
Abstract:In this paper, Taguchi method was applied to design the cutting experiments when end milling Inconel 718 with the TiAlN-TiN coated carbide...
911
Authors: Xiao Li Zhu, Song Zhang, Tong Chao Ding, Yuan Wei Wang
Abstract:The experimental study presented in this paper aims to investigate the effects of cutting parameters on cutting forces, and search the...
96
Authors: Pedro Jose Arrazola, A. Villar, R. Fernández, J. Aperribay
Abstract:This article describes a practical machining training aiming that the students acquire the theoretical-practical knowledge of chip formation...
83
Authors: Yue Feng Yuan, Wen Ying Zhang, Xing Chang
Chapter 6: New Materials and Advanced Materials
Abstract:Cutting force experiments in turning aluminum-silicon alloy ZL104 are carried out with cement carbide tool YG8. The influence of cutting...
971
Authors: Rao T. Sadasiva, K. Satyanarayana, Y. Praneeth, Anne Venu Gopal
Chapter 15: Meso/Micro Manufacturing Equipment and Processes
Abstract:Milling is the most widely applied machining process for producing flat surfaces and prismatic shapes. To minimize the process time and...
3147