Intelligent Monitoring and Prediction of Surface Roughness in Ball-End Milling Process
In order to realize the intelligent machines,the practical model is proposed to predict the in-process surface roughness during the ball-end milling process by utilizing the cutting force ratio.The ratio of cutting force is proposed to be generalized and non-scaled to estimate the surface roughness regardless of the cutting conditions.The proposed in-process surface roughness model is developed based on the experimentally obtained data by employing the exponential function with five factors of the spindle speed,the feed rate,the tool diameter,the depth of cut,and the cutting force ratio.The prediction accuracy and the prediction interval of the in-process surface roughness model at 95% confident level are calculated and proposed to predict the distribution of individually predicted points in which the in-process predicted surface roughness will fall.All those parameters have their own characteristics to the arithmetic surface roughness and the surface roughness.It is proved by the cutting tests that the proposed and developed in-process surface roughness model can be used to predict the in-process surface roughness by utilizing the cutting force ratio with the highly acceptable prediction accuracy.
ball-end milling process monitoring prediction surface roughness cutting force ratio
Somkiat Tangjitsitcharoen Angsumalin Senjuntichai
Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University,Phayathai Road, Pathumwan, Bangkok, 10330, Thailand
国际会议
台湾
英文
2059-2063
2011-12-11（万方平台首次上网日期，不代表论文的发表时间）