The Prediction Model of Surface Roughness Based on Experiments of Turning Titanium Alloy

被引:0
|
作者
Yang, Cuilei [1 ]
Zheng, Qingchun [1 ]
Hu, Yahui [1 ]
机构
[1] Tianjin Univ Technol, Tianjin Key Lab Design & Intelligent Control Adv, Tianjin 300384, Peoples R China
关键词
Titanium alloy; Surface roughness; Turning Parameters;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The experiments of turning titanium alloy are carried out by using central composite design, the influences of cutting speed, feed rate and cutting depth on surface roughness are analyzed. The surface roughness prediction model is established based on the response surface method. The significance of the regression equation is validated and the influences of the cutting parameters on surface roughness are compared. The results show that: within the range of cutting parameters used in the experiments, the most significant parameter on surface roughness is given by feed rate, followed by cutting depth, and the cutting speed has minimal effect on surface roughness; the prediction model is significant. It can be used to select various suitable parameters before the machining processing to predict and control the surface roughness.
引用
收藏
页码:1776 / 1780
页数:5
相关论文
共 50 条
  • [21] The Establishment of a Prediction Model for Surface Roughness in Ultrasonic-assisted Turning
    Yang, Ching-Been
    Deng, Chyn-Shu
    Chiang, Hsiu-Lu
    PRODUCT DESIGN AND MANUFACTURE, 2012, 120 : 119 - +
  • [22] Surface roughness prediction in the turning of high-strength steel by factorial design of experiments
    Choudhury, IA
    ElBaradie, MA
    JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 1997, 67 (1-3) : 55 - 61
  • [23] PREDICTION OF ROUGHNESS IN TURNING SURFACE TREATMENT FOR COATING
    Leonov, S. L.
    Tatarkin, E. Y.
    OBRABOTKA METALLOV-METAL WORKING AND MATERIAL SCIENCE, 2009, (01): : 28 - 30
  • [24] Surface roughness prediction in turning of femoral head
    Nikolaos I. Galanis
    Dimitrios E. Manolakos
    The International Journal of Advanced Manufacturing Technology, 2010, 51 : 79 - 86
  • [25] Surface roughness prediction in turning of femoral head
    Galanis, Nikolaos I.
    Manolakos, Dimitrios E.
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2010, 51 (1-4): : 79 - 86
  • [26] Prediction of surface roughness in CNC turning by model-assisted response surface method
    Misaka, Takashi
    Herwan, Jonny
    Ryabov, Oleg
    Kano, Seisuke
    Sawada, Hiroyuki
    Kasashima, Nagayoshi
    Furukawa, Yoshiyuki
    PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY, 2020, 62 : 196 - 203
  • [27] A knowledge-based system for the prediction of surface roughness in turning process
    Abburi, NR
    Dixit, US
    ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2006, 22 (04) : 363 - 372
  • [28] An energy-based modeling and prediction approach for surface roughness in turning
    Xie, Nan
    Zhou, Junfeng
    Zheng, Beirong
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 96 (5-8): : 2293 - 2306
  • [29] An energy-based modeling and prediction approach for surface roughness in turning
    Nan Xie
    Junfeng Zhou
    Beirong Zheng
    The International Journal of Advanced Manufacturing Technology, 2018, 96 : 2293 - 2306
  • [30] Research on Analytical Model and DDQN-SVR Prediction Model of Turning Surface Roughness
    Chen C.
    Lu J.
    Chen K.
    Li Y.
    Ma J.
    Liao X.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2021, 57 (13): : 262 - 272