Selection of optimal machining parameters for hexapod machine tool

被引:2
作者
Muruganandam, S. [1 ]
Pugazhenthi, S. [1 ]
机构
[1] SASTRA Univ, Sch Mech Engn, Thanjavur 613402, India
关键词
Hexapod machine tool; Stiffness; PSO; Optimal machining parameters; PARALLEL; STIFFNESS;
D O I
10.1007/s00170-009-2123-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Parallel kinematic machine tools (PKM) have the advantages of higher stiffness, higher payload capacity and lower inertia. Still their penetration into the machine tool industry is very less. One of the difficulties in using PKMs such as hexapod machine tools is that the stiffness continuously varies with configuration change at every instant. This makes location of work piece and selection of machining parameters difficult and complicated. A methodology is presented in this article to select optimal machining parameters for hexapod machine tools. Particle swarm optimization is used as a tool in the optimization process. A profile-milling example is also presented to demonstrate the selection of machining parameters.
引用
收藏
页码:801 / 810
页数:10
相关论文
共 27 条
[1]   Instantaneous stiffness analysis and simulation for hexapod machines [J].
Chen, J. ;
Lan, F. .
SIMULATION MODELLING PRACTICE AND THEORY, 2008, 16 (04) :419-428
[2]  
CLINTON CM, 1997, 9729 TR U MAR I SYST
[3]  
CONTI JP, 1997, 9728 TR U MAR I SYST
[4]   Computation of stiffness and stiffness bounds for parallel link manipulators [J].
El-Khasawneh, BS ;
Ferreira, PM .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 1999, 39 (02) :321-342
[5]   DETERMINATION OF THE WORKSPACE OF 6-DOF PARALLEL MANIPULATORS [J].
GOSSELIN, C .
JOURNAL OF MECHANICAL DESIGN, 1990, 112 (03) :331-336
[6]  
HUANG T, 1999, T ASME, V121, P26
[7]  
HUANG T, 1999, ANN CIRP, P347
[8]   A general and novel approach for parameter identification of 6-DOF parallel kinematic machines [J].
Huang, TA ;
Chetwynd, DG ;
Whitehouse, DJ ;
Wang, JS .
MECHANISM AND MACHINE THEORY, 2005, 40 (02) :219-239
[9]  
Ibaraki S, 2004, P AMER CONTR CONF, P1394
[10]  
Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968