Abstract
In this paper, stiffness modelling and analysis of a typical 3-DOF parallel kinematic machine (PKM) that provides translational motion along X, Y and Z axes is presented. The mechanism consists of three limbs each having an arm and a forearm with prismatic-revoluterevolute-revolute joints (PRRR). The joint arrangement is in such a way that the moving or tool platform maintains same orientation in the entire workspace. Through inverse kinematics, the joint angles for a given position of tool platform necessary for the stiffness modelling and analysis are obtained. The stiffness modelling is based on the compliance matrices of arm and forearm of each limb. Typical non-dimensional performance indices, namely, workspace volume index (WVI), global translational stiffness index (GTSI), and global rotational stiffness index (GRSI), are introduced and used to study the influence of dimensions. Attempts are also made to find the optimal dimensions of the translational PKM using multi-objective optimization based on the genetic algorithms (MOGA) in MATLAB. The methodology presented and the results obtained are useful for predicting the performance capability of the PKM under study.
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Recommended by Associate Editor Ki-Hoon Shin
S. Shankar Ganesh is an Assistant Professor of Mechanical Engineering, G.V.P College of Engineering, Visakhapatnam, India. His current research is in Parallel Kinematic Machines.
A. B. Koteswara Rao is a Professor, Mechanical Engineering, G. V. P College of Engineering, Visakhapatnam, India. He received his Ph.D. from IIT Delhi in 2004. His research areas are PKMs, Optimization, Machine tools, Robotics.
Sanjay Darvekar is an Associate Professor of Mechanical Engineering in G.V.P College of Engineering, Visakhapatnam, India. He obtained Ph.D. from JNTUK Kakinada in 2013. His area of interest is PKMs.
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Ganesh, S.S., Koteswara Rao, A.B. & Darvekar, S. Multi-objective optimization of a 3-DOF translational parallel kinematic machine. J Mech Sci Technol 27, 3797–3804 (2013). https://doi.org/10.1007/s12206-013-0957-2
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DOI: https://doi.org/10.1007/s12206-013-0957-2