Indian Journal of Science and Technology

Abstract

Objectives: Parallel Kinematic Machines (PKMs) are closed loop mechanisms. The present study is to find optimal workspace volume of two configurations of translational 3-DOF PKM and optimal location for machining. Methods/ analysis: Kinematic analysis is carried out to find the joint angles of the two configurations of the PKM. Optimal dimensions of two configurations of PKM are obtained considering Workspace Volume Index (WVI) as objective. A source code is developed in MATLAB to find the optimal dimensions using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). Velocity analysis is carried out for configuration-I. The optimal location for best machining for configuration-I is identified using condition number of the jacobian matrix of the PKM. Findings: Using kinematic analysis the joint angles of the two configurations of PKM is obtained. Performance index like Workspace Volume Index (WVI) is introduced for the two configurations of PKM. Using WVI as an objective the optimal dimensions of two configurations of PKM are found using GA and PSO. It is observed from the results configuration-II has more WVI compared with configuration-I. Velocity analysis is done for configuration-I of PKM and from this analysis the location of singularities and non-singularities of the PKM was located. It was observed from the results the optimal location for machining is at the middle plane. Application/Improvements: The novelty of the present work lies in finding the optimal WVI of two configurations of 3-DOF PKM using GA and PSO. This PKM could be used as machine tool for 2-D contouring machining and other applications.

Keywords: Optimal Workspace Volume, 3-DOF GA, PKM, PSO