Litcius/Paper detail

Modeling the Dynamics of Five-Axis Machine Tool Using the Multibody Approach

Hoai Nam Huynh, Yusuf Altıntaş

2020Journal of Manufacturing Science and Engineering39 citationsDOI

Abstract

Abstract A systematic modeling of multibody dynamics of five-axis machine tools is presented in this article. The machine is divided into major subassemblies such as spindle, column, bed, tool changer, and longitudinal and rotary drives. The inertias and mass center of each subassembly are calculated from the design model. The subassemblies are connected with elastic springs and damping elements at contact joints to form the complete multibody dynamic model of the machine that considers the rigid body kinematics and structural vibrations of the machine at any point. The unknown elastic joint parameters are estimated from the experimental modal analysis of the machine tool. The resulting position-dependent multibody dynamic model has the minimal number of degrees-of-freedom that is equivalent to the number of measured modes, as opposed to thousands used in finite element models. The frequency response functions of the machine can be predicted at any posture of the five-axis machine, which are compared against the directly measured values to assess the validity of model. The proposed model can predict the combined rigid body motion and vibrations of the machine with computational efficiency, and hence, it can be used as a digital twin to simulate its dynamic performance in machining operations and tracking control tests of the servo drives.

Topics & Concepts

Multibody systemMachine toolVibrationKinematicsModal analysisFinite element methodControl theory (sociology)Rigid bodyComputer scienceModalDegrees of freedom (physics and chemistry)Point (geometry)EngineeringStructural engineeringMechanical engineeringAcousticsArtificial intelligencePhysicsMathematicsChemistryGeometryClassical mechanicsControl (management)Polymer chemistryQuantum mechanicsAdvanced machining processes and optimizationEngineering Technology and MethodologiesIterative Learning Control Systems