Investigation of the stability and contact stiffness of workpiece inside fixture in different machining conditions

Abstract

The dynamic stability of machining processes is influenced by the dynamic stability of the workpiece and fixture assembly. This effect has not yet been sufficiently considered. Achieving dynamic stability by simply applying a large amount of clamping force is a basic method and involves damages such as elastic deformation of relatively thin workpieces, damage to the clamping surfaces, and high wear of fixture components resulting in malfunction. In spite of this, to the best knowledge of the present authors, the contact stiffness between workpiece and fixture as an influencing parameter has not been sufficiently paid attention by researchers and these parameters have not been taken into account in the equations of dynamic stability. The contact stiffness itself is influenced by the machining parameters. In the present study, the changes in contact stiffness in different machining conditions are investigated as a partial undertaking to fill the gap existing in the modeling of the machining dynamics. In this paper, by defining the mathematical model of the workpiece-fixture system and calculating the matrices of contact stiffness and fixture stiffness, the results of changes in various machining parameters in the stiffness of the workpiece-fixture system have been investigated. The results showed that high contact stiffness cannot be provided simply by applying the maximum force of the clamps. Rather, by increasing the spindle speed, the contact stiffness will increase significantly. Furthermore, by increasing the spindle speed, further increase in the contact stiffness will be achieved with lower feed rates, which will not be economically viable.

Experimental Evaluation of Flexible Fixture Stiffness for Steering Knuckles When Loading a Milling Machine Tool

“…One of the crucial directions in investigations of flexible fixture construction is evaluating their stiffness [9,21,22] and stress-strain states [23]. Currently, the most promising tools of fixture research are digital twin technology, artificial intelligence, finite element methods, topology, and parameter optimization [24].…”