Integrated model based thin-walled part machining precision control for the workpiece-fixture system

Abstract

This article deliberates that thin-walled parts are more easily deformed in the machining process, due to low stiffness, which not only creates elevated machining errors and reduces machining precision. This paper presents a systematic methodology to analyze and control the machining errors caused by machining deformation. With the minimum modulus principle, the kinematics model of the workpiece-fixture system is established and contact force (including friction force) between the fixture components and workpiece are calculated, and further, a model to optimize the clamping force is proposed in maintaining the stability of the workpiece-fixture system. Then, the numerical results obtained from the kinematics model are applied as boundary conditions on the finite element model of the workpiece-fixture system; thus, the deformation value is calculated. Then, the machining error model caused by deformation is used to transfer the deformation value to machining errors. The neural network is employed to establish the highly nonlinear relations between the machining error and the cutting parameter, which facilitates the establishment of the optimization model of cutting parameters to improve machining efficiency and ensure the machining precision. Finally, a case study is used to verify the effectiveness of the proposed method.