Framework and development of data-driven physics based model with application in dimensional accuracy prediction in pocket milling

In the manufacturing of thin wall components for aerospace industry,apart from the side wall contour error,the Remaining Bottom Thickness Error(RBTE)for the thin-wall pocket component(e.g.rocket shell)is of the same importance but overlooked in current research.If the RBTE reduces by 30%,the weight reduction of the entire component will reach up to tens of kilograms while improving the dynamic balance performance of the large component.Current RBTE control requires the off-process measurement of limited discrete points on the component bottom to provide the reference value for compensation.This leads to incompleteness in the remaining bottom thickness control and redundant measurement in manufacturing.In this paper,the framework of data-driven physics based model is proposed and developed for the real-time prediction of critical quality for large components,which enables accurate prediction and compensation of RBTE value for the thin wall components.The physics based model considers the primary root cause,in terms of tool deflection and clamping stiffness induced Axial Material Removal Thickness(AMRT)variation,for the RBTE formation.And to incorporate the dynamic and inherent coupling of the complicated manufacturing system,the multi-feature fusion and machine learning algorithm,i.e.kernel Principal Component Analysis(kPCA)and kernel Support Vector Regression(kSVR),are incorporated with the physics based model.Therefore,the proposed data-driven physics based model combines both process mechanism and the system disturbance to achieve better prediction accuracy.The final verification experiment is implemented to validate the effectiveness of the proposed method for dimensional accuracy prediction in pocket milling,and the prediction accuracy of AMRT achieves 0.014 mm and 0.019 mm for straight and corner milling,respectively.

Engagement Angle Modeling for Multiple-circle Continuous Machining and Its Application in the Pocket Machining

The progressive cutting based on auxiliary paths is an effective machining method for the material accumulating region inside the mould pocket. But the method is commonly based on the radial depth of cut as the control parameter, further more there is no more appropriate adjustment and control approach. The end-users often fall to set the parameter correctly, which leads to excessive tool load in the process of actual machining. In order to make more reasonable control of the machining load and toolpath, an engagement angle modeling method for multiplecircle continuous machining is presented. The distribution mode of multiple circles, dynamic changing process of engagement angle, extreme and average value of engage- ment angle are carefully considered. Based on the engagement angle model, numerous application techniques for mould pocket machining are presented, involving the calculation of the milling force in multiple-circle continuous machining, and rough and finish machining path planning and load control for the material accumulating region inside the pocket, and other aspects. Simulation and actual machining experiments show that the engagement angle modeling method for multiple-circle continuous machining is correct and reliable, and the related numerous application techniques for pocket machining are feasible and effective. The proposed research contributes to the analysis and control tool load effectively and tool-path planning reasonably for the material accumulating region inside the mould pocket.