Position prediction and error compensation for a large thin-walled box-shaped workpiece in a fixture

Peng, Dingqiang; Wang, Liming; Mechefske, Chris K.; Shao, Yimin

doi:10.1007/s00170-021-07632-z

Cited by 4 publications

(3 citation statements)

References 26 publications

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“…The FE is a universal method to identify the dynamic parameters of complex components [25][26][27]. In this section, the radial deformation of the shaft hole under static action is obtained through FE statics analysis, and then the radial stiffness of the shaft hole in different directions can be calculated.…”

Section: A Fe Verification Model For the Directional Stiffness Of The...mentioning

confidence: 99%

A Method for Predicting the Boring Topography Error of Shaft Hole on a Thin-Walled Box Based on a Proposed Dynamic Model

2023

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Traditional boring dynamic model ignores the effect of the uneven radial stiffness of the shaft hole of the thin-walled box on the boring vibration characteristic, which will lead to the deviation in the prediction for both the cutting force and the surface topography of the machining hole. To address this shortcoming, a new calculation model of the equivalent radial stiffness of the shaft hole is proposed and then validated by the finite element (FE) method. On this basis, a boring dynamic model of the shaft hole is developed, and an experimental study on the dynamic characteristics of the shaft hole boring is carried out to verify the correctness and effectiveness of the proposed dynamic model. Moreover, a prediction method for the surface topography error of the machined shaft hole is presented based on the proposed dynamic model. Finally, the comparison investigation on the hole machined surface topography predicted by the proposed method and measured in practice is carried out. The results show that the proposed theoretical models and method can achieve accurate predictions for both the boring cutting force and the machined surface topography error of the shaft hole on the thin-walled box. This study can provide a theoretical basis for machining error control and process optimization of the fine boring of the thin-walled transmission box.INDEX TERMS Thin-walled box, shaft hole machining, boring dynamic model, surface topography prediction.

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Section: A Fe Verification Model For the Directional Stiffness Of The...mentioning

confidence: 99%

A Method for Predicting the Boring Topography Error of Shaft Hole on a Thin-Walled Box Based on a Proposed Dynamic Model

2023

Self Cite

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“…There are two main types of traditional force prediction for machining processes, which are based on cutting mechanism, and finite element simulation.The mechanical analysis modeling mainly refers to the theoretical analysis of the forces and related parameters in the processing process, to establish the corresponding theoretical numerical model 8 , 9 . And the finite element simulation method refers to offline machining simulation prediction using commercial finite element simulation software 10 – 12 .…”

Section: Introductionmentioning

confidence: 99%

Clamping force prediction based on deep spatio-temporal network for machining process of deformable parts

Li¹,

Zhou²,

Yang³

et al. 2023

Sci Rep

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As an important component of the machining system, the influence of fixtures on the machining deformation of the workpiece cannot be ignored. By controlling the clamping force during the machining process is an effective means to suppress or improve the machining deformation. However, due to the dynamic coupling of part geometry, clamping method, manufacturing process and time-varying cutting forces, it is difficult to obtain accurate clamping forces, which hinders the realization of fixture-based deformation control. In this paper, the variation of clamping force is considered as the response of the joint action of cutting force and other working conditions in spatial and temporal terms, and a clamping force prediction method based on deep spatio-temporal network is proposed. The part geometry model is first parameterized based on voxels, after which the cutting forces are dynamically correlated with the clamping forces in spatial and temporal terms. Then, a convolutional network was designed to capture the spatial correlation between the working conditions such as cutting force and clamping force, and a gated recurrent cell network to capture the temporal correlation to predict the clamping force during machining. Finally, an experiment of milling a cylindrical thin-walled part illustrates the effectiveness of the proposed method.

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“…Yang et al [23] developed a comprehensive equivalent fixture error model that can compensate for datum errors, machine path errors, and workpiece deformation during machining through general fixture layouts. Peng et al [24] constructed a comprehensive position prediction model that can be used to predict the position error of large, thin-walled box-shaped workpieces in a fixture type.…”

Section: Introductionmentioning

confidence: 99%

Optimized Design of Flexible Quick-Change System Based on Genetic Algorithm and Monte Carlo Method

Zhang

et al. 2023

Applied Sciences

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In order to realize the high efficiency and precision clamping of large workpieces with several processes and multiple species processing, the distribution number and position of the zero point clamping unit in the flexible quick-change process system for big thin-walled cylindrical structural parts are presented. The error model of the flexible quick-change process system is established by the Monte Carlo method, which is used to optimize the system structure design. The error variation of the flexible quick-change process system under the action of transposition and extreme working conditions such as cutting force is revealed, and further analysis on the sensitivity of the workpiece’s global displacement error and global attitude error to each error source is carried out. After the optimization, a high-quality, cost-effective, flexible quick-change clamping system is created. The three-coordinate measurement experiment is used to test the functionality and accuracy of the flexible quick-change process system. A significantly improved level of the system’s repetitive positioning accuracy (less than 0.01 mm) is detected. Importantly, the flexible quick-change system obtained by the combinatorial optimal design method has been successfully applied to the production of aerospace components with improved quality and efficiency.

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Position prediction and error compensation for a large thin-walled box-shaped workpiece in a fixture

Cited by 4 publications

References 26 publications

A Method for Predicting the Boring Topography Error of Shaft Hole on a Thin-Walled Box Based on a Proposed Dynamic Model

A Method for Predicting the Boring Topography Error of Shaft Hole on a Thin-Walled Box Based on a Proposed Dynamic Model

Clamping force prediction based on deep spatio-temporal network for machining process of deformable parts

Optimized Design of Flexible Quick-Change System Based on Genetic Algorithm and Monte Carlo Method

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