Additive manufacturing technologies enable the production of parts by successively adding layers. In powder-based technologies, each powder layer is selectively solidified following the respective cross-section of the...Additive manufacturing technologies enable the production of parts by successively adding layers. In powder-based technologies, each powder layer is selectively solidified following the respective cross-section of the parts either by the application of high-energy radiation or by the selective deposition of binder. By repeating the steps of layer deposition and selective solidification, parts are fabricated. The layer-wise build-up and the ambient conditions lead to warpage of the parts due to the temporarily and locally uneven distribution of shrinkage throughout the part. This leads to deviations in shape and dimension. The development of these technologies fosters a change fi＇om prototyping to manufacturing applications, As a consequence, higher standards regarding the shape and dimensional accuracy are required. Therefore, new strategies to minimize the resulting deformations are necessary to reduce rejects and widen the range of applications of the described technologies. In this paper, an empirical, a knowledge-based and a simulative approach for warpage compensation are introduced. They are all based on the pre-deformation of the digital 3D part geometry inverse to the expected deformation during manufacturing. The aim of the research is the development of a comprehensive method that enables users to improve their part-quality by supporting the pre-deformation process. Contrary to existing work, this method should not be process-specific but cover a wide range of additive manufacturing techniques. Typical forms of deformation of the processes laser sintering, laser beam melting and 3D printing （powder-binder） are presented and compensation strategies are disenssed. Finally, an outlook on the ongoing research is given.展开更多
Based on plastic bending engineering theory and machine vision technology, the intelligent control technology for forming steel pipe with JCO process is presented in this paper. By ‘twice pre-bending method’ in the ...Based on plastic bending engineering theory and machine vision technology, the intelligent control technology for forming steel pipe with JCO process is presented in this paper. By ‘twice pre-bending method’ in the first forming step, the springback law can be obtained. With the springback law and the target angle, the exact punch displacement which determines the formed angle in each bending step is predicted. In the succedent forming steps, the bending process is carried out with the exact punch displacement by real-time revising the springback law. And the angle error in each forming step is calculated by comparing the actual formed angle with the target angle. By conducting compensation for the last angle error in the next forming step, each precise bending process step is realized. A system of intelligent control technology for forming the steel pipe was developed. A calibration method is proposed to calculate the exterior parameters of the CCD camera, in which the equilateral triangle is em-ployed as the calibrating board and only one image needs to be captured. A mathematical model, which converts the angle in the image into the actual formed angle, is derived. The experimental results showed that the ellipticity of the formed pipes was less than 1.5% and the high-quality pipes can be manufactured without the worker's operating experience by employing the in-telligent control technology.展开更多
文摘Additive manufacturing technologies enable the production of parts by successively adding layers. In powder-based technologies, each powder layer is selectively solidified following the respective cross-section of the parts either by the application of high-energy radiation or by the selective deposition of binder. By repeating the steps of layer deposition and selective solidification, parts are fabricated. The layer-wise build-up and the ambient conditions lead to warpage of the parts due to the temporarily and locally uneven distribution of shrinkage throughout the part. This leads to deviations in shape and dimension. The development of these technologies fosters a change fi＇om prototyping to manufacturing applications, As a consequence, higher standards regarding the shape and dimensional accuracy are required. Therefore, new strategies to minimize the resulting deformations are necessary to reduce rejects and widen the range of applications of the described technologies. In this paper, an empirical, a knowledge-based and a simulative approach for warpage compensation are introduced. They are all based on the pre-deformation of the digital 3D part geometry inverse to the expected deformation during manufacturing. The aim of the research is the development of a comprehensive method that enables users to improve their part-quality by supporting the pre-deformation process. Contrary to existing work, this method should not be process-specific but cover a wide range of additive manufacturing techniques. Typical forms of deformation of the processes laser sintering, laser beam melting and 3D printing （powder-binder） are presented and compensation strategies are disenssed. Finally, an outlook on the ongoing research is given.
基金Supported by the National Natural Science Foundation of China (Grant No. 50805126)the Hebei Natural Science Foundation (Grant No. E2009000389)
文摘Based on plastic bending engineering theory and machine vision technology, the intelligent control technology for forming steel pipe with JCO process is presented in this paper. By ‘twice pre-bending method’ in the first forming step, the springback law can be obtained. With the springback law and the target angle, the exact punch displacement which determines the formed angle in each bending step is predicted. In the succedent forming steps, the bending process is carried out with the exact punch displacement by real-time revising the springback law. And the angle error in each forming step is calculated by comparing the actual formed angle with the target angle. By conducting compensation for the last angle error in the next forming step, each precise bending process step is realized. A system of intelligent control technology for forming the steel pipe was developed. A calibration method is proposed to calculate the exterior parameters of the CCD camera, in which the equilateral triangle is em-ployed as the calibrating board and only one image needs to be captured. A mathematical model, which converts the angle in the image into the actual formed angle, is derived. The experimental results showed that the ellipticity of the formed pipes was less than 1.5% and the high-quality pipes can be manufactured without the worker's operating experience by employing the in-telligent control technology.
