Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard ...Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.展开更多
In order to investigate the sealing performance variation resulted from the thermal deformation of the end faces, the equations to calculate the fluid film pressure distribution, the bearing force and the leakage rate...In order to investigate the sealing performance variation resulted from the thermal deformation of the end faces, the equations to calculate the fluid film pressure distribution, the bearing force and the leakage rate are derived, for the fluid film both in parallel gap and in wedgy gap. The geometrical parameters of the sealing members are optimized by means of heat transfer analysis and complex method. The analysis results indicate that the shallow spiral grooves can generate hydrodynamic pressure while the rotating ring rotates and the bearing force of the fluid film in spiral groove end faces is much larger than that in the flat end faces. The deformation increases the bearing force of the fluid film in flat end faces, but it decreases the hydrodynamic pressure of the fluid film in spiral groove end faces. The gap dimensions which determine the characteristics of the fluid film is obtained by coupling analysis of the frictional heat and the thermal deformation in consideration of the equilibrium condition of the bearing force and the closing force. For different gap dimensions, the relation- ship between the closing force and the leakage rate is also investigated, based on which the leakage rate can be controlled by adjusting the closing force.展开更多
基金Supported by the National High Technology Research and Development Program of China(2014AA041803)the National Natural Science Foundation of China(61320106009)
文摘Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.
文摘In order to investigate the sealing performance variation resulted from the thermal deformation of the end faces, the equations to calculate the fluid film pressure distribution, the bearing force and the leakage rate are derived, for the fluid film both in parallel gap and in wedgy gap. The geometrical parameters of the sealing members are optimized by means of heat transfer analysis and complex method. The analysis results indicate that the shallow spiral grooves can generate hydrodynamic pressure while the rotating ring rotates and the bearing force of the fluid film in spiral groove end faces is much larger than that in the flat end faces. The deformation increases the bearing force of the fluid film in flat end faces, but it decreases the hydrodynamic pressure of the fluid film in spiral groove end faces. The gap dimensions which determine the characteristics of the fluid film is obtained by coupling analysis of the frictional heat and the thermal deformation in consideration of the equilibrium condition of the bearing force and the closing force. For different gap dimensions, the relation- ship between the closing force and the leakage rate is also investigated, based on which the leakage rate can be controlled by adjusting the closing force.