Modeling and optimization of semiconductor manufacturing process with neural networks

A neural network-based process model is proposed to optimize the semiconductor manufacturing process. Being different from some works in several research groups which developed neural network-based models to predict process quality with a set of process variables of only single manufacturing step, we applied this model to wafer fabrication parameters control and wafer lot yield optimization. The original data are collected from a wafer fabrication line, including technological parameters and wafer test results. The wafer lot yield is taken as the optimization target. Learning from historical technological records and wafer test results, the model can predict the wafer yield. To eliminate the "bad" or noisy samples from the sample set, an experimental method was used to determine the number of hidden units so that both good learning ability and prediction capability can be obtained.

过程系统管理与技术的综合集成

在激烈的市场竞争中，过程企业不仅要重视技术、更要加强管理，实现全局优化运行。提高过程企业的市场竞争能力必须全面综合集成人、组织、战略管理、经营管理、过程管理及信息自动化技术等因素。本文以石化企业为背景，对过程企业面临的问题及发展趋势进行了分析，并且对过程企业管理模式、过程企业的体系结构以及过程集成与优化技术进行了探讨。

Orientation-based Continuum Damage Models for Rocks

A general formulation of the Helmholtz free energy used in thermodynamics of damage process of rocks is derived within a multi-scale framework. Such a physically-based thermodynamic state potential has a hybrid, discrete/continuum, nature in the sense tha

Comparison of cooling rates for hot carriers in GaAs AlAs quantum wells based on macroscopic and microscopic phonon models

By using three analytical phonon models in quantum wells-the slab model, the guided-mode model, and the improved version of the Huang-Zhu model [Phys. Rev. B 38, 13 377 (1998)], -and the phonon modes in bulk, the energy-loss rates of hot carriers due to the Frohlich potential scattering in GaAs/AlAs multiple quantum wells (MQW's) are calculated and compared to those obtained based on a microscopic dipole superlattice model. In the study, a special emphasis is put on the effects of the phonon models on the hot-carrier relaxation process when taking the hot-phonon effect into account. Our numerical results show that, the calculated energy-loss rates based on the slab model and on the improved Huang-Zhu model are almost the same when ignoring the hot-phonon effect; however, with the hot phonon effect considered, the calculated cooling rate as well as the hot phonon occupation number do depend upon the phonon models to be adopted. Out of the four analytical phonon models investigated, the improved Huang-Zhu model gives the results most close to the microscopic calculation, while the guided-mode model presents the poorest results. For hot electrons with a sheet density around 10(12)/cm(2), the slab model has been found to overestimate the hot-phonon effect by more than 40% compared to the Huang-Zhu model, and about 75% compared to the microscopic calculation in which the phonon dispersion is fully included. Our calculation also indicates that Nash's improved version [J. Lumin. 44, 315 (1989)] is necessary for evaluating the energy-loss rates in quantum wells of wider well width, because Huang-Zhu's original analytical formulas an only approximately orthogonal for optical phonons associated with small in-plane wave numbers. [S0163-1829(99)08919-5].

Estimating water quality pollution impacts based on economic loss models in urbanization process in Xi'an；China

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Study of remote sensing based parameter uncertainty in Production Efficiency Models

The remote sensing based Production Efficiency Models (PEMs), springs from the concept of "Light Use Efficiency" and has been applied more and more in estimating terrestrial Net Primary Productivity (NPP) regionally and globally. However, global NPP estimates vary greatly among different models in different data sources and handling methods. Because direct observation or measurement of NPP is unavailable at global scale, the precision and reliability of the models cannot be guaranteed. Though, there are ways to improve the accuracy of the models from input parameters. In this study, five remote sensing based PEMs have been compared: CASA, GLO-PEM, TURC, SDBM and VPM. We divided input parameters into three categories, and analyzed the uncertainty of (1) vegetation distribution, (2) fraction of photosynthetically active radiation absorbed by the canopy (fPAR) and (3) light use efficiency (e). Ground measurements of Hulunbeier typical grassland and meteorology measurements were introduced for accuracy evaluation. Results show that a real-time, more accurate vegetation distribution could significantly affect the accuracy of the models, since it's applied directly or indirectly in all models and affects other parameters simultaneously. Higher spatial and spectral resolution remote sensing data may reduce uncertainty of fPAR up to 51.3%, which is essential to improve model accuracy.