Lamb-wave microdevices fabricated on monolithic single crystalsilicon wafers

Reliable and inexpensive microdevices that can be used in physical, chemical, biological, and environmental applications are in great demand. Lamb-wave (LW) ultrasonic devices have been shown to be extremely useful for applications in liquid environments. Working LW devices have been fabricated in this investigation on monolithic single crystal membranes using well-established integrated-circuit technology. The detailed fabrication procedure, photoacoustic testing of the piezoelectric material film, and a demonstration of device performance are presented in this paper. In practice, device performance was very sensitive to the surface quality of the membrane structure. This process presents the possibility for further size reduction, increased integration, and large-scale production     

Defect detection in patterned wafers using anisotropic kernels

Wafer defect detection often relies on accurate image registration of source and reference images obtained from neighboring dies. Unfortunately, perfect registration is generally impossible, due to pattern variations between the source and reference images. In this paper, we propose a defect detection procedure, which avoids image registration and is robust to pattern variations. The proposed method is based on anisotropic kernel reconstruction of the source image using the reference image. The source and reference images are mapped into a feature space, where every feature with origin in the source image is estimated by a weighted sum of neighboring features from the reference image. The set of neighboring features is determined according to the spatial neighborhood in the original image space, and the weights are calculated from exponential distance similarity function. We show that features originating from defect regions are not reconstructible from the reference image, and hence can be identified. The performance of the proposed algorithm is evaluated and its advantage is demonstrated compared to using an anomaly detection algorithm.     

具有多品种晶圆混合加工的单臂组合设备调度

为了提高晶圆制造中组合设备的生产效率,在考虑晶圆驻留时间约束条件下,研究没有共享加工模块的多品种晶圆混合加工的单臂组合设备调度问题.首先,采用面向资源的Petri网模型描述多种晶圆产品的混合加工过程,引入控制变迁避免模型的死锁,采用赋时库所和赋时变迁模拟系统资源的活动时间.其次,通过虚拟加工的方法平衡工序的负载,基于系统Petri网模型和拉式调度策略,推导出单臂组合设备在多品种晶圆混合加工情形下的可调度性判定条件,并以解析形式描述.最后,提出了系统稳态调度求解算法并以实例验证了算法的有效性和可行性.     

Defect spatial pattern recognition using a hybrid SOM–SVM approach in semiconductor manufacturing

As manufacturing geometries continue to shrink and circuit performance increases, fast fault detection and semiconductor yield improvement is of increasing concern. Circuits must be controlled to reduce parametric yield loss, and the resulting circuits tested to guarantee that they meet specifications. In this paper, a hybrid approach that integrates the Self-Organizing Map and Support Vector Machine for wafer bin map classification is proposed. The log odds ratio test is employed as a spatial clustering measurement preprocessor to distinguish between the systematic and random wafer bin map distribution. After the smoothing step is performed on the wafer bin map, features such as co-occurrence matrix and moment invariants are extracted. The wafer bin maps are then clustered with the Self-Organizing Map using the aforementioned features. The Support Vector Machine is then applied to classify the wafer bin maps to identify the manufacturing defects. The proposed method can transform a large number of wafer bin maps into a small group of specific failure patterns and thus shorten the time and scope for troubleshooting to yield improvement. Real data on over 3000 wafers were applied to the proposed approach. The experimental results show that our approach can obtain over 90% classification accuracy and outperform back-propagation neural network.     

Hole-type two-dimensional photonic crystal fabricated in silicon on insulator wafers

We report the realization of two-dimensional (2D) photonic crystal (PhC) holes array using synthesized processing techniques of deep UV lithography, time-multiplexed reactive ion etching (TMRIE) and focus ion beam (FIB) etching. In this study, mixed density of holes and waveguide patterns of 2D PhC structures was first formed in silicon on insulator wafers through use of a scanner. Ultra wide grooves were then defined, aligned to the deep submicron size devices. Following deep etching of more than 50 μm by TMRIE, PhC structures were then revealed for device etching. Such design of fabrication process allows realization of disparate pattern dimensions and also etching depths. Through avoidance of etch lag effect, notching of devices at interface of device silicon and buried oxide layer was avoided. At the same time, through a singular FIB etch in the final step of the process following buried oxide release for PhC structures on critical dimension structures, severe loading effects of such structures were avoided to enable a wide process window of lithography and etch.     

基于半导体硅片的容栅千分传感器的设计

容栅千分传感器广泛应用于位移测量中,设计的容栅千分传感器,将普通容栅传感器在线路板上的刻线划分移植到了半导体硅片上,利用了半导体的工艺技术,实现刻线划分的高精度、高密度,从而达到普通线路板无法达到的精度,将容栅传感器的分辨力提高至0.001 mm.     

An Analytical Subthreshold Swing Model for fully-depleted MOSFETs with vertical Gaussian profile fabricated on modified silicon-on-insulator wafers

Microsystem Technologies - The objective of this study is to present an analytical subthreshold swing model for fully-depleted metal-oxide semiconductor field-effect transistors (MOSFETs) with...     

A nondestructive automated defect detection system for silicon carbide wafers

Manual methods of defect detection and classification on silicon carbide (SiC) wafers are tedious, time consuming, and prone to error. We have developed a nondestructive optical stress technique (photoelasticity) to isolate structural defects on SiC wafers. The technique is rapid, nondestructive, and inexpensive. In this paper we present an image processing system that exploits the optical system to detect structural defects on SiC wafers automatically. We are specifically interested in detecting defects known as micropipes. The philosophy of our approach is to reduce the dependency of the environment factors, image acquisition factors, and user parameters while maintaining the performance and computational speed. The goal is achieved by careful study of patterns that are invariant to the contrast and shift of pixel intensities and a combination of simple image processing techniques that are locally adaptive.Received: 27 January 2004, Accepted: 7 October 2004, Published online: 5 April 2005     

半导体企业高级订单承诺系统

为提高半导体企业的客户服务质量,研究半导体产业多工厂多阶段生产供应链系统和多客户关系、多产品市场环境下的订单承诺（Available-to-Promise,ATP）优化问题.以利润和客户满意度为目标,充分利用半导体产品之间的替代性,建立基于线性规划的高级ATP系统.该系统应用优化软件OPL将模型中的内容转化为OPL语言.仿真实验表明,该方法能帮助半导体企业提高订单响应速度,做出可靠ATP决策.     

一种新型的半导体SMA缺陷识别方法的研究

摘 要: 针对半导体器件在封装工艺中出现表面缺陷,及缺陷形态多样性和不可预测性而带来的模型适应性低等问题,提出了基于双向二维主成分分析和改进的卷积神经网络相结合的缺陷识别方法。首先为克服样本不均匀带来的识别精度低问题,对训练图像进行反射变换等操作构造虚拟样本,然后使用Bi-2DPCA对图像进行降维压缩,提取图像主要特征,再由改进的AlexNet网络进行缺陷识别分类,并提出正态随机采样层,将其加在AlexNet网络的卷积层后进行下采样,同时在全连接层中引入DropConnect来提高网络的泛化性能。实验表明,提出的算法较相关算法有较高的识别率,并在实际的SMA塑封图像数据上得到了验证,同时该算法具有较好的泛化性能。     

A virtual metrology system for semiconductor manufacturing

Nowadays, the semiconductor manufacturing becomes very complex, consisting of hundreds of individual processes. If a faulty wafer is produced in an early stage but detected at the last moment, unnecessary resource consumption is unavoidable. Measuring every wafer’s quality after each process can save resources, but it is unrealistic and impractical because additional measuring processes put in between each pair of contiguous processes significantly increase the total production time. Metrology, as is employed for product quality monitoring tool today, covers only a small fraction of sampled wafers. Virtual metrology (VM), on the other hand, enables to predict every wafer’s metrology measurements based on production equipment data and preceding metrology results. A well established VM system, therefore, can help improve product quality and reduce production cost and cycle time. In this paper, we develop a VM system for an etching process in semiconductor manufacturing based on various data mining techniques. The experimental results show that our VM system can not only predict the metrology measurement accurately, but also detect possible faulty wafers with a reasonable confidence.     

用于半导体气体传感器的程控标定系统

组建了一套用于半导体气体传感器的程控标定系统。该系统使用一台四路输出的程控直流电源对半导体气体传感器进行编程加热 ,计算机控制质量流量计实现低体积分数被测气体的精确配气并实时采集传感器的响应信号。该系统可对由四支气体传感器构成的阵列进行多种工作模式的标定。     

基于频率簇模型的人脸识别

目的 针对复杂条件下人脸识别鲁棒性差的问题,提出了一种基于频率簇（FC）模型的人脸识别方法。方法 该方法首先在人脸图像内检测目标区域,在目标区域内划分特征子区域并设定采样单元,统计采样单元内前景区域和背景区域的信息熵;然后计算采样单元的熵能量和能量频率,归一化频率系数,利用能量频率的二阶偏导确定人脸子区域边界,以此得到有效采样单元,建立人脸主特征信息;最后,根据采样单元的坐标位置、熵能量和能量频率信息进行排序,得到每个采样单元的几何布局,以采样单元的熵能量、能量频率和几何布局构建人脸的频率簇模型,并以此作为人脸特征进行识别匹配。结果 在FERET、ORL、Yale组合人脸库和CMU-PIE人脸库上进行实验测试,该方法的识别准确率分别为99.11%和97.36%,单幅人脸图像的平均识别速度为0.077 s,结果表明,该方法对复杂条件下的人脸识别具有很好的实时性和准确性。结论 该方法可以有效克服光照变化、特征模糊、姿态和表情变化等因素对人脸识别的影响,具有较好的鲁棒性,对提高人脸识别性能具有重要意义。     

用于并行计算的PC集群系统构建*

在注射成形模拟研究过程中,涉及材料的牛顿和非牛顿黏性流动模拟和注射成形后期的冷却过程模拟,以及随时间变化各处的压力变化等科学和工程领域经常应用大规模科学计算。随着基于网格的计算和数据处理日益复杂,很多计算一般PC系统无法满足要求,需要超级计算环境。因为不断追求更高的计算精度和日益复杂的对象而扩大计算规模,传统的串行处理方式难以满足这些要求。因此,现代高性能计算的低成本、高效率成为选择并行计算的解决方式。重点阐述如何构建一个用于并行计算的PC集群系统,结合实例阐明MPI的实现方法,以及对PC集群系统进行了性     

光谱仪群的集中分布式控制系统设计

某大型天文望远镜配置了16台多目标低分辨率光纤光谱仪,每台光谱仪有14个运动部件。为使众多的运动部件快速、准确、安全、协调地运动到位,设计了局域网集中分布式控制方案。控制网络由上级计算机（OCS）、中央控制计算机、工业控制计算机构成。对该控制方案的硬件平台构建和控制系统软件设计进行了详细的介绍。     

An energy management system for cluster infrastructures

This paper presents a general energy management system for High Performance Computing (HPC) clusters and cloud infrastructures that powers off cluster nodes when they are not being used, and conversely powers them on when they are needed. This system can be integrated with different HPC cluster middleware, such as Batch-Queuing Systems or Cloud Management Systems, and can also use different mechanisms for powering on and off the computing nodes. The presented system makes it possible to implement different energy-saving policies depending on the priorities and particularities of the cluster. It also provides a hook system to extend the functionality, and a sensor system in order to take into account environmental information.     

基于多维度映射的类圆簇识别算法

为了深入地探索聚类结果簇的形态特征,提出了一种基于维度映射的类圆簇识别算法。该算法将结果簇按维度进行映射,通过比较、分析簇在各个映射维度上的频数曲线及形态特征,自动将类圆簇从众多结构复杂的聚类结果簇中识别出来。算法经过大量实验验证,具有很好的识别能力和抗干扰能力,对于高维度数据集合也具有很强的扩展性。     

聚类分析在肺结节识别中的应用

针对肺部微小结节难于识别的问题,提出用聚类算法分析肺部感兴趣区域(ROI)的方法。为进一步提高运行速度和识别率,提出全权模糊聚类算法PWFCM,给每个样本及其特征分别赋予权值并引入新的隶属度约束改进收敛性;利用二次聚类策略降低不均衡ROI数据造成的低敏感度。对实际CT影像数据进行测试,实验结果表明：该聚类分析具有高敏感度和低假阳性率,能有效地检测出肺结节。