用Visual Basic 6.0编程实现显微图像测量

Visual Basic 6.0具有强大的图形图像处理功能,并广泛应用于图形设计、图像处理及多媒体技术中。本文着重介绍了Visual Basic 6.0在实现显微图像测量中的编程技术,并应用于半导体芯片尺寸测量。     

数字化体视显微系统的深度测量

随着微系统、微控制等技术的不断发展,工业自动化和生产中对微观测量的需求日益增加,对精度、效率、成本等方面提出了更高的要求.针对这一现状,结合显微技术与双目视觉技术,以常用的体视显微镜及双相机构建了一个数字化显微视觉深度测量系统.首先设计连接件连接相机与显微镜并搭建测量系统;然后通过调整相机位置进行机构对准与系统参数标定...     

基于三坐标测量圆度误差测量的精度分析

本文主要介绍了三坐标测量的原理及应用前景,针对三坐标测量圆度误差所产生的精度问题进行分析,研究三坐标测量圆度误差时产生的测量误差并提出解决措施。     

发动机试验测量参数精度的分析

对发动机台架试验中几个重要测量参数的精度进行了分析计算,并给出了已知总体精度要求的情况下确定其他测量参数精度的方法。     

提高电桥测量精度的探讨

本文论述一种新颖的惠斯登电桥的双电流源激励方式。采用这种方式不仅可增大有用信号的幅度,而且消除了用传统的单电压源或单电流源激励时产生的非线性误差,使其成为一种理想的线性测量电桥。文中详细分析了不同激励方式的非线性,并讨论了其他性能,最后给出了几种实用的恒流源电路。     

周期性脉动流对涡轮流量计测量精度影响的分析

提出流量计如何能在流动存在的情况下准确地测出测量。选择正弦脉动流讨论周期性脉动流对涡轮流量计测量精度的影响,认为脉动流频率的大小严重影响涡轮流量计测量精度,涡轮叶片转动惯量和稳态时的叶片转速也对精度有不同程度的影响。     

相机镜头焦距自动测量系统的设计及精度分析

提出了一种以线阵CCD传感器取代读数显微镜，以8253可编程芯片实现自动测量并实时显示测量结果的相机镜头焦距测量系统，论述了系统的工作原理和软硬件的实现，分析了系统的测量误差；证明了系统的可行性和先进性，系统具有较高的实用价值和应用前景。     

铂电阻温度计及其测量精度的分析

铂电阻温度计是温度测量中最常用的温度传感器,其测量精度是工业精密测量中备受关注的重要指标。本文在研究铂电阻温度计测温特性的基础上确定了其测温公式,并证明了利用测量公式计算测量温度可以提高铂电阻温度计的测量精度。采用本文所提测温公式计算得到的温度偏差在±0.05℃范围之内,测量精度比查表法高了一个数量级。此方法不需增加额外成本和仪器,经济实用性高。     

小孔内径测量的传感器精度分析

针对小孔的结构特点,介绍了电容传感器探针测量小孔孔径的原理;分析了测量时电容传感器由于参数的线性化、电容探针与小孔的中心线偏心带来的测量误差;并针对以上因素影响,采取了自动对中机构实现测量过程中的最小化偏心,通过标定得到了孔径值与测量值之间的对应关系。实验结果表明,系统的重复性精度可达到0.186μm,稳定性能达到6 h内漂移不超过0.375μm,该指标完全可以满足实际测量要求。     

预置旋转正交坐标系测量精度分布解析

预置旋转正交坐标系在姿态测量时可增强原始信号幅度,较大地提高了姿态测量的总体精度.通过解算传感器三轴相对误差公式的方法,对预置旋转正交坐标系测量精度分布进行深入分析,研究了预置旋转正交坐标系姿态测量各区域的精度分布特征.图例表明,三轴相对误差在大角度井斜均存在极值点,并且三轴传感器输出相对误差随井斜和工具面角变化而变化.在小角度姿态测量时利用预置旋转的正交坐标系是比较理想的.     

基于蚁群算法的半导体生产线调度方法研究

为了解决具有可重入特性的半导体生产线调度问题,提出基于蚁群算法的半导体生产线调度模型（ASWFSM）。在模型中,利用图论的方法把调度方案的寻优过程转换为蚂蚁对有向图的搜索,并且,引入专家系统作为推理机避免了寻优过程中对可行节点判断的复杂性。仿真试验证明,此模型具有良好的调度效果和稳定性。     

Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing

Since semiconductor manufacturing consists of hundreds of processes, a faulty wafer detection system, which allows for earlier detection of faulty wafers, is required. statistical process control (SPC) and virtual metrology (VM) have been used to detect faulty wafers. However, there are some limitations in that SPC requires linear, unimodal and single variable data and VM underestimates the deviations of predictors. In this paper, seven different machine learning-based novelty detection methods were employed to detect faulty wafers. The models were trained with Fault Detection and Classification (FDC) data to detect wafers having faulty metrology values. The real world semiconductor manufacturing data collected from a semiconductor fab were tested. Since the real world data have more than 150 input variables, we employed three different dimensionality reduction methods. The experimental results showed a high True Positive Rate (TPR). These results are promising enough to warrant further study.     

Scheduling of multiple in-line steppers for semiconductor wafer fabs

A few prior studies noticed that an in-line stepper (a bottleneck machine in a semiconductor fab) may have a capacity loss while operated in a low-yield scenario. To alleviate such a capacity loss, some meta-heuristic algorithms for scheduling a single in-line stepper were proposed. Yet, in practice, there are multiple in-line steppers to be scheduled in a fab. This article aims to enhance prior algorithms so as to deal with the scheduling for multiple in-line steppers. Compared to prior studies, this research has to additionally consider how to appropriately allocate jobs to various machines. We enhance prior algorithms by developing a chromosome-decoding scheme which can yield a job-allocation decision for any given chromosome (or job sequence). Seven enhanced versions of meta-heuristic algorithms (genetic algorithm, Tabu, GA–Tabu, simulated annealing, M-MMAX, PACO and particle swarm optimisation) were then proposed and tested. Numerical experiments indicate that the GA–Tabu method outperforms the others. In addition, the lower the process yield, the better is the performance of the GA–Tabu algorithm.     

Scheduling cluster tools in wafer fabrication using candidate list and simulated annealing

This paper presents a new method for scheduling cluster tools in semiconductor fabrication. A cluster tool consists of a group of single-wafer chambers organized around a wafer transport device, or robot. Cluster fabrication system considered in this paper consists of serial cluster tools. Due to constraints imposed by multiple routes of each wafer type and machines with no buffer, it is difficult to find an optimal or near-optimal schedule. In order to determine the sequence of the operations to be released and the assignment of the machine to each operation, the proposed method uses a job requirement table with random keys as a solution representation. Simulated annealing seeks the optimal or near-optimal sequence and machine assignment of the operations. In this paper, the scheduling objective is to find a schedule with minimum makespan. A Gantt chart is obtained as the final schedule. To handle the constraints, the proposed method uses a candidate list. To determine which operation can be scheduled in considering the constraints, a negotiation procedure between the operations in the candidate list and a current state of the system is introduced. To show the effectiveness of the proposed method, scheduling example of a real cluster fabrication system is presented. Scheduling results are compared with those obtained by using several dispatching rules. From the experimental results, it is shown that the proposed method is promising.     

晶圆表面缺陷模式的在线探测与自适应识别研究

晶圆表面的缺陷通常反映了半导体制造过程存在的异常问题,通过探测与识别晶圆表面缺陷模式,可及时诊断故障源并进行在线调整。提出了一种晶圆表面缺陷模式的在线探测与自适应识别模型。首先该模型对晶圆表面的缺陷模式进行特征提取,基于特征集对每种晶圆模式构建相应的隐马尔科夫模型（Hidden Markov Model,HMM）,并提出基于HMM动态集成的晶圆缺陷在线探测与识别方法。提出的模型成功应用于WM-811K数据库的晶圆缺陷检测与识别中,实验结果充分证明了该模型的有效性与实用性。     

Decomposition-based classified ant colony optimization algorithm for scheduling semiconductor wafer fabrication system

Due to its typical features, such as large-scale, multiple re-entrant flows, and hybrid machine types, the semiconductor wafer fabrication system (SWFS) is extremely difficult to schedule. In order to cope with this difficulty, the decomposition-based classified ant colony optimization (D-CACO) method is proposed and analyzed in this paper. The D-CACO method comprises decomposition procedure and classified ant colony optimization algorithm. In the decomposition procedure, a large and complicate scheduling problem is decomposed into several subproblems and these subproblems are scheduled in sequence. The classified ACO algorithm then groups all of the operations of the subproblems and schedules them according to machine type. To test the effect of the method, a set of simulations are conducted on a virtual fab simulation platform. The test results show that the proposed D-CACO algorithm works efficiently in scheduling SWFS.     

一种晶上系统互连网络的容错感知结构

晶上系统融合预制件组装和晶圆集成等先进理念,是延续摩尔定律的一种新方法。由于晶圆基板本身制造良率和拼接的不确定性,晶上系统存在路由节点故障或链路故障等问题。为提高系统容错性,提出了一种基于2D-Mesh晶上互连网络的容错感知结构。在Mesh环中交叉使用主副感知器用于获取故障信息,再将其广播至全局路由节点实现数据包的避障绕行,缓解数据包在路由过程中可能发生的阻塞。实验仿真表明该结构在多种故障模式下,相较于传统容错路由算法有更高的饱和注入率,能够有效提高系统容错性,降低局部故障导致的性能影响。     

一种基于光散射原理在线测量晶圆表面质量的方法

在半导体工业中,晶圆表面质量的检测占据着重要的地位。选择粗糙度参数轮廓算术平均偏差R。作为衡量表面质量的参数,根据晶圆的一般粗糙度范围（Rα为0.01—0.8μm）,构建了一种基于光散射原理的视觉系统测量装置。通过分析光散射强度分布图像,提取出一些参数来表征Rα,达到检测晶圆表面质量的目的。给出了初步的实验结果,说明了此方案是可行的。     

晶圆表面微米级缺陷检测

为降低晶圆缺陷对半导体制造的影响,在基于改进的多重中值滤波算法的基础上,以差影法为基本原理,采用归一化互相关的模版匹配方法实现晶圆表面缺陷检测。改进的多重中值滤波算法有效实现噪声点与非噪声点的分辨,归一化模版匹配算法对光照具有很好的鲁棒性。对大量的晶粒进行实验,实验结果表明,该方法可有效检测出晶圆表面的缺陷,精度达到15μm左右,所提检测算法在实际的应用中可代替人工,快速、准确地实现晶圆的缺陷检测。     

IC封装设备切片机电控系统设计

为了高速、高精度切割半导体晶片,切片机的电控系统要求具备高精度及高稳定度。根据系统设计指标和可编程控制器（PLC）的特点,选用日本OMRON公司的CS1G型PLC构成主控系统,FC10/400型高速电机及其配套变频器构成高速主轴系统,Y、Z轴则用PD-0535M型步进电机驱动器驱动步进电机构成开环控制系统,X轴采用交流伺服电机及增量式编码器构成半闭环系统,？轴选用美国Parker公司DM1004B型转台交流伺服电机及DrvMⅡ型电机驱动器,供电系统采用隔离变压器等方法来屏蔽电磁干扰。通过多模块运动控制软件协调控制,该系统完全达到了设计要求。