A Multiscale Bayesian SPRT Approach for Online Process Monitoring

Online monitoring of complex processes, such as semiconductor manufacturing processes, often requires the need to analyze sensor data with multiple characteristics. Some of these characteristics include nonstationary behavior, non-Gaussian distribution, high frequency of data generation, and multiscale (multiple frequencies) noise that mask the true nature of the process. Furthermore, it is necessary to implement process monitoring schemes that take into consideration the cost associated with sampling and incorrect decision making without sacrificing sensitivity, robustness, and ease of implementation. In this paper, a novel multiscale Bayesian sequential probability ratio test (MBSPRT) is developed, which is shown to be efficient in monitoring processes with the above characteristics. The MBSPRT method is also made suitable for online application by developing a moving block data processing strategy, which can match the data processing speed with the rate of data acquisition. The efficacy of the MBSPRT method was tested via detection of the end point occurrence in a chemical–mechanical planarization (CMP) process of semiconductor manufacturing using coefficient of friction (CoF) data. The proposed methodology offers a cost effective alternative to the traditional end point method, which is based on expensive metrology. Test results from both oxide and copper metal CMP are presented which show that MBSPRT is uniquely capable of identifying the start and finish of the end point event.      

Online End Point Detection in CMP Using SPRT of Wavelet Decomposed Sensor Data

Efficient end point detection (EPD) in chemical mechanical planarization (CMP) is critical to quality and productivity of the wafer fabrication process. The cost of over and under polishing, and the cost of ownership of many expensive metrology-based EPD methods have motivated the researchers to seek cost effective and efficient alternatives. This paper presents a novel method for EPD, which uses a sequential probability ratio test (SPRT) on the wavelet decomposed coefficient of friction (CoF) data from the CMP process. The method is made suitable for online application by developing a moving block data processing strategy, which matches the rate of data acquisition. Tests on both oxide and copper metal CMP show that the developed methodology is uniquely capable of identifying the start and finish of the end point event.     

In-process detection of microscratching during CMP using acoustic emission sensing technology

An experimental investigation on the correlation between the microscratches and the signal characteristics of acoustic emission (AE) generated during chemical mechanical planarization (CMP) has been performed. CMP experimental results from both laboratory and production line CMP machines have clearly showed that AE rms voltage in the time domain has distinctive features relating to scratching. The sensitivity of AE signals to the CMP process state change was also investigated. The results show that this AE sensing technology can be used as a tool for in-situ microscratch detection and process monitoring in CMP.     

Moving window-based double Haar wavelet transform for image processing.

Image denoising is a lively research field. The classical nonlinear filters used for image denoising, such as median filter, are based on a local analysis of the pixels within a moving window. Recently, the research of image denoising has been focused on the wavelet domain. Compared to the classical nonlinear filters, it is based on a global multiscale analysis of images. Apparently, the wavelet transform can be embedded in a moving window. Thus, a moving window-based local multiscale analysis is obtained. In this paper, based on the Haar wavelet, a class of nonorthogonal multi-channel filter bank with its corresponding wavelet shrinkage called Lee shrinkage is derived. As a special case of this filter bank, the double Haar wavelet transform is introduced. Examples show that it is suitable for a moving window-based local multiscale analysis used for image denoising, edge detection, and edge enhancement.     

An Intelligent Run-to-Run Control Strategy for Chemical–Mechanical Polishing Processes

This paper presents a novel intelligent run-to-run control strategy for chemical–mechanical polishing (CMP) processes. With the help of the recursive least squares identification method for model building, a real-coded genetic algorithm is applied to adaptively adjust the discount coefficients for double exponentially weighted moving average (EWMA) controller. The online intelligent scheme can effectively prevent the CMP processes from reaching unstable condition and can thus achieve high control performance. To demonstrate the effectiveness and applicability of the proposed intelligent run-to-run control strategy, two typical case studies are worked out in this paper. Extensive simulation comparisons with traditional double EWMA run-to-run control were performed. The simulation results show that the proposed intelligent run-to-run control is able to achieve better control performance than conventional schemes, especially for a process that has nonlinearities, process noise, and extra large metrology delays.      

Comparison of dicarboxylic acids as complexing agents for abrasive-free chemical mechanical planarization of copper

Abrasive particles used in chemical mechanical planarization (CMP) of copper often agglomerate and cause scratches on the finished surface. Abrasive-free CMP offers a feasible solution to this problem, and our present work examines four dicarboxylic acids (oxalic, malonic, succinic and glutaric, with increasing carbon chain lengths) as possible complexing agents for such a chemically dominated CMP process. At pH 3.0-4.0, oxalic and malonic acids are most effective for abrasive-free Cu removal. The rates of Cu dissolution and polish (with or without abrasives) are correlated with pH dependent distributions of mono-anionic (for oxalic and malonic) and neutral (for succinic and glutaric) acid species. The surface morphologies of a Cu wafers obtained by abrasive-free CMP in these acids also are more defect free and flat compared to those obtained using abrasives.     

Mechanical and tribological properties of interlayer films for the damascene-Cu chemical-mechanical planarization process

Chemical-mechanical planarization (CMP) has emerged as the most preferred method to achieve excellent global and local planarity in the damascene-Cu process. As the feature sizes shrink, understanding the fundamentals of CMP is critical for successful implementation of the CMP process in sub 0.35-μm technology. It is also important to understand the effects of mechanical and tribological properties of the interlayer films on the CMP process to conduct successful evaluation and implementation of these materials. In this paper, we present the mechanical and tribological properties of various interlayer films (SiO₂, SiC, low-k B, low-k C, Ta, and Cu) and discuss the CMP process of the films in an alumina-based Cu slurry. Mechanical properties were evaluated using a nanoindentation technique. A micro-CMP tester was used to study the fundamental aspects of the CMP process. The coefficient of friction (COF) was measured during the process and was found to decrease both with downward pressure and with platen rotation. An acoustic sensor, attached to the substrate carrier, was used to monitor the process, and the signal was recorded to examine the difference in polishing behavior of these films. The acoustic emission (AE) signal was found to increase with the increase in platen velocity and pressure. Effects of machine parameters on the polishing behavior of the interlayer films and the correlation of mechanical properties with tribological properties have been discussed.     

Inverse analysis of material removal data using a multiscale CMP model

This paper describes a mechanical model for a representative dual axis rotational chemical mechanical planarization (CMP) tool. The model is three-dimensional, multiscale and includes sub-models for bulk pad deformation, asperity deformation, lubrication based slurry flow, carrier film deformation, wafer compliance and material removal by abrasive particles in the slurry. With the model, material removal rate (MRR) can be determined as a function of stress applied to the wafer, relative sliding speed, and material and geometric parameters of the pad and slurry. Experimental material removal rate profiles obtained from Cu polishing experiments performed on a wafer without rotation are analyzed as an inverse problem. We use MRR data to predict local CMP conditions such as fluid film thickness, fluid pressure and contact pressure. The results are consistent with available experimental and analytical information. This inverse technique offers promise as an improved method of CMP model verification.     

Optimization of tribological properties of silicon dioxide during the chemical mechanical planarization process

Chemical mechanical planarization (CMP) has been proved to achieve excellent global and local planarity, and, as feature sizes shrink, the use of CMP will be critical for planarizing multilevel structures. Understanding the tribological properties of a dielectric layer in the CMP process is critical for successful evaluation and implementation of the materials. In this paper, we present the tribological properties of silicon dioxide during the CMP process. A CMP tester was used to study the fundamental aspects of the CMP process. the accessories of the CMP tester were first optimized for the reproducibility of the results. The coefficient of friction (COF) was measured during the process and was found to decrease with both down pressure and platen rotation. An acoustic sensor attached to this tester is used to detect endpoint, delamination, and uniformity. The effects of machine parameters on the polishing performance and the correlation of physical phenomena with the process have been discussed.     

Multi-stage online task assignment driven by offline data under spatio-temporal crowdsourcing

In the era of the Internet of Things (IoT), the crowdsourcing process is driven by data collected by devices that interact with each other and with the physical world. As a part of the IoT ecosystem, task assignment has become an important goal of the research community. Existing task assignment algorithms can be categorized as offline (performs better with datasets but struggles to achieve good real-life results) or online (works well with real-life input but is difficult to optimize regarding in-depth assignments). This paper proposes a Cross-regional Online Task (CROT) assignment problem based on the online assignment model. Given the CROT problem, an Online Task Assignment across Regions based on Prediction (OTARP) algorithm is proposed. OTARP is a two-stage graphics-driven bilateral assignment strategy that uses edge cloud and graph embedding to complete task assignments. The first stage uses historical data to make offline predictions, with a graph-driven method for offline bipartite graph matching. The second stage uses a bipartite graph to complete the online task assignment process. This paper proposes accelerating the task assignment process through multiple assignment rounds and optimizing the process by combining offline guidance and online assignment strategies. To encourage crowd workers to complete crowd tasks across regions, an incentive strategy is designed to encourage crowd workers’ movement. To avoid the idle problem in the process of crowd worker movement, a drop-by-rider problem is used to help crowd workers accept more crowd tasks, optimize the number of assignments, and increase utility. Finally, through comparison experiments on real datasets, the performance of the proposed algorithm on crowd worker utility value and the matching number is evaluated.     

A signal processing method for the friction-based endpoint detection system of a CMP process

A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing(CMP) process is presented.The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal,extracts the Kalman filter innovation from the denoised signal as the feature signal,and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process.Applying the signal processing method,the ...     

一种面向化学机械抛光终点检测系统的信号处理方法

提出了一种针对基于摩擦的化学机械抛光（Chemical Mechanical Polishing,CMP）终点检测系统的信号处理方法。该信号处理方法采用小波阈值去噪的方法去除包含在原始测量信号中的噪声;从去噪后的信号中提取卡尔曼滤波新息作为特征信号;根据CMP过程中卡尔曼滤波新息的特征来判断何时达到CMP终点。应用该信号处理方法,进行了铜CMP过程的终点检测试验。试验结果表明,该信号处理方法可以判断出铜CMP过程的终点。     

Optimized operations by extended X-factor theory including unithours concept

The relationships between tool performance, cycle time, and throughput have been described to achieve the highest productivity. Though tool utilization is low for manually operated tools, long waits prior to product processing lead to a productivity loss in our production line. We focus on operator efficiency in the CMP (chemical mechanical polishing) operation, which, as a typical manually operated tool, influences cycle time. This paper introduces an online/offline unit hour analysis method, which has been designed to optimize operator allocation and headcount in our production line, using X-factor theory in order to achieve the shortest cycle time. By using online/offline unit hour analysis with X-factor theory, the root cause of waiting time can be identified and the relationship between operator headcount and cycle time can be described. The waiting time can be reduced by 35% and the cycle time can be reduced by 25%, according to a simulator with optimized operator allocation and headcount based on online/offline unit hour analysis     

Evolution equations for continuous-scale morphological filtering

Multiscale signal analysis has emerged as a useful framework for many computer vision and signal processing tasks. Morphological filters can be used to develop nonlinear multiscale operations that have certain advantages over linear multiscale approaches in that they preserve important signal features such as edges. The authors discuss several nonlinear partial differential equations that model the scale evolution associated with continuous-space multiscale morphological erosions, dilations, openings, and closings. These equations relate the rate of change of the multiscale signal ensemble as scale increases to a nonlinear operator acting on the space of signals. The nonlinear operator is characterized by the shape and dimensionality of the structuring element used by the morphological operators, generally taking the form of a nonlinear function of certain partial differential operators     

基于MATLAB的语音增强系统的设计

语音增强是信号处理领域中的一个重要的组成部分。在许多语音处理的应用中,例如移动通信,语音识别和助听器,语音信号的处理不得不在具有噪声的环境下进行。在过去的几十年里,人们提出了许多方法去消除噪声和减少语音失真,例如谱减法,基于小波的方法,隐式马尔科夫模型法和信号子空间法等。小波分析由于能同时在时域和频域中对信号进行分析,所以它能有效地实现对信号的去噪。介绍了一种语音增强系统的设计方法,采用Least Mean Square（LMS）算法和小波变换相结合的方法对带噪语音进行去噪,并在MATLAB的Simulink环境下建立了该系统的模型。通过对该模型的仿真表明：该方法去噪效果明显,为该系统在硬件上的实现打下了理论基础。     

基于EPC离线计费系统的研究

3GPP提出的演进分组核心网(EPC)是一种新的全IP核心网,其计费逻辑体系包括两种机制:离线计费(Offline Charging)和在线计费(On-line Charging)。首先介绍了EPC网络的总体架构,随后具体研究了基于EPC离线计费的系统框架、计费话单触发条件和内容计费的实现策略,最后阐述了离线计费流程。     

“数字电子技术基础”混合式教学方法研究

本文结合中国大学MOOC线上学习平台，围绕“以学生为主体，以教师为主导”的现代教育理念，将线上线下混合式教学模式应用于“数字电子技术基础”课程教学中，对线上/线下教学内容、教学方法、教学资源进行了设计和深入研究。教学实践证明，该教学模式能够改进传统教学模式存在的单一性缺陷，实现线上线下教学方法的紧密结合与有效互补，可以大大激发学生的学习兴趣，培养学生自主学习能力、实践能力和创新能力，提升教学效果。     

Multiscale autoregressive processes. I. Schur-Levinsonparametrizations

In many applications it is of interest to analyze and recognize phenomena occurring at different scales. The recently introduced wavelet transforms provide a time-and-scale decomposition of signals that offers the possibility of such analysis. A corresponding statistical framework to support the development of optimal, multiscale statistical signal processing algorithms is described. The theory of multiscale signal representation leads naturally to models of signals on trees, and this provides the framework for investigation. In particular, the class of isotropic processes on homogeneous trees is described, and a theory of autoregressive models is developed in this context. This leads to generalizations of Schur and Levinson recursions, associated properties of the resulting reflection coefficients, and the initial pieces in a system theory for multiscale modeling     

CMP设备市场及技术现状

综述了全球CMP设备市场概况及适应 0 1 8μm工艺平坦化要求的CMP技术现状 ,给出了向30 0mm圆片转移过程中CMP技术占用成本及CMP设备性能指标。     

基于MDL原理的快速在线信号分选算法

研究了一种基于最小描述长度(MDL)原理的快速在线雷达脉冲信号聚类分选算法,该方法利用幅度或相位差异特征,实现对雷达脉冲数据向量的聚类分选处理。设计了基于MDL原理的在线信号分选算法流程,在每接收到一定数量雷达脉冲信号后,执行一次聚类分选处理;对算法流程中的每个处理模块进行了完备的运算量分析,为工程设计提供有效的理论指导;并对比分析了离线和在线算法的性能。仿真结果表明:在线算法的信号分选正确率与离线方法基本一致,具有很强的工程应用前景。