A Novel Virtual Metrology Scheme for Predicting CVD Thickness in Semiconductor Manufacturing

In an advanced semiconductor fab, online quality monitoring of wafers is required for maintaining high stability and yield of production equipment. The current practice of only measuring monitor wafers may not be able to timely detect the equipment-performance drift happening in-between the scheduled measurements. This may cause defects of production wafers and, thereby, raise the production cost. In this paper, a novel virtual metrology scheme (VMS) is proposed for overcoming this problem. The proposed VMS is capable of predicting the quality of each production wafer using parameters data from production equipment. Consequently, equipment-performance drift can be detected promptly. A radial basis function neural network is adopted to construct the virtual metrology model. Also, a model parameter coordinator is developed to effectively increase the prediction accuracy of the VMS. The chemical vapor deposition (CVD) process in semiconductor manufacturing is used to test and verify the effectiveness of the proposed VMS. Test results show that the proposed VMS demonstrates several advantages over the one based on back-propagation neural network and can achieve high prediction accuracy with mean absolute percentage error being 0.34% and maximum error being 1.15%. The proposed VMS is simple yet effective, and can be practically applied to construct the prediction models of semiconductor CVD processes.     

Intelligent prognostics system design and implementation

This paper proposes an intelligent prognostics system JPS) for semiconductor and TFT-LCD manufacturing. The IPS comprises several generic embedded devices (GEDs) and remote clients. The GED can be easily embedded into various types of equipment to acquire equipment engineering data and meet the specification requirements of Interface A for supporting semiconductor industry equipment engineering capabilities. Furthermore, the GED has an open-standard application interface offering pluggable and customized intelligent applications. With this feature, the intelligent applications can be distributed and localized, releasing the factory network burden and enhancing equipment reliability and processing quality. This paper also develops two typical pluggable applications: the predictive maintenance scheme (PMS) for detecting equipment faults and the virtual metrology scheme (VMS) for conjecturing equipment-processing quality. Integrating the PMS into the IPS and the VMS into the IPS are, respectively, accomplished using the conveyor equipment and the sputtering equipment in a TFT-LCD factory. These two illustrative examples clearly demonstrate that IPS is versatile, configurable, and effective.     

A processing quality prognostics scheme for plasma sputtering in TFT-LCD manufacturing

A novel quality prognostics scheme (QPS) for plasma sputtering in TFT-LCD manufacturing processes is proposed. The QPS consists of a conjecture model and a prediction model. The conjecture model can use processing parameters and sensor data to estimate the processing quality (sputtering thickness) in real time. This conjecture function is also called virtual metrology. On the other hand, the prediction model is capable of predicting the processing quality of the next-lot glasses. Neural networks and weighted moving average algorithms are applied to construct the QPS. In particular, a reliance index is developed such that online evaluation of whether the conjecture results of the QPS are trustworthy or not is possible. For increasing the accuracy of the QPS, a self-searching mechanism is designed to automatically search the best set of parameters and functions used by the conjecture and prediction algorithms for cases that the processing properties vary or the recipe changes. Also, an auto-adjusting mechanism is developed for tuning the system parameters of the QPS and bringing the conjecture accuracy within an acceptable bound. Thorough tests using normal and abnormal processing data on one set of plasma sputtering equipment in a TFT-LCD plant show that the values of the mean absolute percentage error of both the conjecture and the prediction results are less than 2%, which validates the effectiveness of the proposed QPS.     

Accuracy and Real-Time Considerations for Implementing Various Virtual Metrology Algorithms

In the semiconductor industry, run-to-run (R2R) control is an important technique to improve process capability and further enhance the production yield. As the dimension of electronic devices shrink increasingly, wafer-to-wafer (W2W) advanced process control (APC) becomes essential for the critical stages of production processes. W2W APC requires the metrology values of each wafer; however, it will be highly time and cost consuming to obtain actual metrology values from each wafer by physical measurement. Recently, an efficient and cost-effective approach denoted “virtual metrology (VM)” was proposed to substitute the actual metrology. To implement VM in W2W APC, both conjecture-accuracy and real-time requirements need to be considered. In this paper, various VM algorithms, including back-propagation neural networks (BPNN), simple recurrent neural networks (SRNN), and multiple regression (MR), are evaluated to see whether they can meet the accuracy and real-time requirements of W2W APC or not. The fifth generation TFT-LCD chemical–vapor deposition process is used to test and verify the requirements. Test results show that both one-hidden-layered BPNN and SRNN VM algorithms achieve acceptable conjecture accuracy and meet the real-time requirements of semiconductor and TFT-LCD W2W APC applications.      

Performance Analysis of EWMA Controllers Subject to Metrology Delay

Metrology delay is a natural problem in the implementation of advanced process control scheme in semiconductor manufacturing systems. It is very important to understand the effect of metrology delay on performance of advanced process control systems. In this paper, the influences of metrology delay on both the transient and asymptotic properties of the product quality are analyzed for the case when a linear system with an initial bias and a stochastic autoregressive moving average (ARMA) disturbance is under an exponentially weighted moving average (EWMA) run-to-run control. Tuning guidelines are developed based on the study of numerical optimization results of the analytical closed-loop output response. In addition, effective metrology delay of a variable time delay system is analyzed based on the resampling technique implemented to a randomized time delay system. A virtual metrology technique is a possible solution to tackle the problem of metrology delay. The tradeoff between additional error of virtual metrology and reduction in time delay is studied. The results are illustrated using an example of control of the tungsten deposition rate in a tungsten chemical–vapor deposition reactor. The basic conclusion is that metrology delay is only important for processes that experience nonstationary stochastic disturbance. In such a case, use of virtual metrology is justified if the error of the virtual metrology method is less than the error caused by stochastic process noise. The accuracy of the virtual metrology noise with respect to the traditional metrology is not critical, provided that the error due to metrology is much less than that due to process disturbances.      

深度反应离子蚀刻过程的统计关键变量分析与推理控制

随着集成电路（IC）的小型化和智能化的需求不断增加,集成电路的电子封装已成为一个新的研究热点。 3D IC利用硅通孔技术（TSV）满足了这一需求,利用深度反应离子蚀刻（DRIE）过程制造TSV也越来越成熟。然而,能够预测和控制硅蚀刻工艺参数对蚀刻质量的影响是DRIE过程的关键。本研究提出一种基于变量分析建立DRIE过孔深度虚拟测量(VM)模型方法。利用特征提取算法减少过程数据的维度,以便于后续模型辨识的需要。在VM模型的基础上,设计推论控制器,提高晶元的深孔质量。实际工业数据验证表明：该方法可以将误差减少到9*10（-4）,大大的改善现有的DRIE工艺。     

An Approach for Factory-Wide Control Utilizing Virtual Metrology

In the semiconductor manufacturing industry, market demands and technology trends drive manufacturers towards increases in wafer size and decreases in device size. Application of factory-wide advanced process control (APC) techniques down to the wafer-to-wafer (W2W) level control capability is becoming the only choice to cope with the demanding situation. However, one of the main limitations in undertaking W2W control is the nonavailability of timely metrology data at the wafer level. Recently virtual metrology (VM) techniques have been proposed to provide timely wafer level metrology data; they have the potential to be used in realizing W2W control. In this paper, the VM approach to W2W control on factory level is described. VM for an individual process is realized by utilizing the preprocess metrology and the process data from the underlying tools that is generally collected in real time for fault detection purposes. The VM implementation for factory-wide run-to-run control brings unique opportunities and issues to the forefront such as dealing with expected lower quality of VM data, coordination between VM modules of cascading processes for better prediction quality, flexibility of the factory-wide controller to accommodate lower quality VM data, dynamic adjustments to the target values of individual processes by the factory-wide controller when using VM data, and dealing with metrology delays at the factory level. Near and long-term solutions are presented to address these issues in order to allow VM to be used today and become an integral part of the factory-wide APC solution for W2W control.     

Multiblock principal component analysis based on a combined index for semiconductor fault detection and diagnosis

The purposes of multivariate statistical process control (MSPC) are to improve process operations by quickly detecting when process abnormalities have occurred and diagnosing the sources of the process abnormalities. In the area of semiconductor manufacturing, increased yield and improved product quality result from reducing the amount of wafers produced under suboptimal operating conditions. This paper presents a complete MSPC application method that combines recent contributions to the field, including multiway principal component analysis (PCA), recursive PCA, fault detection using a combined index, and fault contributions from Hotelling's T/sup 2/ statistic. In addition, a method for determining multiblock fault contributions to the combined index is introduced. The effectiveness of the system is demonstrated using postlithography metrology data and plasma stripper processing tool data.     

基于数据采集器的虚拟仪器计量技术研究

提出一种便捷的虚拟仪器计量方法,介绍虚拟仪器的基本概念及在硬件平台中技术指标的计量检定方法,其技术指标对测量结果有较大的影响。利用软件产生符合硬件平台技术指标的仿真信号,根据虚拟仪器的软件算法对仿真信号进行处理得到测量结果,对结果进行统计分析得到虚拟仪器的综合性能指标。结果表明,这种方法能够准确地完成对虚拟仪器的计量检定工作。     

Electrical Derivative Measurement of High-Power InGaAs LDs Under Scanning Current with Variable Step

For the large driving current of high-power semiconductor Laser diodes (LDs), a modified method to measure the electrical derivative of LDs under scan-ning driving current with variable step length is proposed, which is to achieve the fast and accurate measurement of optical and electrical characteristic parameters of LDs with a relatively small data acquisition. The experimental re-sults show that, with fewer measurements, this method can effectively and accurately measure and extract the LDs corresponding parameters including threshold cur-rent (Ith), voltage-current characteristic (V-I), luminous power-current relation (P-I), electrical derivative curve (IdV/dI-I). The wavelet transformation singularity testing results of the threshold current also verify the accuracy, reliability, and advantage of this method.     

Neural network-based real-time malfunction diagnosis of reactive ion etching using in situ metrology data

To mitigate capital equipment investments and enhance product quality, semiconductor manufactures are turning to advanced process control (APC) methods. With the objective of facilitating APC, this paper investigates a methodology for real-time malfunction diagnosis of reactive ion etching (RIE) employing two types of in situ metrology: optical emission spectroscopy (OES) and residual gas analysis (RGA). Based on metrology data, time series neural networks (TSNNs) are trained to generate evidential belief for potential malfunctions in real time, and Dempster-Shafer (D-S) theory is adopted for evidential reasoning. Successful malfunction diagnosis is achieved, with only a single missed alarm and a single false alarm occurring out of 21 test runs when both sensors are used in tandem. From the results, we conclude that the OES and RGA sensors, in conjunction with the TSNN models, can be effectively used for RIE monitoring and diagnosis. Furthermore, D-S theory is shown to be an appropriate inference methodology.     

CD-AFM在45nm节点半导体芯片检测过程中的应用

本文介绍了关键尺寸原子力显微镜（CD-AFM）在半导体芯片制造中的应用。通过对比现有的半导体检测仪器与原子力显微镜的工作原理和检测方法,详细探讨了原子力显微镜在目前的半导体芯片45nm节点工艺关键尺寸检测中的优势地位。根据芯片在线关键尺寸检测的具体要求,提出了原子力显微镜急待解决的相关研究内容。     

Similarity approach for reducing qualification tests of electronic components

Qualification analysis and reliability testing of electronic components represent a major activity in the process of development of electronic equipment. Electronics manufacturers have to adopt often costly test programmes to ensure qualification standards and reliability requirements are met. This paper details a novel similarity-based qualification approach for assessing expected reliability of electronic components, and in general electronic products, as an alternative to conventional physical testing. The originality of this work is in the proposed approach which introduces a new way of qualifying electronic components based on similarity with previously assessed and qualified components. This novel approach has the potential to transform in a major way the current operational practices in the industry, demanding at present substantial physical testing, by offering a complementary, “virtual qualification” route for addressing the cost and time challenges associated with qualification tests.A major achievement is the comprehensive and detailed demonstration of the proposed reliability qualification approach. Case studies on qualifying electronic components to the thermal loads induced by a particular post-manufacturing process widely adopted by high-reliability electronics sectors – the robotic hot solder dip (refinishing) process, and associated risks of thermo-mechanical damage are presented and discussed.     

Patterning tool characterization by causal variabilitydecomposition

A spatial and causal classification of process error provides opportunities for the accurate determination and efficient management of process error budget. Traditional metrology is posed with this dilemma: variability sampling requires cheap, highly repeatable metrology, such as electrical measurements, which also confound error sources of the variability sampled. In response, statistical metrology has been proposed as a novel combination of cost-effective metrology with subsequent statistical or experimental data processing to provide a technique that is capable of error decomposition into equipment causes. The methodology, consisting of 1) reticle and experiment design, 2) data filtering, and 3) error budget formulation, is presented and is general to a short-loop thin-film patterning sequence. A .35-μm polygate patterning sequence is chosen to demonstrate this technique. Reticle design and statistical filtering have been presented in a previous publication, and are summarized here. The second causal data filter is presented in this work, Aided by additional experimentation, a physical filter decomposes the separate contributions and interactions of the reticle and stepper. A portion of the error budget is calculated, including the effects of spatial correlation. The results of decomposition yields a numerical metric for equipment and process manufacturability. Results are presented that illustrate the use of the manufacturability metric in equipment selection and process design     

基于表征转换机的SAR图像目标分割方法

针对SAR(Synthetic Aperture Radar)图像中的目标分割问题,由于目标与杂波空间模式(像素强度和分布)不同,通过分析图像空间模式的方式可达到分辨目标和杂波并分割目标的目的。该文基于表征转换机理论提出一种有效的SAR图像目标分割方法,该算法分析SAR图像中的空间模式,计算其与参考杂波图像的相似程度,最后将与参考杂波相似程度较高的部分消除以达到分割目标的目的,并在衡量相似度部分使用基于累积直方图的自动阈值选取办法。仿真和实测数据的实验验证了此算法的有效性。      

基于低频噪声检测的电力MOSFET可靠性分析

针对变电所中通信电源的核心器件电力金属氧化物半导体场效应晶体管(power MOSFET,P-MOSFET)在大功率、强电流下易损坏、故障率高,直接影响电力通信业务的安全稳定运行的问题,提出了一种基于低频噪声检测的可靠性分析方法.利用互功率谱测量方法检测P-MOSFET内部的本征低频噪声,根据频段阈值法的拐点噪声谱,确定P-MOSFET筛选的上下限阈值大小,建立了P-MOSFET的1/f噪声功率谱密度及其阈值的对应关系式.实验结果表明,与传统的有损检测法相比,该方法能够有效评估P-MOSFET的三种可靠性等级,提高了可靠性筛选的准确率,为其他晶体管的可靠性评估提供了参考.     

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.      

Analysis of satellite on-board time-space-time switching networkswith multiple separated space switches

Advanced satellite on-board baseband switching processors have time-space-time (T-S-T) structures which are similar to the terrestrial switching networks (Sw-Nw). Generally, the satellite systems require higher reliability than ground equipment because of more severe environment and lack of repair. This paper proposes fault-tolerant satellite on-board T-S-T Sw-Nw with multiple separated space switches instead of a single spare switch. The authors analyze the mean time to unreliable operation (MTUO), as a performance and reliability index for the T-S-T systems with multiple separated space switches as well as conventional T-S-T systems. The MTUO varies depending on the threshold level of blocking-probability and the offered traffic. In general, T-S-T Sw-Nw with multiple space switches have better performance and reliability than those with the single space switch, and their performabilities are appreciably improved, especially for one additional spare space switch. This study can be extended to analyze the performance and reliability of entire satellite communication systems including the on-board baseband Sw-Nw, Rx interfaces, and Tx interfaces     

Enhancement of semiconductor equipment communications using aweb-enabled equipment driver

Equipment communications are essential for semiconductor manufacturing automation. Equipment managers generally function to communicate between the manufacturing execution system (MES) and equipment. Connecting a different machine to the equipment manager requires modifying the associated equipment driver (ED) accordingly, which needs some efforts. To solve this problem, this study proposes a novel, web-enabled equipment driver (WED) that uses mobile object technology. Initially, a mobile object model with a Java applet, namely WED, is developed. WED is constructed on the equipment (server) side. Then, the equipment manager (client) downloads WED via a web browser. This process does not need to modify ED. Subsequently, the equipment manager can communicate with the equipment by either the Java socket technology using the high-speed SECS message services (HSMS) standard or the object web technology through the common object request broker architecture (CORBA) or distributed component object model (DCOM) protocols using the object-based equipment model (OBEM) standard. This proposed scheme has been successfully implemented. Illustrative examples reveal that the proposed mobile object model and WED establish a novel, efficient, and versatile scheme for semiconductor equipment communications