Intelligent sampling decision scheme based on the AVM system

Wafer inspection plays a significant role in monitoring the quality of wafers production for continuous improvement. However, it requires measuring tools and additional cycle time to do real metrology, which is costly and time-consuming. Therefore, reducing sampling rate to as low as possible is a high priority to reduce production cost. Several sampling methods in the literature were proposed to achieve this goal. They utilised real sampling inspections as the representatives for the other related wafers to monitor the whole production process. Under the condition of stable manufacturing process, virtual metrology (VM) may be applied to monitor the quality of wafers, while real metrology is unavailable. Therefore, the sampling rate may further be reduced with a sampling decision scheme being designed according to reliable VM. Nevertheless, once a new production variation occurs between planned samplings and no real metrology is available during this period for updating the VM models, un-reliable VM predictions may be produced. The authors have developed the automatic virtual metrology (AVM) system for various VM applications. Therefore, this paper focuses on applying various indices of the AVM system to develop an intelligent sampling decision scheme for reducing sampling rate, while VM accuracy is still sustained.     

Total precision inspection of machine tools with virtual metrology

The technology of virtual metrology (VM) has been applied in the semiconductor industry to convert sampling inspection with metrology delay into real time and online total inspection. The purpose of this study is trying to apply VM for inspecting machining precision of machine tools. However, machining processes will cause severe vibrations that make process data collection, data cleaning, and feature extraction difficult to handle. Thus, the tasks of how to accurately segment essential parts of the raw process data from the original numerical-control file, how to effectively handle raw process/sensor data with low signal-to-noise ratios, and how to properly extract significant features from the segmented and clean raw process data are challenging issues for successfully applying VM to machine tools. These issues are judiciously addressed and successfully resolved in this paper. Testing results of machining standard workpieces and cellphone shells of two three-axis CNC machines show that the proposed approach of applying VM to accomplish total precision inspection of machine tools is promising.     

Automatic virtual metrology for wheel machining automation

Total inspection after wheel machining becomes essential for safety consideration and continuous improvement. However, conducting wheel-by-wheel actual metrology is very expensive and time-consuming. A novel idea is to use virtual metrology (VM) that predicts wheel quality based on process data collected from machine tool with a slight supplement of actual metrology data. The technology of automatic virtual metrology (AVM) has been proposed by the authors and successfully deployed in hi-tech industries, such as semiconductor, display and solar cell. The purpose of this study was to propose an approach to apply the AVM system factory-wide to wheel machining automation (WMA) for achieving total inspection of all the precision items of WMA under mass production environment.     

具有几何约束的非等面积界面布局优化方法

目的 由于计算的难度与精度问题,在求解布局的过程中通常不考虑待布局元素面积的大小和形状的几何约束问题,导致求解的布局结果是理论上的,无法达到真正实用的目的。为提高界面布局优化方法生成布局方案的可用性,提出了一种集成启发式算法、多属性决策(MAMD)和整数线性规划(ILP)的方法。方法 首先,在获取到待布局元素间相关性、待布局元素的使用频率和面积等数据情况下,使用遗传算法(GA)通过改变待布局元素几何约束的参数生成一组备选布局方案;其次,将交互成本、GA寻优所花费的时间、有效性、效率和满意度作为评价界面布局的五个指标,根据TOPSIS、AHP和数据包络分析(DEA)等多属性决策方法对所有备选布局方案进行排序;最后,使用ILP方法获取一致性排序。结果 获得一个有效、具有高可用性的布局方案。结论 根据实验结果可知,该方法寻到的最优布局方案比原始方案有效地降低了交互成本和算法寻优的时间,提高了布局方案的可用性。     

计量信息系统在线原始记录编制及证书自动生成的功能实现

针对现有计量信息系统没有把原始记录编制纳入系统流程中,无法实现证书自动生成,从而带来检定校准环节工作效率不高,证书差错率无法降低等问题,提出了如何在线实现原始记录编制及证书自动生成的方法。介绍了在过程设计中遇到的难点和注意事项,并分析了改进后的信息系统的优点和如何规避潜在的风险。     

带SSR修正的异步多传感器系统的无味JPDA跟踪

针对杂波环境下多变采样率传感器多目标跟踪问题,考虑到二次雷达(SSR)具有辨别敌我方目标和更精确的高度探测能力,本文提出了一种带SSR修正的异步多传感器系统的无味JPDA跟踪算法.该算法首先通过测量值映射的异步数据处理方法对多传感器数据进行点迹的合成,然后通过二次雷达对敌方目标的高度信息进行自适应修正,最后用无味JPDA算法对按序到来的异步采样量测进行顺序滤波融合.通过蒙特卡洛仿真,表明该算法在提高目标跟踪精度和正确关联概率上是有效的.     

基于Multi-Agent的人机环境仿真设计系统

提出了用于制造过程仿真和人机工程分析的多Agent智能设计系统。基于模糊多目标决策理论建立了虚拟人自适应作业行为仿真模型。在虚拟环境中,智能化的虚拟人能自主完成作业任务的仿真,优化自身的工作状态,同时提供人机工程的评估结果。通过仿真实验,证明了所用技术的可行性。     

Using reliability analysis to support decision making in phased mission systems

Because of the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary decision diagrams (BDDs) offer fast, accurate reliability analysis that could contribute to real‐time decision making. However, phased mission analysis using existing BDD models is too slow to contribute to the instant decisions needed in time‐critical situations. This paper investigates 2 aspects of BDD models that affect analysis speed: variable ordering and quantification efficiency. Variable ordering affects BDD size, which directly affects analysis speed. Here, a new ordering scheme is proposed for use in the context of a decision‐making process. Variables are ordered before a mission, and reordering is unnecessary no matter how the mission configuration changes. Three BDD models are proposed to address the efficiency and accuracy of existing models. The advantages of the developed ordering scheme and BDD models are demonstrated in the context of their application within a reliability analysis methodology used to support decision making in an unmanned aerial vehicle.     

基于声信号识别的焊后残余应力处理质量检测方法

焊后残余应力处理过程的非线性程度高且参数耦合性强,导致处理质量不稳定。而现有检测方法仅做抽样检测,存在检测精度低、周期长等问题,且无法进行实时在线检测。为此,提出一种新的基于声信号识别的焊后残余应力处理质量在线检测方法。该方法先实时采集焊后残余应力处理过程中的声信号并提取其特征,然后构建基于多权值神经网络的焊后残余应力处理质量检测模型,以实现在线识别。实验结果表明,相比于传统检测方法,所提出方法可实现焊后残余应力处理质量的在线检测,可为焊后处理过程中的参数优化和质量控制提供参考。     

Design of exponential control charts based on average time to signal using a sequential sampling scheme

Exponential charts based on time-between-events (TBE) data are widely investigated and applied in various fields. The average time to signal (ATS) is used instead of the average run length to evaluate the performance of TBE charts, since the ATS involves both the number and the time of samples inspected until a signal occurs. An ATS-unbiased exponential control chart is proposed when the in-control parameter is known. Considering the need in practice to start monitoring a production process as soon as possible, a sequential sampling scheme is adopted and the in-control parameter is estimated by an unbiased and consistent estimator. Some specific guidelines to stop updating control limits are obtained from the relationship between the phase I sample size and the actual false alarm rate. Finally, two real examples are given to illustrate the implementation and efficiency of the proposed method.     

Complex-Valued Wavelet Lifting and Applications

Signals with irregular sampling structures arise naturally in many fields. In applications such as spectral decomposition and nonparametric regression, classical methods often assume a regular sampling pattern, thus cannot be applied without prior data processing. This work proposes new complex-valued analysis techniques based on the wavelet lifting scheme that removes “one coefficient at a time.” Our proposed lifting transform can be applied directly to irregularly sampled data and is able to adapt to the signal(s)’ characteristics. As our new lifting scheme produces complex-valued wavelet coefficients, it provides an alternative to the Fourier transform for irregular designs, allowing phase or directional information to be represented. We discuss applications in bivariate time series analysis, where the complex-valued lifting construction allows for coherence and phase quantification. We also demonstrate the potential of this flexible methodology over real-valued analysis in the nonparametric regression context. Supplementary materials for this article are available online.     

Advanced ART2 scheme for enhancing metrology-data-quality evaluation

The metrology-data-quality-index (DQI_y) algorithm was proposed to perform metrology-data-quality evaluation of the automatic virtual metrology system developed by the authors. The DQI_y algorithm is based on the adaptive-resonance-theory 2 (ART2). ART2 divides data into different patterns according to the similarity of process data, and then calculates the corresponding DQI_y value and its threshold, DQI_yT, for evaluation and judgment. However, in practical applications, the classical ART2 technique still could not cluster process data very precisely. Since some samples with dissimilar process parameters might be sorted into the same cluster, two or more groups could be found in the corresponding metrology-data cluster. This phenomenon may cause invalid DQI_y detection. To solve the problem above, the advanced ART2 scheme is proposed in this paper to enhance the accuracy of the DQI_y algorithm. A large industrial data-set showing both a shift in metrology measurements without a process shift and a process shift that was not captured by the metrology of the actual photo and color-filter production tools of a TFT-LCD factory were adopted as illustrative examples to verify the practicality of the proposed scheme. Experimental results show that the performance of the advanced ART2 is indeed better than that of the original ART2.     

An attribute control chart for multivariate Poisson distribution using multiple dependent state repetitive sampling

In this paper, an attribute control chart for a multivariate Poisson distribution using multiple dependent state repetitive sampling (MDSRS) is presented. The evaluation of the proposed control chart is given through the average run length (ARL). The proposed control chart performs better than the existing control chart based on repetitive sampling and that using multiple dependent state sampling in terms of ARLs. A real example and a simulation study are added to explain the procedure and to demonstrate the power of the proposed control chart.     

On Modified Successive Sampling Based Control Charting Schemes

The presence of variation cannot be avoided in different kinds of manufacturing and non‐manufacturing processes. A better understanding of the causes of variability in any process is necessary to improve the process. Control chart is a very frequently used tool for checking whether the process parameters are stable or not. The current study devises a sampling technique, named as modified successive sampling scheme, that is not only cost‐effective but also efficient as compared with the simple random sampling scheme. A number of Shewhart‐type control charts are proposed based on the said sampling scheme, and average run length is used as a performance indicator. Based on the average run length values, all the proposed charts are compared with existing Shewhart control chart for both positive and negative shifts in the process. Finally, the new proposals are applied to a real dataset where the variable of interest is an inner diameter of automobile engine piston rings made of steel. Copyright © 2015 John Wiley & Sons, Ltd.     

测量与信息技术

测量是获取信息的重要手段。科学研究、生产、高科技发展都离不开测量。测量技术发展的重要特点是它与信息技术的融合,这是提高测量精度、在线和动态测量、复杂参数和复杂环境下测量、智能测量的需要。这一融合贯彻始终,它包括信号调制与解调、采样与重构、信号融合、数据压缩、滤波、信号变换、时间序列分析、谱分析、数据拟合与建模、模式识别、神经网络、仿真与虚拟、误差分离、误差补偿、冗余技术、决策与智能技术等,它们互相支持。章通过三坐标测量机误差补偿、圆度和轴系误差测量,以及大型工程的柔性坐标测量系统,介绍其在提高测量精度、优化、自标定、丢失信息自恢复、系统重组等方面的作用及其关键技术。     

On developing sensitive nonparametric mixed control charts with application to manufacturing industry

Control charts are designed under the normality assumption of the quality characteristic of the process. However, the normality assumption rarely holds in practice. In non-normal conditions, parametric charts tend to display more false alarm rates and invalid out-of-control comparisons. The exponentially weighted moving average chart is a frequently used memory-type control chart for monitoring the process target that only performs effectively under the smoothing parameter's small choices. This study proposes a nonparametric mixed exponentially weighted moving average-progressive mean chart based on sign statistic (NPMEP_SN) under simple and ranked set sampling schemes to address this said drawback. Normal and non-normal distributions are included in this study to observe the proposed chart's in-control behavior and out-of-control efficacy. The prominent feature of the proposed schemes is that it works efficiently in detecting small and persistent shifts in the process location corresponding to the given values of the smoothing parameter. The proposed scheme is also tested under the ranked set sampling scheme to enhance the NPMEP_SN chart's performance (hereafter named “NPMEP_RSN”). The performance of the proposed charts is investigated through simulations using run-length profiles. The proposed schemes were seen to outperform other alternatives, specifically under the ranked set sampling scheme. A real data-set related to the diameter of a piston ring is included as a demonstration of the proposal.     

基于启发式算法的在线多尺寸行李码放问题求解

目的 为了解决目前大部分三维装箱算法无法求解航空运输背景下机场托运行李在线码放的问题,开展在线托运行李码垛算法研究.方法 首先,基于实际应用环境提出一种全新的码放顺序约束以及在线多尺寸行李码放数学模型.然后,设计一种有别于传统在线问题一次仅获取一件物品信息的规则,通过改变获取行李信息三维相机的位置,从而提前获取更多的行李信息,提出每次获取K个行李尺寸信息,并构建组合式码放策略的在线启发式"填充点"算法.最后,采用每次获取3件真实机场托运行李信息进行仿真和实验.结果 结果证明,算法给出的码垛布局方案不仅可以确保在线状态下不同类型尺寸托运行李的高效码放,且优化后的算法可获得84.86％的填充率,同时具有良好码放稳定性.结论 算法给出的码垛布局方案合理,有较好的填充率,为此后航空运输背景下在线三维装箱问题的算法设计提供了一个新方向.     

Dependent Mixed and Mixed Repetitive Sampling Plans for Linear Profiles

In this paper, we present two new dependent mixed sampling plans and a mixed repetitive sampling plan based on the process yield index for linear profiles. A mixed sampling plan includes two stages; the first stage is a combined test by variables and by attributes, and the second stage is tested by attributes only. The first plan is based on the traditional mixed sampling scheme without marginal quality, and the second plan is based on the modified mixed sampling scheme with marginal quality. If a lot is very bad, the probability it can be rejected with the small initial sample is higher for dependent mixed sampling with marginal quality. We compare dependent mixed plans with other types of double sampling plans; the former outperforms the others with respect to average sample number. Additionally, the number of profiles required in the first stage is much smaller than in the second stage. When the inspection is costly and destructive, a mixed repetitive sampling plan includes one stage that combines the inspection by attributes and by variables and allows resampling in some conditions. We compare the mixed repetitive sampling plan with the repetitive sampling plans by attributes and by variables. The probability of acceptance using the mixed repetitive sampling plan performs better than the repetitive sampling plans by attributes and by variables. Three examples are used to illustrate the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.     

A Modeling Approach to Maintenance Decisions Using Statistical Quality Control and Optimization

Maintenance concerns impact systems in every industry and effective maintenance policies are important tools. We present a methodology for maintenance decision making for deteriorating systems under conditions of uncertainty that integrates statistical quality control (SQC) and partially observable Markov decision processes (POMDPs). We use simulation to develop realistic maintenance policies for real‐world environments. Specifically, we use SQC techniques to sample and represent real‐world systems. These techniques help define the observation distributions and structure for a POMDP. We propose a simulation methodology for integrating SQC and POMDPs in order to develop and valuate optimal maintenance policies as a function of process characteristics, system operating and maintenance costs. A two‐state machine replacement problem is used as an example of how the method can be applied. A simulation program developed using Visual Basic for Excel yields results on the optimal probability threshold and on the accuracy of the decisions as a function of the initial belief about the condition of the machine. This work lays a foundation for future research that will help bring maintenance decision models into practice. Copyright © 2005 John Wiley & Sons, Ltd.     

Time finite element based Moreau‐type integrators

With the postulation of the principle of virtual action, we propose, in this paper, a variational framework for describing the dynamics of finite dimensional mechanical systems, which contain frictional contact interactions. Together with the contact and impact laws formulated as normal cone inclusions, the principle of virtual action directly leads to the measure differential inclusions commonly used in the dynamics of nonsmooth mechanical systems. The discretization of the principle of virtual action in its strong and weak variational form by local finite elements in time provides a structured way to derive various time‐stepping schemes. The constitutive laws for the impulsive and nonimpulsive contact forces, ie, the contact and impact laws, are treated on velocity‐level by using a discrete contact law for the percussion increments in the sense of Moreau. Using linear shape functions and different quadrature rules, we obtain three different stepping schemes. Besides the well‐established Moreau time‐stepping scheme, we can present two alternative integrators referred to as symmetric and variational Moreau‐type stepping schemes. A suitable benchmark example shows the superiority of the newly proposed integrators in terms of energy conservation properties, accuracy, and convergence.