A virtual metrology model based on recursive canonical variate analysis with applications to sputtering process

Pan, Tianhong; Sheng, Bi-Qi; Wong, David Shan-Hill; Jang, Shi-Shang

doi:10.1016/j.jprocont.2011.04.004

Cited by 8 publications

(3 citation statements)

References 23 publications

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“…e result of applying recursive RO-DPLS to the digester under feedback control have shown that the control performance was improved by feeding estimates back to a PID controller. In the semiconductor industry, Pan et al (2011) proposed an adaptive virtual metrology (VM) based on recursive canonical variate analysis (RCVA) and applied it to an industrial sputtering process.…”

Section: Changes In Process Characteristics and Operatingmentioning

confidence: 99%

Virtual Sensing Technology in Process Industries: Trends and Challenges Revealed by Recent Industrial Applications

Kano

Fujiwara

2013

J. Chem. Eng. Japan / JCEJ

169

110

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Virtual sensing technology is crucial for high product quality and productivity in any industry. This review aims to clarify the trend of research and application of virtual sensing technology in process industries. After a brief survey, practical issues are clari ed by introducing recent questionnaire survey results: 1) changes in process characteristics and operating conditions, 2) individual di erence of equipment, and 3) reliability of soft-sensors. Since input variable selection is crucial for high estimation performance, conventional methods and new group-wise variable selection methods are introduced, and the usefulness of the group-wise variable selection methods is demonstrated through industrial case studies. Just-in-time (JIT) modeling is dealt with as a promising virtual sensing technology that can cope with changes in process characteristics as well as nonlinearity. Recent developments leading to successful industrial applications are introduced: correlation-based JIT (CoJIT) modeling and locally weighted regression (LWR), especially LW-PLS, with modi ed similarity measures. Manufacturing processes in di erent industries are quite di erent in appearance, but they have very similar problems from the viewpoint of quality issue. There remain practical issues requiring further research e orts to realize high-performance, maintenance-free virtual sensing technology.

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Section: Changes In Process Characteristics and Operatingmentioning

confidence: 99%

Virtual Sensing Technology in Process Industries: Trends and Challenges Revealed by Recent Industrial Applications

Kano

Fujiwara

2013

J. Chem. Eng. Japan / JCEJ

169

110

View full text Add to dashboard Cite

show abstract

“…Naik et al 12 proposed two recursive algorithms for fault detection, which are based on the perturbation theory and the orthogonal iterations. Pan and Sheng et al 19 proposed an online virtual metrology approach based on recursive CVA with application to an industrial sputtering process. In addition, a few monitoring approaches based on the multivariate statistical theory have also been proposed.…”

Section: Introductionmentioning

confidence: 99%

Recursive Fault Detection and Identification for Time-Varying Processes

Shang

Liu²,

Zhang³

2016

Ind. Eng. Chem. Res.

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Canonical variate analysis (CVA) has been extensively applied in monitoring of different industrial processes. However, conventional CVA is unable to handle the characteristics of time-varying processes. It tends to interpret the natural changes of the process as faults, which would cause high false alarm rates. To solve this problem, a recursive canonical variate analysis based on the first order perturbation theory (RCVA-FOP) is proposed to detect faults in time-varying processes. Without recalling past training data, the covariance of past observation vectors is updated by the exponential weighted moving average (EWMA) method. Moreover, the first order perturbation theory is introduced to realize the recursive singular value decomposition (SVD) of the Hankel matrix, which can reduce computational time significantly compared with the conventional SVD. To identify the real reason for a fault, an EWMA contribution plot based on CVA is also proposed to enhance the fault identification rate. The proposed method is verified with simulations of the continuous stirred tank reactor. Simulation results indicate that the RCVA-FOP method not only can effectively adapt to the natural changes of time-varying processes but also can detect and identify three types of faults, which include sensor precision degradation, heat exchanger fouling fault, and sensor bias.

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“…It uses statistical tools such as multiple linear regression, Canonical Variate Analysis (CVA), Neural Networks (NNs), and Partial Least Squares (PLS) to predict the response of process output. Typically, Pan et al (2011aPan et al ( , 2011b applied stepwise regression, CVA, and analysis of covariance models to construct VM model for sputtering and wafer acceptance test problems in semiconductor manufacturing. Chang et al (2006), Su et al (2006), andHung et al (2007) applied NNs to build a VM system for a sputtering process in thin film transistor-liquid crystal display industries, chemical mechanical planarization, and chemical vapor deposition processes in semiconductor manufacturing, respectively.…”

Section: Introductionmentioning

confidence: 99%

Modified EWMA controller subject to metrology delay

2013

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The resource and capacity limitations of the metrology equipment used in the creation of integrated circuits result in delay being a common issue for the practical implementation of run-to-run control scheme. In the literature, several papers have provided the means of using metrology delay data or Virtual Metrology (VM) prediction models on the transient behavior and asymptotic stability of Exponentially Weighted Moving Average (EWMA) controllers. However, these procedures still suffer from large bias and/or variation of the process response variable. To overcome this difficulty, a modified EWMA controller is proposed that adjusts the process by using both the metrology delay data and VM information. The analytical expression of the process output of this developed controller and its long-term stability along with short-term output performance are derived. Furthermore, under some specific parameter settings, a more comprehensive study is presented to illustrate that the proposed controller has the capability to reduce the total mean square error of process response variable compared with existing controllers.

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A virtual metrology model based on recursive canonical variate analysis with applications to sputtering process

Cited by 8 publications

References 23 publications

Virtual Sensing Technology in Process Industries: Trends and Challenges Revealed by Recent Industrial Applications

Virtual Sensing Technology in Process Industries: Trends and Challenges Revealed by Recent Industrial Applications

Recursive Fault Detection and Identification for Time-Varying Processes

Modified EWMA controller subject to metrology delay

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