Supervisory run-to-run control of polysilicon gate etch using in situ ellipsometry

Butler, Stephanie Watts; Stefani, Jerry A.

doi:10.1109/66.286855

Cited by 208 publications

(96 citation statements)

References 22 publications

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“…The U -transformation is similar to principal components transformation. Tseng et al 111 proposed a MEWMA controller under a linear multiple-input-multiple-output model, while Castillo and Rajagopal 112 gave a multiple-input-multiple-output extension to the univariate double EWMA, which was first used by Butler and Stefani 113 . In general, there are several different approaches to the design of MEWMA control charts: (i) statistical design; (ii) economic-statistical design; and (iii) robust design.…”

Section: Mewma Chartsmentioning

confidence: 99%

Multivariate statistical process control charts: an overview

Bersimis

Psarakis

Panaretos

2006

Quality & Reliability Eng

506

313

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In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewharttype control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial least squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.

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Section: Mewma Chartsmentioning

confidence: 99%

Multivariate statistical process control charts: an overview

Bersimis

Psarakis

Panaretos

2006

Quality & Reliability Eng

506

313

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“…control problem that appears in semiconductor manufacturing where batch processing is the norm; see [41], [42], [43], [44]. The loop-shaping procedure is done using the normalized coprime factorization ℋ ∞ design methods of Glover and…”

Section: More Recent Work Done By Tsakalis Et Al [11] [4] [12] [13] Umentioning

confidence: 99%

Discrete-Time PID Controller Tuning Using Frequency Loop-Shaping.

Ashfaque

Tsakalis

2012

IFAC Proceedings Volumes

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i ABSTRACT Proportional-Integral-Derivative (PID) controllers are a versatile category of controllers that are commonly used in the industry as control systems due to the ease of their implementation and low cost. One problem that continues to intrigue control designers is the matter of finding a good combination of the three parameters -P, I and D of these controllers so that system stability and optimum performance is achieved. Also, a certain amount of robustness to the process is expected from the PID controllers. In the past, many different methods for tuning PID parameters have been developed. Some notable techniques are the ZieglerNichols, Cohen-Coon, Astrom methods etc. For all these techniques, a simple limitation remained with the fact that for a particular system, there can be only one set of tuned parameters; i.e. there are no degrees of freedom involved to readjust the parameters for a given system to achieve, for instance, higher bandwidth. Another limitation in most cases is where a controller is designed in continuous time then converted into discrete-time for computer implementation. The drawback of this method is that some robustness due to phase and gain margin is lost in the process.In this work a method of tuning PID controllers using a loop-shaping approach has been developed where the bandwidth of the system can be chosen within an

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“…This kind of control chart is acceptable to detect the large changes in process, but it is insensitive to minor change detection. To overcome this problem, there are many memory-type effective alternatives to the Shewhart chart, namely Cumulative Sum (CUSUM) [1], Exponentially Weighted Moving Average (EWMA) [2], Double Exponentially Weighted Moving Average (DEWMA) [4] and Generally Weighted Moving Average (GWMA) [5] charts have been developed to detect small shifts (about 1.5σ or less).…”

Section: Introductionmentioning

confidence: 99%

Robustness of Memory-Type Charts to Skew Processes

Sukparungsee¹

2016

IJAPM

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This paper aims to study the robustness of Double Exponentially Weighted Moving Average (DEWMA) in order to detect a change in parameter when process are underlying skew distributions. In general, an Average Run Length (ARL) is used as a common measurement to compare the performance of control chart in term of quick detection. The performance of GWMA chart are compared with Exponentially Weighted Moving Average (EWMA) and Generally Weighted Moving Average Control Chart (GWMA) charts which the former outperforms and give a minimal ARL1 for all magnitudes of shift.

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Supervisory run-to-run control of polysilicon gate etch using in situ ellipsometry

Cited by 208 publications

References 22 publications

Multivariate statistical process control charts: an overview

Multivariate statistical process control charts: an overview

Discrete-Time PID Controller Tuning Using Frequency Loop-Shaping.

Robustness of Memory-Type Charts to Skew Processes

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