A multivariate double EWMA process adjustment scheme for drifting processes

Castillo, Enrique Del; Rajagopal, Ramkumar

doi:10.1080/07408170208928934

Cited by 57 publications

(23 citation statements)

References 9 publications

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“…Further extensions have been made by Adivikolanu and Zafiriou (2000). Stability conditions for double-EWMA controllers were presented by Del Castillo and Rajagopal (2002). Adivikolanu and Zafiriou (1997) presented an EWMA controller in an IMC structure (as shown in Fig.…”

Section: Stability Propertiesmentioning

confidence: 97%

Smith–EWMA run-to-run control schemes for a process with measurement delay

Jin

Tsung

2009

IIE Transactions

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The Exponentially Weighted Moving Average (EWMA) controller is a popular run-to-run controller in the semiconductor manufacturing industry. The controller adjusts input based on measurement information from previous runs. EWMA controllers can guarantee satisfactory results in many cases; however, when there is a measurement delay in the process, the stability properties and performance of the EWMA controller cannot be guaranteed. In order to maintain the satisfactory outcomes of EWMA controllers, a Smith predictor control scheme is introduced, created particularly for time delay systems in control theory, into EWMA controllers. A modification of the EWMA controller, called the Smith-EWMA run-to-run controller, is proposed. Comparisons between the stability properties of Smith-EWMA and EWMA run-to-run controllers are studied. Moreover, a performance comparison with the EWMA and recursive-least-square controllers under disturbance conditions based on simulation is conducted. The results show that when there is a measurement delay, the proposed Smith-EWMA run-to-run controllers enlarge the stability region and also achieve better performance when there is serious metrology delay and model uncertainty under process disturbances.

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Section: Stability Propertiesmentioning

confidence: 97%

Smith–EWMA run-to-run control schemes for a process with measurement delay

Jin

Tsung

2009

IIE Transactions

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“…However, the MIMO process cannot be controlled properly by EWMA if there is correlation between different outputs [19]. Tseng et al [18] proposed a multivariate EWMA controller (termed MEWMA) to tackle this problem.…”

Section: Literature Reviewmentioning

confidence: 99%

A Run-to-Run Profile Control Algorithm for Improving the Flatness of Nano-Scale Products

Wang

2015

IEEE Trans. Automat. Sci. Eng.

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In scaling-up Carbon Nanotubes (CNTs) array manufacturing, the uniformity of CNTs' height, or flatness of array, is critical for the yield of nanodevices fabricated from CNTs, and thus needs to be properly controlled. However, since the flatness of the CNTs array is better characterized by a profile, the conventional run-to-run (R2R) controllers that are designed for a single or multiple quality indicators are not effective in controlling the CNTs array manufacturing process. Therefore, in this work, we first develop a statistical model to characterize the variation of the flatness profile, and then derive a novel R2R profile controller based on a state-space model and Kalman filter to improve the flatness of CNTs array. The performance of the proposed R2R control algorithm is studied and compared with existing controller via simulation studies. Note to Practitioners-In the quality control practice, it should be noted that many aggregated quality indicators or the pass/fail conclusions are, in fact, drawn on the basis of complex measurements. Such measurements convey rich information about the process variability and quality patterns, and is therefore critical to quality improvement.This work focuses on a scaling-up nano-manufacturing process. The quality of the product is characterized by a profile, which contains information about both the location and the flatness of the product. We design a statistical model to characterize product quality, then derive a control algorithm to improve the flatness by adjusting controllable process variables. Such data-driven modeling and control framework is critical to study processes with complex quality metrics and large uncertainties.Index Terms-Nano-manufacturing, run-to-run (R2R) control, statistical quality control.

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“…While significant efforts have been devoted to the improvement of the stability and sensitivity in response to process noise of the EWMA scheme (e.g., Wang, 2010;Wang et al, 2010), this scheme becomes insufficient for processes subject to highly nonlinear batch-to-batch dynamics of the process drift. Motivated by this, several authors have proposed using a double exponentially weighted moving average (dEWMA) formula, which can capture the changes in the rate of the process drift, and thus, forecast the process drift in the next batch run (Bulter and Stefani, 1994;Simith et al, 1998;Castillo, 1999;Chen and Guo, 2001;Castillo and Rajagopal, 2002;Su and Hsu, 2004;Tseng and Hsu, 2005;Wu and Maa, 2011).…”

Section: Introductionmentioning

confidence: 99%