&lt;title&gt;Knowledge-based APC methodology for overlay control&lt;/title&gt;

Laidler, David; Leray, Philippe; Crow, David A.; Roberts, Keith E.

doi:10.1117/12.485308

Cited by 5 publications

(4 citation statements)

References 4 publications

(4 reference statements)

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“…When the data from these events is used by the APC system for computing feedback corrections on future lots, instability can result. Therefore, it becomes important to minimize the impact of such events on the performance of the run-to-run controller [ 6]. One method often used for responding to changes in the machine constants is to invalidate all historical data representing the tool state prior to the PM event.…”

Section: Compensating For Tool Pm Adjustmentsmentioning

confidence: 99%

Enhancement of photolithographic performance by implementing an advanced process control system

et al. 2004

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Traditional semiconductor manufacturing relies on a fixed process recipe combined with classic statistical process control to monitor the production process. Leading edge manufacturing processes continue to require increasingly stringent critical dimension and overlay control, which in turn demands innovative methods for process control. Meeting tighter process specifications, while maintaining productivity, dictates implementation of Advanced Process Control (APC) methods. An active control method exercised in APC enables the user to modify recipe variables in order to compensate for various disturbances such as drift or step changes in tool operation, or in the conditions of incoming product. The automated version of this control methodology is termed Run-to-Run (R2R) control. R2R control systems compensate for many of the dynamic issues that stand in the way of high level tool dependability, leading to benefits such as compensation for process variation, improved overlay control, rework reduction, reduction in the use of sendahead wafers, and increased exposure tool availability. For R2R systems, the integrity of the data from metrology tools is critical. In an automated Fab environment, data is fed directly from measurement tools into databases, where it is used to generate feedback corrections on subsequent production material. Metrology measurements are often based on pattern recognition at the measurement site. Therefore, problems with pattern recognition can lead to flyer data, which in turn may impact the quality of data used in the feedback loop. Using operators to inspect and approve each measurement is costly. In a foundry environment, where multiple products are manufactured, an additional challenge is introduced. Historical data used to generate feedback can often be out of date when the product is combined with tool status. Routine Preventive Maintenance (PM) procedures may require updating some machine constant values that are related to overlay performance. In these cases, the R2R controller should be "Reset" and a new send-ahead wafer should be used. At Tower, a R2R control system, which provides overlay process corrections, was integrated into the production environment. Overlay performance metrics were monitored before and after system introduction to show the benefit of R2R control. Additional work was done to characterize the performance benefit of introducing advanced data filters and tool PM data into the same R2R control system. Results from the additional work show how effectively identifying and removing outliers can improve data integrity, and how tool PM data can be used to appropriately respond to step functions following exposure tool PM adjustments.

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Section: Compensating For Tool Pm Adjustmentsmentioning

confidence: 99%

Enhancement of photolithographic performance by implementing an advanced process control system

et al. 2004

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“…There is also the EWMA (exponentially weighted moving average) method, which changes weight factor by (4) (1) (2) (3) expanding mao When the difference between the objective number and the measured number in every run is calculated by the moving average, the EWMA control method applies the weight factor by quotient. The EWMA calculation gives a larger weight factor to the more recent value, and reduces this weight factor with the passage of time.…”

Section: Imentioning

confidence: 99%

“…When equation (2) is reformulated as the predictive model for the next run, it becomes~= bU t_1 + at. In equation (4), the output value is substituted by the target value T to calculate the input parameter. The formula is used to obtain the control value in the next run and the same procedure is repeated for the following runs (moyne et aI., 2001).…”

Section: Problem Descriptionmentioning

confidence: 99%

Dynamic deadband control in semiconductor manufacturing

Kim

Baek

et al. 2009

2009 IEEE International Symposium on Assembly and Manufacturing

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This paper proposes efficient control method to minimize process error and to reduce process variance in semiconductor manufacturing. Photo-lithography process make more detailed complex circuit in semiconductor process and is important for quality. However, obstacles were in the process of the facility itself, vibration, wear and tear, and product and process change and environmental impact are difficult to control. In addition, the existing process that is being used for a series of statistical techniques to control the problem was amplified for the change. Therefore, this paper propose effective process control method for reducing process variance by reducing the unnecessary obstacles, quickly detecting changes in the fair, and accurately reflect the degree of change. This study proposes the dynamic deadband control that has a region (band) to detect the status of a process of change and, according to detect changes in the region itself moves the process control. In this research, the semiconductor manufacturing company is supported to perform a more precise control and reduction of fluctuations due to be producing products of uniform quality. Also it can contribute to yield due to the quality incensement, and more and more minted the process control in semiconductor.

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“…The control parameters are independent of one another. The calculation of each parameter is performed using same control method (Laidler et al 2003).…”

Section: Advanced Semiconductor Process Controlmentioning

confidence: 99%

Advanced semiconductor fabrication process control using dual filter exponentially weighted moving average

Kim

Park³

et al. 2010

J Intell Manuf

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Semiconductor industry needs to meet high standards to ensure survival and success in the 21st century. Rising expectations from the customers are demanding the semiconductor industry to manufacture products with both accuracy and precision. To comply with the strict demands, an effective control method for semiconductor manufacturing is introduced. The process environment is afflicted by process disturbances. Different characteristics of the process disturbances require the control method to be able to respond accordingly. This study utilizes two separate exponentially weighted moving average (EWMA) filters simultaneously to improve the performance of the control method. By utilizing dual filters, the influence of the white noise is reduced and the accurate process control is made possible. The proposed methodology is evaluated through simulation in comparison with two other control methods.

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<title>Knowledge-based APC methodology for overlay control</title>

Cited by 5 publications

References 4 publications

Enhancement of photolithographic performance by implementing an advanced process control system

Enhancement of photolithographic performance by implementing an advanced process control system

Dynamic deadband control in semiconductor manufacturing

Advanced semiconductor fabrication process control using dual filter exponentially weighted moving average

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