Spring 2007 Yield Management Solutions48

modeling. SDM can adjust intra-shot distortion error by adjusting aberration fingerprint and also by stage control.

Figure 2 shows an example of hidden overlay errors. This data shows intra-shot distortion error. Traditional overlay sampling, within the circles, confirms that the Advanced Process Control (APC) system is controlling the overlay to about zero. Cur-rent APC systems utilize linear models for overlay control, but other errors can be seen across the exposure field, which provides evidence of non-linear effects. These errors typically go unnoticed and are hidden from conventional sampling schemes. These errors can be significant and amplified by a mix and match exposure tool environment.

This article explores the value that may be realized by having a direct data link between the exposure tools and overlay tools in terms of productivity and overlay control.

Improving overlay accuracy is now especially critical in semi-conductor manufacturing. The ITRS 2005 roadmap indicated that overlay error should be halved compared to ITRS 2004. When analyzing the sources of overlay errors in semiconductor production, it becomes obvious that there are errors unmodeled by the conventional linear model. Figure 1 shows analysis of overlay in DRAM production. About two-thirds of the error is caused by the unmodeled error. These errors must be reduced in order to meet future requirements. The composition of some of this error belongs to high order terms related to exposure tool matching. To reduce these errors, high order modeling of grid errors and distortion errors can prove very effective. Grid errors are inter-shot position errors. Distortion errors are intra-shot position errors. For Nikon’s exposure system, there are functions for Grid Compensation for Matching (GCM)1 and Super Distortion Matching (SDM). GCM can adjust inter-shot exposure position error by using the coefficients of high order

Improving Scanner Productivity and Control through Innovative Connectivity Applications Yuuki Ishii, Shinji Wakamoto – Precision Equipment Company, Nikon CorporationAtsuhiko Kato, Brad Eichelberger – Optical Metrology Division, KLA-Tencor Corporation

Coupled with decreasing technology node budget allowances, alternative processing techniques are also shrinking

overlay budgets. One source of overlay error is distortion matching between exposure tools. High order modeling of

overlay error is proving to be an effective solution. This article shows how high order modeling of grid and distortion

matching enabled overlay improvement of up to 50%.

10

8

6

4

2

0

BiB X BiB Y

5.3

2.6

0.8

5.6

2.3

1.0

Unmodeled errors

Impact of process

Metrology

Figure 1: Sources of overlay error seen in typical DRAM production.

Patterning

Figure 2: Hidden overlay errors are amplified in a mix and match exposure tool environment.

49

Connectivity — The Grand Picture

KLA-Tencor and Nikon are investigating the feasibility of a solution to minimize the impact of mix and match on overlay error. The solution would involve a direct data link between Nikon exposure tool systems and KLA-Tencor’s advanced overlay system. In addition to improving mix and match performance, several other useful applications are expected to be achieved with a direct scanner-metrology link (Figure 3).

One example is the direct exchange of coefficients for mix and match from KLA-Tencor’s database of overlay data. The mix and match coefficients will improve run-to-run overlay perfor-mance for the exposure tool. The benefit of this implementa-tion will be improved overlay performance and reduced rework caused by mix and match errors.

Another is smart sampling that can be achieved by sharing Enhanced Global Alignment (EGA)2 results. EGA is an align-ment procedure done before exposure for a lithography tool and generates data pertaining to the alignment confidence of each wafer. This data can be very helpful in determining which wafers to select for APC feedback and which wafers should be considered for an accurate disposition. Sharing this data with the overlay tool would allow the wafer slot sampling to be dynamically optimized run-to-run. The main benefit is to provide the most relevant data for process control, and yet find the most relevant wafers that would require potential rework.

From the periodic maintenance (PM) perspective, common ownership of the PM data will provide numerous ways to

optimize productivity within the scanner fleet. Utilizing a history database of PM data will provide opportunities for an algorithm which will assist in optimizing the PM frequency. History data can also be used in the event of unscheduled maintenance to decrease the time to repair. Both of these benefits will optimize the productivity of the exposure tool.

Inter-shot and Intra-shot Overlay Error

Inter-shot error is the same as grid error. Variation in grid error can be attributed to wafer thermal expansion or stage mirror bow. This grid error, presented by these effects, falls into the categories of linear and non-linear error. Linear error is typically measured during the run-to-run alignment sequence before exposure using the exposure tool’s EGA system. Another approach is to use a send-ahead wafer on which the data is measured and modeled by a metrology tool with linear corrections feedback to the remainder of the lot. The sources of non-linear error are typically process-induced wafer deforma-tion, stage grid matching, and wafer thermal effects. Regard-less of the above approaches, it is difficult to characterize the non-linear effect on every wafer and yet still maintain exposure tool productivity. One component of the non-linear error that can be compensated for is grid matching. This offset between scanners is normally stable from wafer-to-wafer over time. Nikon’s exposure tool has GCM, which provides the ability to utilize high order models to improve grid performance.

Intra-shot error is the same as distortion error. It is normally caused by distortion matching between exposure tools. As with inter-shot (grid) error, intra-shot distortion error comprises both linear and non-linear errors. Linear errors are typically compensated for by EGA and APC, but there are additional errors which cannot be fit by linear models. These errors are significant enough and will require compensation for in future technology nodes. Non-linear errors are caused by lens aberration, tool to tool distortion differences and il-lumination matching. For these errors, Nikon’s exposure tool utilizes SDM as a means of compensating for shot distortion by high order modeling.

Mix and Match Overlay using GCM and SDM

Figure 4 shows an example of mix and match overlay improve-ment using GCM and SDM. In total, overlay error was im-proved from 22nm (3s) to 13nm (3s). This data was acquired by overlay matching between a KrF scanner and Nikon’s S207D scanner. For the matching test, a special reticle, which has dense sampling of overlay measurement points within the field, was used.

For the analysis of these improvements, grid error (shown in figure 5) is improved from 13nm (3s) to 7nm (3s) using GCM function. Furthermore, distortion error (figure 6) shows improvement from 13nm (3s) to 8nm (3s). Table 1 shows overall improvements using this adjustment procedure.

Today, these corrections can be done on non-product wafers only. However, this assumes that process induced shift and/or distortion will not fluctuate. In future technology nodes,

www.kla-tencor.com/ymsmagazine

Patterning

Nikon ScannerNSRTM

Higher Litho Process Accuracy Tighter Equipment Control

Direct Data Exchange

AEC ApplicationsAutomated PM

PM wafers run like productionShorter PM time

Stage/optics tuning

APC ApplicationsMix and matchAdaptive samplingMore APC correctibles

KLA-TencorArcherTM Overlay Metrology

Higher ProductivityBetter Tool OEE

Figure 3: Schematic of the Nikon and KLA-Tencor connectivity solution.

Tighter connectivity between Nikon and KLA-Tencor

tools not only leads to improved overlay control but

also improved exposure tool productivity and

overall utilization.

Spring 2007 Yield Management Solutions50

Table 1: Benefit summary of SDM and GCM.

Summary and Future Work

The value created by improving the connectivity between the metrology tool and exposure tool has been studied. By using this direct data exchange as a method to optimize the use of high order fitting, one can expect improved overlay, reducing overlay rework and dynamic optimization of sampling.

KLA-Tencor and Nikon are working to provide an automatic feedback system of high order compensation to the exposure tool directly from metrology results. This feedback system can provide adjustment of coefficients of grid and distortion for periodic maintenance. Automating this process will not only lead to improved overlay control but also improved exposure tool productivity and utilization.

Acknowledgement

Yuuki Ishii, Shinji Wakamoto, Atsuhiko Kato, and Brad Eichelberger, “Improving Scanner Productivity and Control through Innovative Connectivity Application,” in Metrology, Inspection, and Process Control for Microlithography XX, Proc. of SPIE 6152, 615247 (2006).

References

1. K. Takahisa, Y. Ishii and N. Tokuda, “Induction of New Tech-niques for Matching Overlay Enhancement,” Proc. SPIE, Vol .4346, pp.1608-1616, 2001

2. T. Umatate, “Method for Successive Alignment of Chip Patterns on a Substrate,” US Patent, 4,780,617, 1988.

on-product overlay feedback including higher order terms will become necessary. Scanner-metrology linking will play an essential role in automating this procedure, and in doing this while running production lots.

Mix and Match Flowchart

Figure 7 shows a flowchart of mix and match adjustments. Distortion data is acquired at the PM timing using a reference wafer and using an associated matching reticle. The distortion data is stored in the database server. When the production wafer arrives at the scanner, the scanner requests matching information (i.e. coefficients for SDM and GCM) and the server returns the information. Then the scanner makes appropriate corrections for matching, with the end result being improved overlay performance. Another key aspect and benefit of the proposed direct link is that it enables the automatic analysis and run-to-run compensation for distortion matching.

Patterning

Before GCM Correction After GCM Correction

Figure 5: Grid error improvements.

Initial With SDM

Figure 6: Distortion matching improvements.

X Y X Y

(a) Offset -1.4 7.5 -0.4 1.4 Compensated in recipe offset

(b) Grid matching (3σ) 13.4 10.7 5.6 6.6 By GCM

(c) Distortion matching (3σ) 12.2 8.8 7.6 5.5 By SDM

(d) Linear error residuals (3σ) 8.9 5.4 2.2 3.4 Compensated in P.P. offset

(e) Other random errors (3σ) 8.5 7.4 8.5 7.5

Total (|m|+3σ )abs(a)+sqrt(b2+c2+d2+e2) 23.3 24.1 13.3 13.3

Initial Data With SDM & GCM Improvement Method

PM Item

PM wafer arrives at scanner

Production Application

Production wafers arrive at scanner

Scanner requests matching information

Overlay tool returns information

Scanner makes appropriate corrections for matching

Scanner exposes the wafer

Improved overlay control

Scanner exposes PM reference wafer with associated matching

Overlay tool performs distortion metrology

Distortion data stored in database

Figure 7: Mix and match adjustments between Nikon and KLA-Tencor tools.

Initial

3σx = 21.9nm3σy = 16.6nm

3σx = 12.9nm3σy = 11.9nm

With GCM & SDM

Figure 4: Overlay improvements using GCM and SDM.