Improving Scanner Productivity and Control

P atterning
Improving Scanner Productivity
and Control through Innovative
Connectivity Applications
Yuuki Ishii, Shinji Wakamoto – Precision Equipment Company, Nikon Corporation
Atsuhiko 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%.
Improving overlay accuracy is now especially critical in semiconductor 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
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. Current 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.
10
8
6
5.3
5.6
Unmodeled errors
2.6
2.3
Impact of process
0.8
1.0
Metrology
4
2
0
BiB X
BiB Y
Figure 1: Sources of overlay error seen in typical DRAM production.
48
Figure 2: Hidden overlay errors are amplified in a mix and match
exposure tool environment.
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P atterning
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).
Nikon Scanner
NSRTM
KLA-Tencor
ArcherTM
Overlay Metrology
Higher Litho Process Accuracy
Tighter Equipment Control
Direct Data
Exchange
AEC Applications
Higher Productivity
Better Tool OEE
Automated PM
PM wafers run like production
Shorter PM time
Stage/optics tuning
APC Applications
Mix and match
Adaptive sampling
More APC correctibles
Figure 3: Schematic of the Nikon and KLA-Tencor connectivity solution.
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 performance for the exposure tool. The benefit of this implementation will be improved overlay performance and reduced rework
caused by mix and match errors.
Tighter connectivity between
Nikon and KLA-Tencor
tools not only leads to improved
overlay control but
also improved exposure tool
productivity and
overall utilization.
Another is smart sampling that can be achieved by sharing
Enhanced Global Alignment (EGA)2 results. EGA is an alignment 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
www.kla-tencor.com/ymsmagazine
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 deformation, stage grid matching, and wafer thermal effects. Regardless 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 illumination 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 improvement using GCM and SDM. In total, overlay error was improved 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,
49
P atterning
Initial
3σx = 21.9nm
3σy = 16.6nm
3σx = 12.9nm
3σy = 11.9nm
Figure 4: Overlay improvements using GCM and SDM.
Before GCM Correction
Initial Data
With GCM & SDM
With SDM & GCM Improvement
Method
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
Table 1: Benefit summary of SDM and GCM.
Production Application
After GCM Correction
PM Item
PM wafer arrives at scanner
Scanner exposes PM reference
wafer with associated matching
Overlay tool performs
distortion metrology
Distortion data stored
in database
Figure 5: Grid error improvements.
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
Figure 7: Mix and match adjustments between Nikon and KLA-Tencor tools.
Summary and Future Work
Initial
With SDM
Figure 6: Distortion matching improvements.
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.
50
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 Techniques 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.
Spring 2007 Yield Management Solutions