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Reliable, Repeatable Wafer and Tool Dispositioning in 300 mm Fabs Bruce Johnson, Rebecca Pinto, Ph.D, and Stephen Hiebert , KLA-Tencor Corporation
Advances in wafer fabrication along with rising economic pressures on chipmakers have created greater challenges in the dispositioning of wafers and process tools. Such a climate has rendered it nearly impossible for manual disposition inspection to deliver even adequate results in a manufacturing environment or for process tool requalification. Manual inspectors often miss gross process problems, passing wafers downstream, where they will later be scrapped or create yield loss.Automated disposition, on the other hand, can integrate into a fab’s defect analysis infrastructure to enable better yield learning. These advantages, plus an automated system’s capability for high sampling, make it suitable for a low cost of ownership inspection strategy.
Introduction
Advanced fabs require accurate and rapid disposition decision-making during manufacturing, as well as a quick assessment of tool and process module output. Operators at manual or semi-automated inspection stations have historically done much of this, but these methods have been ineffective for quite some time. Manual inspections are expensive, and the results are well known to be unreliable. This is especially true for advanced 300 mm manufacturing, where vanishingly small device features, factory automation, and large wafer surfaces challenge the ability of the operator to assess the wafer and lot; these conditions place large quantities of valuable wafers at risk. There are cases in most fabs where an operator has missed process or tool errors which have resulted in litho hot spots, CMP underpolish, scratches, underetch, splashback, coating failures, and many other types of gross errors. These can happen randomly on one wafer in a lot, on some pattern of wafers within a lot (such as every other wafer due to process tool chamber/stage configuration), or on a whole production lot. Most fabs have had significant yield hits from lots 64
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which were, for example, not coated with resist, but which were not recognized or sampled by the inspector and ultimately had to be scrapped. The cost of a small inspection error – missing a significant, but challenging-to-detect process error – can be very high. In fabs with large product mixes, such as a foundry or a development line, each lot may represent all of the material for a specific customer. The loss of that lot, especially if it happens late in the device manufacturing process, can be devastating to both the fab and its relationship with the fab’s customer. For some smaller fabless semiconductor customers, it can almost be fatal because of the cycle time hit on a key part. Yet, these failures do happen with surprising regularity when fabs are not able to sample at the level and sensitivity required to capture critical excursions consistently and early on. Manual inspection has resulted in many cases of missed problems and resultant loss because of its inability to reliably find important defects. Automated inspection, on the other hand, is well suited to performing the disposition job. Its major strengths are: • Good sensitivity to detect defects of all types • Consistent results from tool to tool, day to day, and fab to fab • High throughput to adequately sample every lot
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Figure 1. Examples of product wafer frontside litho errors targeted at disposition inspection. (Problems routinely missed by inspection operators are highlighted in red.)
• Low cost of operation • Factory automation to work within a fully automated fab • Detailed, documented results compatible with fab defect analysis systems This paper examines these aspects of disposition inspection for both manual and automated approaches.
Low-overhead automatic recipe creation Recipe creation with an automated wafer and tool disposition system can offer many economic advantages for a fab: • Simple, reality-based recipe design and user interface • Derivative recipes (layout, layer,
The job of disposition
The vast majority of production lots are good, and should be passed on to the next processing step. However, every once in a while, there may be a processing problem which impacts any of:
disposition rules) • Low skill level required, especially for derivate recipes • Automated recipe completion at first run
• A large portion of a wafer • One or several wafers within a lot
• Consistent, fast results between recipes
• An entire lot • Multiple lots These problems may come from the challenging process windows of today’s advanced technology, material problems, process recipe errors, process drift, operator error, or production tool errors.
Dispositioning vs. defect line monitoring
The disposition inspection’s goal is to quickly find these larger problems and to identify if there is an overall problem with the process which requires attention. It is not the goal of the inspection to find smaller subtle Spring 2006
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Integrating with the automated factory Even the best manual inspector does not run
• Engineering disposition – for issues which the operator might not be positioned to handle
on factory automation, and s/he needs to be
In addition, the disposition result may flag the need to stop the process or production tool, either by a qualified operator or the responsible engineer.
in proximity to the wafers, which violates the goals of a highly automated fab. Automated inspection, on the other hand, is fully compatible: • Automatic material handling • Remote review • Status reporting • Remote host control • Alarms for wafer and lot results • Alarms for tool status
problems which are ongoing yield detractors, such as is done with defect line monitor, or with film thickness, overlay error, and CD measurement. These inspections and measurements are typically done on a small statistical sample—two or three wafers per lot--and fed directly into a process control scheme. Most fabs perform automated disposition inspection on every lot since the problems can happen on a lot-to-lot basis and resultin expensive loss. Because it is done on (almost) every lot, it is important that the inspection also be fast to keep production moving. Most material will pass. The rejected material may go into one of several paths, depending on the process module and type and severity of problem:
Disposition inspection criteria
The disposition needs to be accurate and consistent; it should neither reject good material (often called the Alpha risk), nor should it pass bad material (Beta risk). Both errors can be costly. The limitations of manual inspection are known to give it a high Beta risk, and this shows up in higher downstream scrap and yield loss. Automated inspection’s higher capture rate of all defect types improves this, but it should not do this at the cost of higher Alpha risk, which may impact fab productivity. It is important that the disposition inspection be immune to normal process variation which could result in false rejects. Along these lines, it is also useful for the inspection to be able to bin defects according to their level of criticality to yield (i.e., nuisance vs. killer defects). Such a capability can further speed up disposition decision-making. The sample size is also important to both of these risks; the sampling should be statistically valid for the nature of the problems that the inspections target. The inspection needs to be fast, so that it does not hold up production material, and it must carry a low operational cost to be feasible in a production environment. Yet, enough material must be sampled to have good discrimination and accurate lot disposition.
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Figure 2. Manual and automated Viper 243X inspection time comparison.
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BACKSIDE DEFECT INSPECTION
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Numerous process steps can leave particles on wafer backsides, due to the process, maintenance or cleaning problems, or handling. When these are carried on to the next step, the backside particles can result in process problems at these subsequent steps. The most common example is in lithography, where a particle causes a bump on the wafer frontside as the wafer is pulled onto the scanner chuck. The scanner can then have a focus error at that point, resulting in a CD error or pattern failure.
Wafer backside particle (right side) caused a defocus hot spot on the wafer
In some cases, the particle will stay with the wafer, but in other cases, it can transfer to the chuck. The high force of the vacuum pull-down often causes it to almost fuse to the scanner chuck. This results in a hot spot at the same location on each wafer. Once the problem is identified, the scanner must be taken down to clean off the particle or replace the chuck, and a requalification is always required. This scanner can incur significant downtime.
frontside. The captured image of the particle is seen at the far right.
Finally, the disposition inspection needs to be compatible with the level of factory automation, especially for advanced 300 mm fabs. This is a challenge for manual inspection, since fabs minimize the number of operators on the production floor.1 Material movement to and from the tool, host control, and results integration are all important considerations. In addition to product disposition, fabs use similar inspection strategies to requalify production tools and cells. After a production tool has been down for maintenance or to correct a problem, it must be requalified before being released back into production. This requalification, depending on the specific process step, typically includes measurement of the appropriate parameters (overlay and CD for litho, film thickness for films and CMP etc.), microdefect qualification, and gross process qualification. The requirements described for disposition inspection apply to this tool qualification inspection as well. These requirements will now be explored in greater detail for manual and automated disposition inspection. The manufacturing challenge
Device manufacture requires fast, accurate decisions to keep good product moving. Integral to this is high productivity from process tools, so rapid decisions are needed to requalify them periodically or after maintenance. In most cases, fabs want to verify that
A backside product disposition inspection is typically done at process steps prior to litho (and other sensitive process steps) to avoid the rework, yield loss, and the hit to scanner productivity. Because the litho process itself can also create backside defects (through splashback, for example), a backside inspection is also typically done as part of the develop inspect disposition. Based on these issues and customer inputs, optional backside inspection has been added to the KLA-Tencor Viper 2435 automated disposition system. An additional backside stage is joined with the primary scanning stage; the scanning motion of the frontside inspection also scans the backside stage. After a wafer is inspected on the first stage, it is transferred to the second stage where it is scanned simultaneously with the following frontside wafer scan. The backside stage has its own darkfield illumination and camera to perform this inspection. Because the backside inspection adds a step to the sequence, the system throughput is slightly reduced. Defect results are shown as an additional channel which may be reviewed just like any other defect, and may be transferred to KLA-Tencor Klarity Defect software. Fabs have used this new capability to identify the cause of hot spots. The above graphic shows an example of a hot spot which was caused by a confirmed backside particle. This backside inspection is a convenient capability to add to an existing frontside disposition inspection. An alternative to consider where no frontside inspection is being done is to use a KLA-Tencor Surfscan SP1 unpatterned wafer inspection tool with a backside inspection module3. Spring 2006
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Figure 3. A comparison of manual and automated (Viper 243X) lot disposition time with 300-mm wafers inspected at a frequency of six wafers per lot. Source: Powerchip, from YMS Europa poster paper.
every production lot is good, paying particular attention to problems which could result in significant yield hits. Because the vast majority of lots are good, the inspection is actually very tedious. The operator expects product to be good, and becomes complacent (or bored), often missing the improperly processed wafers or lot. While a manual inspector must hunt (often unsuccessfully) for defects, an automated system can spend more productive time actually viewing the problems found, and making clear and documented disposition decisions. The following bar graph compares the complete cycle time for a manual inspector and an automated disposition tool for a representative case. The result is that a
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Figure 4. Manual and automated (Viper 243X) defect capture for all types (frontside inspection only). In every case, manual inspection missed defects, and in some cases, complete defect types. Note that dispositions based on the low manual capture rates would result in downstream scrap and yield loss.
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problem can be identified more quickly with automated disposition, putting less production material at risk. One operator can run and manage multiple automated disposition tools at the same time, which s/he obviously cannot do for manual inspection. Consequently, from a cost of ownership (CoO) standpoint, operation costs with an automated inspector are approximately 1/3 of those of a manual inspection operator. In addition, the disposition results are much more consistent than those produced by multiple inspection operators.
Any automated inspection system requires recipes to run. Fabs state that it is necessary to minimize any overhead associated with this disposition activity. Using automated recipe creation (ARC), which draws on recipes already created, most new devices and layers should be completed in well under 10 minutes by an average production operator. Derivative layer recipes are automatically created by the tool at first run. Automated inspection operation should not require an engineer or highly trained technician. Limitations of manual inspection
Multiple fab studies have shown that manual inspection finds only one-tenth to one-quarter of what automated disposition inspection uncovers. These errors come from spinners, exposure tools, developers, etch tools, polishers, other process equipment, and handling. They can be visible to the naked eye or with moderate magnification. But manual inspection completely misses most defects, often because the wafer and inspection conditions are challenging, the operator looks in the wrong place, or the operator is not paying sufficient attention. In many cases, inspection operators have missed the fact that some wafers had no pattern — on the whole lot, even on multiple lots — or the material is not sampled. As automated inspections at ADI (after develop inspect), AEI (after-etch inspect), and after polish have become more routine, it is clear that manual inspection — although relatively low in initial cost — leaves the door wide open for revenue and profitability loss due to increased scrapped wafers and lower yield.
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Automated inspection has the advantage of providing real data rather than anecdotal descriptions from operators. The real data can then be used to understand trends and isolate sources, similar to what is done with micro defect data, allowing quantification and prioritization of problem severity using Klarity Defect or alternative analysis systems. In almost all cases, fabs implementing automated inspection of macro defects have been surprised by the extent of defects and process issues, and their newfound ability to respond quickly to fix them.
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Manual Disposition
Viper 243X Disposition
Inspection area
5 points (< 10%) (operator dependent)
Whole wafer (100%)
Within-lot sampling
3 wafers/lot (10%)
Whole lot (100%)
Lot sampling
100% (desired)
100%
Throughput
23-26 wph*
100 wph*
Inspection time/wafer
1-7 to 2.7 minutes* (3 wafers only)*
0.6 minutes* (25 wafers)*
Lot inspection time
5-8 minutes
15 minutes
Frontside illumination
Brightfield
Brightfield and Darkfield
Device (chip) inspection
Yes
Yes
Scribe line inspection
Limited
Yes
Unpatterned area inspection
Yes (although often ignored)
Yes
Wafer edge exclusion
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Edge bead removal inspection
Inconsistent
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Backside inspection*
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Very good While the operational costs of both the manual and the autoReport detail & archive Limited operator note Lot summary, wafer report, gallery mated disposition inspections report, recipe report are relatively low, they are not Image save No Wafer images, defect clips the most important cost. The main goal of the disposition Factory automation No Yes inspection is to prevent bad Table 1. A comparison of manual and Viper 2345 disposition inspections reveals that automated inspection is more material from continuing down comprehensive and is faster in delivering go/no-go decisions. * Backside inspection requires more time per lot. the line, where it will either be scrapped or result in yield loss. Since these types of process errors can be very large in scope, • Cost due to missed defects is higher for manual these costs have been known to be very high. When inspection in losses through scrap and decreased yield. rework is possible, such as in litho or at some CMP steps, the value of the wafers can even be rescued. The • Risk of zero-yield lots is higher with manual other major goal for disposition inspection is to identify inspection; this can affect a fab’s relationship with a process tool which is unfit for production. This may be its customer. a result of the product wafer inspection, or through a periodic cell monitor. • The value of information is greater from the automated disposition inspection. As seen in Figure 4, manual inspection was found to be inferior in both its sensitivity across all defect types and Table 1 summarizes some additional details of comparison. its ability to even see certain defect types. Each missed problem will move downstream, only to be scrapped later, or rejected as a yield loss. Accurate disposition decisions Ideally, whatever method is used for reaching a disposition, the decision should be as close to the specification Cost and benefit of ownership: as possible. It is sometimes hard to quantify the cormanual vs. automated inspection rectness of decisions. One fab performed an evaluation In summary, the overall cost of manual inspection is of two automated inspection tools to see which one best higher than that of automated disposition inspection: matched the engineer responsible for the process module. The evaluation was done on product wafers with • Manual CoO operational cost is higher for a normal process variation. statistically valid sample size Consistency between operators/ tools, and over time
Very poor
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Figure 5 shows the deviation of the two inspectors from the disposition decision made by the responsible engineer. In the cases where the other tool found too many defects, it was found that these were not real defects, so the tool would be rejecting a good lot (Alpha risk), or incorrectly placing it on hold. Where the tool found far fewer defects, it was failing to reject a bad lot (Beta risk); this would result in downstream scrap or yield loss. The 243X disposition decisions closely matched the engineerâ&#x20AC;&#x2122;s decisions.
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Fabs require the capability to fine-tune go/no go disposition rules based on defect distribution, both by size and location. Rules can include zones on the wafer, as well as overall lot defectivity. This helps to optimize both the alpha and beta risks of the disposition decisions. All results must be available for review, and should be able to be sent to the fab defect analysis system for correlation and historical analysis.
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Figure 5. Field comparison of two automated inspectors in a competitive head-to-head, deviation from engineer decision.
Litho defocus disposition â&#x20AC;&#x201D;â&#x20AC;&#x201D; case studies
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Figure 6. Defocus detection threshold -- the Viper 2435 is demonstrated to be significantly more sensitive. Programmed defocus settings are indicated on the wafer maps.
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Collapsing lithographic process windows mean that there is increasing likelihood of areas of the wafer being out of focus. Defocus can result from scanner errors for a field or within a field, and due to particles on the wafer backside or on the scanner chuck, resulting in a â&#x20AC;&#x153;hot spot.â&#x20AC;? These areas of defocus may result in complete pattern failure or a significant change in CD. In most cases, these are very hard to detect on real product wafers, but they result in yield loss. In the cases where it is due to a persistent particle on a chuck, every wafer may have yield loss at that location. An experiment was run to determine the ability of automated and manual inspectors to identify defocus. A metal 1 logic product wafer was created with fields with known amounts of defocus, and then
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material out of specification. Such a low-level defect may be isolated to its source by stacking the results in the defect analysis system across wafers and even across lots. CMP disposition – case studies
Figure 7. The same defocus hot spot detected on the wafers as indicated2.
inspected by both methods. The results are shown in Figure 6. The automated tool was found to be significantly more sensitive than the inspection operator. The fab’s process window specification for this layer is 0.1 µm defocus; the automated inspector found 50% of the defective fields at this limit. The inspection operator did not find defocused fields until they were well beyond the spec. In this case, the defocus covers the full field. Hot spots may be smaller, and the 2435 has been shown to be effective at finding them. Advanced processes are quite sensitive to even small particles on the backside.
CMP is a process module which is still seeing ongoing challenges and rapid process development. Many fabs have implemented automated disposition inspection of macro defects because of the relatively high rate of such defects and because of process instability. As an example, a fab sampled a portion of a Cu CMP lot and found one wafer with underpolish defects, as shown in the following figure. The cassette map shows that wafer 22 was rejected according to the disposition rules, and the wafer map clearly shows the problem, as does the saved wafer image. In Figure 8, the CMP polish tool did not flag that there was anything wrong with either the wafer or the lot. The inspection result triggered an inspection of the whole lot, where it was found that four additional wafers were bad. In Figure 9, it was possible to rework the wafers by sending them for additional polishing. This saved scrapping high-value, near-end-of-line wafers.
In some cases, the backside event is not a particle on a specific wafer, but on the scanner chuck. Automated disposition results very quickly indicate the problem, as can be seen in the following lot review screen. In this case, a scanner with twin stages produced a hot spot on every second wafer. This can easily be seen in the cassette map, and is highlighted on the individual wafer thumbnail results. Such an inspection result may be used to drive a CD SEM to the specific location and measure the pattern to determine the CD deviation. While Figure 7 clearly shows the nature of the problem, not all such cases are as clear. A small stage problem may be right on the threshold of the process window, and not always produce
Figure 8. Cu CMP lot sample with residual Cu detected. Disposition inspection thumbnails are shown above, and the sampled cassette map is to the left.
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Process flow
Automated disposition inspection fits into the normal process flow, taking the place of the manual inspection. Because the system is fully factory automation compliant, it likely fits into the flow more easily than the manual step. Figure 11 shows an example of how automated disposition inspection can be fit into a litho process flow.
Figure 9. Cu CMP lot with residual Cu detected on five wafers. The cassette map clearly shows the rejected wafers.
Of course, the disposition inspection may be performed within any sequence, but the abovedescribed flow is the most common BKM (bestknown method), following the expected yield and cost cascade. In advanced litho processes, overlay is typically the greatest yield detractor, so it makes sense to do this first. The CD SEM is often the busiest, so any material which can be routed away from it (through rejection at a prior disposition) saves its capacity. Note that this shows that all three inspections and measurements are performed, but there are layers where neither overlay nor CD measurement are done. These non-critical steps can still have process problems which result in gross process errors (such as no resist or no develop), and should still have a disposition inspection performed.
For each wafer or lot which is rejected, an operator will review the result to determine the course of action. In many fabs, for layers where the cause and fix are clear, the operator may directly take the corrective action, particularly when it involves rework. Usually, however, before a lot is scrapped, it will go to an engineer for disposition.
Figure 10. Post CMP disposition inspection identified eight lots of wafers with edge damage. Wafer maps of the failed lots are shown above.
In another case (see Figure 10), an excursion was highlighted during a disposition inspection at metal CMP. Eight full lots (200 wafers) were found to have a similar type of wafer edge defects. Investigation showed that one ECP tool was causing the problem across all the lots. While the wafers had to be scrapped, the quick recognition of the problem allowed the ECP tool to be shut down, minimizing damages to additional lots.
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Similar process flows have been established for other process modules, with attention to the most cost-effective sequence. Process tool requalification takes a similar approach, although it may vary depending on whether the qualification is done on product or test wafers. In litho, for example, the requalification is typically done with PCM4 (Photo Cell Monitoring) on resist test wafers; these same wafers may be used for the gross error requalification
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CAPTURING ALL DEFECT TYPES The goal of disposition inspections is to capture all of the types of errors which can happen. There are several issues which make this very challenging:
such as color due to film errors, spin or develop problems, residual pattern, arcing, striations, and backsplash.
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Defects may have very different reflectivity or scattering profiles. Missing resist, hot spots, copper residual, particles, scratches, and etch errors all look very different from one another.
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Some defects may be uniform, either covering the whole wafer or consistently appearing on a specific location. Manual and some automated inspection may miss these because there is no fixed reference.
– Backside darkfield for backside particles and damage
Problems to address include:
– No resist on a wafer
– No exposure
– No develop
– No etch
These channels are inspected concurrently, maximizing throughput. The frontside inspections are done through two channels, and the backside is inspected while the next wafer is on the frontside stage (discussed in sidebar 1).
• Algorithms – High speed image processing extracts defects from each of the image channels, while suppressing noise from process variations:
– Process window failure which occurs on a particular pattern (in litho, etch, and CMP)
– Die-to-die – Detects random defects such as scratches, striations, and others which vary across the wafer. This will also capture defects which repeat from exposure field to exposure field.
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– Field-to-field – Detects additional random defects, including scribe line problems
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Concurrent brightfield and darkfield channels feed frontside wafer images to the image processor to capture all defect types.
KLA-Tencor’s Viper 2435 automated disposition system (and its predecessor) is designed to specifically target a wide range of defect types. This is done through several aspects of the design: • Hardware – optical channels are designed to detect defects with different characteristics: – Frontside brightfield (direct reflection imaging) for defects which change the appearance,
– Wafer-to-wafer – Wafer reference identifies missing film, uncoated, undeveloped, unetched wafers where the entire wafer processing is incorrect
– EBR – Detects errors in edge bead removal
– Edge Damage Check – Detects problems with the wafer edge and bevel – Unpatterned or partially patterned area outside the main device array – Detects random and process errors outside the main patterned area The specialized hardware and algorithms combine to cover a wide range of defect types, giving good sensitivity to the types of problems which fabs need to capture at disposition inspections at litho, etch, CMP, films, and other process modules.
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Figure 11. Litho disposition process flow with 2435 performing defect disposition.
as well. This quickly and accurately qualifies the resist coat, exposure, and develop process. If PWQ5 (Process Window Qualification) is used for the qualification, then additional test or product wafers are processed for the gross defect portion of the requalification. Conclusion
Fast, accurate disposition decisions are needed in today’s 300 mm fabs. The disposition decisions require the ability to consistently detect a broad range of defects and process failures on the wafer, at the wafer edge, and even on the backside, at as low a cost as possible. That low cost should not, however, come at the cost of broad defect type capture or a low false count rate, not to mention accuracy. Manual inspection approaches have been shown to be inadequate for both product disposition and process tool requalification, due to their limitations in sensitivity to wide-ranging defect types, in repeatability, and in agreement to engineering decisions. Manual inspection has also been shown to not meet the demands of factory automation and good documentation of the results.
Automated gross production disposition and tool qualification have been in use in many wafer fabs, and have been shown to be capable of meeting the requirements of advanced 300 mm fabs. Today’s systems benefit from the learning and development gleaned from prior generations while offering new innovations such as backside inspection. Automated inspection has been shown to be a consistent and reliable tool for fast disposition in litho, CMP, etch, and other process modules. Furthermore, automated disposition inspection in fabs has been shown to result in cost savings from reduced scrap and improved yield, and through increased fab productivity. Acknowledgement
The authors would like to thank Scott Ashkenaz for his contributions to this article. References 1. Electronic News, “Automation to Proliferate in Intel Manufacturing,” December 2005 2. KLA-Tencor, Think Shrink, 2004 3. KLA-Tencor, Start Yield Enhancement from the Wafer Backside, 2005
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