Method and system for dynamically adjusting metrology sampling based upon available metrology capacity

The present invention is generally directed to various methods and systems for dynamically adjusting metrology sampling based upon available metrology capacity. In one illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, and providing the determined available metrology capacity to the metrology control unit wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to an industrial process, and, more particularly, to various methods and systems for dynamically adjusting metrology sampling based upon available metrology capacity.

2. Description of the Related Art

After a complete reading of the present application, those skilled in the relevant art will understand that the present invention has broad application to a variety of industries involving the manufacture of a variety of different types of devices or workpieces. By way of example only, the background of the application will be discussed in the context of various problems encountered in the manufacture of integrated circuit devices. However, the present invention is not to be considered as limited to use only within the semiconductor manufacturing industry.

There is a constant drive within the semiconductor industry to increase the quality, reliability and throughput of integrated circuit devices, e.g., microprocessors, memory devices, and the like. This drive is fueled by consumer demands for higher quality computers and electronic devices that operate more quickly and more reliably. These demands have resulted in a continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well as in the manufacture of integrated circuit devices incorporating such transistors. Additionally, reducing the defects in the manufacture of the components of a typical transistor also lowers the overall cost per transistor as well as the cost of integrated circuit devices incorporating such transistors.

Generally, a set of processing steps is performed on a lot of wafers using a variety of process tools, including photolithography steppers, etch tools, deposition tools, polishing tools, thermal anneal process tools, implantation tools, etc. The technologies underlying semiconductor process tools have attracted increased attention over the last several years, resulting in substantial refinements. However, despite the advances made in this area, many of the process tools that are currently commercially available suffer certain deficiencies. In particular, some of such tools often lack advanced process data monitoring capabilities, such as the ability to provide historical parametric data in a user-friendly format, as well as event logging, real-time graphical display of both current processing parameters and the processing parameters of the entire run, and remote, i.e., local site and worldwide, monitoring. These deficiencies can engender non-optimal control of critical processing parameters, such as throughput, accuracy, stability and repeatability, processing temperatures, mechanical tool parameters, and the like. This variability manifests itself as within-run disparities, run-to-run disparities and tool-to-tool disparities that can propagate into deviations in product quality and performance, whereas an ideal monitoring and diagnostics system for such tools would provide a means of monitoring this variability, as well as providing means for optimizing control of critical parameters.

One technique for improving the operation of a semiconductor processing line includes using a factory wide control system to automatically control the operation of the various process tools. The manufacturing tools communicate with a manufacturing frame-work or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface that facilitates communications between the manufacturing tool and the manufacturing frame-work. The machine interface can generally be part of an advanced process control (APC) system. The APC system initiates a control script based upon a manufacturing model, which can be a software program that automatically retrieves the data needed to execute a manufacturing process. Often, semiconductor devices are staged through multiple manufacturing tools for multiple processes, generating data relating to the quality of the processed semiconductor devices.

During the fabrication process various events may take place that affect the performance of the devices being fabricated. That is, variations in the fabrication process steps may result in variations of the features that comprise the device as well as device performance variations. Factors, such as feature critical dimensions, doping levels, contact resistance, particle contamination, etc., all may potentially affect the end performance of the device. Various tools in the processing line are controlled in accordance with performance models to reduce processing variation. Commonly controlled tools include photolithography steppers, polishing tools, etching tools, and deposition tools. Pre-processing and/or post-processing metrology data is supplied to process controllers for the tools. Operating recipe parameters, such as processing time, are calculated by the process controllers based on the performance model and the metrology information to attempt to achieve post-processing results as close to a target value as possible. Reducing variation in this manner leads to increased throughput, reduced cost, higher device performance, etc., all of which equate with increased profitability.

Target values for the various processes performed are generally based on design values for the devices being fabricated. For example, a particular process layer may have a target thickness. Operating recipes for deposition tools and/or polishing tools may be automatically controlled to reduce variation about the target thickness. In another example, the critical dimensions of a transistor gate electrode may have an associated target value. The operating recipes of photolithography tools and/or etch tools may be automatically controlled to achieve the target critical dimensions.

Typically, a control model is used to generate control actions for changing the operating recipe settings for a process tool being controlled based on feedback or feedforward metrology data collected related to the processing by the process tool. To function effectively, a control model must be provided with metrology data in a timely manner and at a quantity sufficient to maintain its ability to predict the future operation of the process tool it controls.

Within many manufacturing industries great effort is made to insure that processing operations are performed accurately such that the resulting device meets target specifications. This is particularly true within the semiconductor manufacturing industry wherein many metrology tools and sensors are used to acquire a vast amount of metrology data to determine the effectiveness and accuracy of the processing operations performed in a process tool and/or the compliance of the resulting workpiece with product specifications. To that end, a typical semiconductor manufacturing facility may devote a great deal of resources to obtaining such metrology data. Typically, a modern semiconductor manufacturing facility will have many metrology tools or stations where a variety of metrology operations are performed. Illustrative metrology data may include the thickness of a process layer, a critical dimension of a feature formed above a substrate, a planarity of a surface, etc. Some metrology tools are dedicated to performing only one type of metrology operations, e.g., critical dimension measurements, whereas other metrology tools are capable of performing multiple metrology operations. Moreover, a typical semiconductor manufacturing facility may have multiple tools capable of performing the same metrology operation.

In semiconductor manufacturing environments, metrology sampling rates are established for various process operations. The sampling rates may vary depending upon a variety of factors, such as the criticality of the particular process, e.g., gate etch processes, and/or how stable the process operations are in terms of controllability. In semiconductor manufacturing environments, metrology sampling rates are typically set below a level where the aggregate of all of the products selected for sampling would completely utilize all available metrology capacity. This may generally be referred to as baseline sampling rates. The baseline sampling rates are set at less than maximum levels to allow the metrology tools to “catch-up” to accumulated work-in-progress (WIP) after one or more of the metrology tools have been taken out of service for a variety of reasons, e.g., routine maintenance, an unscheduled problem with one of the metrology tools, etc. For example, if one out of four available metrology tools is taken out of service, the work-in-progress (WIP) would slowly accumulate in the metrology queues until the out-of-service metrology tool is returned to service. At that time, all four of the available metrology tools would operate at higher than normal utilization rates until the work-in-progress (WIP) queues are reduced to normal.

One of the problems with the above-described methodology is that it under-utilizes a very valuable resource, i.e., the metrology tools. In general, all other things being equal, as baseline sampling rates are kept higher, more information can be obtained as to how the fabrication facility is operating. The additional metrology information may be used to more quickly identify issues within the fabrication facility that could be degrading yield and/or product performance.

An alternative method of addressing changes in metrology capacity is to maintain sampling rates at very high levels that result in nearly full utilization of all metrology tools under normal production. When one or more metrology tools are taken out of production, the sampling rates may be manually lowered to reduce the amount of work-in-progress (WIP) accumulating in the metrology queues. Under this scheme, when the out-of-service metrology tool(s) is returned to production, the sampling rates are returned to their normally high levels. One problem with this method is that it requires a person to manually reduce the relatively high baseline sampling rates when a metrology tool is taken out of service, and to manually increase the sampling rates back to the relatively high baseline rates when the affected metrology tool is returned to production. This is an inefficient process that requires diligent monitoring of metrology tool capacity by whomever has the authority to adjust the facility's sampling rate plans. If the relatively high baseline sampling rates are not reduced in a timely fashion, work-in-progress (WIP) accumulates in the metrology queues. Moreover, because of the relatively high baseline sampling rates employed in this methodology, when the affected metrology tool is returned to production, there is little excess metrology capacity available to work through the accumulated work-in-progress (WIP). Conversely, if the relatively high baseline sampling rates are not re-established in a timely fashion, production may suffer as the volume of metrology data is reduced, thereby negatively impacting the ability to promptly identify problems within the fabrication facility that may adversely affect production and product yields.

SUMMARY OF THE INVENTION

The present invention is generally directed to various methods and systems for dynamically adjusting metrology sampling based upon available metrology capacity. In one illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, and providing the determined available metrology capacity to the metrology control unit wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity.

In another illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, wherein the step of determining available metrology capacity comprises determining a number of metrology tools that are currently available as compared to a total number of metrology tools that are generally available, wherein all of the metrology tools are assumed to be completely interchangeable, providing the determined available metrology capacity to the metrology control unit, wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity, and performing additional metrology operations in accordance with the new metrology sampling rate.

In yet another illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, wherein the step of determining available metrology capacity comprises determining a number of metrology tools that are currently available for performing a specific metrology operation as compared to a total number of metrology tools that are generally available for performing the specific metrology operation, wherein all of the metrology tools are adapted to perform at least the specific metrology operation, providing the determined available metrology capacity to the metrology control unit, wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity, and performing additional metrology operations in accordance with the new metrology sampling rate.

In a further illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, wherein the step of determining available metrology capacity comprises determining metrology tools that are available for performing the at least one metrology operation and at least a second metrology operation that is different from the at least one metrology operation, providing the determined available metrology capacity to the metrology control unit, wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity, wherein, in determining the new metrology sampling rate, a sampling rate for the second metrology operation is reduced to thereby free up additional metrology capacity for performing the at least one metrology operation, and performing additional metrology operations in accordance with the new metrology sampling rate.

DETAILED DESCRIPTION OF THE INVENTION

Referring toFIG. 1, a simplified block diagram of an illustrative manufacturing system10is provided. In the illustrated embodiment, the manufacturing system10is adapted to fabricate semiconductor devices. Although the invention is described as it may be implemented in a semiconductor fabrication facility, the invention is not so limited and may be applied to other manufacturing environments. The techniques described herein may be applied to a variety of workpieces or manufactured items. For example, the present invention may be employed in connection with the manufacture of a variety of integrated circuit devices, including, but not limited to, microprocessors, memory devices, digital signal processors, application specific integrated circuits (ASICs), or other devices. The techniques may also be applied to workpieces or manufactured items other than integrated circuit devices.

A network20interconnects various components of the manufacturing system10, allowing them to exchange information. The illustrative manufacturing system10includes a plurality of tools30–80. Each of the tools30–80may be coupled to a computer (not shown) for interfacing with the network20. The tools30–80are grouped into sets of like tools, as denoted by lettered suffixes. For example, the set of tools30A–30C represent tools of a certain type, such as a chemical mechanical planarization tool. A particular wafer or lot of wafers progresses through the tools30–80as it is being manufactured, with each tool30–80performing a specific function in the process flow. Exemplary processing tools for a semiconductor device fabrication environment include metrology tools, photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal anneal tools, implantation tools, etc. The tools30–80are illustrated in a rank and file grouping for illustrative purposes only. In an actual manufacturing facility, the tools30–80may be arranged in any physical order or grouping. Additionally, the connections between the tools in a particular grouping are meant to represent connections to the network20, rather than interconnections between the tools30–80.

A manufacturing execution system (MES) server or controller90directs high level operation of the manufacturing system10. The MES server90may monitor the status of the various entities in the manufacturing system10(i.e., lots, tools30–80) and control the flow of articles of manufacture (e.g., lots of semiconductor wafers) through the process flow. A database server100is provided for storing data related to the status of the various entities and articles of manufacture in the process flow. The database server100may store information in one or more data stores110. The data may include pre-process and post-process metrology data, tool states, lot priorities, operating recipes, etc. The controller90may also provide operating recipes to one or more of the tools depicted inFIG. 1or command that various operating recipes be performed in one or more of the tools. Of course, the controller90need not perform all of these functions. Moreover, the functions described for the controller90may be performed by one or more computers spread throughout the system10.

The manufacturing system10also includes a metrology control unit12executing on an illustrative workstation150. The metrology control unit12may be used to control various metrology tools employed in connection with manufacturing operations performed in the manufacturing system10. The metrology control unit12may communicate with the controller90and/or with one or more process controllers145associated with the individual tools30–80for purposes to be described later herein. The particular control models used by the process controllers145depend on the type of tool30–80being controlled. The control models may be developed empirically using commonly known linear or non-linear techniques. The control models may be relatively simple equation-based models (e.g., linear, exponential, weighted average, etc.) or a more complex model, such as a neural network model, principal component analysis (PCA) model, partial least squares projection to latent structures (PLS) model. The specific implementation of the control models may vary depending on the modeling techniques selected and the process being controlled. The selection and development of the particular control models would be within the ability of one of ordinary skill in the art, and accordingly, the control models are not described in greater detail herein for clarity and to avoid obscuring the instant invention.

An exemplary information exchange and process control framework suitable for use in the manufacturing system10is an Advanced Process Control (APC) framework, such as may be implemented using the Catalyst system formerly offered by KLA-Tencor, Inc. The Catalyst system uses Semiconductor Equipment and Materials International (SEMI) Computer Integrated Manufacturing (CIM) Framework compliant system technologies and is based the Advanced Process Control (APC) Framework. CIM (SEMI E81-0699-Provisional Specification for CIM Framework Domain Architecture) and APC (SEMI E93-0999-Provisional Specification for CIM Framework Advanced Process Control Component) specifications are publicly available from SEMI, which is headquartered in Mountain View, Calif.

The processing and data storage functions are distributed amongst the different computers or workstations inFIG. 1to provide general independence and central information storage. Of course, different numbers of computers and different arrangements may be used without departing from the spirit and scope of the instant invention.

FIG. 2is a more specific, simplified block diagram of a metrology system50in accordance with one illustrative embodiment of the present invention. As shown therein, the metrology control unit12is operatively coupled to a plurality of metrology tools14. In the illustrative embodiment, four such illustrative metrology tools,14-1,14-2,14-3and14-n are schematically depicted. However, the present invention may be employed with any such number of metrology tools. The illustrative metrology tools14may perform one or more of a variety of metrology operations. For example, the metrology tools14may perform metrology operations such as measuring the thickness of a process layer, measuring a critical dimension of a feature, measuring the planarity of a surface, film resistivity, film optical properties (e.g., n and k), defectivity, overlay alignment, etc.

The metrology system50may be employed to automatically adjust or control metrology sampling rates based on available metrology tool capacity. In some cases, the metrology tools14perform generally the same type of metrology operation, e.g., measuring the thickness of a layer, measuring the critical dimension of a feature, etc. However, the metrology tools14are not necessarily completely interchangeable for all metrology operations. For example, if there are two metrology tools14and three metrology operations, it is not required that each of the two metrology tools14can be used for each of the three metrology operations. The metrology control unit12also has the ability to implement some constraints on the resulting sampling rate plans. For example, a constraint may be applied that the sampling rate for a given process operation will not be allowed to fall below a preselected limit, e.g., a minimum sampling rate of 75% may be established for a critical process operation. In semiconductor manufacturing operations, such a constraint may be applied to a very critical process operation, such as a gate etch process operation.

In accordance with one aspect of the present invention, the metrology control unit12may employ various control algorithms to control metrology operations performed by the metrology tools14within the metrology system50. In one illustrative embodiment, a first control algorithm is employed wherein all of the metrology tools14of a given type are assumed to be completely interchangeable. In that case, when one or more of the metrology tools14are not in service (for whatever reason), a new or adjusted metrology sampling rate for each operation may be determined as follows:

Ratei,new=Ratei,base⁢NAvailableNTotal(1)
where Ratei,newrepresents the new metrology sampling rate at operation i, Ratei,baserepresents the baseline metrology sampling rate at operation i, NAvailablerepresents the number of metrology tools14currently available, and NTotalrepresents the total number of metrology tools14that are normally available to perform metrology operations. Simply put, in this first algorithm, the new sampling rate reflects a reduction in the base metrology sampling rate due to the unavailability of some of the total number of metrology tools14.

In another illustrative embodiment, a second algorithm may be employed by the metrology system50. Using the second algorithm, the metrology control unit12only considers or counts metrology tools14that can be used for a specific metrology operation. For example, the metrology control unit12may only consider metrology tools14that can perform critical dimension measurements. In this illustrative embodiment, the new or adjusted metrology sampling rate may be determined as follows:

One benefit of the second algorithm is that it is computationally simple. One potential drawback with respect to the second algorithm is that it does not allow the reduction of metrology sampling rates at operations other than those that are run on the metrology tool14that is down. For example, if metrology operation j is not run by a down metrology tool, the second algorithm would not allow the sampling rate at metrology operation j to be reduced in order to free up capacity to run metrology operation i.

In yet another illustrative embodiment, a third control algorithm may be employed by the metrology system50. Using the third algorithm, the metrology control unit12may modify sampling rates at metrology operations other than those that are performed by a metrology tool14that has been taken out of service. This methodology allows maintenance of metrology sampling rates that are (on average) relatively close to the baseline metrology sampling rates for all metrology operations when all metrology tools14are available. In this methodology, the first step is to generate an aggregate sampling rate. This is the sum of all individual metrology sampling rates across all metrology operations:

RateTotal=∑i=1N⁢Ratei(3)
where RateTotalis the aggregate rate, N is the total number of metrology operations allowable for metrology tools14of that type (e.g., thickness measurement, critical dimension measurement), and Rateiis the baseline sampling rate at the operation i.

The next step is to scale the RateTotalvalues according to available metrology tools:

RateAvailable=RateTotal⁢NAvailableNTotal(4)
where RateTotalis defined as above, RateAvailableis the new available capacity, NAvailableis the number of available metrology tools14, and NTotalis the total number of metrology tools14that could potentially be available for that metrology type. Generally, type refers to a group of metrology tools that can be used to perform the same metrology operations. For example, irrespective of the manufacturer of the metrology tools, if several tools can perform the same metrology operation, e.g., film thickness, then all of those tools would be considered to be of the same type.

The final step is to solve the following equation:

min⁢∑i=1N⁢(Ratei,new-Ratei,base)2(5)
subject to the constraint:

In effect, the third algorithm minimize the square of the deviation of the new metrology sampling rates (Ratei,new) from the baseline metrology sampling rates (Ratei,base) subject to the constraint of available metrology capacity (RateAvailable). The benefit of this third methodology is that it allows for small reductions in metrology sampling rates across multiple operations to address reductions in metrology capacity. However, solving this third algorithm is much more computationally complex than the other two algorithms discussed above.

It should be noted that, in the above example, the aggregate rate (RateTotal) was used as a surrogate for total metrology capacity. This is usually a good estimate if the time to measure a lot of wafers does not vary greatly from one operation to another. In cases where measurement time does vary greatly, a modified equation may be used that incorporates those time differences. As one illustrative example, the modified equation could be:

RateTotal=∑i=1N⁢Timei*Ratei(7)
and the constraint would then be:

RateAvailable≤∑i=1N⁢Timei*Ratei,new(8)
where Timeirepresents the cycle time of a lot at operation i and all other variables are defined as above.

The present invention is generally directed to various methods and systems for dynamically adjusting metrology sampling based upon available metrology capacity. In one illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, and providing the determined available metrology capacity to the metrology control unit wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity.

In another illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, wherein the step of determining available metrology capacity comprises determining a number of metrology tools that are currently available as compared to a total number of metrology tools that are generally available, wherein all of the metrology tools are assumed to be completely interchangeable, providing the determined available metrology capacity to the metrology control unit, wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity, and performing additional metrology operations in accordance with the new metrology sampling rate.

In yet another illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, wherein the step of determining available metrology capacity comprises determining a number of metrology tools that are currently available for performing a specific metrology operation as compared to a total number of metrology tools that are generally available for performing the specific metrology operation, wherein all of the metrology tools are adapted to perform at least the specific metrology operation, providing the determined available metrology capacity to the metrology control unit, wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity, and performing additional metrology operations in accordance with the new metrology sampling rate.

In a further illustrative embodiment, the method comprises providing a metrology control unit that is adapted to determine a baseline metrology sampling rate for at least one metrology operation, determining available metrology capacity, wherein the step of determining available metrology capacity comprises determining metrology tools that are available for performing the at least one metrology operation and at least a second metrology operation that is different from the at least one metrology operation, providing the determined available metrology capacity to the metrology control unit, wherein the metrology control unit determines a new metrology sampling rate based upon the determined available metrology capacity, wherein, in determining the new metrology sampling rate, a sampling rate for the second metrology operation is reduced to thereby free up additional metrology capacity for performing the at least one metrology operation, and performing additional metrology operations in accordance with the new metrology sampling rate.