Measurement sampling plan aimed only at detecting out-of-specification

Abstract

A method and system for determining information about a sample are provided. One method includes generating a sampling plan aimed only at detecting out-of-specification of the characteristics of a sample in a measurement process. The method includes generating an output about the sample by performing a measurement process on the sample using the generated sampling plan. Further, the method includes determining the characteristics of the sample based on the generated output, and detecting whether one or more characteristics of the sample are out-of-specification based on the determined characteristics of the sample. Embodiments described herein are particularly suitable for overlay measurements using a substantially sparse sampling plan configured only for detecting out-of-specification of an overlay.

Description

Technical Field

[0001] The present invention generally relates to methods and systems configured to determine information about a sample. Certain embodiments relate to methods and systems for generating and using a sampling plan specially designed for the purpose of detecting out-of-specification samples only.

Background Art

[0002] The following description and examples are not admitted to be prior art merely because they are included in this section.

[0003] The manufacture of semiconductor devices such as logic devices and memory devices typically involves processing a substrate such as a semiconductor wafer using a number of semiconductor manufacturing processes to form various features and multiple levels of the semiconductor device. For example, lithography is a semiconductor manufacturing process that involves transferring a pattern from a reticle to a resist disposed on a semiconductor wafer. Additional examples of semiconductor manufacturing processes include, but are not limited to, chemical mechanical polishing (CMP), etching, deposition, and ion implantation. Multiple semiconductor devices may be fabricated and disposed on a single semiconductor wafer and then separated into individual semiconductor devices.

[0004] The inspection process is used at various steps during the semiconductor manufacturing process to detect defects on the wafer in order to improve the yield and thus the profitability in the manufacturing process. Inspection has always been an important part of the manufacture of semiconductor devices such as ICs. However, as the dimensions of semiconductor devices shrink, smaller defects can cause device failures, making inspection even more critical for the success of manufacturing acceptable semiconductor devices.

[0005] Defect review typically involves re-detecting defects detected as such by an inspection process and generating additional information about the defects at high resolution using either a high-magnification optical system or a scanning electron microscope (SEM). Thus, defect review is performed at discrete locations on the wafer where defects have been detected by inspection. The high-resolution data about the defects generated by defect review is more suitable for determining defect attributes such as profile, roughness, and more accurate size information.

[0006] Measurement processes are also used at various steps during semiconductor manufacturing processes to monitor and control the processes. The measurement process is different from the inspection process in that it is used to measure one or more characteristics of a wafer that cannot be determined using currently available inspection tools. For example, the measurement process is used to measure one or more characteristics of a wafer such as the dimensions of features formed on the wafer during the process (e.g., line width, thickness, etc.), and the performance of the process can be determined from those one or more characteristics. Further, if one or more characteristics of the wafer are not acceptable (e.g., outside a predetermined range of the characteristic), the measured values of the one or more characteristics of the wafer can be used to change one or more parameters of the process so that additional wafers manufactured by that process have acceptable characteristics.

[0007] The measurement process is different from the defect review process in which defects detected by inspection are reexamined in defect review. In that the measurement process may be executed at positions where defects were not detected, it is also different from the defect review process. In other words, different from defect review, the positions on the wafer where the measurement process is executed may be independent of the results of the inspection process executed on the wafer. Specifically, the positions where the measurement process is executed can be selected independently of the inspection results. Further, since the positions on the wafer to be measured can be selected independently of the inspection results, different from defect review where the positions on the wafer for executing defect review cannot be determined until the inspection results for the wafer are generated and available for use, the positions for executing the measurement process can be determined before the inspection process on the wafer is completed.

[0008] For all of the above yield-related processes, it would be convenient to inspect, review, and measure all possible points on all possible samples. Of course, since such sampling is time-consuming and costly, this is neither practical nor desirable. Therefore, which points, positions, regions, etc. on the sample to select for inspection, review, measurement, i.e., sampling, is an important aspect in creating a yield-related process recipe that generates sufficient results for process monitoring and / or control while minimizing the time and cost required to generate the results. In more time-consuming processes such as measurement, this sampling can become much more difficult. For example, it can be extremely difficult to find an appropriate trade-off point between rapid and available measurement results that also provide sufficient data for appropriate out-of-specification detection processes and / or process feedback control.

[0009] In the case of measurement, the sampling method and the in-facility system need to make several decisions, such as which lot to measure, which wafer within that lot to measure, and which point on that wafer to measure. The sampling decision involves a trade-off between the required throughput of the process and the importance or impact of that process step on the yield. In a manufacturing facility, overlay measurement serves two main purposes: run-to-run (R2R) control and out-of-specification detection. A run can be one lot or multiple lots, depending on the importance of the layer. These purposes often conflict with each other because the measurements performed for out-of-specification detection may not be sufficient for R2R control, and R2R control may have a throughput that is too slow to enable the measurements for proper out-of-specification detection. Therefore, designing an overlay measurement process often involves a trade-off between these two purposes.

[0010] Currently, the execution of these two tasks is not separated from each other. Depending on the layer and the device, it is popular to measure 2 to 4 wafers per lot at high density using a sufficient number of measurement points to perform feedback control. In other words, in the currently used method, only a fairly small subset consisting of a subset of lots and wafers within that subset of lots is measured using a complete process-of-record (POR) sampling plan, and the correction of process tools (e.g., scanners, etc.) for advanced process control (APC) is updated to detect out-of-specification wafers. In this way, the currently used method is designed for APC, and as a result, it is possible to also use the results for out-of-specification detection. If the measured wafers or lots do not meet the pre-defined in-specification requirements, they are sent for rework. For more important layers, each lot can be measured. For less important layers, random lot selection is performed.

[0011] Current methods for overlay measurement and sampling have several significant drawbacks. For example, current methods may miss out-of-specification lots due to random lot selection, which can result in a decrease in yield. In other words, when lots are randomly selected for measurement, some out-of-specification lots may not be detected and proceed to the next process step, resulting in yield loss. In another example, current methods may miss out-of-specification lots due to "hit" wafers selected for measurement within a lot. When a relatively small number of wafers are measured per lot, they may not be representative of the entire lot. Specifically, while these wafers may be within specifications, most of the other wafers may be out of specifications. In an additional example, current methods may result in false detection and rework when "off" wafers are selected within a lot. In the worst case, an "off" wafer may turn an in-specification lot out of specifications after rework. Specifically, when a relatively small number of wafers are measured per lot, these wafers may not be representative of the entire lot. While these measured wafers may be out of specifications, most of the unmeasured wafers may be within specifications. In this case, the corrections used for rework are calculated using non-representative wafers. When the lot is reworked, the measured wafers are corrected, but the remaining wafers in the lot may degrade and become out of specifications. In yet another example, current methods do not consider the co-optimization of measurement tool settings and sampling to achieve higher throughput.

Prior Art Documents

Patent Documents

[0012]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0013] Therefore, it would be advantageous to develop a system and method for generating and using a measurement sampling plan that is only for out-of-specification detection and has none or one or more of the above-mentioned drawbacks.

Means for Solving the Problems

[0014] The following description of various embodiments should in no way be construed as limiting the subject matter of the appended claims.

[0015] One embodiment relates to a method and system configured to determine information about a sample. The system includes a computer system configured to generate a sampling plan that is only for out-of-specification detection of the characteristics of the sample in a measurement process. The system also includes a measurement subsystem configured to generate an output about the sample by performing a measurement process on the sample using the generated sampling plan. The computer system is also configured to determine the characteristics of the sample based on the generated output and to detect whether one or more characteristics of the sample are out of specification based on the determined characteristics of the sample. The system may be further configured as described herein.

[0016] Another embodiment relates to a computer-implemented method for determining information about a sample. The method includes generating a sampling plan that is only aimed at detecting out-of-specification of the characteristics of the sample in the measurement process, and generating an output about the sample by performing a measurement process on the sample using a measurement subsystem and the generated sampling plan. The method also includes determining the characteristics of the sample based on the generated output, and detecting whether the characteristics of one or more samples are out-of-specification based on the determined characteristics of the sample. The steps of generating the sampling plan, determining the characteristics, and detecting are performed by a computer system coupled to the measurement subsystem.

[0017] The steps of the method can be performed as described herein. Further, the method can include any other steps of any other methods described herein. Moreover, the method can be performed by any of the systems described herein.

[0018] Another embodiment relates to a non-transitory computer-readable medium storing program instructions executable on one or more computer systems for performing a computer-implemented method for determining information about a sample. The computer-implemented method includes the steps of the above method. The computer-readable medium can be further configured as described herein. The steps of the computer-implemented method can be performed as further described herein. Further, the computer-implemented method for which the program instructions are executable can include any other steps of any other methods described herein.

[0019] Further advantages of the present invention will become apparent to those skilled in the art from the following forms for carrying out the invention and by referring to the accompanying drawings.

Brief Description of the Drawings

[0020]

Figure 1

Figure 2

Figure 3

Figure 4

Best Mode for Carrying Out the Invention

[0021] The present invention is capable of accepting various modifications and alternative forms. However, specific embodiments thereof are shown by way of example in the drawings and are described in detail herein. The drawings may not be to actual scale. However, it should be understood that the drawings and the detailed description thereof are not intended to limit the present invention to the specific forms disclosed, but rather are intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present invention as defined by the appended claims.

[0022] Turning now to the drawings, it should be noted that not all of the figures are drawn to scale. Specifically, the scale of some of the elements of the figures is greatly exaggerated in order to emphasize their characteristics. It should also be noted that not all of the figures are drawn to the same scale. Elements that may be similarly configured as shown in two or more figures are indicated using the same reference numbers. Unless otherwise specified herein, any of the elements described and illustrated may include any suitable commercially available elements.

[0023] Generally, embodiments described herein relate to methods and systems for determining information about a sample. Some embodiments described herein are configured for a very sparse sampling method for detecting out-of-specification samples, such as wafers and lots.

[0024] In one embodiment, the sample is a wafer. The wafer can include any wafer known in semiconductor technology. Although some embodiments can be described with respect to wafers herein, those embodiments are not limited to samples for which wafers can be used. For example, embodiments described herein can be used for samples such as reticles, flat panels, personal computer (PC) boards, and other semiconductor samples.

[0025] FIG. 1 shows an embodiment of a system configured to determine information about a sample. The system includes a measurement subsystem 10 that includes at least an energy source and a detector. The energy source is configured to generate energy directed at the wafer. The detector is configured to detect energy from the wafer and generate an output in response to the detected energy.

[0026] In one embodiment, the measurement subsystem is configured as an optically based measurement subsystem. For example, as the system shown in FIG. 1, the measurement subsystem 10 includes an illumination subsystem configured to direct light at the wafer 14. The illumination subsystem includes at least one light source, such as light source 16. The illumination subsystem is configured to direct light at the wafer at one or more angles of incidence, which can include one or more tilt angles and / or one or more vertical angles. For example, as shown in FIG. 1, light from the light source 16 passes through the optical element 18, then through the lens 20, and is directed at the beam splitter 21, which directs the light at the wafer 14 at a normal angle of incidence. The angle of incidence can include any suitable angle of incidence, which can vary, for example, depending on the characteristics of the wafer.

[0027] The illumination subsystem can be configured to direct light at the wafer at various different angles of incidence at various different timings. For example, the metrology subsystem can be configured to change one or more characteristics of one or more elements of the illumination subsystem so that light can be directed at the wafer at an angle of incidence different from the angle of incidence shown in FIG. 1. In one such example, the metrology subsystem can be configured to move the light source 16, the optical element 18, and the lens 20 so that light is directed at the wafer at a different angle of incidence.

[0028] The metrology subsystem can be configured to direct light at the wafer at two or more angles of incidence simultaneously. For example, the illumination subsystem may include two or more illumination channels, one of those illumination channels may include the light source 16, the optical element 18, and the lens 20 as shown in FIG. 1, and the other of the illumination channels (not shown) may include similar elements that are configured differently or the same, or may include one or more other components such as at least the light source and, optionally, other components further described herein. When such light is directed at the wafer simultaneously with the other light, one or more characteristics of the light directed at the wafer at different angles of incidence (e.g., wavelength, polarization, etc.) may be different such that the light generated by illuminating the wafer at different angles of incidence can be distinguished from each other at the detector.

[0029] The illumination subsystem may also include only one light source (e.g., light source 16 shown in FIG. 1), and the light from the light source can be separated into various different optical paths (e.g., based on wavelength, polarization, etc.) by one or more optical elements (not shown) of the illumination subsystem. Thereafter, the light in each of the different optical paths can be directed towards the wafer. The plurality of illumination channels can be configured to direct light towards the wafer at the same timing or at different timings (e.g., when sequentially illuminating the wafer using different illumination channels). In another example, the same illumination channel may be configured to direct light having different characteristics towards the wafer at different timings. For example, in some examples, the optical element 18 can be configured as a spectral filter, and the properties of the spectral filter can be changed in a wide variety of ways (e.g., by replacing the spectral filter) so as to be able to direct light of different wavelengths towards the wafer at different timings. The illumination subsystem may have any other suitable configuration known in the art.

[0030] The light source 16 may be a broadband plasma (BBP) light source. Thus, the light generated by the light source and directed towards the wafer may include broadband light. However, as the light source, any other suitable light source such as any suitable laser known in the art configured to generate light at any suitable wavelength known in the art may be included. The laser can be configured to generate monochromatic or substantially monochromatic light. Thus, the laser may be a narrowband laser. Also, as the light source, a multi-color light source that generates light at a plurality of discrete wavelengths or wavelength bands may be included.

[0031] Light from the optical element 18 can be focused on the beam splitter 21 by the lens 20. In FIG. 1, the lens 20 is shown as a single refractive optical element, but in reality, the lens 20 may include several refractive optical elements and / or reflective optical elements that, in combination, focus light from the optical element onto the wafer. The illumination subsystem may include other suitable optical elements (not shown). Examples of such optical elements include, but are not limited to, polarization components, spectral filters, spatial filters, reflective optical elements, apodizers, beam splitters, diaphragms, etc., and may include any suitable optical element known in the art. Further, the system may be configured to change one or more elements of the illumination subsystem based on the type of illumination used for the wafer.

[0032] The measurement subsystem may also include a scanning subsystem configured to move the wafer relative to the optical element. For example, the measurement subsystem may include a stage 22, on which the wafer 14 is placed during measurement. The scanning subsystem may include any suitable mechanical assembly and / or robotic assembly (including the stage 22) configured to move the wafer so that one or more different measurement points on the wafer can be placed within the field of view of the measurement subsystem. In addition to, or instead of, this, the measurement subsystem may be configured such that one or more optical elements of the measurement subsystem move relative to the wafer to measure various different points on the wafer. The wafer may be moved relative to the measurement subsystem (or vice versa) in any suitable manner.

[0033] The measurement subsystem further includes one or more detection channels. At least one of the detection channels includes a detector configured to detect light from the wafer resulting from irradiation of the wafer by the measurement subsystem and to generate an output in response to the detected light. For example, the measurement subsystem shown in FIG. 1 includes two detection channels, one formed by condenser 24, element 26, and detector 28, and the other formed by condenser 30, element 32, and detector 34. As shown in FIG. 1, the two detection channels are configured to collect and detect light at different collection angles. In some cases, one detection channel is configured to detect specularly reflected light, and the other detection channel is configured to detect non-specular reflections (e.g., scattering, diffraction, etc.) from the wafer. However, the detection channels may be configured to detect the same type of light (e.g., specularly reflected light) from the wafer. The measurement subsystem may also include a different number of detection channels (e.g., only one detection channel, or two or more detection channels). In FIG. 1, each of the condensers is shown as a single refractive optical element, but each of the condensers may include refractive optical elements and / or reflective optical elements.

[0034] The detection channel may include any suitable detector known in the art, such as a photomultiplier tube (PMT), a charge-coupled device (CCD), and a time delay integration (TDI) camera. The detector may also include a non-imaging detector or an imaging detector. A non-imaging detector may be configured to detect certain characteristics of light, such as intensity, but may not be configured to detect such characteristics as a function of position within the imaging plane. The output generated by such a detector may be a signal or data, but may not be an image signal or image data. In such an example, a computer subsystem, such as computer subsystem 36 of the present system, may be configured to generate an image of the wafer from the non-imaging output of the detector. However, the detector may be configured as an imaging detector configured to generate an imaging signal or image data. Thus, the present system may be configured to generate the outputs described herein in several ways.

[0035] FIG. 1 is provided herein to schematically illustrate the configuration of a measurement subsystem that may be included in the system embodiments described herein. Of course, the configuration of the measurement subsystem described herein may be modified to optimize the performance of the system, as is typically done when designing a commercial system. Further, the systems described herein may be implemented using existing measurement systems, such as the Archer, ATL, SpectraShape, SpectraFilm, Aleris, and WaferSight series of tools commercially available from KLA Corp. of Milpitas, Calif. (e.g., by adding the functions described herein to an existing system). For some such systems, the methods described herein may be provided as an optional function of that system (e.g., in addition to other functions of that system). Alternatively, the systems described herein may be designed "from scratch" to provide a completely new system.

[0036] The computer subsystem 36 of the present system may be coupled to the detector of the measurement subsystem in any suitable manner (e.g., via one or more transmission media which may include "wired" and / or "wireless" transmission media) such that the computer subsystem can receive the output generated by the detector during measurement. The computer subsystem 36 may be configured to perform several functions using the output of the detector as described herein and to perform any other optional functions further described herein. For example, the computer subsystem may be configured to determine the characteristics of a sample based on the generated output.

[0037] The characteristics of the sample determined by the computer subsystem may vary depending on the configuration of the measurement subsystem and the sample being measured. In one embodiment, the characteristic is an overlay of one or more first patterned features formed on the sample with respect to one or more second patterned features formed on the sample. The characteristics of the sample may be any other characteristic of interest, such as film thickness, patterned structure profile, critical dimension (CD), line edge roughness (LER), line width roughness (LWR), etc. These characteristics may be determined using the generated output in any method known in the art. This computer subsystem may be further configured as described herein.

[0038] This computer subsystem (and other computer subsystems described herein) may also be referred to herein as a computer system. Each of the computer subsystems or systems described herein may take various forms, including a personal computer system, an image computer, a mainframe computer system, a workstation, a network appliance, an Internet appliance, or other devices. In general, the term "computer system" may be broadly defined to include any device having one or more processors and executing instructions from a storage medium. A computer subsystem or system may also include any suitable processor known in the art, such as a parallel processor. Further, a computer subsystem or system may include a high-speed processing computer platform and software, either as a stand-alone tool or as a networked tool.

[0039] If the system includes two or more computer subsystems, the different computer subsystems may be coupled to each other so that images, data, information, instructions, etc. can be transmitted between the computer subsystems, as further described herein. For example, computer subsystem 36 can be coupled to computer subsystem 102 by any suitable transmission medium, which may include any suitable wired and / or wireless transmission media known in the art (as shown by the dashed line in FIG. 1). Two or more such computer subsystems may also be effectively coupled by a shared computer-readable storage medium (not shown).

[0040] In another embodiment, the measurement subsystem is configured as an electron beam measurement subsystem. In one such embodiment shown in FIG. 2, the measurement subsystem includes an electron column 122, which is coupled to a computer subsystem 124. As further shown in FIG. 2, the electron column includes an electron beam source 126, which is configured to generate electrons that are focused onto a wafer 128 by one or more elements 130. Examples of the electron beam source may include a cathode source or an emitter chip, and examples of the one or more elements 130 may include a gun lens, an anode, a beam limiting aperture, a gate valve, a beam current selection aperture, an objective lens, and a scanning subsystem, all of which may include any suitable such elements known in the art.

[0041] Electrons (e.g., secondary electrons) returning from the wafer may be focused onto a detector 134 by one or more elements 132. The one or more elements 132 may include, for example, a scanning subsystem, which may be the same as the scanning subsystem included in the element 130.

[0042] The electron column may include any other suitable elements known in the art. Further, the electron column may be further configured as described in U.S. Patent No. 8,664,594 issued to Jiang et al. on April 4, 2014, U.S. Patent No. 8,692,204 issued to Kojima et al. on April 8, 2014, U.S. Patent No. 8,698,093 issued to Gubbens et al. on April 15, 2014, and U.S. Patent No. 8,716,662 issued to MacDonald et al. on May 6, 2014, which are hereby incorporated by reference in their entirety.

[0043] The electron column is shown in FIG. 2 as being configured such that electrons are directed at the wafer at an inclined angle of incidence and collected from the wafer at another angle of inclination. However, the electron beam may be directed at and collected from the wafer at any suitable angle. Further, the measurement subsystem may be configured to use multiple modes to generate an output about the wafer (e.g., using various different illumination angles, collection angles, etc.). The multiple modes of the measurement subsystem may differ in any of the image generation parameters of the subsystem.

[0044] Computer subsystem 124 may be coupled to detector 134 as described above. The detector may form an electron beam image of the wafer by detecting electrons returned from the surface of the wafer. Any suitable electron beam image may be included as the electron beam image. Computer subsystem 124 may be configured to perform any of the functions described herein using the output of the detector and / or the electron beam image. Computer subsystem 124 may be configured to perform any additional steps described herein. The system including the electron beam subsystem shown in FIG. 2 may be further configured as described herein.

[0045] FIG. 2 is provided herein to schematically illustrate the configuration of a measurement subsystem that may be included in the embodiments described herein. Similar to the optical subsystem described above, the electron beam subsystem described herein may be modified to optimize the performance of the measurement subsystem as is typically done when designing a commercial system. Further, the systems described herein may be implemented using an existing electron beam system (e.g., by adding the functions described herein to an existing electron beam system). For some such systems, the methods described herein may be provided as an optional function of that system (e.g., in addition to the other functions of that system). Alternatively, the systems described herein may be designed "from scratch" to provide a completely new system.

[0046] The measurement subsystem has been described above as being an optical subsystem or an electron beam subsystem, but the measurement subsystem may be an ion beam subsystem. Such a measurement subsystem may be configured as shown in FIG. 2, except that the electron beam source may be replaced with any suitable ion beam source known in the art. Further, the measurement subsystem may be any other suitable ion beam tool, such as an ion beam tool included in a commercially available focused ion beam (FIB) system, a helium ion microscope (HIM) system, and a secondary ion mass spectrometry (SIMS) system.

[0047] As described above, the measurement subsystem is configured to generate an output about a physical version of a sample by directing energy (e.g., light, electrons, etc.) at the physical version of the sample. Thus, the measurement subsystem can be configured as a "substantial" subsystem rather than a "virtual" subsystem. However, the storage medium (not shown) and computer system 102 shown in FIG. 1 may be configured as a "virtual" system. Specifically, the storage medium and computer subsystem may be configured as a "virtual" system as described in U.S. Patent No. 8,126,255 issued to Bhaskar et al. on February 28, 2012 and U.S. Patent No. 9,222,895 issued to Duffy et al. on December 29, 2015, both of which patents are hereby incorporated by reference in their entirety as if fully set forth herein. The embodiments described herein may be further configured as described in these patents.

[0048] The measurement subsystem described in this specification may be configured to generate outputs of a wafer, such as images, in a plurality of modes. Generally, a "mode" is defined by the value of a parameter of the measurement subsystem used to generate an output for the wafer. Thus, different modes may have different values for at least one of the parameters of the measurement subsystem (other than the location where the output is generated). In this way, an output may be generated by the measurement subsystem using two or more different values of one parameter of the measurement subsystem. For example, in an optical subsystem, different modes may use light of different wavelengths for illumination. As further described in this specification, modes may have different illumination wavelengths for different modes (e.g., by using different light sources, different spectral filters, etc.). In another embodiment, different modes may use different illumination channels. For example, as described above, the measurement subsystem may include two or more illumination channels. In this way, different illumination channels may be used for different modes.

[0049] Similarly, the outputs generated by an electron beam subsystem may include outputs such as images generated by the electron beam subsystem using two or more different values of one parameter of the electron beam subsystem. The plurality of modes of the electron beam subsystem can be defined by the values of the parameters of the electron beam subsystem used to generate an output and / or an image for the wafer. Thus, different modes may have different values for at least one of the electron beam parameters of the electron beam subsystem. For example, in an electron beam subsystem, different modes may use different incident angles for illumination.

[0050] The computer system is configured to generate a sampling plan aimed only at detecting out-of-specification characteristics of a sample in a measurement process. For example, as shown in step 304 of FIG. 3, the computer system may generate a sampling plan aimed only at out-of-specification monitoring. In one embodiment, the sampling plan is not configured for the purpose of feedback control of characteristics. Configuring the sampling plan to be aimed only at out-of-specification detection and not for the purpose of feedback control can be done in several different ways described herein. Thus, these embodiments represent a significant departure from conventional methods in that the sampling plan is targeted only at out-of-specification detection rather than overlay feedback control.

[0051] The computer system determines the number and location of measurement points on the wafer to be used for out-of-specification detection. For example, a sampling plan generated as described herein will generally include information about which wafers of which lots to measure and where to perform the measurements on each wafer. This information can be included in the sampling plan in any suitable way. For example, the location where measurements are taken on the wafer can be expressed in several coordinates such as wafer coordinates, die coordinates, design coordinates, coordinates relative to alignment marks, etc. Information about the lot on which the wafer is measured can also be expressed in various different ways, such as lot ID, for example, information about the number or frequency of lots measured, such as every lot, every other lot, etc., or the proportion or portion of the lot being measured. Information about the wafer being measured can also be expressed in a similar way, such as wafer ID, for example, information about the number or frequency of wafers measured, such as every wafer, every other wafer, etc., or the proportion or portion of the wafer being measured.

[0052] In one embodiment, the density of the sampling plan is lower than the density required to enable feedback control of the characteristics. For example, the embodiments described herein generate and use substantially sparse sampling specifically for the purpose of detecting only out-of-spec wafers. Specifically, a sampling plan aimed only at out-of-spec monitoring is substantially sparser compared to the measurement sampling required for overlay feedback control. More specifically, in the substantially sparse sampling plan proposed herein aimed only at out-of-spec detection, there are not enough measurement points to perform overlay feedback control based on the measurement results generated at the measurement points. For example, the sampling plan generated as described herein may be configured to have only one or two measurement points for each wafer (or subset of wafers) within each lot. Thus, the embodiments described herein can be configured to detect out-of-spec wafers by measuring a small number of points on each wafer.

[0053] In contrast, currently used overlay measurements typically have dozens or hundreds of measurement points on each of a small number of wafers within a number of lots less than all lots, so as to prevent this measurement from adversely affecting the throughput of the entire process. Out-of-spec detection of the overlay is typically performed using these same results. Thus, the embodiments described herein perform overlay measurement in a completely new way compared to currently used methods and systems. Specifically, the embodiments described herein are configured to generate a sampling plan for measuring many or all wafers within a lot (each lot) using an extremely sparse sampling plan in order to maximize out-of-spec detection.

[0054] In additional embodiments, the sampling plan is configured to generate an output for each sample within a lot. For example, the embodiments described herein provide a sampling method that can detect out-of-spec wafers within a lot while reducing the measurements for each wafer. In further embodiments, the sampling plan is configured to generate an output for a subset of samples within a lot. For example, a computer system may generate a sampling plan to measure a subset of wafers within each lot using substantially sparse sampling to detect out-of-spec wafers. The embodiments described herein preferably measure all wafers within a lot using substantially sparse sampling. If that is not practical or possible, the computer system may determine the number of wafers within the subset based on throughput requirements. The computer system may select a subset of wafers from a lot uniformly, randomly, or based on some known distribution (e.g., if the user or computer system has observed that wafers in lots processed first or last by a manufacturing tool are more likely to be defective). Thus, the sampling method generated as described herein can detect out-of-spec lots while reducing the measurements for each wafer within the lot or for a subset of wafers.

[0055] In one embodiment, generating the sampling plan includes selecting the number and coordinates of positions at which the measurement subsystem generates an output in the measurement process to conform to out-of-spec criteria for the sample. For example, the number and positions of measurement points (i.e., the sampling plan) may be selected to conform to the out-of-spec criteria used for a given layer and device in the manufacturing process. In this way, the number of out-of-spec wafers that can be detected and corrected is maximized while minimizing throughput hits.

[0056] As described in the following example, a computer system can select the number and location of measurement points that meet out-of-specification criteria. A user (such as a device manufacturer) may use statistics such as the absolute value of the average of the measured overlays +3×standard deviation for wafer quality control. For each layer and device, a threshold is defined on the statistical value such that if it is exceeded, the wafer or lot will be considered out of specification. If the computer system has access to historical data (e.g., overlay measurements performed with a relatively dense sampling plan for multiple wafers of a given layer and device), the computer system may use one of the existing sampling optimization methods to generate a relatively sparse plurality of sampling plans. For each wafer, the computer system can first calculate the statistical value using all the points measured initially, and then estimate the statistical value using a subset of the points defined by the optimization method. The sampling plan that best tracks the first statistical value can be selected as the sampling plan for out-of-specification detection.

[0057] In some embodiments, the computer system is configured to determine an indicator based on the generated output and a predetermined statistical process control indicator that separates in-spec samples from out-of-spec samples. Such a configuration of the computer system is optional when historical measurement data is available. For example, the computer system may calculate the indicator using measurements collected using a sampling plan generated for out-of-spec detection only, which tracks existing SPC indicators for separating in-spec wafers from out-of-spec wafers. More specifically, the user may measure multiple overlay points per wafer and calculate the mean and standard deviation of these measurements. A statistical value such as the absolute value of the mean + 3 × standard deviation is an example of such an indicator. The computer system may use the resulting quality control chart to determine how this statistical value changes run-to-run. The computer system may define a threshold value for this indicator to separate in-spec wafers from out-of-spec wafers. This threshold value may be linked to a yield indicator of the manufacturing process, such as the yield of an electrical test performed later in the process.

[0058] In one such embodiment, the computer system is configured to determine a threshold value for a determined metric that separates in-spec samples from out-of-spec samples. For example, the embodiments described herein may calculate a threshold value for detecting out-of-spec wafers for substantially sparse measurement data. Such a configuration of the computer system is also optional when historical measurement data is available. The computer system may calculate a threshold value for a new metric to separate in-spec wafers from out-of-spec wafers. In one such example, the computer system may track some reference metric (e.g., wafer yield, electrical test, average absolute value of a high-density sampling plan + 3× standard deviation) that has already been used to separate out-of-spec wafers from in-spec wafers. The computer system may correlate a metric calculated using substantially a small number of measurements with the reference metric and define a threshold value such that the new metric captures all out-of-spec wafers while minimizing the number of false detections. This calculation of the threshold value may be added to the currently used method, and the same threshold value for out-of-spec detection is typically used regardless of the underlying sampling plan.

[0059] In another embodiment, the generation of the sampling plan includes determining measurement subsystem settings based on the lot sampling frequency, the in-lot sampling frequency, the in-sample sampling plan, and the constraints of the measurement budget and the throughput of the measurement subsystem. For example, the computer system may determine the lot sampling frequency, the in-lot sampling frequency, the in-wafer sampling plan, and the tool settings under the constraints of the available measurement budget and the required tool throughput. Thus, the embodiments described herein may be configured to co-optimize sampling and measurement tool parameters to achieve the required throughput. The generation of the sampling plan in such a manner is improved compared to currently used methods because it explicitly considers the trade-off between measurement accuracy / precision and tool throughput when allocating the measurement budget.

[0060] In a further embodiment, generating the sampling plan includes allocating a given measurement budget among lot sampling, sample sampling, and in-sample sampling to maximize the detection of out-of-specification samples. For example, embodiments described herein provide a sampling system that optimally allocates the available measurement budget among lots, wafers, and in-wafer sampling to maximize the number of out-of-specification wafers detected. The measurement budget can be expressed in several different ways, such as the time allowed for measurement or the number of measurements that can be performed without affecting the overall throughput. The allowed time, number of measurements, or other measurement budget specifications can then be divided across wafers, lots, and measurement points per wafer to maximize the detection of out-of-specification samples. In one such example, the total number of measurements within a given measurement budget can be allocated such that each wafer within each lot is measured, even if it means that only a significantly limited number of measurement points can be measured on each wafer.

[0061] In an additional embodiment, generating the sampling plan includes co - optimizing the sampling frequency and measurement subsystem settings to maximize the detection of out - of - specification samples at the throughput of a given measurement subsystem. In other words, an important feature of the embodiments described herein is a sampling system that co - optimizes the sampling frequency and measurement tool settings to achieve optimal out - of - specification detection at the required tool throughput. For example, a measurement subsystem, such as the measurement subsystem further described herein, has several settings that can be used for the trade - off between measurement time and measurement quality. In one such example, several image frames can typically be collected during measurement to reduce the noise of the measurement values, or, instead of a single image acquisition, double image acquisition can typically be performed. These measurement parameters can be investigated to determine whether they can be modified to shorten the time taken for the measurement while having an acceptable impact on the measurement results. In the above example, the computer system can determine whether it can reduce the number of image frames collected without generating excessive noise in the measurement values, or whether out - of - specification detection can be performed with only single image acquisition instead of double image acquisition. In this way, the computer system can determine the measurement settings that can be used to appropriately detect out - of - specification wafers within a minimum time. By shortening the measurement time, it becomes possible to increase the number of measurement points per wafer and / or increase the number of wafers in a lot to detect out - of - specification wafers.

[0062] As shown in step 300, the embodiments or another system or method described herein can perform manufacturing process steps on one or more samples, a lot consisting of one or more samples, etc. This manufacturing process step can be a lithography process performed by a lithography tool including a scanner or other exposure tool. However, this manufacturing process step can vary depending on the characteristics monitored by the embodiments described herein. For example, this manufacturing process step can be an etching process step performed using an etching tool. Any of these manufacturing process steps can be performed in any suitable manner known in the art.

[0063] Manufacturing process step 300 generates a manufactured sample 302. Generally, these manufactured samples can be wafers on which patterned features are formed in one of the above manufacturing process steps. However, the manufactured sample can be any other sample described herein. As described above, in one embodiment, a characteristic is an overlay of one or more first patterned features formed on a sample with respect to one or more second patterned features formed on the sample. Generally, the term "overlay" (also referred to as "overlay misregistration") as used herein is defined as the position of a first patterned feature on a sample with respect to a second patterned feature on that sample. The first patterned feature and the second patterned feature are formed in different process steps, i.e., different lithography process steps. Typically, an overlay is determined for patterned features formed on separate layers of a sample such that one is below the other, but this is not essential. For example, the embodiments described herein can be configured for out-of-specification detection of other spatial relationships between patterned features formed on a sample, e.g., the spatial relationship between different patterned features formed on the same layer using different lithography exposure steps.

[0064] The measurement subsystem is configured to generate an output for a sample by performing a measurement process on the sample using the generated sampling plan. Thus, the system includes a measurement tool that performs measurements according to a sampling plan generated by a computer system. As shown in step 306 of FIG. 3, the measurement subsystem can perform the measurement process using the sparse sampling plan generated in step 304. For example, the computer system and / or the measurement subsystem can be configured to use the results of one or more of the steps described herein to perform the measurement process on the sample.

[0065] In one embodiment, the sampling plan includes information about one or more selected lots, one or more selected samples within one or more selected lots, one or more positions on one or more selected samples, and one or more metrology subsystem settings for generating an output at one or more positions. The computer system is configured to send the information within the sampling plan to the metrology subsystem, and the generation of the output using the generated sampling plan is based on information from the computer system. For example, the computer system can communicate decisions regarding the lot to be measured, the wafers within the lot, and the sampling points within the wafers, as well as the tool recipe parameters to be used, all of which can be determined according to any of the embodiments described herein.

[0066] In some such embodiments, the computer system can be configured to store the information of the sampling plan generated for use in the metrology process. The computer system can be configured to store the information within a recipe or by generating a recipe for the process in which the sampling plan is to be used. As used herein, the term "recipe" can generally be defined as a set of instructions that can be used by a tool to perform a process on a sample. Thus, generating a recipe includes generating information about how to perform the process, which information can then be used to generate instructions for performing that process. Each embodiment can be used to set up a new process or recipe. Each embodiment can also be used to modify an existing process or recipe, whether it is a process or recipe used for multiple samples, or a process or recipe created for one sample and being adjusted for another sample.

[0067] The information about the sampling plan stored by a computer system can include any information that can be used to identify and / or use that sampling plan (e.g., file name and storage location, and the file can include information for the sampling plan such as information about the wafer to be measured, the lot to be measured, the location on the wafer to be measured, etc.). The computer system can be configured to store information about the sampling on any suitable computer-readable storage medium. That information can be stored together with any of the results described herein and can be stored in any method known in the art. The storage medium can include any of the storage media described herein or any other suitable storage medium known in the art. After being stored, the information is accessed in the storage medium, used by any of the method embodiments or system embodiments described herein, formatted for display to the user, and can be used by another software module, method, or system, etc. For example, the embodiments described herein may generate a measurement recipe as described above. Then, that measurement recipe is stored and used by that system or method (or another system or method) to perform a measurement process on a sample, thereby generating information about the sample (e.g., measured characteristics).

[0068] As shown in step 308, the computer system determines the characteristics of the sample based on the generated output, and as shown in step 310, is configured to detect whether the characteristics of one or more samples are out of specification based on the determined characteristics of the sample. For example, the computer system may receive measurement data from a measurement tool and determine characteristics from that measurement data. The computer system may use any suitable measurement method or algorithm known in the art to determine the characteristics of the sample. Generally, in the case of overlay measurement, such an algorithm may identify different patterned features within one or more images generated by the measurement subsystem and, for example, be configured to determine the spatial relationship between those different patterned features based on the distance between features within the image and the dimensions of the pixels within the image. The computer system may detect whether the characteristics are out of specification by applying the metrics or thresholds determined as described herein to the determined characteristics to determine which lot and / or wafer is out of specification.

[0069] In one embodiment, the measurement subsystem is configured to generate additional output for at least one of the samples by performing an additional measurement process on at least one of the samples using another sampling plan suitable for feedback control of the characteristics, and the computer system is configured to determine a correction process for at least one of the samples based on the generated additional output. Another sampling plan suitable for feedback control of the characteristics can be any currently used sampling plan that is capable of providing sufficient measurements for feedback control of the characteristics. The measurements performed using such a sampling plan can be performed as further described herein or by any other suitable method known in the art. The computer system can determine the correction process as further described herein or by any suitable method known in the art.

[0070] In one such example, at step 306, the measurement process is performed using a substantially sparse sampling plan, e.g., measuring a subset (or all) of the wafers within each lot to detect out-of-specification wafers. This measurement is performed independently of, and optionally in addition to, the measurement process using a process of record (POR) sampling plan designed to support the stability of advanced process control (APC). In this way, the embodiments described herein provide a sampling method for monitoring out-of-specification wafers and rework determination. Further, the embodiments described herein provide a sampling system that separates overlay control from out-of-specification detection and rework determination. This out-of-specification targeted measurement can be performed in addition to the measurement designed for APC.

[0071] In another embodiment, the computer system is configured to select at least one of one or more samples detected as out-of-specification, and for this at least one sample, the measurement process is performed using a sampling plan with a higher density than the generated sampling plan. In another such embodiment, the higher density sampling plan is configured for the purpose of feedback control of characteristics. For example, the computer system receives measurement data from the measurement tool and uses the metrics or thresholds determined as described herein to determine which lots and / or wafers are out-of-specification and whether they need to be re-measured with a higher density (e.g., POR) sampling to determine rework corrections. As shown in step 312 of FIG. 3, when the computer system determines that one or more samples are out-of-specification, the measurement subsystem may perform a measurement process using POR sampling on at least one of those samples. Thus, since the sampling plan is generated herein for the purpose of detecting out-of-specification and not for the purpose of feedback control, the measured values generated using those sampling plans cannot be used to determine rework corrections or other appropriate feedback control parameters. Therefore, measuring one or more samples detected as out-of-specification using a higher density POR sampling can make it possible to determine whether one or more parameters of the lithography process need to be changed and how they need to be changed.

[0072] A higher density sampling plan used for feedback control of characteristics can be a predetermined sampling plan, such as a POR sampling plan, which is generated by a computer system or another system or method and may be available for the embodiments described herein. A "higher density" sampling plan can be defined as simply being of higher density than a sampling plan generated for the sole purpose of detecting out-of-specification, as described herein. For example, a "higher density" sampling plan can be configured to measure dozens or hundreds of measurement points on a small number of samples or lots.

[0073] Accordingly, the computer system described herein may use a predetermined higher density sampling plan for the purpose of feedback control. However, in some embodiments, the computer system may be configured to generate a higher density sampling plan, for example, based on any of the results described herein. For example, if a sample is determined to be out-of-specification with respect to a characteristic, a higher density sampling plan may be generated by the computer system based on how far the characteristic deviates from the specification. In one such example, if the characteristics of one or more samples are determined to deviate significantly from the specification, the higher density sampling plan may include measuring a greater number of measurement points on a greater number of samples than if the characteristics of one or more samples were determined to deviate slightly from the specification. Any suitable relationship between the degree to which a characteristic deviates from the specification and the density of the sampling plan for the purpose of feedback control may be used by the computer system to determine the higher density sampling plan. This relationship may be based on, for example, historical data, theoretical models, or information about the process.

[0074] Thus, the embodiments described herein can be configured to perform out-of-specification detection using a sampling plan generated as described herein and select samples for APC-type monitoring based on the results of the out-of-specification detection. However, this series of measurement processes may be modified depending on the situation. In one such example, a sampling plan generated as described herein may include information about which samples to send for POR measurement for APC and which samples to send for out-of-specification detection. Thus, a first subset of samples may be sent for APC measurement, and a second subset may be sent for out-of-specification measurement, and these different subsets may be pre-determined and may not be based on the results of any measurement process. In such a case, APC measurement and out-of-specification measurement can be performed using the same measurement subsystem in the same measurement process (e.g., while the lot is loaded into the measurement tool), but other variations are possible, such as performing different measurements using different measurement tools in different processes.

[0075] In one such embodiment, the computer system is configured to determine a correction process for at least one of one or more samples based on the output generated using a high-density sampling plan. For example, the computer system may determine the characteristics of the sample based on the output generated in the POR measurement process, as shown in step 314 of FIG. 3. The computer system may determine the characteristics based on the POR measurement process output in any suitable method known in the art. The computer system may also determine, in step 316 of FIG. 3, whether the characteristics of one or more samples are out of control. Determining whether the characteristics of one or more samples are out of control may include applying a threshold to the determined characteristics and determining that the sample is out of control if the determined characteristics exceed this threshold (or, depending on the characteristics and the threshold, are below the threshold). The threshold may be an SPC threshold determined as further described herein.

[0076] If the computer system determines that the characteristics of one or more samples are out of control, the computer system may determine the reprocessing parameters at step 318. The determined reprocessing parameters and the one or more samples having out-of-control characteristics may then be sent back to the manufacturing process step 300. For example, if it is determined that the characteristics are outside the control limits, the computer system may change one or more parameters of the manufacturing process step or the tool, and then determine whether the characteristics of the out-of-control samples can be improved by re-executing the process on the samples using the changed parameters. In one such example, after performing lithography, it may be possible to remove the patterned features formed by lithography from the sample using, for example, an etching process, a polishing process, etc. Then, lithography may be re-executed on the sample using the new process parameters. Determining the reprocessing parameters may include determining any of the parameters associated with the reformation of the patterned features on the sample, including any parameters of any stripping process, any new parameters of the lithography process, etc. Determining the reprocessing parameters may be done using any suitable predetermined relationship between the process parameters and the sample characteristics.

[0077] Whether the reprocessing parameters are determined according to the embodiments described herein may depend on the process performed on the sample. For example, not all manufacturing processes may be reprocessed, or it may simply be unrealistic to reprocess some manufacturing processes. One such example is the etching process. If the manufacturing process step is an etching process, detecting out-of-specification and / or out-of-control samples may still be beneficial. For example, such wafers and / or lots may be discarded rather than proceeding to the next manufacturing process step, thereby avoiding spending time and cost on wafers that need to be discarded anyway.

[0078] If it is not determined in step 310 that the characteristics of the sample are out of specification and / or if it is not determined in step 316 that the characteristics of the sample are out of control, the sample can be sent to the next manufacturing process step of step 320. In other words, if the sample is determined to be acceptable, such as, for example, not out of specification and / or within the control limits, the sample can be sent to the next manufacturing process step. In one such example, if manufacturing process step 300 is a lithography process, manufacturing process step 320 can be an etching process. In another example, if manufacturing process step 300 is an etching process, manufacturing process step 320 can be a deposition step.

[0079] The computer system can be configured to generate results for the sample, and the results can include any of the information described herein, such as the determined characteristics, whether any of the samples are out of specification, which samples are out of specification, rework parameters, etc. The results for the sample can be generated by the computer system in any suitable manner. Further, the results for the sample can be stored as further described herein and used to perform one or more functions for the sample or other samples of the same type.

[0080] Such functions include, but are not limited to, changing a process such as a manufacturing process or step that has been or will be performed on a sample in a feedback or feedforward manner. For example, as further described herein, a computer system may be configured to determine one or more changes to a process that has been performed on a sample and / or a process that will be performed on a sample based on the determined characteristics. Changes to the process may include any suitable changes to one or more parameters of the process. The computer system preferably determines these changes such that in other samples on which the modified process is performed, out-of-control characteristics can be prevented, in another process performed on the sample, out-of-control characteristics can be corrected or eliminated, and in another process performed on the sample, out-of-control characteristics can be compensated for. The computer system may determine such changes in any suitable manner known in the art.

[0081] Those changes can then be transmitted to a semiconductor manufacturing system (not shown) or a storage medium (not shown) accessible to both the computer system and the semiconductor manufacturing system. The semiconductor manufacturing system may or may not be part of the system embodiments described herein. For example, the measurement subsystem and / or computer system described herein may be coupled to the semiconductor manufacturing system via one or more common elements such as, for example, a housing, a power supply, a sample handling device, or a mechanism. Examples of semiconductor manufacturing systems may include any semiconductor manufacturing system known in the art, such as a lithography tool, an etching tool, a chemical mechanical polishing (CMP) tool, a deposition tool, etc.

[0082] The embodiments described herein have several important advantages compared to the methods for out-of-specification measurement currently in use. For example, the embodiments described herein are configured to capture and rework more out-of-specification lots at a relatively low measurement cost, avoiding yield losses. In another example, the embodiments described herein enable capturing and reworking more out-of-specification wafers within a lot at a relatively low measurement cost, avoiding yield losses. In an additional example, the embodiments described herein enable avoiding unnecessary processing by measuring more wafers within a lot at a relatively low measurement cost. The embodiments described herein can also avoid the degradation of good lots due to unnecessary rework. Further, the embodiments described herein enable co-optimizing measurement tool settings and sampling to achieve the required throughput and accuracy of out-of-specification detection.

[0083] The advantages of the embodiments described herein compared to currently used measurement systems and methods are provided by some of the new features of the embodiments described herein, including, but not limited to, sampling methods and systems aimed only at monitoring and rework determination of out-of-specification wafers. Another new feature of the embodiments described herein is a sampling system that separates overlay control from out-of-specification detection and rework determination. An additional new feature of the embodiments described herein is a sampling method that can detect out-of-specification lots while reducing the measurement of a subset of wafers within the lot. Further new features include a sampling method that can detect out-of-specification wafers within a lot while reducing the measurement for each wafer. New features also include a sampling system that optimally allocates the available measurement budget among lots, wafers, and in-wafer sampling to maximize the number of detected out-of-specification wafers. Yet another new feature is a sampling system that co-optimizes sampling frequency and measurement tool settings to achieve optimal out-of-specification detection at the required tool throughput.

[0084] Each of the embodiments of the respective systems described above can be combined into a single embodiment.

[0085] Another embodiment relates to a computer-implemented method for determining information about a sample. The method includes generating a sampling plan that is only aimed at detecting out-of-specification characteristics of the sample in the measurement process, as shown in step 304 of FIG. 3. The method also includes generating an output for the sample by performing a measurement process on the sample using a measurement subsystem and the generated sampling plan, as shown in step 306. Further, the method includes determining the characteristics of the sample based on the generated output, as shown in step 308. The method further includes detecting whether the characteristics of one or more samples are out-of-specification based on the determined characteristics of the sample, as shown in step 310. The steps of generating the sampling plan, determining the characteristics, and detecting are performed by a computer system (e.g., computer subsystems 36 and / or 102 shown in FIG. 1) coupled to the measurement subsystem (e.g., measurement subsystem 10).

[0086] Each of the steps of the method can be performed as further described herein. The method may also include other steps that can be performed by the systems, computer systems, and / or measurement subsystems described herein. The computer system and the measurement subsystem can be configured in accordance with any of the embodiments described herein, for example, computer subsystems 36 and / or 102 and measurement subsystem 10, respectively. Further, the method described above can be performed by any of the system embodiments described herein.

[0087] Additional embodiments relate to a non - transitory computer - readable medium storing program instructions executable on a computer system for performing a computer - implemented method for determining information about a sample. An embodiment of one such system is shown in FIG. 4. Specifically, as shown in FIG. 4, a non - transitory computer - readable medium 400 includes program instructions 402 executable on a computer system 404. This computer - implemented method may include any step of any method described herein.

[0088] Program instructions 402 implementing a method such as the methods described herein may be stored on the computer - readable medium 400. The computer - readable medium can be a storage medium such as a magnetic disk or optical disk, magnetic tape, or any other suitable non - transitory computer - readable medium known in the art.

[0089] The program instructions can be implemented in any of a variety of ways, including, among other things, procedure - based techniques, component - based techniques, and / or object - oriented techniques. For example, the program instructions can be implemented using, as needed, ActiveX controls, C++ objects, JavaBeans, Microsoft Foundation Classes (“MFC”), Streaming SIMD Extensions (SSE), or other technologies or methodologies.

[0090] The computer system 404 can be configured according to any of the embodiments described herein.

[0091] Further modifications and alternative embodiments of various aspects of the present invention will be apparent to those skilled in the art in view of the present specification. For example, methods and systems for determining information about a sample are provided. Accordingly, the present specification should be construed as illustrative only and is intended to teach those skilled in the art a general way of implementing the present invention. It should be understood that each form of the present invention illustrated and described herein should be regarded as a presently preferred embodiment. Elements and materials may be substituted for those illustrated and described herein, parts and processes may be reversed, and specific features of the present invention may be utilized independently, as will become apparent to those skilled in the art after obtaining the benefit of the present specification. Changes may be made to the elements described herein without departing from the spirit and scope of the present invention as set forth in the following claims.

Claims

Claim 1 A system configured to determine information about a sample, comprising: a computer system configured to generate a sampling plan aimed only at detecting out-of-specification of characteristics of the sample in a measurement process; a measurement subsystem configured to generate an output about the sample by performing the measurement process on the sample using the generated sampling plan; wherein the computer system is further configured to determine the characteristics of the sample based on the generated output, and to detect whether the characteristics of one or more of the samples are out-of-specification based on the determined characteristics of the sample. Claim 2 The system according to claim 1, wherein the characteristic is an overlay of one or more first patterned features formed on the sample with respect to one or more second patterned features formed on the sample. Claim 3 The system according to claim 1, wherein the sampling plan is not configured for the purpose of feedback control of the characteristic. Claim 4 The system according to claim 1, wherein the density of the sampling plan is lower than the density required to enable feedback control of the characteristic. Claim 5 The system according to claim 1, wherein the sampling plan is configured to generate the output for each of the samples within a lot. Claim 6 The system according to claim 1, wherein the sampling plan is configured to generate the output for a subset of the samples within a lot. Claim 7 The system according to claim 1, wherein the generation of the sampling plan includes selecting the number and coordinates of positions at which the measurement subsystem generates the output in the measurement process so that the measurement subsystem conforms to out-of-specification criteria for the sample. Claim 8 The system according to claim 1, wherein the computer system is further configured to determine an index based on the generated output and a predetermined statistical process control index for separating in-specification samples from out-of-specification samples. Claim 9 The system according to claim 8, wherein the computer system is further configured to determine a threshold value for the determined index for separating in-specification samples from out-of-specification samples. Claim 10 The system according to claim 1, wherein the generation of the sampling plan includes determining a measurement subsystem setting based on the frequency of lot sampling, the frequency of in-lot sampling, the in-sample sampling plan, and the constraints of the measurement budget and the throughput of the measurement subsystem.

11. The system according to claim 1, wherein the generation of the sampling plan includes allocating a predetermined measurement budget among lot sampling, sample sampling, and in-sample sampling in order to maximize the detection of out-of-specification samples.

12. The system according to claim 1, wherein the generation of the sampling plan includes co-optimizing the sampling frequency and the measurement subsystem setting in order to maximize the detection of out-of-specification samples in the throughput of a predetermined measurement subsystem.

13. The sampling plan includes information about one or more selected lots, one or more selected samples within the one or more selected lots, one or more positions on the one or more selected samples, and one or more measurement subsystem settings for generating the output at the one or more positions. The computer system is further configured to transmit the information within the sampling plan to the measurement subsystem. The system according to claim 1, wherein the generation of the output using the generated sampling plan is based on the information from the computer system.

14. The measurement subsystem is further configured to generate additional output for at least one of the samples by performing an additional measurement process on at least one of the samples using another sampling plan suitable for feedback control of the characteristic. The computer system is further configured to determine a correction process for at least one of the samples based on the generated additional output.

15. The computer system is further configured to select at least one of the one or more samples detected as being out of specification, and for the at least one sample, the measurement process is performed using a sampling plan that is denser than the generated sampling plan. The system according to claim 1.

16. The computer system is further configured to determine a correction process for the at least one of the one or more samples based on the output generated using the denser sampling plan. The system according to claim 15.

17. The denser sampling plan is configured for feedback control of the characteristic. The system according to claim 15.

18. The measurement subsystem is further configured as an optical-based measurement subsystem. The system according to claim 1.

19. A non-transitory computer-readable medium storing program instructions executable on a computer system for executing a computer-implemented method for determining information about a sample, the computer-implemented method comprising generating a sampling plan aimed only at detecting out-of-specification characteristics of a sample in a measurement process; generating an output about the sample by performing the measurement process on the sample using the generated sampling plan; determining the characteristic of the sample based on the generated output; detecting whether the characteristics of one or more of the samples are out of specification based on the determined characteristics of the sample. A non-transitory computer-readable medium.

20. A computer-implemented method for determining information about a sample, comprising generating a sampling plan aimed only at detecting out-of-specification characteristics of a sample in a measurement process; generating an output about the sample by performing the measurement process on the sample using a measurement subsystem and the generated sampling plan; determining the characteristic of the sample based on the generated output; detecting whether the characteristics of one or more of the samples are out of specification based on the determined characteristics of the sample, A method, wherein generating the sampling plan, performing the determination, and performing the detection are executed by a computer system coupled to the measurement subsystem.

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