Method for determining failure event on lithographic system and associated failure detection assembly

Abstract

A method for determining a failure event on a lithographic system is disclosed. The method includes decomposing at least one signal generated within the lithographic system into a plurality of component signals, each component signal associated with a different respective frequency range; evaluating at least one of the component signals with respect to nominal lithographic system behavior; and identifying any deviation of at least one of the component signals from the nominal lithographic system behavior as a failure event.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to European application 22176549.8 filed on May 31, 2022, and the entire contents of this European application are incorporated herein by reference. Technical Field

[0003] The present invention relates to methods and apparatus which may be used, for example, for manufacturing devices by photolithographic techniques, and to methods of manufacturing devices using photolithographic techniques. The invention more particularly relates to failure detection for such devices. Background Art

[0004] A lithographic apparatus is a machine that applies a desired pattern to a substrate (usually to a target portion of the substrate). A lithographic apparatus can be used, for example, in the manufacture of integrated circuits (ICs). In that case, a pattern forming device (which is alternatively referred to as a mask or reticle) can be used to produce a circuit pattern to be formed on a single layer of the IC. This pattern can be transferred to a target portion (e.g., a portion including a die, a die, or several dies) on a substrate (e.g., a silicon wafer). The transfer of the pattern is usually performed via imaging onto a layer of radiation-sensitive material (resist) disposed on the substrate. Typically, a single substrate will include a network of adjacent target portions that are patterned continuously. These target portions are typically referred to as "fields."

[0005] In the manufacture of complex devices, many lithographic patterning steps are typically performed, thereby forming functional features in successive layers on a substrate. Therefore, a key aspect of the performance of a lithographic apparatus is the ability to properly and accurately place the applied pattern relative to features placed in a previous layer (either by the same apparatus or by a different lithographic apparatus). For this purpose, the substrate is provided with one or more sets of alignment marks. Each mark is a structure whose position can be measured later using a position sensor (usually an optical position sensor). The lithographic apparatus includes one or more alignment sensors, by which the position of the mark on the substrate can be accurately measured. Different types of marks and different types of alignment sensors are well known from different manufacturers and different products of the same manufacturer.

[0006] In other applications, metrology sensors are used to measure exposed structures on the substrate (or in the resist and / or after etching). A fast and non-invasive form of a specialized inspection tool is a scatterometer, in which a radiation beam is directed onto a target on the surface of the substrate and the properties of the scattered or reflected beam are measured. Examples of known scatterometers include angle-resolved scatterometers of the type described in US2006033921A1 and US2010201963A1. In addition to measurement of feature shapes by reconstruction, such devices can also be used to measure diffraction-based overlays, as described in published patent application US2006066855A1. Diffraction-based overlay metrology using dark field imaging of diffraction orders enables overlay measurements of smaller targets. Examples of dark field imaging metrology can be found in international patent applications WO 2009 / 078708 and WO 2009 / 106279, the full text of the documents of which are hereby incorporated by reference. Further developments of the technology have been described in published patent publications US20110027704A, US20110043791A, US2011102753A1, US20120044470A, US20120123581A, US20130258310A, US20130271740A and WO2013178422A1. These targets can be smaller than the illumination spot and can be surrounded by product structures on the wafer. Composite grating targets can be used to measure multiple gratings in one image. The contents of all these applications are also incorporated herein by reference.

[0007] When a lithography system fails, it is important to identify the cause of the failure as quickly as possible. Currently, this is done by trying to reproduce the problem. The triggering of failure detection is based on time domain signals.

[0008] It would be desirable to improve such failure event detection methods. Summary of the invention

[0009] In a first aspect, the present invention provides a method for determining a failure event on a lithography system, the method comprising: decomposing at least one signal generated within the lithography system into a plurality of component signals, each component signal being associated with a different corresponding frequency range; evaluating at least one of the component signals relative to a nominal lithography system behavior; and identifying any deviation of at least one of the component signals from the nominal lithography system behavior as a failure event.

[0010] In a second aspect, the present invention provides a signal deviation detection module capable of operating to determine a failure event on a lithography system, comprising: one or more filters, the one or more filters being capable of operating to decompose at least one signal generated within the lithography system into multiple component signals, each component signal being associated with a different corresponding frequency range; and a processor, the processor being capable of operating to evaluate at least one of the component signals relative to a nominal lithography system behavior, and identifying any deviation of at least one of the component signals from the nominal lithography system behavior as a failure event.

[0011] A computer program operable to perform the method of the first aspect is also disclosed.

[0012] The above and other aspects of the invention will be understood from consideration of the examples described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0014] Figure 1 Describe the lithographic equipment;

[0015] Figure 2 Schematically illustrated Figure 1 Measurement and exposure processes in devices;

[0016] Figure 3 is a schematic diagram of a failure detection system including a plurality of failure detection components according to an embodiment; and

[0017] Figure 4 is a schematic diagram of a signal deviation detection module of a failure detection assembly according to a first embodiment;

[0018] Figure 5 (a) Figure 5 (b) Figure 5 (c) and Figure 5 (d) schematic diagrams of signal decomposer modules each including a signal deviation detection module according to different embodiments; and

[0019] Figure 6 is a schematic diagram of a signal deviation detection module of a failure detection component according to the second embodiment. DETAILED DESCRIPTION

[0020] Before describing embodiments of the invention in detail, it is instructive to present an example environment that can be used to implement embodiments of the invention.

[0021] Figure 1A lithographic apparatus LA is schematically depicted. The apparatus comprises an illumination system (illuminator) IL configured to condition a radiation beam B (e.g. UV radiation or DUV radiation), a patterning device support or support structure (e.g. mask table) MT configured to support a patterning device (e.g. mask) MA and connected to a first positioner PM configured to accurately position the patterning device according to certain parameters, two substrate tables (e.g. wafer stages) WTa and WTb each configured to hold a substrate (e.g. resist-coated wafer) W and each connected to a second positioner PW configured to accurately position the substrate according to certain parameters, and a projection system (e.g. refractive projection lens system) PS configured to project a pattern imparted to the radiation beam B by the patterning device MA onto a target portion C (e.g. comprising one or more dies) of the substrate W. A reference frame or frame RF connects the various elements and serves as a reference for setting and measuring the position of the patterning device and substrate and the positions of features on the patterning device and substrate.

[0022] The illumination system may include various types of optical elements for directing, shaping, or controlling radiation, such as refractive, reflective, magnetic, electromagnetic, electrostatic, or other types of optical elements, or any combination thereof.

[0023] The patterning device support MT holds the patterning device in a manner that depends on the orientation of the patterning device, the design of the lithographic apparatus, and other conditions (such as whether the patterning device is held in a vacuum environment). The patterning device support may use mechanical, vacuum, electrostatic or other clamping techniques to hold the patterning device. The patterning device support MT may be, for example, a frame or a stage, which may be fixed or movable as required. The patterning device support may ensure that the patterning device is in a desired position, for example, relative to a projection system.

[0024] The term "patterning device" as used herein should be broadly interpreted as referring to any device that can be used to impart a radiation beam with a pattern in its cross-section so as to produce a pattern in a target portion of the substrate. It should be noted that, for example, if the pattern imparted to the radiation beam includes phase-shifting features or so-called assist features, the pattern may not exactly correspond to the desired pattern in the target portion of the substrate. Typically, the pattern imparted to the radiation beam will correspond to a specific functional layer in a device (such as an integrated circuit) created in the target portion.

[0025] As depicted here, the device is of the transmissive type (e.g., using a transmissive patterning device). Alternatively, the device may be of the reflective type (e.g., using a programmable mirror array of the type mentioned above, or using a reflective mask). Examples of patterning devices include masks, programmable mirror arrays, and programmable LCD panels. Any use of the term "reticle" or "mask" herein may be considered synonymous with the more general term "patterning device". The term "patterning device" may also be interpreted as referring to a device that stores pattern information in digital form for controlling the programmable patterning device.

[0026] The term "projection system" as used herein should be broadly interpreted as covering any type of projection system suitable for the exposure radiation used or for other factors such as the use of immersion liquid or the use of a vacuum, including refractive, reflective, catadioptric, magnetic, electromagnetic and electrostatic optical systems, or any combination thereof. Any use of the term "projection lens" herein should be considered synonymous with the more general term "projection system".

[0027] The lithographic apparatus may also be of a type in which at least a portion of the substrate may be covered by a liquid having a relatively high refractive index (e.g., water) so as to fill the space between the projection system and the substrate. Immersion liquid may also be applied to other spaces in the lithographic apparatus, for example, the space between the mask and the projection system. Immersion techniques are well known in the art for increasing the numerical aperture of a projection system.

[0028] In operation, the illuminator IL receives a radiation beam from a radiation source SO. For example, when the radiation source is an excimer laser, the radiation source and the lithographic apparatus may be separate entities. In these cases, the radiation source is not considered to form part of the lithographic apparatus, and the radiation beam is transferred from the radiation source SO to the illuminator IL by means of a beam delivery system BD comprising, for example, suitable directional mirrors and / or a beam expander. In other cases, for example, when the radiation source is a mercury lamp, the radiation source may be an integral part of the lithographic apparatus. The radiation source SO and the illuminator IL together with the beam delivery system BD may be referred to as a radiation system when necessary.

[0029] The illuminator IL may, for example, comprise an adjuster AD for adjusting the angular intensity distribution of the radiation beam, an integrator IN and a condenser CO. The illuminator may be used to condition the radiation beam, to have a desired uniformity and intensity distribution in its cross-section.

[0030] The radiation beam B is incident on a patterning device MA held on a patterning device support MT and is patterned by the patterning device. Having traversed the patterning device (e.g. a mask) MA, the radiation beam B passes through a projection system PS which focuses the beam onto a target portion C of the substrate W. With the aid of a second positioner PW and a position sensor IF (e.g. an interferometer, a linear encoder, a 2D encoder or a capacitive sensor), the substrate table WTa or WTb can be accurately moved, for example in order to position a different target portion C in the path of the radiation beam B. Similarly, the first positioner PM and a further position sensor (which is not in the Figure 1 ) can be used to accurately position the patterning device (eg, mask) MA relative to the path of the radiation beam B, for example, after mechanical retrieval from a mask library or during scanning.

[0031] Mask alignment marks M1, M2 and substrate alignment marks P1, P2 can be used to align the pattern forming device (e.g., mask) MA and the substrate W. Although the substrate alignment marks as shown occupy dedicated target portions, the marks can be located in the spaces between target portions (these marks are called scribe alignment marks). Similarly, where more than one die is provided on the pattern forming device (e.g., mask) MA, the mask alignment marks can be located between the dies. Small alignment marks can also be included in the die among the device features, in which case it is desirable to make the marks as small as possible and without requiring any imaging or process conditions that are different from adjacent features. An alignment system for detecting alignment marks is further described below.

[0032] The depicted apparatus can be used in a variety of modes. In a scan mode, the pattern forming device support (e.g., mask table) MT and the substrate table WT are scanned synchronously while a pattern imparted to the radiation beam is projected onto a target portion C (i.e., a single dynamic exposure). The speed and direction of the substrate table WT relative to the pattern forming device support (e.g., mask table) MT can be determined by the (re)magnification and image reversal characteristics of the projection system PS. In the scan mode, the maximum size of the exposure field limits the width of the target portion in a single dynamic exposure (in the non-scanning direction), while the length of the scanning movement determines the length of the target portion (in the scanning direction). As is well known in the art, other types of lithographic apparatus and operating modes are possible. For example, stepping modes are known. In so-called "maskless" lithography, the programmable pattern forming device is held stationary, but with a changing pattern, and the substrate table WT is moved or scanned.

[0033] Combinations and / or variations on the above-described modes of use or entirely different modes of use may also be employed.

[0034] The lithographic apparatus LA is of the so-called dual-platform type, having two substrate tables WTa, WTb and two stations - an exposure station EXP and a measurement station MEA - between which the substrate tables can be exchanged. While exposing one substrate on one substrate table at the exposure station, another substrate can be loaded onto the other substrate table at the measurement station and various preparatory steps can be performed. This situation achieves a considerable increase in the throughput of the apparatus. The preparatory steps can include using a horizontal sensor LS to map the surface height profile of the substrate, and using an alignment sensor AS to measure the position of alignment marks on the substrate. If the position sensor IF is not able to measure the position of the substrate table when the substrate table is at the measurement station and at the exposure station, a second position sensor can be provided to enable tracking of the position of the substrate table relative to the reference system RF at the two stations. Instead of the dual-platform arrangement shown, other arrangements are known and available. For example, other lithographic apparatuses that provide a substrate table and a measurement table are well known. These substrate tables and measurement tables are docked together when performing preparatory measurements, and then are not docked when the substrate table is exposed.

[0035] Figure 2 Diagram for exposing a target portion (e.g., die) to Figure 1 200 , a new substrate W' is loaded into the apparatus by a mechanism or mechanism not shown in the figure. Such two substrates are processed in parallel in order to increase the throughput of the lithographic apparatus.

[0036] Reference is initially made to a newly loaded substrate W', which may be a previously unprocessed substrate, which is prepared with a new resist for exposure for the first time in the apparatus. However, typically, the lithographic process described will be just a sequence of exposure and processing steps, such that the substrate W' has passed through this apparatus and / or other lithographic apparatus several times, and may also have undergone subsequent processes. Especially for the problem of improving overlay performance, the task should be to ensure that the new pattern is applied exactly in the correct position on a substrate that has been subjected to one or more cycles of patterning and processing. These processing steps gradually introduce deformations in the substrate, which must be measured and corrected to achieve satisfactory overlay performance.

[0037] Previous and / or subsequent patterning steps (as just mentioned) may be performed in other lithographic equipment, and may even be performed in different types of lithographic equipment. For example, some layers in the device manufacturing process that are very demanding in terms of parameters such as resolution and overlay may be performed in more advanced lithographic tools than other layers that are less demanding. Thus, some layers may be exposed in immersion lithographic tools, while other layers are exposed in "dry" tools. Some layers may be exposed in tools operating at DUV wavelengths, while other layers are exposed using EUV wavelength radiation.

[0038] At 202, alignment measurements using substrate marks P1 etc. and an image sensor (not shown) are used to measure and record the alignment of the substrate relative to the substrate table WTa / WTb. In addition, an alignment sensor AS will be used to measure a number of alignment marks across the substrate W'. In one embodiment, these measurements are used to establish a "wafer grid" that very accurately maps the distribution of the marks across the substrate, including any deformations from the nominal rectangular grid.

[0039] At step 204, a level sensor LS is also used to measure a wafer height (Z) map relative to the XY position. Typically, the height map is only used to achieve accurate focus of the exposed pattern. It can additionally be used for other purposes.

[0040] When the substrate W' is loaded, the recipe data 206 are received, which define the exposure to be performed and also define the properties of the wafer and the previously generated pattern and the pattern to be generated on the wafer. The measurements of the wafer position, wafer grid and height map performed at 202, 204 are added to these recipe data so that the complete set of recipe and measurement data 208 can be transferred to the exposure station EXP. The measurement results of the alignment data (for example) include the X position and Y position of the alignment target formed in a fixed or nominally fixed relationship with the product pattern of the product of the lithography process. These alignment data obtained just before the exposure are used to generate an alignment model, which has parameters that fit the model to the data. These parameters and the alignment model will be used during the exposure operation to correct the position of the pattern applied in the current lithography step. The model in use interpolates the position deviations between the measured positions. Conventional alignment models may include four, five or six parameters, which together define the translation, rotation and scaling of the "ideal" grid at different sizes. Advanced models using more parameters are known.

[0041] At 210, wafers W' and W are exchanged so that substrate W' to be measured becomes substrate W and enters exposure station EXP. Figure 1In the example apparatus of , this exchange is performed by exchanging supports WTa and WTb within the apparatus so that the substrates W, W' remain accurately clamped and positioned on those supports to preserve the relative alignment between the substrate table and the substrate itself. Therefore, once the tables have been exchanged, in order to utilize the measurement information 202, 204 for the substrate W (formerly W') to control the exposure step, it is necessary to determine the relative position between the projection system PS and the substrate table WTb (formerly WTa). At step 212, reticle alignment is performed using the mask alignment marks M1, M2. In steps 214, 216, 218, scanning movements and radiation pulses are applied at successive target locations across the substrate W in order to complete the exposure of a certain number of patterns.

[0042] By using the alignment data and height map obtained at the measurement station in performing the exposure step, these patterns are accurately aligned relative to the desired locations, and in particular, relative to features previously placed on the same substrate. The exposed substrate, now labeled W", is unloaded from the apparatus at step 220 to undergo etching or other processes according to the exposed patterns.

[0043] Those skilled in the art will appreciate that the above description is a simplified overview of the multiple very detailed steps involved in one example of a real manufacturing situation. For example, there will often be different stages of coarse and fine measurements using the same or different markings, rather than measuring alignment in a single pass. The coarse and / or fine alignment measurement steps may be performed before the height measurement or after the height measurement, or interleaved.

[0044] In lithography systems, an important issue that has a significant impact on system uptime is the ability to quickly and efficiently detect and / or diagnose events or trends that may indicate irregular or abnormal behavior (e.g., failure events). However, such systems are very complex, including a number of different components (e.g., including, among others, projection optics components, wafer stage components, mask stage components, mask shielding components), each of which generates a large amount of data. Complex problems involving multiple components can be a particular challenge for diagnosis due to the lack of data on failure events. Complete contextual information at the time of failure (e.g., traces from all components) is typically not available.

[0045] To address this problem, one current approach attempts to reproduce the problem (failure event) in order to collect contextual information for diagnosis. This is very time consuming and results in long downtime, especially for (non-reproducible) intermittent problems. Additionally, no cross-component failure event triggering is available; even when reproducing the problem, only single component information can be collected.

[0046] Furthermore, in current diagnostic approaches, triggers for failure event detection are based on time domain signals. Typically a trigger is generated when a specified signal crosses a predefined threshold. This is typically time domain anomaly detection based on the sensor signal amplitude. As a result, many failures that excite a specific frequency band are not captured. This can result in a considerable amount of time spent finding the root cause, or even failure to identify the root cause.

[0047] In order to address one or more of these issues, a method for determining a failure event on a lithography system is provided. The method comprises the steps of: decomposing a signal generated within the lithography system into a plurality of component signals, each component signal being associated with a different respective frequency range; evaluating each of the component signals relative to a nominal lithography system behavior (e.g., comparing each of the component signals to an indicator of the nominal lithography system behavior); and identifying any deviation of at least one of the component signals from the nominal lithography system behavior as a failure event. For example, the indicator may be a threshold value of a component signal or a reference signal.

[0048] Figure 3 is a high-level diagram of the proposed failure event triggering architecture according to an embodiment. Each lithography system component MOD1 to MOD k There are corresponding failure detection components FD1 to FD k The lithography system component MOD1 and its failure detection component FD1 are shown in more detail than the other components. Each system component may generate a certain number of measurable signals. For example, here, the first lithography system component MOD1 generates n measurable signals V1 to V n (From each lithography system component MOD1 to MOD k The number of output signals may vary. In an embodiment, each failure detection component FD1 to FD k can be configured to be used for the corresponding lithography system components MOD1 to MOD k In the example shown, each of the m signals in the small subset of n signals generated by the lithography system component MOD1 is sampled by a corresponding signal deviation detection module SDD1 to SDD2 of the failure detection component FD1. m Monitoring. The subset of signals monitored (e.g., m) may include less than 30%, less than 10%, less than 5%, less than 2%, or less than 1% of the generated signals (e.g., n), and / or the number of signals monitored may be any appropriate subset of the generated signals.

[0049] A subset of the monitored signals may be selected on a per-component basis, for example, based on user or domain knowledge of which signals are most relevant to the system dynamics for a particular component. Alternatively or in addition, the monitored signals may be selected based on a particular system state. For example, the monitoring described herein may be performed primarily or only during certain predefined system states. The relevant signals for an exposure state (e.g., when the system is performing an exposure) may be different from the signals for a "transmission image sensor (TIS) scan" state (during which the actinic spatial image of the projected (TIS) reticle marking is measured). Thus, the monitored signals may be selected based on the system state (those skilled in the art will recognize that there are more system states than the two specific examples provided here). In this way, the signals monitored by each failure detection component may be configurable, for example, based on a particular state or action performed by the system.

[0050] Each signal deviation detection module SDD1 to SDD m One or more suitable filters may be included to define a plurality of component signals from the signal monitored by the signal deviation detection module, each component signal being associated with a corresponding frequency range or frequency interval. Thus, monitoring of each monitored signal may be performed within a frequency interval, so that, for example, an event trigger signal may be generated if a deviation is detected within one or more frequency intervals. Deviations may be detected by comparing parameters of the signal components (e.g., signal energy) with corresponding thresholds for the signal components. In this way, complex frequency analysis may be performed without complex computational implementation.

[0051] The signal deviation detection modules SDD1 to SDD m The outputs of each signal deviation detection module in the signal deviation detection module are combined into a single output, for example, via a suitable logical operator. For example, an OR gate can be used to gate these outputs so that if one (or more) of the signal deviation detection modules generates a trigger TG SDD , the failure detection component generates a corresponding failure event to trigger TG FD . The use of an OR gate is merely an example, and other logic operations may be possible. For example, specific two (or more than two) signal deviation detection modules may be AND-gated with respect to their respective signals where appropriate; the output of the AND gate may then be OR-gated (or otherwise combined) with the output of the other signal deviation detection module. This is a single specific example, and those skilled in the art will recognize that any type, number, and combination of logic operations may be used.

[0052] The outputs of the failure detection components can be similarly combined with appropriate logic gates (e.g., OR gates, or combinations of logic operations / gates) to detect a failure in, for example, one of the multiple failure detection components and generate a FD trigger TG. FD When the system fails, a trigger signal TG is generated. SY .

[0053] Figure 4 is an example schematic diagram of a signal deviation detection module according to an embodiment. At a high level, the signal deviation detection module may include a signal decomposer module SD, a signal comparator module SC and a logic module or health check logic module HCL.

[0054] The signal decomposer module SD decomposes the input signal S into multiple signal components S d1 To S dp , each signal component is associated with a different frequency range or frequency interval. More specifically, the input time domain signal S(t) is decomposed into multiple time domain signals S using a filter bank. i (t), i=1, ..., p. Each signal S i (t), i=1, ..., p, including information from the original signal S(t) in a specific frequency range. Optionally, the signal S i (t), one of i=1, ..., p can be obtained via the through path to monitor the full input signal S(t).

[0055] The signal comparator module compares each signal component S d1 To S dp The corresponding comparison output signal S is compared with a corresponding indicator (e.g., a threshold or reference value) of the nominal lithography system behavior in order to determine whether the signal component (and optionally, the entire signal) is within specification. c1 To S cp For each signal component S d1 To S dp is output.

[0056] The health check logic module combines and compares the output signals S according to one or more logic operations. c1 To S cp , so that when appropriate (for example, when comparing the output signal S c1 To S cp At least one comparison output signal indicates a signal component S d1 To S dp When at least one signal component in the SDD As already described, the logic operation may comprise a single logic gate, such as a single OR gate, or a more complex combination of multiple logic gates.

[0057] Figure 5 Shown can be used for example Figure 4 Four example embodiments of the signal decomposer module SD in the signal deviation detection module are illustrated in FIG. Figure 5 (a) shows an example of a signal decomposer module, which uses a high-pass filter HPF and a low-pass filter LPF to obtain three signal components: a high-frequency component, which covers the higher frequency range of the input signal directly obtained by applying the high-pass filter HPF to the input signal S(t); a low-frequency component, which covers the lower frequency range of the input signal directly obtained by applying the low-pass filter LPF to the input signal S(t); and an intermediate frequency component, which covers the intermediate frequency range obtained by removing the high-frequency component and the low-frequency component of the input signal from the input signal S(t). In this way, three frequency intervals are defined for signal monitoring. As mentioned above, an optional through path is provided to monitor the full input signal or the complete input signal S(t).

[0058] Figure 5 (b) shows a second example of a signal decomposer module, and in particular, shows an example filter bank for implementing such a signal decomposer module. For some applications, depending on the nature of the failure or system behavior, it may be necessary to define frequency ranges of different lengths. In such a shown arrangement, one or more bandpass filters BPF1 to BPF p-1 , the one or more bandpass filters can be provided to provide the flexibility of defining such different frequency ranges. These bandpass filters can be implemented in combination with a low pass filter LPF and a high pass filter HPF to define the highest frequency range and the lowest frequency range, and if necessary, define a straight-through path as already described.

[0059] For time-invariant signals (e.g., , where A is the amplitude, is 2πf and ɸ is the phase), frequency domain analysis using the Fast Fourier Transform (FFT) is sufficient. In this case, for a time-invariant signal, Figure 5 The signal decomposer module in (b) is able to generate the required trigger.

[0060] However, for time-varying signals (e.g. , where the frequency content changes over time), Figure 5 The signal decomposer module of (b) may not be sufficient. In such a situation, the Figure 5 (c) and Figure 5 (d) or a variation thereof. This is similar to generating a trigger based on wavelet coefficients. Figure 5(c), in each layer, the low-pass signal from the previous layer (or the input signal for the first layer) is divided into two signals using a high-pass filter HPF and a low-pass filter LPF. This figure shows the resulting frequency range (where F s is the sampling frequency). Figure 5 (d) shows an arrangement in which each layer uses a high pass filter HPF and a low pass filter LPF on each component of the previous layer to double the number of signal components. Of course, fewer or more layers than those shown in these figures may be used.

[0061] It will be appreciated that if certain failures are preferably monitored at particular frequencies, this may be achieved using a suitable arrangement such as a Goertzel algorithm or a tuned bandpass filter (e.g., in combination with any of the examples disclosed herein and / or within the scope of the present disclosure).

[0062] Application of the filter may be performed in real time to enable online diagnostics.

[0063] Figure 6 is a specific implementation of the signal deviation detection module according to the embodiment. This shows the signal decomposer module SD (e.g., Figure 5 (a)), a specific implementation of each of the modules in the signal decomposer module, the signal comparator module SC, and the health check logic module HCL. The specific implementation of each of these modules as shown here can be implemented by different specific implementations of the modules as disclosed herein and / or within the scope of the present disclosure. Thus, the specific signal decomposer module SD shown here can be implemented using different examples of the signal comparator module and / or the health check logic module HCL, the specific signal comparator module SC shown here can be implemented using different examples of the signal decomposer module SD and / or the health check logic module HCL, and so on.

[0064] In the signal comparator module SC, the monitoring indicator calculation module ENG can be used to calculate a specific monitoring parameter for each signal component. For example, the monitoring parameter may include the signal energy E of the corresponding signal component. L 、E M 、E H 、E T These energy values ​​E L 、E M 、E H 、E T Each of the energy reference values ​​Ref (e.g., ) The corresponding reference value B defined L , B M , B H, B T compared to.

[0065] More generally, the signal comparator module SC may be used to evaluate the decomposed signal S i (t), i=1, ..., p has deviated from a reference (or a subset of the components of the decomposed signal) for nominal or healthy behavior.

[0066] The energy of the decomposed signal can be measured relative to the signal The squared sum of the offset / bias error is calculated, where N is the squared sum of the offset / bias error from S i (t) of the entire measurement for the sample of interest.

[0067]

[0068] The expected or reference energy of the decomposed signal corresponding to a healthy machine It can be calculated by collecting data from healthy machines. A healthy machine can be defined as a machine state when system performance (eg, total system performance) is within specification.

[0069] Relative to reference Current measurement of Deviation in can be calculated as:

[0070]

[0071] Decomposed signal energy The threshold value of the deviation in You can use reference is defined as:

[0072]

[0073] in is relative to For example, if the maximum relative deviation allowed for the decomposed signal S1 is is 50%, then is 0.5, and if for the decomposed signal S2, the maximum relative deviation allowed is relative to is 400%, then is 4.

[0074] When the threshold is crossed, the comparator state is output can be defined as 1, otherwise 0, that is:

[0075]

[0076] It should be noted that the monitoring parameter may include a maximum value S during the N samples of interest. i (t), instead of comparing the decomposed signal S i (t) of energy.

[0077] It will be appreciated that each signal deviation detection module will monitor the signal health of several signals in real time during system operation. Therefore, it is desirable to keep the computational requirements from each signal deviation detection module as low as possible. In a specific example, the corresponding low-pass signal component and high-pass signal component are defined as , A computationally efficient first-order low-pass and high-pass filter can be described by:

[0078]

[0079] in is the filter cutoff frequency, and is the sampling frequency.

[0080] In summary, a method is provided that uses frequency grouping, i.e., frequency binning, to provide signal deviation detection that can capture a larger set of failures that are not captured using existing methods. The method also provides cross-component triggering to collect complete contextual information from all system components.

[0081] It should be understood that the term color is used synonymously with wavelength throughout this document, and that color can include those colors outside the visible band (eg, infrared or ultraviolet wavelengths).

[0082] While specific embodiments of the invention have been described above, it will be appreciated that the invention may be practiced otherwise than as described.

[0083] Although the above may have specifically referred to the use of embodiments of the invention in the context of optical lithography, it will be appreciated that the invention may be used in other applications, such as imprint lithography, and is not limited to optical lithography where the context permits. In imprint lithography, the topography in a patterning device defines a pattern produced on a substrate. The topography of the patterning device may be pressed into a layer of resist supplied to a substrate, on which the resist is cured by applying electromagnetic radiation, heat, pressure, or a combination thereof. After the resist is cured, the patterning device is removed from the resist, leaving a pattern therein.

[0084] As used herein, the terms "radiation" and "beam" encompass all types of electromagnetic radiation, including ultraviolet (UV) radiation (e.g., having a wavelength of at or about 365 nm, 355 nm, 248 nm, 193 nm, 157 nm, or 126 nm) and extreme ultraviolet (EUV) radiation (e.g., having a wavelength in the range of 1 nm to 100 nm), as well as particle beams, such as ion beams or electron beams.

[0085] The term "lens" may refer to any one or combination of various types of optical elements, including refractive, reflective, magnetic, electromagnetic and electrostatic optical elements, as the context permits. Reflective elements are likely to be used in devices operating in the UV and / or EUV range.

[0086] The breadth and scope of the present invention should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.

[0087] Further aspects of the invention are set forth in the following numbered aspects:

[0088] 1. A method for determining a failure event on a lithography system, the method comprising:

[0089] decomposing at least one signal generated within the lithography system into a plurality of component signals, each component signal being associated with a different respective frequency range;

[0090] evaluating at least one of the component signals relative to nominal lithography system behavior; and

[0091] Any deviation of at least one of the component signals from the nominal lithography system behavior is identified as a failure event.

[0092] 2. The method of clause 1, wherein the evaluating step comprises evaluating each of the component signals relative to a nominal lithography system behavior.

[0093] 3. A method according to clause 1 or 2, wherein the evaluating step comprises comparing each of the component signals to at least one indicator of nominal lithography system behavior.

[0094] 4. A method according to aspect 3, wherein the at least one indicator comprises a respective threshold or reference signal for each component signal.

[0095] 5. A method according to any preceding aspect, comprising: combining the outputs of the evaluation and identification steps associated with each component signal to generate a failure event trigger signal for at least one of the component signals based on the identification of any deviation of at least one of the component signals.

[0096] 6. The method according to aspect 5, comprising:

[0097] performing the method individually for each of a plurality of signals associated with a lithography system component of the lithography system; and

[0098] The failure event trigger signal for each of the plurality of signals associated with the lithography system component is combined to generate a failure event trigger signal for the lithography system component.

[0099] 7. The method of clause 6, wherein the plurality of signals comprises a subset of measurable signals generated by the lithography system components.

[0100] 8. The method of clause 7, comprising selecting the subset of measurable signals based on one or both of: a system state of the lithography system, and domain knowledge.

[0101] 9. The method according to aspect 6, 7 or 8, comprising:

[0102] performing the method individually for each lithography system component of a plurality of lithography system components associated with the lithography system; and

[0103] The failure event trigger signals associated with each lithography system component are combined to generate a failure event trigger signal for the lithography system.

[0104] 10. A method according to any one of aspects 5 to 9, wherein in one or more of the combining steps, the outputs are combined using one or more logical operators.

[0105] 11. The method according to clause 10, wherein the one or more logical operators include at least an OR operator.

[0106] 12. A method according to any preceding aspect, wherein the decomposing step comprises applying one or more high pass filters, low pass filters and / or band pass filters to the at least one signal.

[0107] 13. A method according to aspect 12, wherein the decomposing step comprises applying one or more layers of at least low pass filters and high pass filters to one or more signals of a previous layer.

[0108] 14. A method according to aspect 11, wherein the decomposition step includes applying at least a low-pass filter and a high-pass filter to the at least one signal to produce at least three of the signal components: a low-frequency component, the low-frequency component covers a lower frequency range of the at least one signal; a high-frequency component, the high-frequency component covers a higher frequency range of the at least one signal; and an intermediate frequency component, the intermediate frequency component covers an intermediate frequency range of the at least one signal between the lower frequency range and the higher frequency range.

[0109] 15. The method according to any preceding aspect, wherein the decomposing step comprises applying at least one Goertzel algorithm or a bandpass filter to the at least one signal to produce signal components at a specific frequency or a specific frequency range.

[0110] 16. A method according to any preceding aspect, comprising the steps of: evaluating the at least one signal without decomposition relative to a nominal lithography system behavior; and identifying any deviation of the at least one signal from the nominal lithography system behavior as a failure event.

[0111] 17. The method of any preceding aspect, wherein the step of evaluating the component signals comprises evaluating signal energy of the component signals.

[0112] 18. A signal deviation detection module operable to determine a failure event on a lithography system, comprising:

[0113] one or more filters operable to decompose at least one signal generated within the lithography system into a plurality of component signals, each component signal being associated with a different respective frequency range; and

[0114] A processor is operable to evaluate at least one of the component signals relative to a nominal lithography system behavior and to identify any deviation of at least one of the component signals from the nominal lithography system behavior as a failure event.

[0115] 19. The signal deviation detection module of clause 18, wherein the processor is operable to evaluate each of the component signals relative to nominal lithography system behavior.

[0116] 20. A signal deviation detection module according to clause 18 or 19, wherein the processor is operable to compare each of the component signals to at least one indicator of nominal lithography system behaviour.

[0117] 21. The signal deviation detection module of aspect 20, wherein the at least one indicator comprises a respective threshold or reference signal for each component signal.

[0118] 22. A signal deviation detection module according to any one of Aspects 18 to 21, comprising one or more logical operators, which are capable of operating to combine the outputs of the evaluation and identification steps associated with each component signal to generate a failure event trigger signal for the signal based on the identification of any deviation of at least one of the component signals.

[0119] 23. The signal deviation detection module according to aspect 22, wherein the one or more logical operators include at least an OR operator.

[0120] 24. A signal deviation detection module according to any one of aspects 18 to 23, wherein the one or more filters include one or more high pass filters, low pass filters and / or band pass filters.

[0121] 25. The signal deviation detection module of aspect 24, wherein the one or more filters comprise one or more layers of at least low pass filters and high pass filters.

[0122] 26. A signal deviation detection module according to any one of aspects 18 to 20, wherein the one or more filters include at least a low-pass filter and a high-pass filter arranged to produce at least three of the following signal components: a low-frequency component, the low-frequency component covering a lower frequency range of the signal; a high-frequency component, the high-frequency component covering a higher frequency range of the signal; and an intermediate frequency component, the intermediate frequency component covering an intermediate frequency range of the signal between the lower frequency range and the higher frequency range.

[0123] 27. A signal deviation detection module according to any one of aspects 18 to 26, comprising a Goertzel algorithm or a tuned bandpass filter operable to produce a signal component at a specific frequency or a specific frequency range.

[0124] 28. A signal deviation detection module according to any one of aspects 18 to 27, wherein the processor is further capable of evaluating the undecomposed signal relative to a nominal lithography system behavior; and identifying any deviation of the signal from the nominal lithography system behavior as a failure event.

[0125] 29. A signal deviation detection module according to any one of aspects 18 to 28, wherein the processor is operable to evaluate signal energy of the component signal.

[0126] 30. A failure detection assembly operable to determine a failure event on a lithography system, comprising:

[0127] a plurality of signal deviation detection modules according to any one of clauses 18 to 29, each signal deviation detection module being operable to determine a failure event for a corresponding signal of a plurality of signals associated with a lithography system component of the lithography system; and

[0128] At least one logic operator operable to combine the output of each signal deviation detection module to generate a failure event trigger signal for the lithography system component.

[0129] 31. A failure detection assembly according to aspect 30, wherein the at least one logical operator operable to combine the output of each signal deviation detection module comprises at least an OR operator.

[0130] 32. A failure detection assembly according to clause 30 or 31, wherein the plurality of signals comprises a subset of the measurable signals generated by the lithography system component.

[0131] 33. A failure detection system operable to determine a failure event on a lithography system, comprising:

[0132] a plurality of failure detection components according to clause 30, 31 or 32, each failure detection component being operable to determine a failure event for a corresponding lithography system component of the lithography system;

[0133] At least one logic operator operable to combine the output of each failure detection component to generate a failure event trigger signal for the lithography system.

[0134] 34. A failure detection system according to aspect 33, wherein the one or more logical operators operable to combine the output of each failure detection component comprises at least an OR operator.

[0135] 35. A computer program comprising program instructions operable to perform a method according to any one of clauses 1 to 15 when run on a suitable device.

[0136] 36. A non-transitory computer program carrier comprising a computer program according to clause 35.

[0137] 37. A processing arrangement comprising:

[0138] A non-transitory computer program carrier according to clause 36; and

[0139] A processor operable to run the computer program included on the non-transitory computer program carrier.

[0140] 38. A lithography system comprising a failure detection system according to clause 33 or 34.

Claims

1. A method for determining a failure event on a lithography system, the method comprising: decomposing at least one signal generated within the lithography system into a plurality of component signals, each component signal being associated with a different respective frequency range; evaluating at least one of the component signals relative to nominal lithography system behavior; and Any deviation of at least one of the component signals from the nominal lithography system behavior is identified as a failure event.

2. The method according to claim 1, wherein: The evaluating step includes evaluating each of the component signals relative to a nominal lithography system behavior.

3. A method according to any preceding claim, comprising: The outputs of said evaluating and identifying steps associated with each component signal are combined to generate a failure event trigger signal for at least one of said component signals based on said identification of any deviation of said at least one component signal.

4. The method according to claim 3, comprising: performing the method individually for each of a plurality of signals associated with a lithography system component of the lithography system; and The failure event trigger signal for each of the plurality of signals associated with the lithography system component is combined to generate a failure event trigger signal for the lithography system component.

5. The method according to claim 4, wherein: The plurality of signals includes a subset of measurable signals generated by the lithography system components.

6. The method of claim 5, comprising selecting the subset of measurable signals based on one or both of: a system state of the lithography system, and domain knowledge.

7. The method according to claim 4, 5 or 6, comprising: performing the method individually for each lithography system component of a plurality of lithography system components associated with the lithography system; and The failure event trigger signals associated with each lithography system component are combined to generate a failure event trigger signal for the lithography system.

8. The method according to any one of claims 4 to 7, wherein: In one or more of the combining steps, the outputs are combined using one or more logical operators.

9. A method according to any preceding claim, wherein: The decomposing step comprises applying one or more high pass filters, low pass filters and / or band pass filters to the at least one signal.

10. A method according to any preceding claim, wherein: The decomposing step comprises applying at least one Goertzel algorithm or a bandpass filter to the at least one signal in order to generate signal components at a specific frequency or a specific frequency range.

11. A method according to any preceding claim, wherein: The step of evaluating the component signals comprises evaluating signal energies of the component signals.

12. A signal deviation detection module operable to determine a failure event on a lithography system, comprising: one or more filters operable to decompose at least one signal generated within the lithography system into a plurality of component signals, each component signal being associated with a different respective frequency range; and A processor is operable to evaluate at least one of the component signals relative to a nominal lithography system behavior and to identify any deviation of at least one of the component signals from the nominal lithography system behavior as a failure event.

13. The signal deviation detection module according to claim 12, wherein: The processor is operable to evaluate each of the component signals relative to nominal lithography system behavior.

14. A signal deviation detection module according to claim 12 or 13, comprising one or more logical operators, which are capable of operating to combine the outputs of the evaluation and identification steps associated with each component signal to generate a failure event trigger signal for the signal based on the identification of any deviation of at least one of the component signals.

15. A signal deviation detection module according to any one of claims 12 to 14, comprising a Goertzel algorithm or a tuned bandpass filter operable to produce a signal component at a specific frequency or a specific frequency range.

16. The signal deviation detection module according to any one of claims 12 to 15, wherein: The processor is operable to evaluate signal energy of the component signals.

17. A failure detection assembly operable to determine a failure event on a lithography system, comprising: a plurality of signal deviation detection modules according to any one of claims 12 to 16, each signal deviation detection module being operable to determine a failure event for a corresponding signal of a plurality of signals associated with a lithography system component of the lithography system; and At least one logic operator operable to combine the output of each signal deviation detection module to generate a failure event trigger signal for the lithography system component.

18. A failure detection system operable to determine a failure event on a lithography system, comprising: a plurality of failure detection assemblies according to claim 17, each failure detection assembly being operable to determine a failure event for a corresponding lithography system component of the lithography system; At least one logic operator operable to combine the output of each failure detection component to generate a failure event trigger signal for the lithography system.

19. A computer program comprising program instructions operable to perform the method according to any one of claims 1 to 11 when run on a suitable device.

20. A non-transitory computer program carrier comprising a computer program according to claim 19.

21. A processing arrangement comprising: The non-transitory computer program carrier according to claim 20; and A processor operable to run the computer program included on the non-transitory computer program carrier.

22. A lithography system comprising the failure detection system according to claim 18.

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