Method and associated apparatus for controlling a manufacturing process

Abstract

A method and associated apparatus for controlling a process for manufacturing a semiconductor device on a substrate is disclosed. The method includes obtaining process data associated with the process, and determining a correction for the process based on the process data and a first control target associated with the device on the substrate. A first probability that the first control target is achievable is determined, and the correction is adjusted based on the probability and at least a second control target, the second control target having a second probability of being achievable compared to the first control target.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to EP Application No. 20156961.3 filed on February 12, 2020, EP Application No. 20158387.9 filed on February 20, 2020, and EP Application No. 20177353.8 filed on May 29, 2020, which are incorporated herein by reference in their entirety. Technical Field

[0003] The present invention relates to methods and apparatus for applying a pattern to a substrate during a photolithographic process. Background Art

[0004] A lithographic apparatus is a machine that applies a desired pattern to a substrate (usually applied to a target portion of a substrate). A lithographic apparatus can be used, for example, in the manufacture of an integrated circuit (IC). In this example, a pattern forming device (alternatively referred to as a mask or reticle) can be used to generate a circuit pattern to be formed on a single layer of an IC. The pattern can be transferred to a target portion (e.g., including a portion of a tube core, one or more tube cores) on a substrate (e.g., a silicon wafer). The transfer of the pattern is usually via imaging onto a radiation-sensitive material (resist) layer provided on the substrate. Typically, a single substrate will contain a network of adjacent target portions that are patterned continuously. Known lithographic apparatus include so-called steppers (where each target portion is radiated by exposing the entire pattern to the target portion at one time) and so-called scanners (where each target portion is radiated by scanning a pattern with a radiation beam in a given direction ("scanning" direction), while synchronously scanning a substrate parallel or antiparallel to the direction. The pattern can also be transferred from the pattern forming device to the substrate by imprinting the pattern onto the substrate.

[0005] In order to monitor the lithography process, parameters of the patterned substrate are measured. The parameters may include, for example, the overlay error between successive layers formed in or on the patterned substrate and the critical line width (CD) of the developed photoresist. The measurement may be performed on a production substrate and / or a dedicated metrology target. There are a variety of techniques for measuring the microstructures formed during the lithography process, including the use of scanning electron microscopes and various dedicated tools. A fast and non-invasive form of dedicated inspection tool is a scatterometer, in which a radiation beam is directed onto a target on the substrate surface and the properties of the scattered or reflected beam are measured. Two main types of scatterometers are known. Spectral scatterometers direct a broadband radiation beam onto a substrate and measure the spectrum (intensity according to wavelength) of the radiation scattered into a specific narrow angular range. Angular resolved scatterometers use a monochromatic radiation beam and measure the intensity of the scattered radiation according to the angle.

[0006] Examples of known scatterometers include angle-resolved scatterometers of the type described in US2006033921A1 and US2010201963A1. The target used by such scatterometers is a relatively large (e.g. 40 μm x 40 μm) grating, and the measuring beam generates a spot that is smaller than the grating (i.e., the grating is not filled). In addition to measuring feature shapes by reconstruction, diffraction-based overlay can also be measured using such equipment, as described in published patent application US2006066855A1. Diffraction-based overlay measurements using dark field imaging of diffraction orders can make overlay measurements on smaller targets. Examples of dark field imaging measurements can be found in international patent applications WO 2009 / 078708 and WO 2009 / 106279, which are incorporated herein by reference in their entirety. Further developments of this technology have been described in published patent publications US20110027704A, US20110043791A, US2011102753A1, US20120044470A, US20120123581A, US20130258310A, US20130271740A and WO2013178422A1. These targets can be smaller than the irradiation spot and can be surrounded by product structures on the wafer. Multiple gratings can be measured in one image using a composite grating target. The contents of all these applications are also incorporated herein by reference.

[0007] When performing a lithography process, such as applying a pattern on a substrate or measuring such a pattern, process control methods are used to monitor and control the process. Such process control techniques are typically performed to obtain corrections for controlling the lithography process. It is desirable to improve such process control methods. Summary of the invention

[0008] In a first aspect of the present invention, a method for controlling a process for manufacturing a semiconductor device on a substrate is provided, the method comprising: obtaining process data related to the process; determining a correction of the process based on the data and a first control target associated with the device on the substrate; determining a first probability that the first control target can be achieved; and adjusting the correction based on the probability and at least a second control target, the second control target having a second probability of being achievable compared to the first control target.

[0009] In a second aspect of the invention, there is provided a lithographic apparatus configured to provide a product structure to a substrate in a lithographic process, the lithographic apparatus comprising a processor operable to optimize control of the lithographic apparatus during the lithographic process by executing the method of the first aspect.

[0010] In a third aspect of the invention there is provided a computer program comprising program instructions operable, when run on a suitable apparatus, to perform the method of the first aspect.

[0011] Other aspects, features and advantages of the present invention and the structure and operation of various embodiments of the present invention are described in detail below with reference to the accompanying drawings. It should be noted that the present invention is not limited to the specific embodiments described herein. Such embodiments are presented herein for illustrative purposes only. Based on the teachings contained herein, additional embodiments will be apparent to those skilled in the relevant art(s). BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Embodiments of the present invention will now be described by way of example with reference to the accompanying drawings, in which:

[0013] Figure 1 Depicts lithography equipment that, along with other equipment, forms a production facility for semiconductor devices;

[0014] Figure 2 including a schematic diagram of a scatterometer for measuring a target according to an embodiment of the present invention;

[0015] Figure 3 Exemplary sources of processing parameters are shown;

[0016] Figure 4 Schematically illustrates the concept of Overlapping Process Windows (OPW);

[0017] Figure 5 schematically illustrates a method of determining a correction for controlling a lithographic apparatus; and

[0018] Figure 6 is a flowchart describing a method of determining slack variables according to an embodiment of the present invention.

[0019] Figure 7 Depicted is a relationship between a yield parameter / throughput parameter and an exposure dose used in controlling a semiconductor manufacturing process according to an embodiment. DETAILED DESCRIPTION

[0020] Before describing embodiments of the present invention in greater detail, it is helpful to present an example environment in which embodiments of the present invention may be implemented.

[0021] In 200, Figure 1A lithographic apparatus LA is shown as part of an industrial production facility implementing a high-volume lithographic manufacturing process. In this example, the manufacturing process is applicable to the manufacture of semiconductor products (integrated circuits) on substrates such as semiconductor wafers. Those skilled in the art will appreciate that various products can be manufactured by processing different types of substrates in variations of the process. The production of semiconductor products is used only as an example, which is of great commercial significance today.

[0022] Within a lithographic apparatus (or simply "lithography tool" 200), a measurement station MEA is shown at 202, and an exposure station EXP is shown at 204. A control unit LACU is shown at 206. In this example, each substrate visits a measurement station and an exposure station to apply a pattern. For example, in an optical lithographic apparatus, a projection system is used to transfer a product pattern from a patterning device MA to a substrate using conditioned radiation and a projection system. This is done by forming an image of the pattern in a layer of radiation-sensitive resist material.

[0023] The term "projection system" as used herein should be broadly interpreted to cover any type of projection system, including refractive, reflective, reflective-refractive, magnetic, electromagnetic and electrostatic optical systems or any combination thereof, as appropriate for the exposure radiation used or other factors such as the use of immersion liquid or the use of vacuum. The patterned MA device can be a mask or a reticle that imparts a pattern to a radiation beam transmitted or reflected by the pattern forming device. Well-known operating modes include stepping mode and scanning mode. It is well known that the projection system can cooperate with a support and positioning system for the substrate and the pattern forming device in a variety of ways to apply the desired pattern to many target portions on the substrate. A programmable pattern forming device can be used instead of a reticle with a fixed pattern. For example, the radiation can include electromagnetic radiation in the deep ultraviolet (DUV) or extreme ultraviolet (EUV) band. The present disclosure is also applicable to other types of lithography processes, such as imprint lithography and direct write lithography, such as by electron beam.

[0024] The lithographic apparatus control unit LACU controls all movements and measurements of the various actuators and sensors to accommodate the substrate W and mask MA, and to perform patterning operations. The LACU also includes signal processing and data processing capabilities to perform the desired calculations related to the operation of the apparatus. In practice, the control unit LACU will be implemented as a system of many sub-units, each handling real-time data acquisition, processing and control of a subsystem or component within the apparatus.

[0025] Before the pattern is applied to the substrate at the exposure station EXP, the substrate is processed at the measurement station MEA so that various preparation steps can be performed. The preparation steps may include mapping the surface height of the substrate using a level sensor and measuring the position of the alignment marks on the substrate using an alignment sensor. The alignment marks are nominally arranged in a regular grid pattern. However, due to the imprecision of creating the marks and due to the deformation of the substrate during the entire process, the marks deviate from the ideal grid. Therefore, in addition to measuring the position and orientation of the substrate, if the device is to print product features at the correct position with very high accuracy, then in fact, the alignment sensor must measure the position of many marks on the substrate area in detail. The device can be a so-called dual-stage type, which has two substrate tables, each substrate table having a positioning system controlled by a control unit LACU. While one substrate on one substrate table is exposed at the exposure station EXP, another substrate can be loaded onto the other substrate table at the measurement station MEA so that various preparation steps can be performed. Therefore, the measurement of the alignment marks is very time-consuming, and providing two substrate tables can significantly increase the throughput of the device. If the position sensor IF is unable to measure the position of the substrate table when it is located at the measurement station as well as the exposure station, a second position sensor may be provided so that the position of the substrate table can be tracked at both stations. For example, the lithographic apparatus LA may be of a so-called dual-stage type having two substrate tables and two stations - an exposure station and a measurement station - between which the substrate table can be exchanged.

[0026] Within the production facility, the apparatus 200 forms part of a "lithography unit" or "lithography cluster", which also includes a coating apparatus 208 for applying photoresist and other coatings to substrates W for patterning by the apparatus 200. On the output side of the apparatus 200, a baking apparatus 210 and a developing apparatus 212 are provided for developing the exposed pattern into a physical resist pattern. Between all these apparatuses, a substrate handling system is responsible for supporting the substrates and transferring them from one apparatus to the next. These apparatuses, which are generally collectively referred to as tracks, are controlled by a track control unit, which itself is controlled by a monitoring system SCS, which also controls the lithography apparatus via the lithography apparatus control unit LACU. Thus, different apparatuses can be operated to maximize throughput and processing efficiency. The monitoring system SCS receives recipe information R, which provides a definition of the steps to be performed in more detail to create each patterned substrate.

[0027] Once the pattern is applied and developed in the lithography unit, the patterned substrate 220 is transferred to other processing equipment, such as illustrated in 222, 224, and 226. In a typical manufacturing facility, a wide range of processing steps are implemented by various devices. For example, the device 222 in this embodiment is an etching station, and the device 224 performs a post-etching annealing step. Other physical and / or chemical processing steps are applied to other devices 226, etc. Multiple types of operations may be required to manufacture a real device, such as the deposition of materials, the modification of surface material characteristics (oxidation, doping, ion implantation, etc.), chemical mechanical polishing (CMP), etc. In fact, the device 226 can represent a series of different processing steps performed in one or more devices. As another example, equipment and processing steps for implementing self-aligned multiple patterning can be provided to produce multiple smaller features based on the precursor pattern laid by the lithography equipment.

[0028] As is well known, the manufacture of semiconductor devices involves multiple repetitions of such processing to build up device structures with appropriate materials and patterns layer by layer on a substrate. Thus, the substrates 230 arriving at the lithography cluster may be newly prepared substrates, or they may be substrates that have been previously processed in the cluster or in another device entirely. Similarly, depending on the processing required, the substrates 232 leaving the device 226 may be returned for subsequent patterning operations in the same lithography cluster, they may be sent to patterning operations in a different cluster, or they may be finished products to be sent for dicing and packaging.

[0029] Each layer of the product structure requires a different set of process steps, and the type of equipment 226 used at each layer may be completely different. Further, even in the case where the processing steps to be applied by the equipment 226 are nominally the same, in a large facility, there may be several supposedly identical machines working in parallel to perform steps 226 on different substrates. Minor differences in the set-up or failures between these machines may mean that they affect different substrates in different ways. Even relatively common steps for each layer, such as etching (equipment 222), can be implemented by several etching equipment that are nominally the same but work in parallel to maximize production. Moreover, in practice, different layers require different etching processes, such as chemical etching, plasma etching, depending on the details and specific requirements of the material to be etched (such as, for example, anisotropic etching).

[0030] Previous and / or subsequent processes may be performed in other lithography equipment, and as just mentioned, even in different types of lithography equipment. For example, some layers in the device manufacturing process that have very high requirements on parameters such as resolution and overlay may be performed in more advanced lithography tools than other layers with lower requirements. Thus, some layers may be exposed in an immersion lithography tool, while others are exposed in a 'dry' tool. Some layers may be exposed in a tool operating at DUV wavelengths, while others are exposed using EUV wavelength radiation.

[0031] In order for the substrates exposed by the lithography apparatus to be correctly and consistently exposed, it is desirable to inspect the exposed substrates to measure characteristics such as overlay errors between subsequent layers, line thickness, critical dimensions (CD), etc. Therefore, the manufacturing facility in which the lithography unit LC is located also includes a measurement system that receives some or all of the substrates W that have been processed in the lithography unit. The measurement results are provided directly or indirectly to the monitoring system SCS. If an error is detected, adjustments can be made to the exposure of subsequent substrates, especially if the measurement can be completed immediately and quickly enough so that other substrates of the same batch are still to be exposed. Moreover, the already exposed substrates can be stripped and reworked to improve the yield, or discarded to avoid further processing of the substrates known to be defective. In the case where only some target portions of the substrate are defective, further exposure can be performed only on those good target portions.

[0032] exist Figure 1 Also shown is a metrology device 240, which is provided for making measurements of product parameters at desired stages in the manufacturing process. A common example of a metrology station in a modern lithography production facility is a scatterometer, such as a dark field scatterometer, an angle resolved scatterometer or a spectral scatterometer, and it can be adapted to measure the characteristics of the developed substrate in 220 prior to etching in the device 222. Using the metrology device 240, it can be determined that, for example, important performance parameters such as overlay or critical dimension (CD) do not meet the accuracy requirements specified in the developed resist. Prior to the etching step, there is an opportunity to strip the developed resist and reprocess the substrate 220 through the lithography cluster. By making small adjustments over time by the monitoring system SCS and / or the control unit LACU 206, the metrology results 242 from the device 240 can be used to maintain accurate performance of the patterning operation in the lithography cluster, thereby minimizing the risk of manufacturing products that do not meet specifications and require rework.

[0033] Additionally, the metrology equipment 240 and / or other metrology equipment (not shown) may be adapted to measure characteristics of the processed substrates 232, 234 and the incoming substrate 230. The metrology equipment may be used on the processed substrates to determine important parameters such as overlay or CD.

[0034] The measuring device applicable to the embodiment of the present invention is Figure 2 (a) shows the target T and the diffracted rays of the measurement radiation used to illuminate the target. Figure 2 (b) is illustrated in more detail. The illustrated measurement device is a type called dark field measurement device. The measurement device can be an independent device or incorporated into the lithography device LA, for example at the measurement station, or incorporated into the lithography unit LC. The optical axis with multiple branches in the whole device is represented by the dotted line O. In this device, the light emitted by the source 11 (for example, a xenon lamp) is directed to the substrate W via a beam splitter 15 by an optical system, which includes lenses 12, 14 and an objective lens 16. These lenses are arranged in a double sequence of 4F arrangements. Different lens arrangements can be used, provided that it still provides the substrate image to the detector while allowing access to the intermediate pupil plane for spatial frequency filtering. Therefore, the angle range in which the radiation is incident on the substrate can be selected by defining the spatial intensity distribution in the plane that presents the spatial spectrum of the substrate plane (here referred to as the (conjugate) pupil plane). Specifically, this can be accomplished by inserting an aperture plate 13 of appropriate form between lenses 12 and 14 in the plane of the back-projected image of the objective lens pupil plane. In the illustrated example, the aperture plate 13 has different forms, labeled 13N and 13S, allowing different illumination modes to be selected. The illumination system in this example forms an off-axis illumination mode. In a first illumination mode, the aperture plate 13N provides off-axis to a direction designated as 'North' (for illustration only). In a second illumination mode, the aperture plate 13S is used to provide similar illumination, but from the opposite direction, labeled 'South'. By using different apertures, other illumination modes are possible. The rest of the pupil plane is preferably dark, as any unnecessary light outside the desired illumination mode will interfere with the desired measurement signal.

[0035] like Figure 2 As shown in (b), the target T is placed with the substrate W in the direction of the optical axis O of the objective lens 16. The substrate W can be supported by a support (not shown). The rays of measurement radiation I that hit the target T from an angle offset from the axis O produce a zero-order ray (solid line 0) and two first-order rays (dash-dotted line +1 and double-dash-dotted line -1). It should be remembered that with an overfilled small target, these rays are only one of many parallel rays covering the substrate area including the measurement target T and other features. Since the hole in the plate 13 has a finite width (it must allow an effective amount of light to enter), the incident ray I will actually occupy a certain angle range, and the diffracted rays 0 and +1 / -1 will be slightly spread out. According to the point spread function of the small target, each order +1 and -1 will be further spread out to a certain angle range, rather than the single ideal ray shown. It should be noted that the grating pitch and illumination angle of the target can be designed or adjusted so that the first-order rays entering the objective are closely aligned with the central optical axis. Figure 2The rays illustrated in (a) and 2(b) are shown slightly off-axis purely to make them easier to distinguish in the drawings.

[0036] At least the 0th and +1st orders diffracted by the target T on the substrate W are collected by the objective lens 16 and directed back through the beam splitter 15. Figure 2 (a), the first illumination mode and the second illumination mode are illustrated by designating radially opposite apertures marked as north (N) and south (S). When the incident ray I of the measurement radiation comes from the north side of the optical axis, that is, when the first illumination mode is applied using the aperture plate 13N, the +1 diffracted ray marked as +1 (N) enters the objective lens 16. In contrast, when the second illumination mode is applied using the aperture plate 13S, the -1 diffracted ray (marked as 1 (S)) is the ray that enters the lens 16.

[0037] The second beam splitter 17 divides the diffracted beam into two measurement branches. In the first measurement branch, the optical system 18 uses the zero-order and first-order diffracted beams to form a diffraction spectrum (pupil plane image) of the target on a first sensor 19 (e.g., a CCD or CMOS sensor). Each diffraction order hits a different point on the sensor, so that image processing can compare and contrast multiple orders. The pupil plane image captured by the sensor 19 can be used for many measurement purposes, such as reconstruction used in the methods described herein. The pupil plane image can also be used to focus the metrology device and / or normalize the intensity measurement of the first-order beam.

[0038] In the second measurement branch, the optical systems 20, 22 form an image of the target T on a sensor 23 (e.g., a CCD or CMOS sensor). In the second measurement branch, an aperture stop 21 is arranged in a plane conjugate to the pupil plane. The aperture stop 21 acts to block the zero-order diffracted beam so that the target image formed on the sensor 23 is formed only by the -1 or +1 order beams. The image captured by the sensors 19 and 23 is output to a processor PU that processes the image, the function of which will depend on the specific type of measurement being performed. Note that the term 'image' is used here in a broad sense. If only one of the -1 order and the +1 order is present, such a grating line image will not be formed.

[0039] Figure 2 The particular forms of aperture plate 13 and field stop 21 shown are examples only. In another embodiment of the invention, on-axis illumination of the target is used, and an aperture stop with an off-axis hole is used to pass substantially only one first order diffracted light to the sensor. In other embodiments, first, third and higher order beams ( Figure 2 ) can be used for measurement instead of or in addition to the first-order beam.

[0040] The target T may include multiple gratings, which may have different bias overlap offsets to facilitate measuring the overlap between layers forming different parts of the composite grating. The orientation of the gratings may also be different so as to diffract incoming radiation in the X and Y directions. In one example, the target may include two X-direction gratings with bias overlap offsets of +d and -d, and a Y-direction grating with bias overlap offsets of +d and -d. Individual images of these gratings may be identified in the image captured by the sensor 23. Once the individual images of the gratings have been identified, the intensities of these individual images may be measured, for example by averaging or summing the intensity values ​​of selected pixels within the identified area. The intensities and / or other characteristics of the images may be compared to each other. These results may be combined to measure different parameters of the lithography process

[0041] Various techniques can be used to improve the accuracy with which patterns are copied onto substrates. Accurately copying patterns onto substrates is not the only concern in IC production. Another issue is yield, which typically measures how many functional devices a device manufacturer or device manufacturing process can produce on each substrate. Various methods can be employed to improve yield. One such method attempts to make the production of devices (e.g., using a lithography device such as a scanner to image a portion of a design layout onto a substrate) more tolerant of perturbations in at least one processing parameter during processing of the substrate, such as during the use of a lithography device to image a portion of the design layout onto a substrate. The concept of overlapping process windows (OPW) is a useful tool for this approach. The production of devices (e.g., ICs) can include other steps, such as substrate measurements before, after, or during imaging, loading or unloading of substrates, loading or unloading of patterning devices, positioning dies under projection optics before exposure, stepping from one die to another, and the like. Further, various patterns on the patterning device may have different process windows (i.e., the processing parameter space in which the pattern will be produced within the specification). Examples of pattern specifications related to potential system defects include checking for necking, line pullback, line thinning, CD, edge placement, overlap, anti-top loss, anti-bite edge and / or bridging. The process window of all or some (usually patterns within a specific area) of the patterns on the pattern forming device can be obtained by merging (e.g., overlapping) the process windows of each individual pattern. The process windows of these patterns are therefore called overlapping process windows. The boundaries of the OPW may contain the boundaries of the process windows of some individual patterns. In other words, these individual patterns limit the OPW. These individual patterns can be called "hot spots" or "process window limiting patterns (PWLP)", which are used interchangeably in this article. It is possible and usually economical to pay attention to hot spots when controlling the lithography process. When the hot spots are defect-free, it is likely that all patterns are defect-free. If the value of the processing parameter is outside the OPW, then when the value of the processing parameter is closer to the OPW, or if the value of the processing parameter is within the OPW, then when the value of the processing parameter is farther away from the boundary of the OPW, the imaging becomes more tolerant to disturbances.

[0042] Figure 3Exemplary sources of processing parameters 350 are shown. One source may be data 310 of the processing equipment, such as sources of the lithographic equipment, projection optics, substrate stages, etc., parameters of the track, etc. Another source may be data 320 from various substrate metrology tools, such as substrate height maps, focus maps, critical dimension uniformity (CDU) maps, etc. The data 320 may be obtained before a suitable substrate is subjected to a step (e.g., development), which may prevent rework of the substrate. Another source may be data 330 from one or more patterning device metrology tools, patterning device CDU maps, patterning device (e.g., mask) film stack parameter variations, etc. Yet another source may be data 340 from an operator of the processing equipment.

[0043] Figure 4 The concept of OPW is schematically illustrated. To illustrate the concept, an area or grid element / pixel 500 on a patterning device is assumed to have only two separate patterns 510 and 520. The area may include more patterns. The process windows of the individual patterns 510 and 520 are 511 and 512, respectively. To illustrate the concept, the processing parameters are assumed to include only focus (horizontal axis) and dose (vertical axis). However, the processing parameters may include any suitable parameters. The OPW 550 of the area may be obtained by finding the overlap between the process windows 511 and 512. The OPW 550 is Figure 4 550 may have an irregular shape. However, to easily represent the OPW and to easily determine whether a set of processing parameter values ​​is within the OPW, a "fit OPW" (e.g., ellipse 560) may be used instead. For example, the "fit OPW" may be the largest super ellipsoid that fits inside the OPW (e.g., an ellipse in the 2-dimensional processing parameter space in this example, an ellipsoid in the 3-dimensional processing parameter space, etc.). Using a "fit OPW" tends to reduce computational cost, but does not utilize the full size of the OPW.

[0044] The values ​​of the process parameters may be selected so that they are far from the boundaries of the OPW or the fitted OPW to reduce the chance that the process parameters drift outside the OPW, thereby causing defects and reducing yield. One method of selecting the values ​​of the process parameters includes, prior to actual imaging, (1) optimizing the lithographic equipment (e.g., optimizing the source and projection optics) and optimizing the design layout, (2) determining the OPW or the fitted OPW (e.g., by simulation), and (3) determining a point in the process parameter space (i.e., determining the value of the process parameter) that is as far as possible from the boundaries of the OPW or the fitted OPW (this point may be referred to as the "center" of the OPW or the fitted OPW). Figure 4In the example of , point 555 is a point in the processing parameter space that is as far away as possible from the boundary of the OPW 550, and point 565 is a point in the processing parameter space that is as far away as possible from the boundary of the fitted OPW 560. Points 555 and 565 may be referred to as nominal conditions. During or prior to imaging, if the processing parameters shift from point 555 or point 565 toward the boundary of the OPW, or even to the outside of the boundary of the OPW, it is beneficial to have the ability to realize such a shift and make appropriate corrections to bring the processing parameters back to the OPW and away from its boundary, desirably without interrupting imaging or other processing.

[0045] During or before the actual imaging, the process parameters may be perturbed, causing them to deviate from a point as far as possible from the OPW or the boundaries of the fitted OPW. For example, the focus may change due to the topography of the substrate to be exposed, drift of the substrate stage, deformation of the projection optics, etc.; the dose may change due to drift of the source intensity, dwell time, etc. The perturbation may be large enough to cause the process parameters to exceed the OPW, which may lead to defects. Various techniques can be used to identify the perturbed process parameters and correct them. For example, if the focus is perturbed, for example because a substrate area that is slightly elevated from the rest of the substrate is being exposed, the substrate stage can be moved or tilted to compensate for the perturbation.

[0046] The control of the lithography process is typically based on feedback or feedforward measurements, which are then modeled using, for example, an inter-field (cross-substrate fingerprint) or intra-field (cross-field fingerprint) model. Within the die, there may be separate functional areas, such as memory areas, logic areas, contact areas, and the like. Each different functional area or different functional area types may have a different process window, each with a different process window center. For example, different functional area types may have different heights and therefore different best focus settings. Moreover, different functional area types may have different structural complexities, and therefore different focus tolerances (focus process windows) around each best focus. However, due to limitations in the control grid resolution, each of these different functional areas will typically be formed using the same focus (or dose or position, etc.) settings.

[0047] Lithographic control is typically performed using an off-line calculation of one or more set-point corrections for one or more specific control degrees of freedom, based on, for example, measurements of previously formed structures. Set-point corrections may include corrections to specific process parameters, and may include corrections to the settings of specific degrees of freedom to compensate for any drift or error, such that the measured process parameters remain within specification (e.g., within an allowed deviation from an optimal set-point or optimum value; e.g., OPW or process window). For example, an important process parameter is focus, and focus errors may manifest as defect structures formed on the substrate. In a typical focus control loop, a focus feedback method may be used. Such an approach may include a metrology step that may measure the focus setting for a formed structure; for example, by using a diffraction-based focusing (DBF) technique, in which a target with focus-dependent asymmetry is formed, such that the focus setting may then be determined by measuring the asymmetry on the target. The measured focus setting may then be used to determine corrections to the lithographic process off-line; for example, a position correction of one or both of the reticle stage or substrate stage to correct for focus drift (defocus). This off-line position correction may then be communicated to the scanner as a set-point best focus correction for direct actuation by the scanner. The measurement results may be obtained over a plurality of batches, wherein an average (over the batches) best focus correction is applied to each substrate of one or more subsequent batches.For example, the control method is described in EP3495888, which is incorporated herein by reference.

[0048] Figure 5This approach is illustrated. It shows that product information 605 (such as product layout, irradiation pattern, product microtopography, etc.) and metrology data 610 (e.g. defocus data or overlay data measured from previously produced substrates) are fed to an offline processing device 615, which executes an optimization algorithm 620. The output of the optimization algorithm 620 includes one or more set point corrections 625, such as actuators for controlling the positioning of the reticle stage and / or substrate stage within the scanner 635. The set point corrections 625 typically include simple correction offsets that are calculated to compensate for any offset errors (e.g. defocus, dose or overlay offset errors) included in the metrology data 610. The corrections that control the positioning of the reticle stage and / or substrate stage can be, for example, control corrections in any direction, i.e., in the x, y and / or z directions, where x and y define the substrate plane and z is perpendicular to this plane. More specifically, they can include x / y direction corrections to correct overlay / alignment errors and / or z direction corrections to correct focus errors. The control algorithm 640 (e.g., a leveling algorithm) uses the substrate specific metrology data 650 to calculate control set points 645. For example, a leveling exposure trajectory (e.g., a relative movement or acceleration profile that determines the position of the substrate stage relative to the reticle stage during the lithography process) can be calculated using the leveling data (e.g., a wafer height map) and outputs a position set point 645 for the scanner actuator. For each substrate, the scanner 635 directly applies the set point correction (offset) 625 to the calculated set point 645 equally.

[0049] In other embodiments, the optimization may be performed in real time for such process parameters to determine corrections (e.g., corrected set points) on a per-substrate and / or per-layer basis, for example. Thus, rather than calculating set point corrections offline (e.g., based on offline measurements) and feeding the set point corrections forward to the scanner, an optimization sub-recipe (e.g., a suitable optimization function) may be calculated based on offline measurements, using the results of any per-substrate metrology, where the actual optimization is performed and set points are calculated within the scanner (additional set point corrections may optionally be calculated offline).

[0050] Conventional optimization strategies may include least squares minimization or other minimizations that apply an average optimization across a substrate based on differences or residuals from actual values ​​and set point values. Another strategy that may have advantages over the least squares strategy may include "die within specification" optimization. This aims to maximize the number of dies within specification, rather than the overall or average residual across the entire substrate. Therefore, the "die within specification" optimization uses a priori knowledge of the product (die layout) when optimizing process parameters. Least squares optimization typically treats each location equally, regardless of die layout. Because of this, least squares optimization may prefer a correction that "only" causes four locations to be out of specification, but each location is in a different die, rather than a correction that has seven locations out of specification but only affects two dies (e.g., one die has four defects and another die has three defects). However, since only one defect can cause a die to be defective, maximizing the number of defect-free dies (i.e., dies that meet specifications) is ultimately more important than simply minimizing the number of defects or the average residual per substrate.

[0051] One type of on-spec optimization may include a maximum absolute value (max abs) optimization for each die. This max abs optimization may minimize the maximum deviation of a performance parameter from a control target. This should produce a solution, but will not prevent the die from not meeting the specification (only attempting to minimize the number of dies that meet the specification). Therefore, other strategies may be preferred, such as constraint-constrained strategies, in which the goal (objective) is formulated in a way that includes adding constraints to the optimization problem; for example, such that one or more parameters or indicators are constrained to be within a range; that is, they are not allowed to exceed the specification. However, there are other constraints, such as physical constraints of the system, such as constraints on the field size and how much each field can change, constraints on the slit width and how much each slit can change, actuation constraints on how the stage can physically move, etc. The result of this is that for some constrained optimization problems, there is no solution at all; that is, the optimization problem is infeasible such that no solution satisfies all constraints. In these cases, the optimization solver is unable to produce a result at all, and the recipe is sent to, for example, a scanner.

[0052] To address this issue, the proposed method disclosed herein formulates control objectives and constraints as a hierarchy so that a control action (e.g., a control correction or instruction for any aspect of the lithography process) is always the best possible choice, taking into account the imposed constraints and objective hierarchy.

[0053] It is suggested to use a hierarchical control framework, where a hierarchy of control objectives provides guidance to the scanner control framework to control the process when a specific control objective cannot be met.Alternatively or additionally, a flexible control framework may be provided to take into account many control factors.

[0054] Such a method may include obtaining process data related to the process (e.g., one or more of metrology data, such as overlay data, critical dimension data, edge placement error data, alignment data, throughput data, focus data, dose data, leveling data CD data, CD uniformity data), and determining a correction for the process based on the data and a first control target associated with the device on the substrate. A first probability that the first control target can be achieved is determined, and the correction is adjusted based on the probability and at least a second control target having a second probability of being achieved compared to the first control target.

[0055] For example, if a primary control goal (such as ensuring that all critical features of all dies of an exposure field are within specification) cannot be achieved, the proposed method can determine which of multiple possible secondary control strategies should be followed. Similarly, even if the primary goal is feasible, the proposed method can also suggest which one or more secondary options should also be followed and in what order, for example to improve quality and / or throughput.

[0056] For example, and more relevant to situations where the primary objective is not feasible, the secondary objective may be in the form of a constraint that changes the primary objective, for example to move one or more imposed limits and widen the process window. Alternatively, different constraints on different parameters or metrics (e.g. from edge placement error EPE to critical dimension uniformity CDU or overlap) may be imposed in place of the original constraints; or a combination of these approaches is possible, where the process window is widened but additional restrictions are imposed. Other secondary objectives may include applying a different optimization problem, such as from maximum absolute value to least squares minimization (again, this can be combined with any of the other suggestions above, or moving from constrained compliant die where no die is allowed to exceed the specification to maximizing the number of compliant die thereby accepting one or more maximum absolute compliant die that may be lost. This may be multiple levels in the hierarchy, such as a third level (e.g. further widening the process window) or a third level with different control objectives (e.g. maximizing throughput), etc.

[0057] More relatedly, when the primary objective and / or objectives immediately above it are feasible, other secondary or non-primary objectives may include those aimed at further improvement (bringing one or more parameters closer to a set point or other optimum, such as by maximizing the distance to a process window boundary), imposing further constraints on other parameters, or, for example, maximizing production throughput.

[0058] The hierarchy may have an easier goal as a primary goal and become more difficult to achieve with successive levels; for example a primary goal of all die yield and a secondary goal of a challenging throughput constraint (such as minimum throughput). Alternatively, the order may be reversed, or the hierarchy may not be ordered by difficulty at all, but by importance or other criteria.

[0059] By way of example, a hierarchy may include at least two objectives, in a purely exemplary order from most important to less important, one or more of which may include:

[0060] 1) Keep the actuation setpoint within the actuator constraints. The scanner actuator operates on an exposure field level, where each exposure field determines a single set of corrections. An exposure field may include multiple dies or a single die (or even portions of a die, which are then "stitched" together). Corrections may be based on evaluation of an estimated fingerprint, typically on a regular grid defining "pixels" (e.g., each pixel is 1nmx1nm). Other actuator constraints may include, for example, the degrees of freedom in which the stage can move, the accelerations and forces allowed, etc.

[0061] 2) Ensure all features meet the die specifications

[0062] 3) Ensure all critical features (such as the hot spots mentioned above) are within specification of the die

[0063] 4) Maximize all features of the die that meet the specification

[0064] 5) Maximize the compliant die for all key features

[0065] 6) Optimize key features CDU

[0066] 7) Optimize all feature CDUs

[0067] 8) Maximizing the distance from the control limit (process window boundary); for example, process window optimization, which may include minimizing the maximum deviation of the performance parameter from the corresponding optimal parameter value and / or maximizing the distance of the performance parameter from the edge of the corresponding allowable variation space. More specifically, process window optimization may include maximizing the minimum distance between a) the local deviation of the performance parameter from the corresponding optimal parameter value (or other control target value) and b) the local edge of the corresponding allowable variation space in the optimization space.

[0068] 9) Maximize production

[0069] 10) Compensation for optical process control residuals

[0070] 11) Optimize MA and MSD balance; MA / MSD weight ratio includes the relative importance given to the temporal moving average (MA) error and the temporal moving standard deviation (MSD) of the errors of the lithography stage in the leveling algorithm.

[0071] Note that these are examples in a non-exhaustive list, and so is their order; the order may depend on the actual product and the desired production volume and quality balance, for example.

[0072] A number of specific examples will now be described. In this specific example, the die optimization that meets the specification may include an iterative process whereby the first estimate The residuals of the algorithm (which may include a least squares fit) are calculated, and based on this, the probability that each residual results in a defect is calculated. The maximum defect probability for each die is calculated, and the number of dies that are likely to have defects is determined. Then, in multiple iterations of restarting the calculation of the residuals, the relevant parameters are changed to minimize the number of dies that are likely to be defective. More specifically, the optimization can be based on estimating the fingerprint (or other results that depend on the parameters) The minimization of the sum of dot products with a suitable design matrix C and a correction set p to be determined, although this is exemplary. More specifically, the primary optimization can be expressed as:

[0073]

[0074] subject to certain constraints, including actuator or scanner constraints and At least one limit on (e.g., upper and lower limits UB, LB) is defined to define an allowed space, solution space, or process window within the limits of the correction set p, for example:

[0075] Constrained by: Equation (1)

[0076] In this equation, a slack variable Δ is defined to achieve the hierarchy; for example, the primary objective sets this to zero. If the constraints cause the optimization to be infeasible, then slack variables can be implemented to widen the process window. Of course, this will increase the defect risk to a higher (and possibly very high) probability.

[0077] This approach can be performed on a per-field basis, e.g., with the relaxation variable being increased uniformly for all pixels within the field (and therefore equal for all dies and features in an exposure field). Alternatively, it can be performed on a per-die basis, specifically relaxing the process window only for the die in the field that is considered least likely to produce yield in any case (e.g., effectively sacrificing that die). The die least likely to produce yield can be the die determined to have the greatest absolute violation of any bound associated with any pixel of that die. This approach can optionally use a "dead die" database. Such a database can be dynamically maintained to record all instances where a die is considered to have or is estimated to have at least one defect (e.g., using previous yield data, data from other lithography processes, and / or an estimation map / fingerprint).

[0078] In other embodiments, if the primary optimization is feasible (e.g., for Δ=0), then negative Δ can be applied at the next level to achieve secondary constraints (e.g., bring values ​​closer to the set point / further away from the process window boundary). This can be repeated for increasing orders of magnitude of negative slack variables until the problem is infeasible, and the last feasible solution is selected.

[0079] Figure 6 is a flow chart describing a first embodiment of a slack variable method in which slack variables are iteratively incremented. The process begins at step 700 and in step 710, a solution to equation (1) (e.g., for Δ=0) is determined, if possible. If a solution is found, then in decision 720, the optimization is deemed feasible and the process stops in 730, returning the solution; e.g., for forwarding to the scanner. If in decision 720, it is determined that the optimization is not feasible, then a determination is made whether to stop 740 and continue with the optimization only subject to the scanner constraints 750 (e.g., when a stopping criterion is met, such as exceeding a scanner constraint or a throughput constraint). If the stopping criterion is not met in decision 740, the slack variables are not updated 760 (e.g., in small increments), and the loop defined by steps 710, 720, 760 is repeated until a feasible optimization is found and a solution is returned.

[0080] exist Figure 6 In a refinement of the illustrated procedure, the initial step of determining (e.g., optimizing) the slack variables may be performed instead of using Figure 7 A trial and error approach to the loop shown. In this way, the primary optimization needs to be performed only once, rather than for each iteration of the loop. This approach can be performed only after the primary objective is deemed infeasible by initially performing the main optimization without slack variables, or before any testing of the primary objective. In the latter case, the slack variable optimization can return zero slack variables, indicating that the primary objective is feasible.

[0081] The initial slack variable optimization may include minimizing appropriate weights w using slack variables, subject to the same constraints as the primary optimization (and all values ​​are positive). The weights may represent the importance of one entity relative to another (e.g., an arrangement); the entity may be a die, a feature, or a pixel. For example, the weighting may weight the slack to be applied only to a specific die or dies, such as the die that were determined to be least likely to produce yield in the non-primary objectives. Thus, the optimized slack variable Δ * This can be determined in the scanner optimization by:

[0082] Constrained by: Equation (2)

[0083] The second optimization is the same as Eq. (1), but uses the slack variables defined in Eq. (2); for example:

[0084] Constrained by: Equation (3)

[0085] A more hierarchical optimization may include further partitioning the relaxation optimization into a hierarchy of feasible optimization problems, which optimize different elements of the relaxation variables (e.g., for different dies and / or pixels) in order of importance (ranking): For example, the optimization problem of equation (2) may be split into two or more levels:

[0086] Level 1 Constrained by:

[0087] Level 2 Constrained by:

[0088] Level N Constrained by:

[0089] Thus, different levels may relate to different dies, regions (groups of pixels), features and / or individual pixels. In this way, greater importance may be given to certain dies or regions (e.g., for key features or important dies or regions of dies), while other regions corresponding to lower levels in the hierarchy may be given increasingly lower importance. More specifically, slack variables for important regions may be first fixed (e.g., at a low or zero value), with other regions thereafter fixed according to the hierarchy. Other variations may include constraining the most important regions, dies, or features to have zero slack (Δ=0 for a first permutation), with slack variables in other regions determined according to the hierarchical approach described above (for one or more additional levels).

[0090] In all the above cases, the optimization may be to optimize (e.g. correct) a specific process parameter; e.g. indicate quality or speed. Such process parameters may include one or more of the following non-exhaustive list: overlay, CD, CDU, edge placement error, focus, dose, contrast MSDxyz from stage, throughput.

[0091] Within the present disclosure, any reference to allowed variation space or process window may include the described overlapping process windows and / or N-dimensional process windows (e.g., axes may include one or more of focus, dose, overlap, contrast, etc.). In an embodiment, process window tracking may be employed. This includes locally limiting one (or more) process window axes, thereby shifting the set point of another axis or axes. Process window tracking is described in WO2016202559, which is incorporated herein by reference. In all cases, the process window (or more generally, key indicators) can be determined by product information or mask design information (related to the exposed structure) and / or simulation design information to determine the process window information.

[0092] In another embodiment, a first control target is associated with a portion of a yield product unit (die on a substrate, substrate, substrate batch), and a second control target is associated with the number of product units processed per time unit. By configuring a control strategy corresponding to the mentioned control targets, an optimal number of yield product units per unit of time is achieved. The control strategy is configured to improve the creation of added value (per time unit) compared to prior art control strategies that focus on maximum yield or maximum throughput.

[0093] Typically, one or more parameters of the process of interest drive the first and second control objectives. In the case where the process of interest is a lithography process, the process parameter may be the dose applied to the substrate during exposure (of the photoresist on the substrate). There is typically a limited range of dose values ​​corresponding to a large number of yield dies on the substrate. The dimensions of the features provided to the product unit need to meet strict requirements so that the final manufactured semiconductor device has the desired electrical characteristics (e.g. resistance, capacitance). This is in the Figure 7. The solid line 805 represents the relationship between the failure rate (Y-axis) and the process parameters (dose, X-axis) of the product units. The failure rate represents the expected number of non-yielding product units scaled by the total number of manufactured product units. Therefore, the failure rate can be viewed as a measure of the probability of meeting a certain yield standard (e.g., a minimum required proportion of yielding product units). It is best to operate under process parameter states associated with low failure rates (e.g., a high probability of meeting yielding product units). The selection of one or more dose values ​​801 corresponding to an acceptable failure rate 803 corresponds to control based only on the first control objective; maximizing the number of yielding product units. In the example, the product units are dies, and the first control objective corresponds to the number of yielding dies per substrate (wafer). In this example, the failure rate represents the probability of meeting the yield control target, and the solid line 705 represents how this probability depends on the dose (process parameter).

[0094] Figure 7 The dashed line 810 in represents the relationship between the throughput criterion (the number of product units processed per time unit, Y-axis) and the process parameter (dose, X-axis). Typically, a lithographic apparatus can increase the dose provided to a substrate up to a certain amount without reducing its throughput. If the requested dose amount exceeds this amount, the lithographic apparatus may inevitably reduce its throughput to allow the substrate to be exposed for a long time to receive the requested dose. This is depicted by the drop in the dashed line 810 observed when the dose exceeds a certain threshold. The selection of one or more dose values ​​811 corresponding to a high throughput value 813 corresponds to control based only on the second control objective; maximizing the number of product units processed per unit time. In this example, the product units are dies, and the second control objective corresponds to the number of dies processed (patterned) per hour.

[0095] In the same Figure 7In this case, the solid line 815 represents the relationship between the number of good product units processed per time unit and the process parameter (dose, X-axis) based on an acceptable failure rate criterion (number of die produced per hour, Y-axis). The curve 815 is derived from both the relationship between the probability of good product units (failure rate) and the dose (curve 805) and the relationship between the production volume and the dose (curve 810). Note that for the different curves 805, 810, and 815, the Y-axis units are different; only the dose axis is common to all the curves. By depicting all three curves in one figure, a better comparison can be made between the dose values selected for each of the selected control objectives. Determining the dose value 817 corresponds to finding the maximum of the curve 815, which is associated with the maximum number of good product units (die) per time unit. This determination of the dose 817 corresponds to the control strategy based on the first control objective and the second control objective. The value of the dose 817 is essentially obtained by modifying the dose 801 based on: 1) the probability of meeting the first objective (yield) over a range of dose values (e.g., the modified dose needs to conform to an acceptable failure rate), and 2) within the (acceptable) range of dose values, the dose is modified to further correspond to achieving the second control objective (production volume). The control strategy implemented in this way is then configured to provide the maximum number of good (e.g., not exceeding an acceptable failure rate) product units per time unit.

[0096] The proposed control strategy can be described by the following steps:

[0097] 1) Determine the correction of the process based on the first control objective, e.g., determine the dose value 801 based on a yield criterion. The correction is typically based on process data that conveys the processing quality before the correction is applied, and the expected improvement in an indicator (yield) associated with the first control objective achieved by applying the correction. In the example given by Figure 7 the process data may include measured critical dimension (CD) data and dose data.

[0098] 2) Determine the probability that the first control objective can be achieved, e.g., determine the failure rate of at least a subset of the dose value 801. This can be determined by examining the product units produced at different dose levels. By counting the defective and functional product units at each dose level, the failure rate curve can be derived, such as the solid line 805.

[0099] 3) Adjust the correction by using the dose 817 that takes into account the failure rate (probability of meeting the first control objective) and the second control objective (number of process product units per time unit). The adjusted correction (modified dose 817) is based on the first control objective and the second control objective, while taking into account the allowed range of modification (e.g., not exceeding the probability of not meeting the first control objective).

[0100] Additionally, other control objectives may also be considered, such as being configured to penalize yield loss due to material loss.

[0101] In an embodiment, a method for controlling a process for manufacturing a semiconductor device is disclosed, the method comprising:

[0102] Obtain process data related to the process;

[0103] determining a correction to the process based on the process data and a first control target associated with a yield indicator related to a number of functional devices;

[0104] determining a first probability that the first control objective can be achieved; and

[0105] Based on the first probability and at least a second control target associated with a throughput indicator related to a number of devices produced per time unit, a correction is adjusted.

[0106] In an embodiment, the process data comprises yield data.

[0107] In an embodiment, the process is a photolithography process.

[0108] In an embodiment, the number of functional devices corresponds to the number of product units including only the functional devices.

[0109] In embodiments, a product unit may be one or more of: a die, a substrate (wafer), or a batch of wafers.

[0110] In an embodiment, the first probability is associated with a failure rate of a manufactured device.

[0111] In an embodiment, the correction of the process is a dose correction corresponding to one or more values ​​of the dose applied by the device to the die, substrate or substrate batch when performing the lithography process.

[0112] In an embodiment, the adjusting is further based on a third control objective associated with a cost of material loss due to accepting a non-functional product unit.

[0113] Other embodiments of the invention are disclosed in the following numbered item list:

[0114] 1. A method for controlling a process for manufacturing a semiconductor device on a substrate, the method comprising:

[0115] Obtain process data related to the process;

[0116] determining a correction for the process based on the process data and a first control objective associated with the device on the substrate;

[0117] determining a first probability that the first control objective can be achieved; and

[0118] A correction is adjusted based on the first probability and at least a second control target having a second probability of being achievable compared to the first control target.

[0119] 2. A method according to clause 1, wherein the step of determining the first probability includes: determining whether the first control target is feasible.

[0120] 3. A method according to clause 1 or 2, wherein the first control objective is subject to one or more constraints.

[0121] 4. The method of clause 3, wherein the first control objective is related to maximizing the number of dies disposed on the substrate that are estimated to be within a specification indicating that the dies are functional, the first control objective being subject to an actuation constraint associated with the corrected actuation.

[0122] 5. The method of clause 4, wherein the first control objective constrains the correction to a correction that ensures a high probability that all dies are functional.

[0123] 6. A method according to clause 4 or 5, wherein the one or more constraints include an upper limit and a lower limit of a performance parameter, wherein an allowable variation space is defined between the upper limit and the lower limit, and values ​​of the performance parameter outside the allowable variation space indicate a high probability that the defect will result in a non-functional die, and the second control objective involves changing the constraint by moving one or both of the upper limit and the lower limit.

[0124] 7. The method of clause 6, wherein moving one or both of the upper and lower limits comprises: moving one or both of the upper and lower limits away from a set point value to increase an allowable variation space, and determining whether the modified constraints can be achieved.

[0125] 8. A method according to clause 7, wherein the method comprises: repeating the steps of moving the upper and / or lower limits away from the set point value and determining whether the modified constraints can be achieved until it is determined that the modified constraints can be achieved.

[0126] 9. A method according to clause 7, comprising: an initial step of optimizing the amount by which the upper and / or lower limits are moved based on the same one or more constraints.

[0127] 10. A method according to clause 9, wherein the initial step comprises: optimizing the amount by which the upper and / or lower limits are moved according to a hierarchy, such that the amount is optimized separately for each level in the hierarchy.

[0128] 11. A method according to clause 10, wherein the hierarchy involves different parts of the field and / or substrate.

[0129] 12. A method according to clause 6, wherein if the first probability of the first control objective indicates that it is achievable, at least the second control objective comprises: moving one or both of the upper and lower limits towards the set point value to reduce the allowed variation space.

[0130] 13. A method according to any preceding clause, wherein at least a second control objective is applied only to parts of the field and / or substrate.

[0131] 14. The method of clause 13, wherein the portion of the field and / or substrate relates to one or more dies estimated to be least likely to be produced.

[0132] 15. A method according to any of clauses 1 to 12, wherein at least a second control objective is applied equally to the entire field and / or substrate.

[0133] 16. A method according to any preceding clause, wherein at least the second control objective relates to a different performance parameter than the first control objective.

[0134] 17. A method according to any preceding clause, wherein at least the second control objective involves a different optimization strategy than the first control objective.

[0135] 18. A method according to any preceding clause, wherein if the first probability of the first control objective indicates that it is achievable, at least the second control objective is adjusted and corrected to further improve the quality and / or increase the throughput of the process.

[0136] 19. A method according to any of the preceding clauses, wherein at least a second control objective includes: minimizing the maximum deviation of a performance parameter from a corresponding control target value and / or maximizing the distance between the performance parameter and the edge of the corresponding allowable variation space of the process parameter, and the second control objective involves changing the constraint by moving one or both of the upper and lower limits to increase the allowable variation space.

[0137] 20. A method according to any preceding clause, wherein at least the second control objective comprises: maximizing throughput.

[0138] 21. A method according to any preceding clause, wherein at least the second control objective comprises a plurality of control objectives implemented according to a hierarchy.

[0139] 22. A method according to any preceding clause, wherein the calibration involves control of one or more of a substrate stage, a reticle stage and a projection system of the lithographic apparatus.

[0140] 23. A method according to any preceding clause, wherein the at least one performance parameter comprises one of: focus, dose, overlay, edge placement error, critical dimension, critical dimension uniformity, and contrast shift standard deviation of errors in the substrate stage and / or the mask stage.

[0141] 24. A lithographic apparatus configured to provide a product structure to a substrate during a lithographic process, the lithographic apparatus comprising a processor operable to optimize control of the lithographic apparatus during the lithographic process by performing the method of any preceding clause.

[0142] 25. A lithographic apparatus according to clause 24, further comprising:

[0143] A substrate workbench for holding a substrate;

[0144] a reticle stage for holding a patterning device; and

[0145] A projection system is operable to project a radiation beam patterned by a patterning device onto a substrate.

[0146] 26. A computer program comprising program instructions operable, when run on suitable apparatus, to perform the method of any one of clauses 1 to 23.

[0147] 27. A non-transitory computer program carrier comprising the computer program of clause 26.

[0148] 28. The method of clause 1, wherein the first control target is associated with a yield indicator related to the number of functional devices, and the second control target is associated with a throughput indicator related to the number of devices produced per time unit.

[0149] 29. The method of clause 28, wherein the process data comprises yield data.

[0150] 30. The method of clause 28, wherein the process is a photolithographic process.

[0151] 31. The method of clause 28, wherein the number of functional devices corresponds to the number of product units that include only functional devices.

[0152] 32. The method of clause 31, wherein the product unit can be one or more of: a die, a substrate (wafer), or batches of wafers.

[0153] 33. The method of any of clauses 28 to 32, wherein the first probability is associated with a failure rate of the manufactured device.

[0154] 34. A method according to any of clauses 28 to 33, wherein the correction is a dose correction corresponding to one or more values ​​of dose applied to the die, substrate or substrate batch during execution of the process.

[0155] 35. The method of any of clauses 28 to 34, wherein the adjusting is further based on a third control target associated with material loss costs resulting from accepting non-functional product units.

[0156] The terms "radiation" and "beam" as used with respect to a lithographic apparatus encompass all types of electromagnetic radiation, including ultraviolet (UV) radiation (e.g., having a wavelength equal to or approximately 365, 355, 248, 193, 157 or 126 nm) and extreme ultraviolet (EUV) radiation (e.g., having a wavelength in the range of 5 to 20 nm), as well as particle beams such as ion beams or electron beams.

[0157] The term "lens," where the context permits, may refer to any one or combination of various types of optical components, including refractive, reflective, magnetic, electromagnetic, and electrostatic optical components.

[0158] The foregoing description of the specific embodiments will fully demonstrate the generality of the present invention, and through the application of knowledge in the field of technology, others can easily modify and / or adapt various applications of such specific embodiments without excessive experimentation and without departing from the general concept of the present invention. Therefore, based on the teachings and guidance set forth herein, such adaptations and modifications are intended to be within the meaning and scope equivalent to the disclosed embodiments. It is to be understood that, by way of example and not limitation, the wording or terminology herein is for descriptive purposes, so that the terms or wording of this specification are interpreted by those skilled in the art in view of teaching and guidance.

[0159] 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.

Claims

1. A method for controlling a process for manufacturing a semiconductor device on a substrate, the method include: obtaining process data associated with the process; determining a correction to the process based on the process data and a first control objective associated with the device on the substrate; determining a first probability that the first control objective can be achieved; and The correction is adjusted based on the first probability and at least a second control objective having a second probability of being achievable compared to the first control objective.

2. The method of claim 1, wherein the step of determining a first probability include: Determine whether the first control target is feasible. The method according to claim 1 , wherein the first control objective is subject to one or more constraints.

4. The method of claim 3, wherein the first control objective is associated with maximizing the number of dies disposed on the substrate that are estimated to be within a specification indicating that the dies are functional, and wherein the one or more constraints are associated with an actuation constraint associated with the corrected actuation. 5 . The method of claim 4 , wherein the first control objective constrains the correction to a correction that ensures a high probability that all dies are functional.

6. The method of claim 4, wherein the one or more constraints include upper and lower limits on a performance parameter, an allowable variation space being defined between the upper and lower limits, values ​​of the performance parameter outside the allowable variation space indicating a high probability of causing a non-functional die, and the second control objective involves modifying the constraint by moving one or both of the upper and lower limits.

7. The method of claim 6, wherein the moving one or both of the upper and lower limits include: One or both of the upper and lower limits are moved away from a set point value to increase the allowable variation space, and it is determined whether the modified constraint can be achieved.

8. The method according to claim 6, in, If the first probability of the first control objective indicates that it is achievable, the at least second control objective comprises: moving one or both of the upper and lower limits towards a set point value to reduce the allowed variation space.

9. The method of claim 1, wherein the at least second control objective involves a different optimization strategy than the first control objective.

10. The method according to claim 1, in, If the first probability of the first control objective indicates that it is achievable, the at least second control objective adjusts the correction to further improve the quality and / or increase the throughput of the process.

11. The method of claim 1, wherein the first control target is associated with a yield indicator related to the number of functional devices, and the second control target is associated with a throughput indicator related to the number of devices produced per time unit.

12. The method according to claim 11, wherein the first probability is associated with the failure rate of manufacturing the device, and the correction is a dose correction corresponding to one or more values of the dose applied to the die, substrate, or substrate lot during the execution of the process.

13. A non-transitory computer program carrier comprising a computer program, the computer program comprising instructions that, when executed on a computer system, control a process of manufacturing a semiconductor device on a substrate by performing the following steps: Obtain process data related to the process; Determine a correction for the process based on the process data and a first control objective associated with the device on the substrate; Determine a first probability that the first control objective can be achieved; and Adjust the correction based on the first probability and at least a second control objective, the second control objective having a second probability of being achievable compared to the first control objective.

14. The non-transitory computer program carrier according to claim 13, wherein the first control objective is associated with a yield metric related to the number of functional devices, and the second control objective is associated with a production volume metric related to the number of devices produced per unit of time.

15. The non-transitory computer program carrier according to claim 13, wherein the first probability is associated with the failure rate of manufacturing the device, and the correction is a dose correction corresponding to one or more values of the dose applied to the die, substrate, or substrate lot during the execution of the process.

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