CN114896435A

CN114896435A - Scheduling method and scheduling device for measurement machine

Info

Publication number: CN114896435A
Application number: CN202210501451.8A
Authority: CN
Inventors: 郭海玲; 汪韦刚
Original assignee: Changxin Memory Technologies Inc
Current assignee: Changxin Memory Technologies Inc
Priority date: 2022-05-10
Filing date: 2022-05-10
Publication date: 2022-08-12

Abstract

The utility model provides a dispatching method and a dispatching device of a measuring machine, which relate to the technical field of semiconductor measurement, wherein the dispatching method of the measuring machine comprises the following steps: acquiring process characteristic information of a semiconductor graph to be measured, wherein the process characteristic information at least comprises process site information of the graph to be measured and graph characteristic information of the semiconductor graph; obtaining classification information of a plurality of measuring machines, wherein the classification information is used for representing the corresponding relation between each measuring machine and the process characteristic information; and dispatching a target machine from the plurality of measuring machines to measure the semiconductor graph at least according to the process characteristic information and the classification information. By adopting the dispatching method of the measuring machine, the classification and management efficiency of the measuring machine is improved, the reasonable and scientific distribution of the measuring machine is realized, the production capacity can be quickly regulated and controlled according to the semiconductor graph to be measured, and the dynamic and fine management of the measuring machine is realized.

Description

Scheduling method and scheduling device for measurement machine

Technical Field

The present disclosure relates to the field of semiconductor measurement technologies, and in particular, to a scheduling method and a scheduling apparatus for a measurement machine.

Background

As the feature size of semiconductor integrated circuit devices is continuously reduced, the number of transistors in a DRAM (Dynamic Random Access Memory) is continuously increased, and the measurement and monitoring of critical dimensions become more and more important. Currently, in a semiconductor manufacturing process, Critical dimensions of a pattern on a wafer are measured by using a CDSEM (Critical dimensions 1n Scanning Electronic Microscope) to monitor a line width of the measured pattern to monitor process stability. Therefore, in the process of mass production of chips, the CDSEM measuring machine and the process information of the measured object are scientifically and reasonably classified and managed, and the method has important significance for improving the productivity and the efficiency.

Disclosure of Invention

The following is a summary of the subject matter described in detail in this disclosure. This summary is not intended to limit the scope of the claims.

The disclosure provides a scheduling method and a scheduling device for a measurement machine.

According to a first aspect of the embodiments of the present disclosure, a method for scheduling a metrology tool is provided, where the method for scheduling a metrology tool includes:

acquiring process characteristic information of a semiconductor pattern to be measured, wherein the process characteristic information at least comprises process site information of the pattern to be measured and pattern characteristic information of the semiconductor pattern;

obtaining classification information of a plurality of measuring machines, wherein the classification information is used for representing the corresponding relation between each measuring machine and the process characteristic information;

and dispatching a target machine from the plurality of measuring machines to measure the semiconductor graph at least according to the process characteristic information and the classification information.

Wherein, the scheduling method further comprises: classifying the plurality of measuring machines;

the classifying the plurality of metrology tools comprises:

obtaining a plurality of test patterns, wherein the test patterns at least have different process site information, each test pattern with the same process site information has different pattern feature information, each test pattern has a corresponding target critical dimension, and the target critical dimensions of each test pattern with the same process site information and the same pattern feature information are the same;

setting a plurality of measurement modes, and respectively measuring each test pattern in each measurement mode by adopting a plurality of measurement machines;

and classifying the plurality of measuring machines based on the measuring performance of each measuring machine.

Wherein, based on the measurement performance of each measurement machine, classifying the plurality of measurement machines comprises:

comparing the measured critical dimension obtained by measuring each test pattern by each measuring machine under each measuring mode with the target critical dimension, and screening each measuring machine corresponding to each test pattern and the target measuring mode adopted by each measuring machine;

the measurement machines adopting the same target measurement mode are classified into one type.

Wherein, screening out each of the measurement machines corresponding to each of the test patterns and a target measurement mode adopted by each of the measurement machines comprises:

and when the measured critical dimension is judged to be within the preset range of the target critical dimension, determining the measuring machine and the measuring mode for measuring the test pattern to obtain the measured critical dimension, and determining the measuring mode as the target measuring mode of the measuring machine.

Wherein the process site information includes: a lithography process station or a non-lithography process station.

Wherein the pattern feature information includes a line-shaped test pattern or a hole-shaped test pattern.

The plurality of measurement modes comprise a first measurement mode, a second measurement mode, a third measurement mode and a fourth measurement mode, wherein the first measurement mode is applied to the linear test pattern of the photoetching station, the second measurement mode is applied to the hole test pattern of the photoetching station, the third measurement mode is applied to the linear test pattern of the non-photoetching station, and the fourth measurement mode is applied to the hole test pattern of the non-photoetching station.

Wherein the first measurement mode has a first measurement voltage, the second measurement mode has a second measurement voltage, the third measurement mode has a third measurement voltage, and the fourth measurement mode has a fourth measurement voltage, wherein the first measurement voltage and the second measurement voltage are the same, and the third measurement voltage and the fourth measurement voltage are the same.

Wherein, at least according to the process characteristic information and the classification information, the method for measuring the semiconductor pattern by dispatching a target machine from the plurality of measuring machines comprises the following steps:

acquiring state information of each measuring machine in the plurality of measuring machines, wherein the state information comprises an occupied state and an idle state;

and searching the measuring machines which correspond to the process characteristic information and are in an idle state from the plurality of measuring machines to be used as the target machines according to the process characteristic information, the classification information and the state information.

Wherein, according to the process characteristic information, the classification information and the state information, searching a measurement machine corresponding to the process characteristic information and in an idle state from the plurality of measurement machines as the target machine comprises:

according to the process characteristic information and the classification information, searching a measuring machine corresponding to the process characteristic information from the plurality of measuring machines as a pre-distribution machine;

selecting a measuring machine in an idle state from the pre-distribution machines as a distributable machine according to the state information of each pre-distribution machine;

and selecting the target machine from the distributable machines.

The measuring machine state information further includes real-time working duration and preset working duration, and the selecting the target machine from the distributable machines includes:

and selecting the machine with the real-time working duration less than the preset working duration from the distributable machines as the target machine.

Wherein the process characteristic information further includes a number of semiconductor patterns to be measured, and the selecting the target tool from the assignable tools includes:

and selecting the machines with the real-time working duration less than the target number of the preset working duration from the distributable machines as the target machines according to the number of the semiconductor graphs to be measured.

Wherein the target number is not greater than the number of semiconductor patterns to be measured.

According to a second aspect of the embodiments of the present disclosure, there is provided a scheduling apparatus for a metrology tool, the scheduling apparatus comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire processing characteristic information of a semiconductor graph to be measured, and the processing characteristic information at least comprises process site information of the graph to be measured and graph characteristic information of the semiconductor graph;

the obtaining module is further configured to obtain classification information of a plurality of metrology tools, where the classification information is used to characterize a corresponding relationship between each metrology tool and the process characteristic information;

and the scheduling module is configured to schedule a target machine from the plurality of metrology machines to measure the semiconductor graph at least according to the process characteristic information and the classification information.

Wherein, the scheduling device of the measuring machine further comprises:

a classification module configured to classify the plurality of metrology tools.

According to the scheduling method and the scheduling device for the measuring machines, the manufacturing process characteristic information of the semiconductor graph to be measured is obtained, the classification information of the measuring machines is utilized, the target machines are rapidly and accurately distributed to measure the semiconductor graph in the measuring machines in the process of measuring the wafer, the classification and management efficiency of the measuring machines is improved, the measuring machines are reasonably and scientifically distributed, the production capacity can be rapidly regulated and controlled according to the semiconductor graph to be measured, and dynamic and fine management of the measuring machines is achieved.

Other aspects will be apparent upon reading and understanding the attached drawings and detailed description.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the embodiments of the disclosure. In the drawings, like reference numerals are used to indicate like elements. The drawings in the following description are directed to some, but not all embodiments of the disclosure. For a person skilled in the art, other figures can be derived from these figures without inventive effort.

FIG. 1 is a flow chart illustrating a method for scheduling metrology tools in accordance with an exemplary embodiment;

FIG. 2 is a flow chart illustrating a method for scheduling metrology tools in accordance with an exemplary embodiment;

FIG. 3 is a flow chart illustrating a method for scheduling metrology tools in accordance with an exemplary embodiment;

FIG. 4 is a block diagram illustrating a scheduler of a metrology tool in accordance with an exemplary embodiment;

FIG. 5 is a block diagram illustrating a scheduling apparatus of a metrology tool in accordance with an exemplary embodiment.

Detailed Description

To make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions in the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some embodiments of the present disclosure, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure. It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be arbitrarily combined with each other without conflict.

The minimum feature size is a Critical Dimension (CD) that characterizes integrated circuit fabrication techniques. In the semiconductor manufacturing process, after exposure and development, the pattern on the photomask is transferred onto a wafer, and in order to ensure the accuracy of the pattern, the wafer with the pattern is placed on a CDSEM measuring machine to confirm whether the key dimension of the pattern meets the design requirement of a large-scale integrated circuit or not, so that the photoetching accuracy is known.

Currently, in many CDSEM metrology tools, all metrology tools are turned on, and each metrology tool can measure all operating voltages and all patterns of pattern characteristics. Since the semiconductor pattern to be measured and the material of the measurement object are different, and the type of the measurement machine and the pattern suitable for measurement are different, if the semiconductor pattern to be measured is randomly allocated to each measurement machine for measurement, the measurement result may be poor. Meanwhile, if not all the measurement machines are allocated collectively, the waiting time for the wafer to be measured may be prolonged, which affects the measurement efficiency.

The scheduling method of the metrology tools provided by the embodiment of the disclosure can acquire the process characteristic information of the semiconductor pattern to be measured and the classification information of the metrology tools before the wafer is measured, and quickly and accurately allocate the target tool among the metrology tools to measure the semiconductor pattern by using the process characteristic information and the classification information of the semiconductor pattern to be measured, thereby improving the classification and management efficiency of the metrology tools, realizing reasonable and scientific allocation of the metrology tools, quickly regulating and controlling the production capacity according to the semiconductor pattern to be measured, and realizing dynamic and fine management of the metrology tools.

The present disclosure provides a method for scheduling a metrology tool, as shown in fig. 1, fig. 1 shows a flowchart of a method for scheduling a metrology tool according to an exemplary embodiment of the present disclosure, which may include the following steps:

s110, acquiring process characteristic information of the semiconductor graph to be measured, wherein the process characteristic information at least comprises process site information of the graph to be measured and graph characteristic information of the semiconductor graph;

s120, obtaining classification information of a plurality of measuring machines, wherein the classification information is used for representing the corresponding relation between each measuring machine and the process characteristic information;

and S130, dispatching a target machine from the plurality of measuring machines to measure the semiconductor graph at least according to the process characteristic information and the classification information.

An integrated circuit (integrated circuit) is a microelectronic device or component, which is fabricated on one or more small semiconductor substrates by interconnecting transistors, resistors, capacitors, inductors, and other devices and wiring required in a circuit, so that the formation of semiconductor patterns on a wafer requires many steps, each of which includes information about a plurality of process parameters. In step S110, before performing the measurement on the wafer, process characteristic information of the semiconductor pattern to be measured needs to be obtained in advance, and the part of the process characteristic information may be stored in the storage unit in advance, or may be extracted directly from each apparatus through which the wafer passes, if necessary.

In one example, process parameter information of the wafer in the upstream process may be extracted first, so as to determine the process characteristics of the semiconductor pattern to be measured according to the process parameter information, extract a part of the process parameter information as the process characteristic information of the semiconductor pattern to be measured, and extract at least process site information of the semiconductor pattern to be measured and pattern characteristic information of the semiconductor pattern in the process parameter information as the process characteristic information of the semiconductor pattern. In this embodiment, the process characteristic of the semiconductor pattern may be identified by the process site information and the pattern feature information, so as to assign a measurement machine suitable for the process characteristic to the semiconductor pattern for measurement.

When a wafer is measured, many different semiconductor patterns may need to be measured, and each semiconductor pattern may have different process characteristics, so that the measurement machine needs to operate under the optimal working condition to obtain more accurate measurement data according to the process characteristics of the different semiconductor patterns. Therefore, aiming at the process characteristics of the semiconductor pattern, a measuring machine matched with the process characteristics is selected for measurement, and the method has important significance for improving and maintaining the product stability and expanding the production. In step S120, in order to quickly and accurately match a suitable measurement machine according to the process characteristics of the semiconductor pattern to be measured, classification information of a plurality of measurement machines may be obtained before or during the measurement of the semiconductor pattern, the classification information representing a corresponding relationship between each measurement machine and the process characteristic information of each semiconductor pattern, and then the measurement machine suitable for measuring the semiconductor pattern is searched according to the corresponding relationship. Wherein the classification information may be pre-stored in the apparatus for implementing the scheduling method.

In step S130, according to the characteristic information parameter of the semiconductor pattern to be measured obtained in step S110 and the classification information of the plurality of measurement machines obtained in step S120, the correlation between the process characteristic information of the semiconductor pattern and the measurement machines is utilized to directly determine a measurement machine suitable for measuring the semiconductor pattern from the plurality of measurement machines as a target machine, and the suitable target machine is used to measure the semiconductor pattern to be measured, thereby improving the measurement accuracy and the measurement efficiency. The number of the measuring machines suitable for measuring the semiconductor pattern may be one or more.

The scheduling method of the measurement machine provided by the embodiment of the disclosure, especially for the measurement task of the batch of wafers, may respectively obtain the process characteristic information of the semiconductor pattern and the corresponding relationship between the process characteristic information of the semiconductor pattern and the measurement machine before or during the measurement of the semiconductor pattern, so as to search one or more measurement machines most suitable for the current semiconductor pattern as a target machine among the plurality of measurement machines according to the process characteristic information of the semiconductor pattern and the corresponding relationship, thereby measuring the semiconductor pattern using the target machine, and improving the matching degree between the semiconductor pattern to be measured and the measurement machine. According to the technical scheme, the semiconductor graph is measured by selecting the measuring machine most suitable for measuring the semiconductor graph directly according to the characteristics of the manufacturing process of the semiconductor graph, the corresponding measuring machine is rapidly and accurately distributed for measurement, the measurement efficiency is improved, the maintenance time and cost of the measuring machine can be reduced, and the stability of the measuring machine is improved.

According to an exemplary embodiment, in the measurement of a lot of wafers, a lot of metrology tools may be required to perform the measurement. In order to scientifically and reasonably distribute the metrology tools according to the process characteristics of the semiconductor pattern of the wafer, all CDSEM metrology tools may be classified before the semiconductor pattern is measured, so as to obtain the classification information of the metrology tools. For example, the measurement machines with similar performance may be classified into one type, or the measurement machines with similar equipment information may be classified into one type, and the process characteristic information of the semiconductor pattern may be directly utilized to classify the measurement machines to obtain the classification information of the plurality of measurement machines, so as to utilize the classification information of the measurement machines to dynamically refine the production capacity of the measurement machines.

FIG. 2 is a flowchart illustrating a method for scheduling metrology tools according to yet another exemplary embodiment. Referring to fig. 2, the method provided in this embodiment adds a step of classifying a plurality of metrology tools based on the method shown in fig. 1, and mainly describes an optional implementation manner of classifying a plurality of metrology tools. As shown in fig. 2, in the present embodiment, the classifying the plurality of metrology tools may include the following steps:

s210, obtaining a plurality of test patterns, wherein the test patterns at least have different process site information, each test pattern with the same process site information has different pattern characteristic information, each test pattern has a corresponding target critical dimension, and the target critical dimensions of each test pattern with the same process site information and the same pattern characteristic information are the same.

In the process of classifying the measuring machines, the measuring conditions and the material of the semiconductor patterns need to be considered, and since there are many semiconductor patterns on the wafer, in order to achieve scientific and reasonable distribution of the measuring machines according to the process characteristics of the semiconductor patterns, for example, some different semiconductor patterns with representative process characteristics can be selected as test patterns, a plurality of different semiconductor patterns can be selected as test patterns, and the process characteristic information of the semiconductor patterns is collected as the classification basis of the measuring machines to classify the types of the measuring machines.

In order to collect the semiconductor patterns and the process characteristic information thereof, at least the semiconductor patterns respectively from a plurality of different process stations can be obtained as test patterns, that is, the corresponding semiconductor patterns are selected from each process station as the test patterns, and the different process stations include, for example, a lithography station and a non-lithography station, wherein the non-lithography station can include process stations such as an etching station, a chemical mechanical mask station, and a thin film deposition station. Here, a plurality of semiconductor patterns may be selected as test patterns in the same process site, and the test patterns from the same process site may have different pattern characteristics. Then, the test patterns with the same process site information and the same pattern feature information are divided into a group to divide all the test patterns into a plurality of types, and the target critical dimension of each test pattern in the same type is the same.

In some exemplary embodiments, the process characteristic information may be process site information selected according to the material of the test pattern, for example, test patterns from a lithography process site and a non-lithography process site are selected, and pattern characteristic information having a line shape or a hole shape is selected according to a pattern etched by a lithography process or a non-lithography process. All test patterns may then be typed according to a combination of process site information and pattern features. The test patterns can be divided into linear test patterns of a photoetching station, hole-shaped test patterns of a photoetching station, linear test patterns of a non-photoetching station and hole-shaped test patterns of a non-photoetching station. It should be noted that the test patterns from the same process site information and having the same pattern feature information are the same type of test pattern, and are composed of a plurality of semiconductor patterns having the same process characteristics.

S220, setting a plurality of measurement modes, and measuring each test pattern by adopting a plurality of measurement machines under each measurement mode.

In the process of classifying the measurement machines, the test patterns used are various, that is, the test patterns are respectively from different process station information and have different pattern characteristic information. The measurement conditions of each measurement machine for different test patterns are different, and the measurement effect of each measurement machine on different test patterns may be different under different measurement conditions. For example, some measuring machines have higher measuring accuracy when measuring the hole-shaped pattern, and some measuring machines have higher measuring accuracy when measuring the linear pattern. Therefore, a measurement mode is set for each measurement machine based on the measurement condition of each measurement machine, and a plurality of measurement modes can be set for each measurement machine in the test stage. In an exemplary embodiment, the measurement modes may be set to a first measurement mode, a second measurement mode, a third measurement mode and a fourth measurement mode, respectively, for example, each of the measurement machines is used to perform measurement on each of the test patterns respectively in the first measurement mode, the second measurement mode, the third measurement mode and the fourth measurement mode.

In this step, in order to classify the measurement machines more carefully and accurately so that the measurement precision of each measurement machine involved in the measurement task on the measured graph is optimal, in the test stage, each measurement machine needs to measure each test graph in each measurement mode, so as to obtain the measurement data of each measurement machine in each measurement mode, and to more comprehensively grasp the performance of each measurement machine in each measurement mode.

S230, comparing the measured critical dimension obtained by each measurement machine measuring each test pattern in each measurement mode with the target critical dimension.

After each measuring machine respectively operates in each measuring mode to measure each test pattern, each measuring machine obtains the measurement critical dimension of the test pattern measured in each measuring mode. The measurement critical dimension may be an average value of a plurality of measurement values measured by the measurement machine for the same type of test pattern in a certain measurement mode. The measuring performance of the measuring test pattern of the measuring machine under each measuring mode can be evaluated by utilizing the proximity degree of the measuring critical dimension and the target critical dimension of the type of test pattern, and a plurality of measuring machines are classified based on the measuring performance of each measuring machine.

S240, when the measured critical dimension is within the preset range of the target critical dimension, determining the measurement test pattern to obtain a measurement machine and a measurement mode of the measured critical dimension, and determining the measurement mode as the target measurement mode of the measurement machine.

It is understood that the closer the metrology critical dimension is to the target critical dimension, the better the performance of the type of test pattern that the metrology tool operates in the metrology mode, i.e., the best the metrology state of the metrology tool in the metrology mode for the measured test pattern. In one exemplary embodiment, the proximity between the measured cd and the target cd may be determined based on whether the measured cd is within a predetermined range of the target cd, which may be 95% to 105% of the target cd. When the measured critical dimension is determined to be within the preset range of the target critical dimension, the measuring machine is suitable for operating in the measuring mode to measure the type of test pattern.

For example, taking the evaluation of the measurement performance of the machine 1 as an example, the test patterns to be tested are all hole-shaped test patterns from the photolithography station, and assuming that the target size of the test pattern of the type is a, the machine 1 respectively operates in a first measurement mode, a second measurement mode, a third measurement mode and a fourth measurement mode to measure the test patterns of the type one by one. The measured critical dimension obtained after the machine 1 performs the measurement in the first measurement mode is a1, the measured critical dimension obtained after the machine 1 performs the measurement in the second measurement mode is a2, the measured critical dimension obtained after the machine 1 performs the measurement in the third measurement mode is A3, and the measured critical dimension obtained after the machine 1 performs the measurement in the fourth measurement mode is a 4. A1, a2, A3, and a4 can be compared to a, respectively. For example, it may be sequentially determined whether a1, a2, A3, and a4 are within a range from a × 95% to a × 105%, and when a2 is within a range from a × 95% to a × 105%, a2 is measured when the tool 1 is operating in the second measurement mode, which means that the tool 1 is suitable for operating in the second measurement mode, that is, the tool 1 performs the best measurement on the hole test patterns from the photolithography station in the second measurement mode, and the second measurement mode is determined as the best measurement mode of the tool 1, that is, the target measurement mode. The optimal measurement mode of each measurement machine can be determined according to the above method, and a target measurement mode is determined for each measurement machine.

In the process of determining the target measurement mode for each measurement machine, the type of the test pattern suitable for measurement in each measurement mode can be determined, so that the measurement mode can be set according to the process site information and the pattern feature information of the test pattern suitable for the type. For example, a first measurement mode is set for measuring the linear test pattern of the lithography station, a second measurement mode is set for measuring the hole test pattern of the lithography station, a third measurement mode is set for measuring the linear test pattern of the non-lithography station, and a fourth measurement mode is set for measuring the hole test pattern of the non-lithography station.

In addition, the measurement tool may operate at different voltages in each measurement mode, and in one example, the measurement tool may operate at a first measurement voltage in the first measurement mode, a second measurement voltage in the second measurement mode, a third measurement voltage in the third measurement mode, and a fourth measurement voltage in the fourth measurement mode. Since the first and second measurement mode settings are applied to the pattern measurement from the lithography station, the operating voltages of the first and second measurement modes may be the same, i.e., the first and second measurement voltages are the same. Similarly, since the third measurement mode and the fourth measurement mode are both configured for pattern measurement from non-lithography stations, the operating voltages of the third measurement mode and the fourth measurement mode may be the same, i.e. the third measurement voltage and the fourth measurement voltage are the same

In one example, the metrology mode may be simply flagged with operating voltage and graphical characteristic information. For example, LINE may be used for LINE-shaped pattern feature information, HOLE may be used for HOLE-shaped pattern feature information, and the first measurement voltage and the second measurement voltage may be 500V, for example. The third measurement voltage and the fourth measurement voltage may be 800V, for example, as shown in table 1 below, which exemplarily shows the labeling situation for different measurement modes, and for the first measurement mode of the linear test pattern applied to the lithography station, the pattern characteristic information of the measured test pattern is LINE and the measurement mode operates at a voltage of 500V, then, the first measurement mode may be simply labeled as 500V/LINE mode; for the second measurement mode, the measured graphic characteristic information of the test pattern is HOLE and works at 500V voltage, and the second measurement mode can be simply marked as 500V/HOLE mode; similarly, the third measurement mode may be labeled as 800V/LINE mode and the fourth measurement mode may be labeled as 800V/HOLE mode.

As shown in the following Table 1, 6 metrology machines are exemplarily shown, namely, the machine 1, the machine 2, the machine 3, the machine 4, the machine 5 and the machine 6, each of which is respectively provided with four metrology modes, namely, a first metrology mode (500V/LINE mode), a second metrology mode (500V/HOLE mode), a third metrology mode (800V/LINE mode) and a fourth metrology mode (800V/HOLE mode), the measurement can be performed by using 6 measurement machines respectively operating in the modes of 500V/LINE, 500V/HOLE, 800V/LINE and 800V/HOLE, so that each measurement machine can obtain the measured critical dimension of the measured test pattern under each measurement mode, and comparing the measured critical dimension with a target critical dimension corresponding to the measured test pattern to evaluate the measurement performance of the 6 measurement machines.

As shown in table 1 below, the measurement performance of each measurement machine in different measurement modes is also recorded in the table. The measurement performance is respectively divided into good measurement mode and poor measurement mode, for example, the machine 1 performs measurement in the 500V/LINE mode as poor measurement mode, performs measurement in the 500V/HOLE mode as poor measurement mode, performs measurement in the 800V/LINE mode as poor measurement mode, and performs measurement in the 800V/HOLE mode as good measurement mode, which means that the machine 1 performs measurement in the 800V/HOLE mode most suitably, i.e. 800V/HOLE is the target measurement mode of the machine 1, and it can be understood that the target measurement mode of the machine 2 is 500V/HOLE, the target measurement mode of the machine 3 is 800V/LINE, the target measurement mode of the machine 4 is 800V/LINE, the target measurement mode of the machine 5 is 500V/LINE, and the target measurement mode of the machine 6 is 500V/LINE.

And S250, classifying the measuring machines adopting the same target measuring mode into one type.

After the target measurement mode of each measurement machine is determined in step S240, the measurement machines that perform well with the machine 1 in the same measurement mode can be screened out and classified into a group. As shown in table 1, only the target measurement mode of the tool 1 is 800V/HOLE, i.e. only the tool 1 is in the category 1 with the target measurement mode of 800V/HOLE. The machine 3 and the machine 4 have good measurement performance in the 800V/LINE mode, that is, the category 3 with the target measurement mode of 800V/LINE includes the machine 3 and the machine 4, and the category 4 with the target measurement mode of 500V/LINE includes the machine 5 and the machine 6. According to the mode, the measuring machines adopting the same target measuring mode are classified into one class, and the target measuring mode and the measuring machines can be associated, so that the classification of a plurality of measuring machines is completed.

TABLE 1 measurement performance record chart of each measurement machine

As shown in table 1, there may be a plurality of metrology tools using the same target metrology mode. For example, in the 800V/LINE mode, the measurement performance results of the machines 3 and 4 are good, so that the target measurement mode can be determined according to the process site information and the graphic feature information of the semiconductor graphic to be measured, and a plurality of measurement machines can be allocated to perform measurement according to the target measurement mode, thereby improving the measurement efficiency.

In one example, as shown in table 1, if the machine 1 performs well in the 800V/HOLE mode, the machine 1 may perform a correlation detection on the HOLE test pattern from the non-lithography station when the measurement task is subsequently allocated to the measurement machine. The machine 3 and the machine 4 perform good measurement in the 800V/LINE mode, and then the machine 3 and the machine 4 can be called simultaneously to perform related detection on the linear test pattern from the non-lithography station when the measurement task is subsequently allocated to the measurement machine. The machine 2 has good measurement performance in the 500V/LINE mode, and then the machine 2 can be called to perform relevant detection on the linear test pattern of the incoming lithography station when the measurement task is subsequently allocated to the measurement machine, so that scientific and reasonable allocation of the measurement machine can be realized according to the type of the semiconductor pattern and the performance of the measurement machine.

In some embodiments, the classification of the metrology tools is divided according to the measurement performance of each metrology tool for different types of test patterns, so that, in order to quickly and accurately match a semiconductor pattern to be measured to a suitable metrology tool, the metrology programs of the metrology tools may be named directly according to the process site information and the pattern feature information in the test pattern, so as to control the measurement mode of the metrology tools by calling the metrology programs.

In one example, the process site information and the pattern feature information representing the type of the test pattern may be directly extracted as the name of the measurement program, for example, for the test pattern of Product B _ BLCEH _ SL1, the measurement program of the measurement tool may be named directly by using Product B _ BLCEH _ SL1_800 CH. Product B represents a Product name, BLC in BLCEH represents a semiconductor pattern to be measured, EH represents a process site where the semiconductor pattern to be measured is located, namely, an etching site, namely, a non-lithography site, SL1 represents a process name, 800 represents a working voltage of 800V, and ch (contact hole) represents hole-shaped pattern feature information. In the process of measuring the semiconductor pattern and distributing the measurement machines, when the semiconductor pattern to be measured is determined to be Product B _ BLCEH _ SL1, the measurement machine with the measurement program of Product B _ BLCEH _ SL1_800CH can be directly searched, that is, the measurement machine with the measurement mode of measuring the HOLE shape of the non-lithography station as the target measurement mode (that is, 800V/HOLE mode) is selected to perform measurement on the semiconductor pattern, so that the semiconductor pattern to be measured can be reasonably, quickly and accurately distributed to the measurement machines.

According to an exemplary embodiment, as shown in fig. 3, the method for scheduling a metrology tool provided in this embodiment may include the following steps:

s310, obtaining process characteristic information of the semiconductor pattern to be measured, wherein the process characteristic information at least comprises process information and pattern information of the semiconductor pattern.

S320, obtaining the classification information of the plurality of measuring machines, wherein the classification information is used for representing the corresponding relation between each measuring machine and the process characteristic information.

Steps S310 to S320 of this embodiment are the same as steps S110 to S120 of the above embodiments, and are not described herein again.

S330, acquiring the state information of each measuring machine in the plurality of measuring machines, wherein the state information comprises an occupied state and an idle state.

In step S330, when a plurality of suitable metrology tools are found, each metrology tool suitable for measuring the semiconductor pattern may be determined by obtaining status information of each metrology tool to determine whether each found metrology tool can perform a measurement task. In one embodiment, the state information includes, but is not limited to, one or more of an occupied state, an idle state, an abnormal state, a normal state, and a maintenance state.

S340, according to the process characteristic information and the classification information, searching a measuring machine corresponding to the process characteristic information from a plurality of measuring machines as a pre-distribution machine.

In a measurement task for a lot of wafers, a lot of measurement machines are required to perform measurements on different types of semiconductor patterns. The process characteristic information of the semiconductor pattern to be measured, that is, the process site information and the pattern characteristic information of the semiconductor pattern to be measured, may be determined by obtaining the process parameter information of the upstream process, after the classification information of the plurality of measurement machines is obtained in step S320, the target measurement mode of each measurement machine and the corresponding measurement machine in the same target measurement mode may be determined, the measurement mode is determined for the semiconductor pattern to be measured according to the process site information and the pattern characteristic information of the semiconductor pattern to be measured, and the measurement machine with the measurement mode as the target measurement mode is invoked according to the measurement mode to perform measurement. For example, when the process site information of the semiconductor pattern to be measured is the lithography site and the pattern feature information is the line pattern, it is necessary to search for a measurement mode suitable for measuring the lithography site and the line pattern, so that it is possible to search for a measurement machine that uses the measurement mode as the optimal measurement mode to perform measurement on the semiconductor pattern to be measured. The number of the measurement machines using the same measurement mode as the target measurement mode may be one or more. When a plurality of measuring machines adopting the same target measuring mode exist, the plurality of measuring machines are used as pre-distribution machines. In this step, the type of the semiconductor pattern may be determined according to the process characteristic information of the semiconductor pattern, a measurement mode suitable for measuring the type of the semiconductor pattern may be determined according to the type of the semiconductor pattern, and a measurement machine using the measurement mode as a target measurement mode may be searched according to the measurement mode, so as to implement pre-allocation of the measurement machine among a plurality of measurement machines.

And S350, selecting the measurement machine in an idle state from the pre-distributed machines as a distributable machine according to the state information of each pre-distributed machine.

In the process of selecting the assignable machines from the plurality of measuring machines, in order to select the measuring machines which can be assigned at any time from the pre-assigned machines to measure the semiconductor graph, the state information of each pre-assigned machine is judged, the measuring machines in an idle state from the plurality of pre-assigned machines can be selected as the assignable machines, and the measurement pre-assigned machines in the idle state are selected as the assignable machines.

In the process of selecting the assignable machines from the assignable machines, the type of the semiconductor pattern can be determined according to the process characteristic information of the semiconductor pattern, the measurement mode suitable for measuring the type of the semiconductor can be determined according to the type of the semiconductor, and the measurement machine taking the measurement mode as the target measurement mode can be searched according to the measurement mode, so that the measurement machine taking the target measurement mode suitable for measuring the type of the semiconductor pattern as the pre-assignable machine is preferentially searched and adopted from the assignable machines, and the pre-allocation of the measurement machine is realized. In order to select the measurement machines capable of being distributed at any time from the pre-distribution machines to measure the semiconductor graph, judge the state information of each pre-distribution machine, and select the measurement machines in an idle state as the distributable machines, thereby realizing the accurate scheduling of the measurement machines and preventing the distributed measurement machines from being incapable of executing the measurement task.

And S360, selecting a target machine from the allocable machines.

By selecting the target machine from the distributable machines and utilizing the target machine to measure the semiconductor pattern to be measured, the unnecessary measuring machines in the distributable machines can be controlled to be closed according to the actual production condition so as to save energy.

In an exemplary embodiment, when the distributable machine is selected from the pre-distributed machines, the real-time working duration and the preset working duration of each pre-distributed machine can be considered, the real-time working duration and the preset working duration of each pre-distributed machine are preferentially judged, and the machine with the real-time working duration smaller than the preset working duration is selected from the distributable machines as a target machine, so that the accurate scheduling of the measuring machines is realized. The real-time working time can be the actual working time of the measuring machine after the measuring machine leaves the factory and is put into use, and the preset working time can be the maintenance time set when the measuring machine leaves the factory, so that the measuring machine with the actual working time within the maintenance time range can be selected for measurement, and the error rate of the measuring machine is reduced.

In an exemplary embodiment, the process characteristic information of the semiconductor pattern further includes completing the number of the semiconductor patterns to be measured, in the process of selecting a target machine from the allocable machines, after selecting a measuring machine with a real-time working duration smaller than a preset working duration from the allocable machines, in order to achieve reasonable and scientific allocation of the measuring machines, according to the number of the semiconductor patterns to be measured, in the allocable machines, the measuring machines with the number same as the number of the types of the semiconductor patterns can be selected as the target machines according to the types of the semiconductor patterns, and the target machines are used for measuring the semiconductor patterns of the corresponding types by adopting corresponding target measuring modes, so that the measuring machines can be dynamically and finely managed according to the number of the types of the semiconductor patterns. Wherein the target number is not greater than the number of semiconductor patterns to be measured.

In this embodiment, when the number of semiconductor patterns to be measured is large, all the measurement tools in the idle state can be put into the measurement task in the assignable tools, so as to improve the measurement efficiency and the throughput. When the number of the semiconductor patterns to be measured is gradually reduced and more measuring machines are not needed to perform measurement, the unnecessary measuring machines can be controlled to be closed according to the actual production condition so as to control the measuring machines with corresponding number to measure the semiconductor patterns, the method has the advantage of high predictability, dynamic and fine management of the measuring machines is realized, and the waiting time of wafers between stations is reduced.

In an exemplary embodiment of the present disclosure, a scheduling apparatus for a metrology tool is provided for executing a scheduling method for the metrology tool, as shown in fig. 4, the apparatus at least includes an obtaining module 401 and a scheduling module 402.

An obtaining module 401 configured to obtain process characteristic information of a semiconductor pattern to be measured, where the process characteristic information at least includes process site information of the semiconductor pattern to be measured and pattern characteristic information of the semiconductor pattern;

the obtaining module 401 is further configured to obtain classification information of the plurality of metrology tools, where the classification information is used to represent a corresponding relationship between each metrology tool and the process characteristic information;

a scheduling module 402 configured to schedule a target tool from the plurality of metrology tools to perform metrology on the semiconductor pattern based at least on the process characteristic information and the classification information.

In some embodiments, the apparatus for scheduling metrology tools comprises:

a classification module 400 configured to classify a plurality of metrology tools.

The scheduling device for the metrology tools provided by the embodiment of the disclosure is configured to acquire process characteristic information of a semiconductor pattern to be measured, and utilize classification information of the metrology tools to quickly and accurately distribute a target tool among a plurality of metrology tools to measure the semiconductor pattern during a process of measuring a wafer, so that classification and management efficiency of the metrology tools is improved, reasonable and scientific distribution of the metrology tools is realized, production capacity can be quickly regulated according to the semiconductor pattern to be measured, and dynamic and fine management of the metrology tools is realized.

Fig. 5 is a block diagram of a scheduling apparatus, i.e., a computer apparatus 500, for a metrology tool for a scheduling method of a metrology tool according to an example embodiment. For example, the computer device 500 may be provided as a terminal device. Referring to fig. 5, the computer device 500 includes a processor 501, and the number of the processors may be set to one or more as necessary. The computer device 500 further comprises a memory 502 for storing instructions, such as an application program, executable by the processor 501. The number of the memories can be set to one or more according to needs. Which may store one or more application programs. The processor 501 is configured to execute instructions to perform the above-described method.

As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, apparatus (device), or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media having computer-usable program code embodied in the medium. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, including, but not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computer, and the like. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.

In an exemplary embodiment, a non-transitory computer readable storage medium is provided that includes instructions, such as memory 502, that are executable by processor 501 of apparatus 500 to perform the above-described method. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

A non-transitory computer readable storage medium, wherein instructions, when executed by a processor of a scheduling apparatus of a metrology tool, cause the scheduling apparatus of the metrology tool to perform:

acquiring process characteristic information of a semiconductor graph to be measured, wherein the process characteristic information at least comprises process site information of the graph to be measured and graph characteristic information of the semiconductor graph; obtaining classification information of a plurality of measuring machines, wherein the classification information is used for representing the corresponding relation between each measuring machine and the process characteristic information; and dispatching a target machine from the plurality of measuring machines to measure the semiconductor graph at least according to the process characteristic information and the classification information.

The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices) and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In the present disclosure, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that an article or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such article or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of additional like elements in the article or device comprising the element.

While preferred embodiments of the present disclosure have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the disclosure.

It will be apparent to those skilled in the art that various changes and modifications may be made to the present disclosure without departing from the spirit and scope of the disclosure. Thus, it is intended that the present disclosure also cover the modifications and variations of this disclosure provided they come within the scope of the appended claims and their equivalents.

Claims

1. A method for scheduling metrology tools, the method comprising:

2. The method of claim 1, further comprising: classifying the plurality of measuring machines;

the classifying the plurality of metrology tools comprises:

obtaining a plurality of test patterns, wherein the test patterns at least have different process site information, the test patterns with the same process site information have different pattern feature information, each test pattern has a corresponding target critical dimension, and the target critical dimensions of the test patterns with the same process site information and the same pattern feature information are the same;

3. The method of claim 2, wherein classifying the metrology tools based on the metrology performance of each metrology tool comprises:

4. The method as claimed in claim 3, wherein the screening of each metrology tool corresponding to each test pattern and the target metrology mode adopted by each metrology tool comprises:

5. The method of claim 2, wherein the process site information comprises: a lithography process station or a non-lithography process station.

6. The method of claim 5, wherein the pattern feature information comprises a line test pattern or a hole test pattern.

7. The method as claimed in claim 6, wherein the plurality of metrology modes includes a first metrology mode, a second metrology mode, a third metrology mode and a fourth metrology mode, wherein the first metrology mode is applied to the line test pattern of the lithography station, the second metrology mode is applied to the hole test pattern of the lithography station, the third metrology mode is applied to the line test pattern of the non-lithography station, and the fourth metrology mode is applied to the hole test pattern of the non-lithography station.

8. The method of claim 7, wherein the first measurement mode has a first measurement voltage, the second measurement mode has a second measurement voltage, the third measurement mode has a third measurement voltage, and the fourth measurement mode has a fourth measurement voltage, wherein the first measurement voltage and the second measurement voltage are the same, and the third measurement voltage and the fourth measurement voltage are the same.

9. The method as claimed in claim 2, wherein the step of scheduling a target metrology tool from the plurality of metrology tools to measure the semiconductor pattern based on at least the process characteristic information and the classification information comprises:

10. The method as claimed in claim 9, wherein searching the metrology tools corresponding to the process characteristic information and in an idle state from the plurality of metrology tools as the target tool according to the process characteristic information, the classification information and the status information comprises:

and selecting the target machine from the distributable machines.

11. The method of claim 10, wherein the status information of the metrology tools further comprises a real-time operating duration and a preset operating duration, and selecting the target tool from the allocable tools comprises:

12. The method of claim 11, wherein the process recipe information further includes a number of completed semiconductor patterns to be measured, and selecting the target tool from the assignable tools comprises:

13. The method of claim 12, wherein the target number is not greater than the number of semiconductor patterns to be measured.

14. The utility model provides a scheduling device of measurement board which characterized in that, scheduling device of measurement board includes:

15. The apparatus of claim 14, further comprising: