Automatic scheduling method for photomask defect inspection

Abstract

The present application provides a kind of automatic scheduling method of photomask defect inspection, obtains the photomask information of each site;Define future N site without photomask to be detected as the lowest inspection level I, future N site has photomask to be detected as priority inspection group;According to the photomask risk level of each inspection machine, the cumulative overstock volume after the last inspection is set to define value, define the site that meets the definition value in priority inspection group as the highest detection level A;For each site in priority inspection group that does not meet the definition value, obtain the time when the photomask in each site is not inspected and the photomask inspection cycle control line, obtain the time difference from the required inspection date according to the difference between the two;According to the size of time difference, the detection level from high to low is divided;According to the detection level from high to low, the photomask in the site is sequentially inspected. The present application automatically arranges the photomask to be detected every day, greatly improves the efficiency, and accurately controls the photomask defect inspection.

Description

Technical Field

[0001] This invention relates to the field of semiconductor technology, and in particular to an automated scheduling method for inspecting photomask defects. Background Technology

[0002] Photolithography is a core technology in the semiconductor manufacturing industry, and photomasks are the molds used in photolithography. Defect inspection of photomasks is an important means of measuring their quality, which requires regular defect inspections according to established rules to ensure their quality and maintain production safety. Traditionally, defect inspection scheduling in the industry relies on manual scheduling, calculating the risk level of the photomask based on factors such as the type of photolithography machine used (different inspection cycles), cumulative exposure times, and product input volume, and scheduling photomask inspections daily. This method is not only inefficient, but also lacks precise control over the inspection cycle, leading to risks such as missed inspections and product delays. It also cannot adjust the inspection level based on real-time wafer input. With a daily demand of nearly 70 photomasks, manual or semi-automatic scheduling cannot meet the needs of flexible wafer input and fast-paced work.

[0003] To address the aforementioned issues, a novel automated scheduling method for photomask defect inspection needs to be proposed. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide an automatic scheduling method for photomask defect inspection, which solves the problem of the existing technology that uses manual scheduling, which calculates the photomask risk level based on the photolithography machine model used for the photomask (different inspection cycles), the cumulative number of exposures, the product delivery quantity, etc., and schedules photomask inspections daily. This method is not only inefficient, but also lacks precise control over the photomask inspection cycle, resulting in risks such as missed inspections and blocked deliveries. It also cannot adjust the inspection level according to real-time wafer delivery, and cannot meet the needs of flexible wafer delivery and fast-paced work.

[0005] To achieve the above and other related objectives, the present invention provides an automatic scheduling method for photomask defect inspection, comprising:

[0006] Step 1: Obtain photomask information for each site;

[0007] Step 2: Define the photomasks that have no inspection in the future N sites as the lowest inspection level I, and the photomasks that have inspection in the future N sites as the priority inspection group, where N is a positive integer;

[0008] Step 3: Based on the photomask risk level of each inspection machine and the cumulative throughput since the previous inspection, set a defined value, and define the station in the priority inspection group that meets the defined value as the highest inspection level A;

[0009] Step 4: For each site in the priority inspection group that does not meet the defined value, obtain the time when the photomask was not inspected and the photomask inspection cycle control line for each site, and obtain the time difference from the required inspection date based on the difference between the two.

[0010] Step 5: Divide the detection levels from high to low based on the magnitude of the time difference;

[0011] Step 6: Inspect the photomasks at each of the stations in sequence according to the different detection levels from high to low.

[0012] Preferably, the state of the photomask in step one includes both "to be detected" and "in detection".

[0013] Preferably, N in step two is 3.

[0014] Preferably, the method for setting the defined value in step three includes: defining the stations with a cumulative throughput of ≥1000 for Arf immersion lithography machines, ≥2000 for Krf scanning lithography machines, or ≥3000 for I-line scanning lithography machines as the highest detection level A.

[0015] Preferably, the inspection equipment in step three is a photolithography machine.

[0016] Preferably, the method for classifying the detection levels from high to low based on the magnitude of the inspection time difference in step five includes: defining the photomask as level C to G and NA that does not require inspection at this time based on the magnitude of the time difference.

[0017] Preferably, in step five, a grade B is defined as more than ten days past the required inspection date, a grade C is defined as more than five days past the required inspection date, a grade D is defined as more than three days past the required inspection date, a grade E is defined as just reaching the required inspection date, a grade F is defined as less than four days past the required inspection date, a grade G is defined as less than six days past the required inspection date, and a grade NA is defined as less than six days past the required inspection date.

[0018] Preferably, the detection level of the photomask at each of the stations in step six is ​​displayed in the inspection machine menu.

[0019] As described above, the automatic scheduling method for photomask defect inspection of the present invention has the following beneficial effects:

[0020] This invention utilizes a big data monitoring model, combined with the model of the photomask used, cumulative shipment volume, product delivery volume, and real-time photomask delivery schedule, to automatically schedule daily photomasks to be inspected. This significantly improves efficiency while ensuring precise control over photomask defect inspection, meeting flexible wafer delivery needs, and guaranteeing photomask quality and product quality. Attached Figure Description

[0021] Figure 1 The diagram shows an automatic scheduling method for photomask defect inspection according to the present invention. Detailed Implementation

[0022] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0023] Please see Figure 1 This invention provides an automatic scheduling method for photomask defect inspection, comprising:

[0024] Step 1: Obtain photomask information for each site. Online data of the equipment at each site can be obtained through big data monitoring and other methods.

[0025] In one alternative implementation, the state of the photomask in step one includes "to be detected" and "in detection".

[0026] Step 2: Define the photomasks without inspection in the future N sites as the lowest inspection level I, and the photomasks with inspection in the future N sites as the priority inspection group, where N is a positive integer;

[0027] In one alternative implementation, N in step two is 3. It should be noted that N can also be other values ​​depending on the actual situation, and no specific limitation is made here.

[0028] Step 3: Set defined values ​​based on the photomask risk level of each inspection machine and the cumulative throughput since the last inspection. Define the stations in the priority inspection group that meet the defined values ​​as the highest inspection level A.

[0029] In one optional implementation, the method for setting the defined value in step three includes: defining stations with a cumulative throughput of ≥1000 for Arf immersion lithography machines, ≥2000 for Krf scanning lithography machines, or ≥3000 for I-line scanning lithography machines as the highest detection level A.

[0030] In one optional implementation, the inspection equipment in step three is a lithography machine.

[0031] Step 4: For each site in the priority inspection group that does not meet the defined value, obtain the time when the photomask was not inspected and the photomask inspection cycle control line for each site, and obtain the time difference from the required inspection date based on the difference between the two.

[0032] Step 5: Classify the detection levels from high to low based on the size of the time difference;

[0033] In one optional implementation, the method for classifying the detection levels from high to low based on the magnitude of the inspection time difference in step five includes: defining the photomask as levels C to G and NA (Near-Near) for which inspection is not required at this time, based on the magnitude of the time difference. It should be noted that the number of detection levels can also be other values.

[0034] In one optional implementation, step five defines the following grades as follows: more than ten days past the required inspection date is grade B; more than five days past the required inspection date is grade C; more than three days past the required inspection date is grade D; just past the required inspection date is grade E; less than four days past the required inspection date is grade F; less than six days past the required inspection date is grade G; and more than six days past the required inspection date is grade NA (not required for inspection at this time).

[0035] Step 6: Inspect the photomasks at each site in sequence according to the different detection levels from high to low.

[0036] In one optional implementation, the detection level of the photomask at each station in step six is ​​displayed in the inspection machine menu.

[0037] In one alternative implementation, based on the inspection level and the real-time status of the photomask, and within the limits of production capacity, the capacity of the inspection machine is maximized, the inspection of photomask defects is flexibly arranged, big data is used, and logical operations are combined to coordinate the online photomask inspection sequence, which improves efficiency by 94% (reducing 3 hours to 10 minutes), reduces the missed inspection rate to 0%, and achieves 100% product coverage, thus maximizing the satisfaction of existing flexible film casting needs and ensuring the quality and safety of online photomasks.

[0038] It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0039] In summary, this invention, through a big data monitoring model, combined with the model of the photomask used, cumulative shipment volume, product delivery volume, and real-time photomask delivery schedule, automatically schedules daily photomasks to be inspected. This significantly improves efficiency while precisely controlling photomask defect inspection, meeting flexible wafer fabrication needs, and ensuring photomask and product quality. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and has high industrial application value.

[0040] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. An automatic scheduling method for inspecting photomask defects, characterized in that, At least including: Step 1: Obtain photomask information for each site; Step 2: Define the photomasks that have no inspection in the future N sites as the lowest inspection level I, and the photomasks that have inspection in the future N sites as the priority inspection group, where N is a positive integer; Step 3: Based on the photomask risk level of each inspection machine and the cumulative throughput since the previous inspection, set a defined value, and define the station in the priority inspection group that meets the defined value as the highest inspection level A; Step 4: For each site in the priority inspection group that does not meet the defined value, obtain the time when the photomask was not inspected and the photomask inspection cycle control line for each site, and obtain the time difference from the required inspection date based on the difference between the two. Step 5: Divide the detection levels from high to low based on the magnitude of the time difference; Step 6: Inspect the photomasks at each of the stations in sequence according to the different detection levels from high to low.

2. The automatic scheduling method for photomask defect inspection according to claim 1, characterized in that: The state of the photomask in step one includes both "to be detected" and "in detection".

3. The automatic scheduling method for photomask defect inspection according to claim 1, characterized in that: The N mentioned in step two is 3.

4. The automatic scheduling method for photomask defect inspection according to claim 1, characterized in that: The inspection equipment mentioned in step three is a photolithography machine.

5. The automatic scheduling method for photomask defect inspection according to claim 4, characterized in that: The method for setting the defined value in step three includes: defining the stations with a cumulative throughput of ≥1000 for Arf immersion lithography machines, ≥2000 for Krf scanning lithography machines, or ≥3000 for I-line scanning lithography machines as the highest detection level A.

6. The automatic scheduling method for photomask defect inspection according to claim 1, characterized in that: The method for classifying detection levels from high to low based on the magnitude of the inspection time difference in step five includes: defining the photomask as level C to G and NA that does not require inspection at this time based on the magnitude of the time difference.

7. The automatic scheduling method for photomask defect inspection according to claim 6, characterized in that: In step five, the following grades are defined: more than ten days past the required inspection date is grade B; more than five days past the required inspection date is grade C; more than three days past the required inspection date is grade D; just past the required inspection date is grade E; less than four days past the required inspection date is grade F; less than six days past the required inspection date is grade G; and more than six days past the required inspection date is grade NA (not required for inspection at this time).

8. The automatic scheduling method for photomask defect inspection according to claim 1, characterized in that: The detection level of the photomask at each of the stations mentioned in step six is ​​displayed in the inspection machine menu.

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