CN115206823A - Method and system for monitoring product interval influenced by machine abnormality - Google Patents
Method and system for monitoring product interval influenced by machine abnormality Download PDFInfo
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- CN115206823A CN115206823A CN202210900401.7A CN202210900401A CN115206823A CN 115206823 A CN115206823 A CN 115206823A CN 202210900401 A CN202210900401 A CN 202210900401A CN 115206823 A CN115206823 A CN 115206823A
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/10—Measuring as part of the manufacturing process
- H01L22/12—Measuring as part of the manufacturing process for structural parameters, e.g. thickness, line width, refractive index, temperature, warp, bond strength, defects, optical inspection, electrical measurement of structural dimensions, metallurgic measurement of diffusions
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L21/00—Processes or apparatus adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof
- H01L21/67—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere
- H01L21/67005—Apparatus not specifically provided for elsewhere
- H01L21/67242—Apparatus for monitoring, sorting or marking
- H01L21/67288—Monitoring of warpage, curvature, damage, defects or the like
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/20—Sequence of activities consisting of a plurality of measurements, corrections, marking or sorting steps
Abstract
The invention provides a method for monitoring product intervals influenced by machine abnormality, which comprises the following steps: the detection unit detects defect information on the wafer; the control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and a corresponding abnormal machine if the defect belongs to the preset defect type; the manufacturing execution system generates a wafer batch list influenced by the wafer with the defect in the abnormal machine; the grabbing unit grabs the wafer batches adjacent to the wafer with the defects according to the wafer batch list; and the detection unit detects the defects of the adjacent wafer batches until no wafer batch with the same defect type as the wafer batch with the defects exists. And locking the affected wafer interval in time, and taking action on an abnormal machine in time to ensure the minimum quantity of the affected wafer batch and the optimal value of the yield guarantee.
Description
Technical Field
The invention relates to the technical field of semiconductors, in particular to a method and a system for monitoring product intervals influenced by machine abnormality.
Background
In a wafer processing factory, defect monitoring of an online process is an essential important link, when a scanner detects a problem wafer lot (lot), according to the existing detection rule, more than 2 wafers (wafers) in the wafer lot have the same defect, which means that a non-accidental event of the process machine causing the defect (defect) may have similar problems with other lots of wafers, and therefore, on the premise of determining the problem machine, timely locking of occurrence time and the number of affected wafer lots becomes a key for ensuring stable yield.
However, in the actual production operation of the semiconductor manufacturing process, along with the increase of production line products, the yield detection scanner cannot monitor each wafer batch, and only can detect a part of batches of wafers in a sample extraction manner, so that the affected wafer batch interval cannot be locked in time, and yield loss of more wafers is caused.
And the number and the severity of the wafers in the influence interval of the existing problem machine are artificially judged, so that careless mistakes are easy to occur in the judgment method, the required manpower is more, the time is long, and the timely management and control of the quality of a production line are not facilitated.
As shown in fig. 1, the yield detection scanner detects that the wafer 10 with the Defect, and the wafer lots adjacent to the wafer 10 with the Defect are the first wafer lot 11 adjacent to the front, the second wafer lot 12 adjacent to the front, the third wafer lot 13 adjacent to the front, the fourth wafer lot 14 adjacent to the front, the fifth wafer lot 15 adjacent to the front, the sixth wafer lot 16 adjacent to the front, the first wafer lot 21 adjacent to the back, the second wafer lot 22 adjacent to the back, the third wafer lot 23 adjacent to the back, the fourth wafer lot 24 adjacent to the back, the fifth wafer lot 25 adjacent to the back, and the sixth wafer lot 26 adjacent to the back, in sequence, after the yield detection scanner detects the wafer 10 with the Defect, the yield detection scanner ideally locks the time of the occurrence of the abnormality and the wafer of the affected lot in time, for example, it is determined according to the time of the machine failure that the first wafer lot 11 adjacent to the front and the first wafer lot 21 adjacent to the back are the most likely to be affected lots, but the yield detection scanner cannot capture the wafer lot of the wafer lot (the wafer lot) in sequence, the wafer lot cannot be the Defect capture the wafer lot) in sequence, the wafer lot number of the wafer lot 15 adjacent to the Defect.
Disclosure of Invention
The invention aims to provide a method and a system for monitoring product intervals influenced by machine abnormality, which are used for solving the problems of low wafer yield, more manpower and long time in wafer defect monitoring.
In order to solve the technical problem, the invention provides a method for monitoring product intervals influenced by machine abnormality, which comprises the following steps:
the detection unit detects defect information on the wafer;
the control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and a corresponding abnormal machine if the defect belongs to the preset defect type;
the manufacturing execution system generates a wafer batch list influenced by the wafer with the defect in the abnormal machine;
the grabbing unit grabs the wafer batch adjacent to the wafer with the defect according to the wafer batch list;
and the detection unit detects the defects of the adjacent wafer batches until no wafer batch with the same defect type as the wafer batch with the defects exists.
Optionally, the step of detecting the defect of the adjacent wafer lot by the detecting unit until there is no wafer lot with the same defect type as the wafer with the defect includes:
detecting the first batch of wafers adjacent to the front and the back of the wafer with the defect;
and judging whether the two first batches of wafers have the defects of the same defect types as the wafers with the defects, if not, triggering a mechanism to stop operation, if so, triggering severity level reminding, continuously grabbing second batches of wafers adjacent to the front and back of the wafers with the defects to detect the defects, and sequentially circulating until the triggering mechanism stops operation.
Optionally, before defect detection is performed on the first batch of wafers, the two first batch of wafers are upgraded into batch wafers which must enter the monitoring station.
Optionally, before performing defect detection on the second batch of wafers, the two second batches of wafers are upgraded into batches of wafers that must enter the monitoring station.
Optionally, the defect types include wafer internal defects, wafer edge defects, and randomly distributed defects.
Optionally, the abnormal machines generating defects include a chemical mechanical polishing machine, a single-cavity machine, a multi-cavity machine, and a photolithography machine.
Optionally, the chemical mechanical polishing machine includes a plurality of polishing heads, and the wafers processed by each polishing head are distinguished.
Optionally, the inside of the multi-cavity machine is divided into a plurality of cavities, and the plurality of cavities are used for performing different processes to capture wafer batches processed by the cavities.
Optionally, the influencing factors causing the defect in the photolithography machine table include a product lot of the photoresist and a classification of the photoresist.
Based on the same inventive concept, the invention also provides a monitoring system for the product interval influenced by the machine station abnormity, which comprises:
the detection unit is used for detecting the defect information on the wafer and carrying out defect detection on the adjacent wafer batches until no wafer batch with the same defect type as the wafer with the defect exists;
the control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and the corresponding abnormal machine if the defect belongs to the preset defect type;
the manufacturing execution system is connected with the control unit and used for generating a wafer batch list influenced by the wafer with the defect in the abnormal machine;
and the grabbing unit is used for grabbing the wafer batches adjacent to the wafer with the defect according to the wafer batch list.
In the monitoring method and system for the product interval affected by the machine station abnormity, the monitoring method detects the defect information on the wafer through the detection unit; the control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and a corresponding abnormal machine if the defect belongs to the preset defect type; the manufacturing execution system generates a wafer batch list influenced by the wafer with the defect in the abnormal machine; the grabbing unit grabs the wafer batch adjacent to the wafer with the defect according to the wafer batch list; and the detection unit detects the defects of the adjacent wafer batches until no wafer batch with the same defect type as the defective wafer exists. The affected wafer batches are screened and judged by the defect wafer batches generated by the monitoring system, the affected wafer batch interval is locked in time, and actions are taken on the abnormal machine in time, so that the minimum quantity of the affected wafer batches and the optimal value of yield guarantee are ensured.
Drawings
FIG. 1 is a schematic diagram of product intervals affected by abnormal machine;
FIG. 2 is a schematic diagram of a monitoring system for product intervals affected by abnormal machine equipment according to an embodiment of the present invention;
FIG. 3 is a flowchart of a method for monitoring product intervals affected by abnormal equipment according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a step of detecting product intervals affected by abnormal machine conditions according to an embodiment of the present invention;
in the figure, the position of the upper end of the main shaft,
10-a defective wafer; 11-the first batch of wafers adjacent in front; 12-the second batch of wafers adjacent in front; 13-the previously adjacent third batch of wafers; 14-the fourth previous adjacent lot of wafers; 15-the immediately preceding fifth batch of wafers; 16-the preceding adjacent sixth batch of wafers; 21-next first lot of wafers; 22-next second lot of wafers; 23-next following third lot of wafers; 24-next fourth batch of wafers; 25-next following fifth batch of wafers; 26-next following sixth batch of wafers; 31-a detection unit; 32-a control unit; 33-a manufacturing execution system; 34-a grabbing unit.
Detailed Description
The following describes a method and a system for monitoring product intervals affected by machine anomaly according to the present invention in further detail with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become more apparent from the following description. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is provided for the purpose of facilitating and clearly illustrating embodiments of the present invention.
Specifically, please refer to fig. 2, which is a schematic diagram of a monitoring system for monitoring product intervals affected by abnormal equipment according to an embodiment of the present invention. As shown in fig. 2, the present embodiment provides a monitoring system for a product interval affected by a machine anomaly, including: the inspection unit 31, the control unit 32, the manufacturing execution system 33 and the grabbing unit 34 are used for inspecting the defect information on the wafer and performing defect inspection on the wafer batch adjacent to the wafer with the defect until detecting that the wafer batch without the defect with the same defect type as the wafer with the defect is detected. The control unit 32 is connected to the detection unit 31, and acquires Defect information detected by the detection unit 31, where the control unit 32 is configured to determine whether the Defect belongs to a preset Defect type, and if the Defect belongs to the preset Defect type, a Defect alarm (delete Notice, DN) is sent, so as to further determine a wafer batch of wafers with the Defect and a corresponding abnormal machine, and if the Defect does not belong to the preset Defect type, no further monitoring is needed. The MES 33 is connected to the control unit 32, and the MES 33 is used for generating a lot list of wafers affected by the defect wafer in the abnormal machine. The grabbing unit 34 is connected to the control unit 32 and controlled by the control unit 32, and the grabbing unit 34 grabs the wafer lots adjacent to the defective wafer according to the wafer lot list.
A Manufacturing Execution System (MES) 33 for storing production information including wafer lots, machine or process names of each station, production time, inspection data, and the like.
The abnormal machines generating defects include a chemical mechanical polishing machine, a single-cavity machine, a multi-cavity machine and a photoetching machine. The chemical mechanical polishing machine of some models includes a plurality of polishing heads, each polishing head processes wafers of different batches, and wafers processed by each polishing head are distinguished, for example, only one polishing head in the plurality of polishing heads is abnormal, and only the wafer batch processed by the abnormal polishing head needs to be detected. Aiming at a machine station which only operates in a single cavity, no special clamping condition exists, and the wafer batch which is actually next to the wafer with the defect in the process can be grabbed. The multi-cavity machine is internally divided into a plurality of cavities, the plurality of cavities are subjected to different processes, for example, if a wafer with defects has an obvious cavity convergence effect, and it is presumed that a certain cavity is abnormal to cause the wafer defects, the wafer batch processed by the corresponding cavity is captured. The multi-cavity machine is, for example, a dry etching machine and a chemical vapor deposition machine. The influence factors of the defects generated in the photoetching machine table comprise the product batch of the photoresist and the classification of the photoresist. Besides being influenced by the electrostatic chuck (by chunk), the photoresist product batches and bottles also cause differences in product performance, and therefore, for the photolithography tool, the classification of the photoresist needs to be discriminated to capture a nearby wafer batch.
The defect types include wafer internal defects, wafer edge defects, randomly distributed defects, and other pattern defects. The wafer internal defect is a specially formed pattern in the wafer, such as a pattern which is specially distributed due to the linear, accumulation of a plurality of defects at a fixed position, fan shape, water flow scouring shape and the like. The wafer edge defect is, for example, a film thickness abnormality defect, a pattern of a special distribution of the wafer edge caused by the fact that a photolithography tool cannot accurately judge the thickness and the flatness of the wafer edge and cannot focus, or a film thickness abnormality caused by chemical vapor deposition, physical vapor deposition or grinding, and the like. Randomly distributed defects are, for example, scratches, small particle defects, randomly distributed patterns with no characteristic effect on the area. Other pattern defects are, for example, the remaining special patterns that may occur.
FIG. 3 is a flowchart of a method for monitoring product intervals affected by abnormal machine equipment according to an embodiment of the present invention; the embodiment provides a method for monitoring product intervals influenced by machine abnormality, which comprises the following steps:
s10, detecting defect information on the wafer by a detection unit;
step S20, a control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and a corresponding abnormal machine if the defect belongs to the preset defect type;
s30, generating a wafer batch list influenced by the wafer with the defect in the abnormal machine by the manufacturing execution system;
s40, a grabbing unit grabs the wafer batches adjacent to the wafer with the defect according to the wafer batch list;
and S50, the detection unit detects the defects of the adjacent wafer batches until no wafer batch with the same defect type as the wafer with the defects exists.
In step S10, the production line product is extracted, defect detection and monitoring are performed, and the detected defect data is uploaded to the control unit 32.
In step S20, the control unit 32 is connected to the detection unit 31, and acquires Defect information detected by the detection unit 31, where the control unit 32 is configured to determine whether the Defect belongs to a preset Defect type, and if the Defect belongs to the preset Defect type, a Defect alarm (delete note, DN) is issued, so as to further determine a wafer batch of wafers with the Defect and a corresponding abnormal machine, and if the Defect does not belong to the preset Defect type, no further monitoring is needed.
The defect types include wafer internal defects, wafer edge defects, randomly distributed defects, and other pattern defects. The wafer internal defects are specially formed patterns in the wafer, such as patterns which are linear, stacked by a plurality of defects at a fixed position, fan-shaped, water flow scouring and the like and cause special distribution. The wafer edge defect is, for example, a film thickness abnormality defect, a pattern of a special distribution of the wafer edge caused by the fact that a photolithography tool cannot accurately judge the thickness and the flatness of the wafer edge and cannot focus, or a film thickness abnormality caused by chemical vapor deposition, physical vapor deposition or grinding, and the like. Randomly distributed defects are for example scratches, small particle defects, randomly distributed patterns with no characteristic effect on the area. Other pattern defects are, for example, the remaining special patterns that may occur. The abnormal machines generating defects include a chemical mechanical polishing machine, a single-cavity machine, a multi-cavity machine and a photoetching machine. The chemical mechanical polishing machine of some machine types comprises a plurality of polishing heads, each polishing head processes wafers of different batches, and the wafers processed by each polishing head are distinguished, for example, only one polishing head in the plurality of polishing heads is abnormal, and only the wafer batch processed by the abnormal polishing head needs to be detected. Aiming at a machine station which only operates in a single cavity, no special clamping condition exists, and the wafer batch which is actually next to the wafer with the defect in the process can be grabbed. The multi-cavity machine is internally divided into a plurality of cavities, the cavities are subjected to different processes, for example, if a wafer with defects has obvious cavity convergence effect, and if the wafer defect caused by abnormality of one cavity is presumed, a wafer batch processed by the corresponding cavity is captured. The multi-cavity machine is, for example, a dry etching machine and a chemical vapor deposition machine. The influencing factors of the defects in the photoetching machine table comprise the product batch of the photoresist and the classification of the photoresist. Besides being affected by the electrostatic chuck (by chunk), the photoresist product lot and the bottle also cause differences in product performance, so that the photoresist needs to be sorted and the wafer lot needs to be captured.
In step S30, the manufacturing execution system 33 is used to store the production information, including the wafer lot, the machine or process name of each station, the production time, and the inspection data.
FIG. 4 is a flowchart illustrating a step of detecting product intervals affected by abnormal machine conditions according to an embodiment of the present invention; fig. 4 is a flowchart showing the detailed steps of step S40 and step S50. The method comprises the following steps:
step S41, capturing the nth batch of wafers adjacent to each other before and after the wafer with the defect, where N =1, that is, the capturing unit 34 captures the first batch of wafers adjacent to each other before and after the wafer with the defect;
s51, detecting the first batch of wafers adjacent to the front and the back of the wafer with the defect;
s52, judging whether the two first-batch wafers have the same defect type as the wafer with the defect;
step S53a, if not, the trigger mechanism stops the operation;
and S53b, if yes, triggering severity level reminding, continuously grabbing the second batch of wafers adjacent to the front and back of the wafer with the defect for defect detection, and sequentially circulating until the triggering mechanism stops operation.
In step S51, before defect detection is performed on the first lot of wafers, the two first lot of wafers are upgraded to wafer lots that must enter the monitoring station. Because the number of the existing products is too many, the detection unit cannot monitor each batch of wafers, only part of batches of wafers can be detected in a sample extraction mode, and the first batch of wafers adjacent to the front and back of the wafer with the defect needs to be upgraded into the batch of wafers which must enter the monitoring station, and then the wafer can enter the monitoring station to detect whether the wafer with the defect has the defect of the same defect type as the wafer with the defect. Similarly, before the second batch of wafers are subjected to defect detection, the two second batches of wafers are upgraded into the wafer batch which must enter the monitoring station.
In step S52, it is determined whether the two first wafers have the same defect type as the wafer having the defect to determine whether the two first wafers are caused by the same abnormal machine.
In step S53a, if not, it indicates that the wafer with defects is a single case and does not affect more other similar products, and the triggering mechanism stops the operation.
In step S53b, if it is determined that the wafer with the defect is not a single case, and the wafer lot with the same defect exists, a severity level prompt is triggered, and an influence interval of the product is found. And locking the wafer interval of the affected batch in time, and taking action on the abnormal machine in time to ensure the minimum quantity of the affected wafer batch and the optimal value of the yield guarantee.
In summary, in the monitoring method and system for the product section affected by the machine abnormality provided by the embodiment of the invention, the monitoring method detects the defect information on the wafer through the detection unit; the control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and a corresponding abnormal machine if the defect belongs to the preset defect type; the manufacturing execution system generates a wafer batch list influenced by the wafer with the defect in the abnormal machine; the grabbing unit grabs the wafer batch adjacent to the wafer with the defect according to the wafer batch list; and the detection unit detects the defects of the adjacent wafer batches until no wafer batch with the same defect type as the wafer batch with the defects exists. The affected wafer batches are screened and judged by the defect wafer batches generated by the monitoring system, the affected wafer batch interval is locked in time, the abnormal machine is acted in time, and the minimum quantity of the affected wafer batches and the optimal value of the yield guarantee are guaranteed.
The above description is only for the purpose of describing the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and any variations and modifications made by those skilled in the art based on the above disclosure are intended to fall within the scope of the appended claims.
Claims (10)
1. A monitoring method for product interval affected by machine abnormality is characterized by comprising the following steps:
the detection unit detects defect information on the wafer;
the control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and a corresponding abnormal machine if the defect belongs to the preset defect type;
the manufacturing execution system generates a wafer batch list influenced by the wafer with the defect in the abnormal machine;
the grabbing unit grabs the wafer batch adjacent to the wafer with the defect according to the wafer batch list;
and the detection unit detects the defects of the adjacent wafer batches until no wafer batch with the same defect type as the defective wafer exists.
2. The method as claimed in claim 1, wherein the step of detecting the defect of the adjacent wafer lots by the detecting unit until there is no wafer lot with the same defect type as the defective wafer includes:
detecting the front and back adjacent first batches of wafers with the defects;
and judging whether the two first batches of wafers have the defects of the same defect types as the wafers with the defects, if not, triggering a mechanism to stop operation, if so, triggering severity level reminding, continuously grabbing second batches of wafers adjacent to the front and back of the wafers with the defects to detect the defects, and sequentially circulating until the triggering mechanism stops operation.
3. The method as claimed in claim 2, wherein two of the first wafers are upgraded to the wafers required to enter the monitoring station before the first wafers are detected for defects.
4. The method as claimed in claim 2, wherein before the defect detection is performed on the second lot of wafers, two of the second lot of wafers are upgraded to the lot of wafers that must enter the monitoring station.
5. The method as claimed in claim 1, wherein the defect types include wafer internal defects, wafer edge defects, and randomly distributed defects.
6. The method of claim 1, wherein the abnormal tool that generates the defect comprises a chemical mechanical polishing tool, a single chamber tool, a multi-chamber tool, and a photolithography tool.
7. The method of claim 6, wherein the chemical mechanical polishing tool includes a plurality of polishing heads, each of the polishing heads being configured to process a wafer.
8. The method of claim 6, wherein an interior of the multi-chamber tool is divided into a plurality of chambers, and the plurality of chambers are processed by different processes to capture wafer lots corresponding to the processing of the chambers.
9. The method as claimed in claim 6, wherein the influencing factors of the occurrence of defects in the tool of the lithography machine include the product lot of the photoresist and the classification of the photoresist.
10. The utility model provides a machine station influences monitored control system between product interval unusually which characterized in that includes:
the detection unit is used for detecting the defect information on the wafers and carrying out defect detection on the adjacent wafer batches until the wafer batches with the same defect type as the wafers with the defects do not exist;
the control unit acquires the defect information detected by the detection unit, confirms whether the defect belongs to a preset defect type, and determines the wafer batch of the wafer with the defect and the corresponding abnormal machine if the defect belongs to the preset defect type;
the manufacturing execution system is connected with the control unit and used for generating a wafer batch list influenced by the wafer with the defect in the abnormal machine;
and the grabbing unit grabs the wafer batch adjacent to the wafer with the defect according to the wafer batch list.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116990022A (en) * | 2023-09-26 | 2023-11-03 | 成都工业职业技术学院 | Bearing detection method and system for new energy automobile transmission system |
| CN117410215A (en) * | 2023-12-15 | 2024-01-16 | 合肥晶合集成电路股份有限公司 | Method for determining machine parameters, control method, control system and device thereof |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116990022A (en) * | 2023-09-26 | 2023-11-03 | 成都工业职业技术学院 | Bearing detection method and system for new energy automobile transmission system |
| CN117410215A (en) * | 2023-12-15 | 2024-01-16 | 合肥晶合集成电路股份有限公司 | Method for determining machine parameters, control method, control system and device thereof |
| CN117410215B (en) * | 2023-12-15 | 2024-04-09 | 合肥晶合集成电路股份有限公司 | Method for determining machine parameters, control method, control system and device thereof |
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