WO2010044358A1 - Method and device for inspecting wafer pattern - Google Patents
Method and device for inspecting wafer pattern Download PDFInfo
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- WO2010044358A1 WO2010044358A1 PCT/JP2009/067442 JP2009067442W WO2010044358A1 WO 2010044358 A1 WO2010044358 A1 WO 2010044358A1 JP 2009067442 W JP2009067442 W JP 2009067442W WO 2010044358 A1 WO2010044358 A1 WO 2010044358A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/9501—Semiconductor wafers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/956—Inspecting patterns on the surface of objects
- G01N21/95607—Inspecting patterns on the surface of objects using a comparative method
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/001—Industrial image inspection using an image reference approach
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- H10P74/203—
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- H10P74/23—
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30148—Semiconductor; IC; Wafer
Definitions
- the present invention relates to a pattern inspection method and apparatus for inspecting a wafer pattern.
- a wafer pattern comprising: means for determining pass / fail of the apparatus; means for storing the input inspection image as a new master image when the difference amount is equal to or less than a predetermined value; and means for outputting the determination result of pass / fail Inspection devices are known.
- the conventional pattern matching inspection cannot be performed if the patterns are greatly different. This is because the difference amount is too large and the determination result may always be negative.
- wafers having different patterns depending on the manufacturing process may be subject to inspection.
- the difference in pattern may not be a problem in quality and performance.
- Such products could not be properly inspected by wafer pattern matching inspection.
- the inspection can be performed to some extent if the averaging of the reference image and the inspection sensitivity are reduced by the learning process.
- the averaging or detection sensitivity of the reference image by the difference learning process is made too sweet, the defect detectability deteriorates.
- the learning process is automatically performed, it is difficult to ensure desired defect detectability.
- An object of the present invention is to provide a wafer pattern inspection method and apparatus that enable an automatic learning function for wafers having different patterns.
- Examples of the solution means of the present invention for solving the above-described problems are as follows. (1.) A step of inputting an inspection image of a wafer pattern or chip to be inspected, comparing the input inspection image with a pre-stored reference image, and determining whether the wafer is good or bad based on the difference between the comparison images
- a wafer pattern inspection method comprising: If the non-defective product rate falls below a predetermined threshold during the inspection, the learning process is performed again using the pattern or chip image being inspected to create a new reference image, or uniform after learning the pattern through the learning process.
- a wafer inspection is performed by an inspection other than the pattern matching inspection, such as a pitch inspection.
- a pattern matching inspection and a pitch inspection are simultaneously performed on the uniform pattern part.
- a wafer pattern inspection method characterized by determining a sensitivity of pattern matching inspection from a result and inspecting a pattern or a chip on the entire surface of the wafer with the determined sensitivity.
- a wafer pattern inspection apparatus comprising a processing means having a determination means for determining, When the non-defective product rate falls below a predetermined threshold during the inspection, the arithmetic processing means creates a new reference image by performing the learning process again using the image of the pattern or chip under inspection, or the pattern by the learning process.
- a wafer pattern inspection apparatus characterized in that the sensitivity of the pattern matching inspection is determined from the result of the pitch inspection, and the pattern or chip on the entire wafer surface is inspected with the determined sensitivity. Even if there is a pattern or chip with greatly different pattern deviation or color unevenness from the original reference, it is judged whether it is a non-defective wafer as a product that does not cause a problem in product performance. Can maintain the non-defective rate. The best mode for carrying out the present invention will be described below.
- the learning process is performed again. More specifically, after learning the pattern by the learning process, a uniform pattern is searched, and if it is a uniform pattern portion, the wafer is inspected by an inspection other than the pattern matching inspection such as a pitch inspection. (2) The pattern matching inspection and the pitch inspection are simultaneously performed on the uniform pattern portion, and the sensitivity of the pattern matching inspection is determined from the result of the pitch inspection. (3) The pattern or chip on the entire wafer surface is inspected with the sensitivity determined as described above.
- the predetermined threshold can be arbitrarily set by the user of the apparatus (for example, a non-defective product between 90 and 95%). rate). However, the predetermined threshold value may be fixed to only one desired value, or only the lowest value may be fixed, and the desired value may be made variable and adjusted as necessary. Also good.
- the lowest value may be fixed at 90%, and an arbitrary threshold value (for example, 95%) higher than that may be set.
- the present invention includes a step of inputting an inspection image of a wafer pattern or chip, comparing the input inspection image with a pre-stored reference image, and determining whether the wafer is good or bad based on a difference amount of the comparison image.
- the pattern inspection method and apparatus are improved.
- the non-defective product rate is extremely lowered during inspection and becomes a predetermined value (for example, 90%, 95%, or other values)
- the learning process is performed again on the pattern or chip image being inspected.
- pattern matching inspection and pitch inspection are simultaneously performed on the uniform pattern portion to determine the sensitivity of the pattern matching inspection, and the pattern or chip on the entire wafer surface is inspected with the determined sensitivity.
- FIG. 1A and 1B are diagrams showing an outline of a wafer pattern inspection apparatus according to the present invention.
- FIG. 2 is a diagram for explaining recipe (reference) creation.
- FIG. 3 is a diagram for explaining a chip in which a pattern shift, which is an object of the present invention, is generated.
- FIG. 4 is a diagram for explaining creation of a reference image by relearning.
- FIG. 5 is a diagram for explaining the inspection after re-learning.
- FIG. 6 is a diagram for explaining a difference between pattern inspection and pitch inspection.
- FIG. 7 is a flowchart.
- FIG. 1 shows an appearance inspection apparatus 10 suitable for carrying out a wafer pattern (appearance) inspection method according to the present invention.
- an appearance inspection apparatus 10 has each circuit pattern formed on a large number of semiconductor chips 11a formed in alignment on a semiconductor wafer 11 as shown in FIG. Used to determine if the defect is acceptable.
- the present invention will be described along an example in which the present invention is applied to an inspection of a semiconductor chip 11 a formed on a semiconductor wafer 11.
- the appearance inspection apparatus 10 controls the operation of the optical imaging mechanism 10a and the optical imaging mechanism, and performs arithmetic processing on the image information obtained by the optical imaging mechanism 10a.
- the optical imaging mechanism 10a moves the moving unit 12 provided with the stage 12a for holding the semiconductor wafer 11 and the stage 12a of the moving unit in the X-axis direction and the Y-axis direction on the XY plane, and moves around the Z-axis.
- the imaging unit 15 is constituted by, for example, a CCD imaging device and its optical system.
- the control arithmetic means (arithmetic processing unit) 10 b includes an arithmetic processing circuit 16, and the arithmetic processing circuit 16 can be configured by a central processing unit (CPU) that operates in accordance with a program stored in the memory 17, for example. .
- the arithmetic processing circuit 16 controls the operations of the driver 13, the illumination unit 14, and the imaging unit 15 of the optical imaging mechanism 10a via the control circuit 18, and is obtained by the imaging unit 15 according to the information stored in the memory 17.
- the detected image is subjected to defect detection processing.
- the arithmetic processing circuit 16 includes an area setting unit 16a for dividing the inspection region of the image obtained by the imaging unit 15 into a plurality of areas, and a defect by comparing the inspection region of the image with a template for inspection.
- a defect extraction unit 16b for extracting a part a determination unit 16c for determining whether or not the defect part extracted by the defect extraction part is within an allowable range, and a pattern that is within the allowable range but has no problem in product performance.
- a learning function unit 16d is provided that learns the image of the shifted pattern, the image of the chip, or the average image thereof as a reference image (reference image or reference image).
- the arithmetic processing circuit 16 is connected to a monitor 19 having a display unit composed of, for example, a liquid crystal or a CRT, and an input unit 20 composed of, for example, a keyboard and a mouse.
- the monitor 19 can display an image captured by the imaging unit 15 and an image processed by the arithmetic processing circuit 16, and can display information necessary for operating the optical imaging mechanism 10a. Based on the information displayed on the monitor 19, a command necessary for operating the appearance inspection apparatus 10 can be appropriately input from the input unit 20.
- the imaging unit 15 captures a reference image (reference image or standard image) and an image for the object to be inspected. A desired inspection region is cut out from the surface image of the semiconductor chip 11 a photographed by the imaging unit 15 and displayed on the monitor 19. In FIG.
- the image on the left is an example of the display screen 21A for the examination area cut out as described above.
- This display screen 21A shows an example in which the semiconductor chip 11a is a memory chip.
- FIG. 6 shows a pattern image and a chip image. In the surface image, a defective portion is observed at a position indicated by a star, that is, a star.
- the observed defect is a defect such as adhesion of a foreign substance to the circuit pattern or a partial defect of the circuit pattern.
- an average image is selected and used as a reference image (reference image).
- This reference image (reference image) and the surface image 21A of the other semiconductor chip 11a that is the inspection object, that is, the inspection object, are compared by the arithmetic processing circuit 16 for defect extraction.
- the arithmetic processing circuit 16 compares a reference image (reference image) with an image of the semiconductor chip 11a of the object to be inspected.
- the sensitivity adjustment is performed for the reference image (reference image) and the entire pattern or chip of the object to be inspected.
- shading processing for removing illumination unevenness by the illumination unit 14 multi-value processing for promoting the clarification of edges, and reducing the influence of pattern density and image shading upon edge detection
- color tone conversion processing for color recognition, chromaticity conversion for facilitating pattern recognition, or expansion / contraction processing using an expansion / contraction filter for removing noise is performed. These processes can be performed by a well-known method. These can be appropriately selected and combined.
- the arithmetic processing circuit 16 compares the reference image (reference image) with the image subjected to the image preprocessing of the object to be inspected, and uses the reference image (reference image) based on pattern density, image density, chromaticity, and the like. Adjust the detection sensitivity.
- an image to be compared is registered in advance.
- a reference image (reference image) as a reference for inspection is created (recipe creation).
- the reference image (reference image) is, for example, one chip as shown on the left side of FIG. However, a plurality of chip images may be set as a reference image.
- the reference image (reference image) is stored in a storage unit (memory) provided separately from the arithmetic processing unit of the apparatus, and is learned through the learning function of the arithmetic processing unit. After learning, the average image is stored in the storage unit as a reference image (reference image) as shown on the right side of FIG. As a result, as shown in FIG. 3, since the left pattern matches the reference image (reference image), it is determined to be inspected, but the right pattern is different from the reference image (reference image). , It is determined that the inspection is NG.
- the non-defective product ratio ratio of non-defective products with a small difference from the reference image
- a reference image reference image
- the reference before the change on the left side is set to the reference on the right side (relearning, average image change).
- the non-defective product rate has decreased to 95%, but a reference image is re-created using a wafer pattern (or chip) having a deviation that does not cause a problem in the product as a reference image.
- the average image is changed, the reference image (reference image) is relearned, and the wafer pattern or chip inspection is restarted based on the reference image (reference image).
- the inspection result is OK even if the pattern is different from the pattern before the reference image correction.
- the re-learning process is immediately performed, and the reference image (reference image) is obtained. It is desirable to make it again.
- the present invention is not limited to a fixed fixed product rate (95% or other set values), and the operator can achieve a predetermined minimum product rate (for example, 90%, but not limited to this).
- the learning function can be adjusted to re-learn freely at any threshold within the range.
- the arithmetic control unit has a function of automatically adjusting detection sensitivity in combination with a pattern matching inspection based on a reference image (reference image).
- the automatic sensitivity adjustment refers to a function of automatically determining the sensitivity by comparing the detectability of the pattern matching inspection and the pitch inspection.
- the entire chip is usually compared with the entire reference image (reference image) to check whether they match, as shown on the right side.
- the sensitivity of the pattern matching inspection is adjusted so that the same defect can be detected by comparing the result of the pattern matching inspection with the result of the pitch inspection.
- Pattern matching detection and pitch inspection are performed on the same inspection image, and the detection sensitivity of the pattern inspection is adjusted so that the defect detection performance is almost the same.
- the pattern matching inspection can inspect the entire chip, but the pitch inspection can usually inspect only the uniform pattern portion.
- FIG. 7 shows a flowchart.
- an inspection recipe is created with the first wafer and wafer inspection is performed.
- the non-defective product rate is lower than a set value (for example, 90%)
- the learning process is performed on the wafer under inspection.
- the inspection is performed again based on the re-learned reference image (reference image).
- the inspection result of the re-learned reference image (reference image) is stored as the wafer inspection result, and the inspection is terminated.
- the apparatus it is preferable to deal with the following in response to a chip whose pattern has shifted. Even if there is a shift in the pattern for each lot or for each wafer, it is possible to make it non-defective. If the pattern is misaligned, the generated wafer is subjected to the learning process again and inspected. Although it is not easy for the apparatus to automatically determine whether the cause of the decrease in the non-defective product rate is a pattern shift, it is preferable to perform the learning process again when the non-defective product rate falls below a predetermined threshold value. In a preferred aspect of the present invention, the learning process is performed again when the yield rate falls below a predetermined threshold.
- the detection performance may be reduced by learning. For example, a significant decrease in detection performance appears on wafers with severe color irregularities and wafers with continuous defects at the same position. Therefore, it is possible to determine a pattern or chip that does not cause a problem in performance as a non-defective product, and to maintain the work efficiency of the inspection and the original good product rate.
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Abstract
Description
本発明は、ウェハのパターンを検査するパターン検査方法及び装置に関する。 The present invention relates to a pattern inspection method and apparatus for inspecting a wafer pattern.
従来から、例えば、特開平5−281151に示すように、ウェハの検査画像を入力する手段と、入力した検査画像と予め記憶されたマスタ画像とを比較する手段と、比較画像の相違量よりウェハの良否を判定する手段と、上記相違量が所定値以下の時に、上記入力された検査画像を新たなマスタ画像として記憶する手段と、上記良否の判定結果を出力する手段とを具備するウェハパターン検査装置が知られている。
しかしながら、従来のパターンマッチング検査ではパターンが大きく異なると、検査ができない。なぜなら、相違量が大きすぎて、判定結果が常に否となってしまう虞があるからである。
一方、現状では製造プロセスによってパターンが異なるウェハ、すなわちパターンのずれ、色むら等が異なるウェハが検査対象となることがある。
また、製品によってはパターンの差異が品質、性能上問題にならない場合がある。このような製品はウェハのパターンマッチング検査では適正に検査できなかった。
他方、パターンが異なるウェハの場合、差異について学習処理によるリファレンス画像の平均化と検査感度を甘くすれば、ある程度検査を行う事ができる。
しかし、差異の学習処理によるリファレンス画像の平均化や検出感度を甘くしすぎると、欠陥検出性が低下してしまう。
しかも、学習処理を自動で行う場合、所望の欠陥検出性を保証することが難しい。
Conventionally, for example, as shown in Japanese Patent Laid-Open No. 5-281151, a means for inputting an inspection image of a wafer, a means for comparing the input inspection image with a master image stored in advance, and a wafer based on the difference between the comparison images A wafer pattern comprising: means for determining pass / fail of the apparatus; means for storing the input inspection image as a new master image when the difference amount is equal to or less than a predetermined value; and means for outputting the determination result of pass / fail Inspection devices are known.
However, the conventional pattern matching inspection cannot be performed if the patterns are greatly different. This is because the difference amount is too large and the determination result may always be negative.
On the other hand, at present, wafers having different patterns depending on the manufacturing process, that is, wafers having different pattern deviations, color irregularities, and the like may be subject to inspection.
Also, depending on the product, the difference in pattern may not be a problem in quality and performance. Such products could not be properly inspected by wafer pattern matching inspection.
On the other hand, in the case of wafers having different patterns, the inspection can be performed to some extent if the averaging of the reference image and the inspection sensitivity are reduced by the learning process.
However, if the averaging or detection sensitivity of the reference image by the difference learning process is made too sweet, the defect detectability deteriorates.
In addition, when the learning process is automatically performed, it is difficult to ensure desired defect detectability.
本発明の課題は、パターンの異なるウェハに対して自動学習機能を可能とするウェハパターン検査方法及び装置を提供することである。
上記課題を解決するための本発明の解決手段を例示すると、次のとおりである。
(1.)検査対象であるウェハのパターン又はチップの検査画像を入力し、入力した検査画像と予め記憶されていたリファレンス画像とを比較し、比較画像の相違量よりウェハの良否を判定する段階を備えたウェハのパターン検査方法であって、
検査中に良品率が所定の閾値以下に低下した場合、検査中のパターン又はチップの画像を用いて学習処理を再度行い新たなリファレンス画像を作成し、又は、学習処理でパターンを学習した後に均一なパターンを探し、均一なパターン部分であれば、パターンマッチング検査以外の、ピッチ検査などの検査でウェハの検査を行うか、あるいは均一パターン部分でパターンマッチング検査とピッチ検査を同時に行ない、ピッチ検査の結果からパターンマッチング検査の感度を決定し、決定した感度でウェハ全面のパターン又はチップを検査することを特徴とするウェハのパターン検査方法。
(2.)検査対象であるウェハのパターン又はチップの検査画像を入力する手段と、入力した検査画像と予め記憶されていたリファレンス画像とを比較する手段と、比較した結果に基づきウェハの良否を判定する判定手段を有する演算処理手段とを備えたウェハのパターン検査装置であって、
演算処理手段は、検査中に良品率が所定の閾値以下に低下した場合、検査中のパターン又はチップの画像を用いて学習処理を再度行い新たなリファレンス画像を作成し、又は、学習処理でパターンを学習した後に均一なパターンを探し、均一なパターン部分であれば、パターンマッチング検査以外の、ピッチ検査などの検査でウェハの検査を行うか、あるいは均一パターン部分でパターンマッチング検査とピッチ検査を同時に行ない、ピッチ検査の結果からパターンマッチング検査の感度を決定し、決定した感度でウェハ全面のパターン又はチップを検査することを特徴とするウェハのパターン検査装置。
もとのリファレンスからのパターンずれ、色むら等が大きく異なるパターンやチップがあった場合であっても、製品の性能上問題にならないウェハとして良品か否かを判定し、検査の作業効率、本来の良品率の維持を保つことができる。
本発明を実施するための最良の形態を以下説明する。
(1)検査中に過剰検出が大量に発生した場合(良品率が極端に低下した場合)、学習処理を再度行なう。詳述すると、学習処理でパターンを学習した後に均一なパターンを探し、均一なパターン部分であれば、ピッチ検査などのパターンマッチング検査以外の検査でウェハの検査を行う。
(2)均一パターン部分でパターンマッチング検査とピッチ検査を同時に行ない、ピッチ検査の結果からパターンマッチング検査の感度を決定する。
(3)上記のように決定した感度でウェハ全面のパターン又はチップを検査する。
このようにすることで、パターンが大きく異なる場合であっても、製品の性能上問題にならないウェハとして良品を判定し、検査の作業効率、本来の良品率の維持を保つことができる。
良品率が極端に低下して所定の閾値以下になる場合、学習処理を再度行なうが、その所定の閾値は、装置の使用者が任意に設定可能である(例えば90~95%の間の良品率)。ただし、所定の閾値は、1つの所望の値のみに固定してもよいし、最低の値のみを固定しておいて、所望の値を可変にしておいて必要に応じて調整するようにしてもよい。例えば、最低の値を90%に固定し、それ以上の任意の閾値(例えば95%)を設定するようにしてもよい。とくに、検査対象に応じて所望の閾値に調整することを可能とするのが好ましい。
本発明は、ウェハのパターン又はチップの検査画像を入力し、入力した検査画像と予め記憶されていたリファレンス画像とを比較し、比較画像の相違量によってウェハの良否を判定する段階を備えたウェハのパターン検査方法及び装置を改良したものである。
本発明においては、検査中に良品率が極端に低下して所定値(例えば90%や95%、あるいは他の値)以下になった場合、検査中のパターン又はチップの画像で学習処理を再度行い新たなリファレンス画像を作成し、又は、学習処理でパターンを学習した後に均一なパターンを探し、均一なパターン部分であれば、ピッチ検査などのパターンマッチング検査以外の検査でウェハの検査を行うか、あるいは均一パターン部分でパターンマッチング検査とピッチ検査を同時に行ない、パターンマッチング検査の感度を決定し、決定した感度でウェハ全面のパターン又はチップを検査する。
An object of the present invention is to provide a wafer pattern inspection method and apparatus that enable an automatic learning function for wafers having different patterns.
Examples of the solution means of the present invention for solving the above-described problems are as follows.
(1.) A step of inputting an inspection image of a wafer pattern or chip to be inspected, comparing the input inspection image with a pre-stored reference image, and determining whether the wafer is good or bad based on the difference between the comparison images A wafer pattern inspection method comprising:
If the non-defective product rate falls below a predetermined threshold during the inspection, the learning process is performed again using the pattern or chip image being inspected to create a new reference image, or uniform after learning the pattern through the learning process. If a uniform pattern part is searched for, a wafer inspection is performed by an inspection other than the pattern matching inspection, such as a pitch inspection. Alternatively, a pattern matching inspection and a pitch inspection are simultaneously performed on the uniform pattern part. A wafer pattern inspection method characterized by determining a sensitivity of pattern matching inspection from a result and inspecting a pattern or a chip on the entire surface of the wafer with the determined sensitivity.
(2.) A means for inputting an inspection image of a wafer pattern or chip to be inspected, a means for comparing the input inspection image with a pre-stored reference image, and the quality of the wafer based on the comparison result A wafer pattern inspection apparatus comprising a processing means having a determination means for determining,
When the non-defective product rate falls below a predetermined threshold during the inspection, the arithmetic processing means creates a new reference image by performing the learning process again using the image of the pattern or chip under inspection, or the pattern by the learning process. After learning the above, search for a uniform pattern, and if it is a uniform pattern part, inspect the wafer by inspections other than pattern matching inspection, such as pitch inspection, or perform pattern matching inspection and pitch inspection simultaneously on the uniform pattern part. A wafer pattern inspection apparatus characterized in that the sensitivity of the pattern matching inspection is determined from the result of the pitch inspection, and the pattern or chip on the entire wafer surface is inspected with the determined sensitivity.
Even if there is a pattern or chip with greatly different pattern deviation or color unevenness from the original reference, it is judged whether it is a non-defective wafer as a product that does not cause a problem in product performance. Can maintain the non-defective rate.
The best mode for carrying out the present invention will be described below.
(1) If a large amount of over-detection occurs during the inspection (when the yield rate is extremely reduced), the learning process is performed again. More specifically, after learning the pattern by the learning process, a uniform pattern is searched, and if it is a uniform pattern portion, the wafer is inspected by an inspection other than the pattern matching inspection such as a pitch inspection.
(2) The pattern matching inspection and the pitch inspection are simultaneously performed on the uniform pattern portion, and the sensitivity of the pattern matching inspection is determined from the result of the pitch inspection.
(3) The pattern or chip on the entire wafer surface is inspected with the sensitivity determined as described above.
By doing so, it is possible to determine a non-defective product as a wafer that does not cause a problem in product performance even when the patterns are greatly different, and to maintain the work efficiency of inspection and the maintenance of the original non-defective product rate.
When the non-defective product rate is extremely reduced and falls below a predetermined threshold, the learning process is performed again. The predetermined threshold can be arbitrarily set by the user of the apparatus (for example, a non-defective product between 90 and 95%). rate). However, the predetermined threshold value may be fixed to only one desired value, or only the lowest value may be fixed, and the desired value may be made variable and adjusted as necessary. Also good. For example, the lowest value may be fixed at 90%, and an arbitrary threshold value (for example, 95%) higher than that may be set. In particular, it is preferable to be able to adjust to a desired threshold according to the inspection object.
The present invention includes a step of inputting an inspection image of a wafer pattern or chip, comparing the input inspection image with a pre-stored reference image, and determining whether the wafer is good or bad based on a difference amount of the comparison image. The pattern inspection method and apparatus are improved.
In the present invention, when the non-defective product rate is extremely lowered during inspection and becomes a predetermined value (for example, 90%, 95%, or other values), the learning process is performed again on the pattern or chip image being inspected. Create a new reference image, or search for a uniform pattern after learning the pattern using the learning process, and if it is a uniform pattern part, do you inspect the wafer with an inspection other than pattern matching inspection such as pitch inspection? Alternatively, pattern matching inspection and pitch inspection are simultaneously performed on the uniform pattern portion to determine the sensitivity of the pattern matching inspection, and the pattern or chip on the entire wafer surface is inspected with the determined sensitivity.
図1(A)、(B)は、本発明に係るウェハのパターン検査装置の概略を示す図。
図2は、レシピ(リファレンス)作成を説明するための図。
図3は、本発明で対象としたパターンズレの発生しているチップを説明するための図。
図4は、再学習によるリファレンス画像の作成を説明するための図。
図5は、再学習した後の検査を説明するための図。
図6は、パターン検査とピッチ検査の違いを説明するための図。
図7は、フローチャートを示す図。
1A and 1B are diagrams showing an outline of a wafer pattern inspection apparatus according to the present invention.
FIG. 2 is a diagram for explaining recipe (reference) creation.
FIG. 3 is a diagram for explaining a chip in which a pattern shift, which is an object of the present invention, is generated.
FIG. 4 is a diagram for explaining creation of a reference image by relearning.
FIG. 5 is a diagram for explaining the inspection after re-learning.
FIG. 6 is a diagram for explaining a difference between pattern inspection and pitch inspection.
FIG. 7 is a flowchart.
図面を参照して、本発明の好適な実施例を説明する。
図1は本発明に係るウェハのパターン(外観)検査方法を実施するのに好適な外観検査装置10を示す。
図1の(A)において、外観検査装置10は、例えば図1の(B)に示すような半導体ウェハ11上に整列して形成された多数の半導体チップ11aに形成されたそれぞれの回路パターンの欠陥が許容内であるか否かを判定するのに使用される。以下、本発明を半導体ウェハ11上に形成された半導体チップ11aの検査に適用した例に沿って説明する。
外観検査装置10は、図1の(A)に示すように、光学的撮影機構10aと、該光学的撮影機構の動作を制御しかつこの光学的撮影機構10aにより得られた画像情報を演算処理するための制御演算手段10bとを備える。
光学的撮影機構10aは、半導体ウェハ11を保持するステージ12aが設けられた移動部12と、該移動部のステージ12aをXY平面上でX軸方向、Y軸方向に移動させ、Z軸の回りに回転させるためのドライバ13と、照明部14による照明下でステージ12a上の半導体ウェハ11に形成された所望の半導体チップ11aの表面画像を撮影するための撮像部15とを有する。この撮像部15は、従来よく知られているように、例えばCCD撮像素子およびその光学系で構成される。
制御演算手段(演算処理部)10bは演算処理回路16を有し、該演算処理回路16は、例えばメモリー17に格納されたプログラムに沿って動作する中央処理装置(CPU)により構成することができる。演算処理回路16は、制御回路18を介して、光学的撮影機構10aのドライバ13、照明部14および撮像部15の各作動を制御し、またメモリー17に格納された情報に従って撮像部15により得られた画像に欠陥検出処理を施す。
この演算処理回路16には、撮像部15により得られた画像の検査領域を複数のエリアに区画するためのエリア設定部16aと、前記画像の検査領域と検査のためのテンプレートとの比較により欠陥部位を抽出する欠陥抽出部16bと、該欠陥抽出部により抽出された欠陥部位が許容内であるか否かを判定する判定部16cと、許容内であるが製品の性能上問題がないパターンのズレがある場合に、そのずれたパターンの画像あるいはチップの画像、あるいはそれらの平均画像をリファレンス画像(参照画像または基準画像)として学習する学習機能部16dが設けられている。
また、演算処理回路16には、例えば液晶あるいはCRTで構成された表示部を有するモニタ19と、例えばキーボードおよびマウス等で構成された入力部20とが接続されている。モニタ19には、撮像部15で撮影された画像および演算処理回路16で処理された画像が表示可能であり、また光学的撮影機構10aの操作に必要な情報が表示される。これらモニタ19に表示される情報に基づいて、入力部20から外観検査装置10の操作に必要な命令を適宜入力することができる。
撮像部15は、リファレンス画像(参照画像または基準画像)および被検査体のための画像を撮影する。撮像部15により撮影された半導体チップ11aの表面画像から所望の検査領域が切り出され、モニタ19上に表示される。
図2において、左側の画像は、前述のようにして切り出された検査領域の表示画面21Aの一例である。この表示画面21Aは、半導体チップ11aがメモリーチップである例を示している。
図6には、パターン画像、チップ画像が示されている。表面画像中、星印つまり★印で示す箇所に欠陥部位が観察される。観察される欠陥は、回路パターンへの異物の付着あるいは回路パターンの部分的な欠損等の欠陥である。
リファレンス画像(基準画像)には、半導体ウェハ11の各半導体チップ11aから得られる前記した表面画像21Aのうち、欠損や異物から成る前記欠陥が少ない最も良質の半導体チップ11aの表面画像(21A)、あるいは平均画像が選択され、これがリファレンス画像(基準画像)として使用される。このリファレンス画像(基準画像)と、検査対象つまり被検査体である他の半導体チップ11aの表面画像21Aとが、演算処理回路16により、欠陥の抽出のために比較される。
演算処理回路16は、従来よく知られているように、リファレンス画像(基準画像)と被検査体の半導体チップ11aの画像との比較を行う。パターン画像全体、あるいはパターン画像中の一部のチップ画像について、リファレンス画像(基準画像)と被検査体のパターン全体、あるいはチップについて、感度調整を行う。
その際、前処理として、照明部14による照明むらを除去するためのシェーディング処理、エッジの明確化を促進するための多値化処理、エッジ検出に際してパターンの粗密や画像の濃淡の影響を低減するための色調変換処理、パターンの認識を容易とするための色度変換あるいはノイズを除去するための膨張/収縮フィルタを用いた膨張/収縮処理等の処理を行う。これらの処理は、従来よく知られている方法で実施できる。これらは、適宜選択して組み合わせることができる。
演算処理回路16は、リファレンス画像(基準画像)と被検査体の画像前処理が施された画像を比較し、パターンの粗密や画像の濃淡、色度などから、リファレンス画像(基準画像)を用いた検出の感度を調整する。
以下、最適の検査手順の一例を説明する。
図2に示すように、パターンマッチング検査において、事前に比較対象となる画像を登録する。
まず、検査の基準とするリファレンス画像(基準画像)を作成する(レシピ作成)。この場合、リファレンス画像(基準画像)は、図2の左側に示すように、例えば1チップとする。ただし、複数のチップ画像を組として基準画像としてもよい。
装置の演算処理部と別体に設けられた記憶部(メモリー)に、このリファレンス画像(基準画像)を記憶させ、演算処理部の学習機能を介して、学習させておく。学習後、図2の右側に示すように、平均画像がリファレンス画像(基準画像)として記憶部に記憶される。
その結果、図3に示すように、左側のパターンは、リファレンス画像(基準画像)と一致するので、検査OKと判定されるが、右側のパターンは、リファレンス画像(基準画像)とパターンが異なるため、検査NGであると判定される。
しかしながら、この場合、パターンがズレているので、検査するウェハのパターン(あるいはチップ)がNGになってしまうが、製品には多少のパターンズレは問題にならないためOKにしたいものがある。そこで、良品率(基準画像との相違量が少ない良品の占める割合)が所定値以下に下がると、自動的にリファレンス画像(基準画像)を作り直す。例えば、ほぼ97%の良品率でパターン検査作業を続けるうちに、急に良品率が95%に下がってしまう場合、閾値が95%に設定されていると、そこで自動的にリファレンス画像(基準画像)を作り直し、その良品率でパターン検査を再開する。
図4に示すように、左側の変更前のリファレンスを右側のリファレンス(再学習、平均画像変更)にする。例えば95%に良品率が下がってしまったが、製品には問題にならないズレがあるウェハのパターン(あるいはチップ)を基準画像としてリファレンス画像を作成し直すのである。平均画像を変更し、リファレンス画像(基準画像)を再学習し、そのリファレンス画像(基準画像)をもとにウェハのパターンあるいはチップの検査を再開する。
図5に示すように、リファレンス画像(基準画像)が修正されると、リファレンス画像修正前のパターンと異なっていても、検査結果はOKとなる。
本発明によれば、例えば、良品率が最低の90%よりも小さい、例えば、85%、あるいは他の所定値に下がってしまった場合に直ちに再学習処理を行い、リファレンス画像(基準画像)を作り直すことが望ましい。
なお、本発明は、一定の固定された良品率(95%やその他の設定値)に限定されず、作業者が所定の最低良品率(例えば90%であるが、これに限らない)までの範囲内の任意の閾値で自由に再学習するように、学習機能を調整することができる。
また、好ましくは、リファレンス画像(基準画像)をもとにしたパターンマッチング検査とあわせて、検出感度を自動調整する機能を演算制御部が有する。ここで、感度の自動調整とは、パターンマッチング検査とピッチ検査の検出性を比較して感度を自動決定する機能をいう。
図6に示すように、パターンマッチング検査では、通例、左側に示すように、チップ全体をリファレンス画像(基準画像)の全体と比較し、一致するかどうかの検査を行うが、右側に示すように、パターンのうち均一なパターン部分のみを検査画像内で比較検査するピッチ検査も同時に行うのが好ましい。
好ましくは、パターンマッチング検査の結果とピッチ検査の結果を比較して、同じ欠陥が検出できるようにパターンマッチング検査の感度を調整する。同一の検査画像でパターンマッチング検査とピッチ検査を行い欠陥検出性能がほぼ同一になるように、パターン検査の検出感度を調整する。
なお、パターンマッチング検査はチップ全体を検査できるが、ピッチ検査は、通例、均一パターン部分しか検査できない。
図7は、フローチャートを示す。
この図示例においては、1枚目のウェハで検査レシピを作成し、ウェハ検査を行う。良品率が設定した値(例えば90%)よりも低い場合は検査中のウェハで学習処理を行う。再学習後のリファレンス画像(基準画像)を元に再度検査を行う。再学習後のリファレンス画像(基準画像)での検査結果をウェハの検査結果として保存して検査を終了する。
パターンにズレの生じたチップに対して次のような対応をするのが好ましい。
ロット毎又はウェハ毎にパターンにズレがある場合でも良品にすることを可能にする。パターンにズレが発生したら、発生したウェハを学習処理し直して検査を行う。
なお、良品率低下の原因がパターンズレか否かを装置で自動的に判断するのは容易ではないが、良品率が所定の閾値以下になったら学習処理をやり直して検査することが好ましい。
本発明の好ましい態様では、良品率が所定の閾値を下回った時に学習処理をやり直す。
実験例において、良品率が低下した場合に再度学習処理を行い検査すると、パターンズレの過剰検出を大幅に抑えた検査ができた。
なお、ウェハによっては学習によって検出性能が落ちるものがある。例えば、色むらの激しいウェハや同じ位置に欠陥の連続するウェハなどにおいて検出性能の低下が顕著に現れるが、それらのウェハにおいても、ピッチ検査との併用、検出感度の調整を行うことによって、製品の性能上問題にならないパターン又はチップを良品と判定し、検査の作業効率、本来の良品率の維持を保つことができる。
A preferred embodiment of the present invention will be described with reference to the drawings.
FIG. 1 shows an
In FIG. 1A, an
As shown in FIG. 1A, the
The optical imaging mechanism 10a moves the moving unit 12 provided with the
The control arithmetic means (arithmetic processing unit) 10 b includes an
The
The
The
In FIG. 2, the image on the left is an example of the
FIG. 6 shows a pattern image and a chip image. In the surface image, a defective portion is observed at a position indicated by a star, that is, a star. The observed defect is a defect such as adhesion of a foreign substance to the circuit pattern or a partial defect of the circuit pattern.
In the reference image (reference image), the surface image (21A) of the highest
As is well known in the art, the
At that time, as preprocessing, shading processing for removing illumination unevenness by the
The
Hereinafter, an example of the optimal inspection procedure will be described.
As shown in FIG. 2, in the pattern matching inspection, an image to be compared is registered in advance.
First, a reference image (reference image) as a reference for inspection is created (recipe creation). In this case, the reference image (reference image) is, for example, one chip as shown on the left side of FIG. However, a plurality of chip images may be set as a reference image.
The reference image (reference image) is stored in a storage unit (memory) provided separately from the arithmetic processing unit of the apparatus, and is learned through the learning function of the arithmetic processing unit. After learning, the average image is stored in the storage unit as a reference image (reference image) as shown on the right side of FIG.
As a result, as shown in FIG. 3, since the left pattern matches the reference image (reference image), it is determined to be inspected, but the right pattern is different from the reference image (reference image). , It is determined that the inspection is NG.
However, in this case, since the pattern is misaligned, the pattern (or chip) of the wafer to be inspected becomes NG, but some products are desired to be OK because some pattern misalignment is not a problem. Therefore, when the non-defective product ratio (ratio of non-defective products with a small difference from the reference image) falls below a predetermined value, a reference image (reference image) is automatically recreated. For example, if the non-defective product rate suddenly drops to 95% while continuing the pattern inspection operation at a good product rate of approximately 97%, if the threshold is set to 95%, the reference image (reference image) is automatically set there. ) And restart pattern inspection at the non-defective rate.
As shown in FIG. 4, the reference before the change on the left side is set to the reference on the right side (relearning, average image change). For example, the non-defective product rate has decreased to 95%, but a reference image is re-created using a wafer pattern (or chip) having a deviation that does not cause a problem in the product as a reference image. The average image is changed, the reference image (reference image) is relearned, and the wafer pattern or chip inspection is restarted based on the reference image (reference image).
As shown in FIG. 5, when the reference image (reference image) is corrected, the inspection result is OK even if the pattern is different from the pattern before the reference image correction.
According to the present invention, for example, when the non-defective product rate is lower than the minimum 90%, for example, 85%, or another predetermined value, the re-learning process is immediately performed, and the reference image (reference image) is obtained. It is desirable to make it again.
Note that the present invention is not limited to a fixed fixed product rate (95% or other set values), and the operator can achieve a predetermined minimum product rate (for example, 90%, but not limited to this). The learning function can be adjusted to re-learn freely at any threshold within the range.
Preferably, the arithmetic control unit has a function of automatically adjusting detection sensitivity in combination with a pattern matching inspection based on a reference image (reference image). Here, the automatic sensitivity adjustment refers to a function of automatically determining the sensitivity by comparing the detectability of the pattern matching inspection and the pitch inspection.
As shown in FIG. 6, in the pattern matching inspection, as shown on the left side, the entire chip is usually compared with the entire reference image (reference image) to check whether they match, as shown on the right side. In addition, it is preferable to simultaneously perform a pitch inspection in which only a uniform pattern portion of the pattern is comparatively inspected in the inspection image.
Preferably, the sensitivity of the pattern matching inspection is adjusted so that the same defect can be detected by comparing the result of the pattern matching inspection with the result of the pitch inspection. Pattern matching detection and pitch inspection are performed on the same inspection image, and the detection sensitivity of the pattern inspection is adjusted so that the defect detection performance is almost the same.
The pattern matching inspection can inspect the entire chip, but the pitch inspection can usually inspect only the uniform pattern portion.
FIG. 7 shows a flowchart.
In this illustrated example, an inspection recipe is created with the first wafer and wafer inspection is performed. When the non-defective product rate is lower than a set value (for example, 90%), the learning process is performed on the wafer under inspection. The inspection is performed again based on the re-learned reference image (reference image). The inspection result of the re-learned reference image (reference image) is stored as the wafer inspection result, and the inspection is terminated.
It is preferable to deal with the following in response to a chip whose pattern has shifted.
Even if there is a shift in the pattern for each lot or for each wafer, it is possible to make it non-defective. If the pattern is misaligned, the generated wafer is subjected to the learning process again and inspected.
Although it is not easy for the apparatus to automatically determine whether the cause of the decrease in the non-defective product rate is a pattern shift, it is preferable to perform the learning process again when the non-defective product rate falls below a predetermined threshold value.
In a preferred aspect of the present invention, the learning process is performed again when the yield rate falls below a predetermined threshold.
In the experimental example, when the non-defective product rate was lowered and the inspection was performed again, the inspection with the excessive detection of the pattern deviation suppressed significantly.
Depending on the wafer, the detection performance may be reduced by learning. For example, a significant decrease in detection performance appears on wafers with severe color irregularities and wafers with continuous defects at the same position. Therefore, it is possible to determine a pattern or chip that does not cause a problem in performance as a non-defective product, and to maintain the work efficiency of the inspection and the original good product rate.
Claims (2)
検査中に良品率が所定の閾値以下に低下した場合、検査中のパターン又はチップの画像を用いて学習処理を再度行い新しいリファレンス画像を作成し、又は、学習処理でパターンを学習した後に均一なパターンを探し、均一なパターン部分であれば、パターンマッチング検査以外の、ピッチ検査などの検査でウェハの検査を行うか、あるいは均一パターン部分でパターンマッチング検査とピッチ検査を同時に行ない、ピッチ検査の結果からパターンマッチング検査の感度を決定し、決定した感度でウェハ全面のパターン又はチップを検査することを特徴とするウェハのパターン検査方法。 A wafer comprising a step of inputting an inspection image of a wafer pattern or chip to be inspected, comparing the input inspection image with a pre-stored reference image, and determining whether the wafer is good or bad based on a difference amount of the comparison image Pattern inspection method,
If the non-defective product rate falls below a predetermined threshold during the inspection, the learning process is performed again using the pattern or chip image being inspected to create a new reference image, or the pattern is uniform after learning the pattern through the learning process. Search for patterns, and if the pattern part is uniform, inspect the wafer by inspection other than pattern matching inspection, such as pitch inspection, or perform pattern matching inspection and pitch inspection at the same time on the uniform pattern part. A pattern inspection method for a wafer, wherein the sensitivity of the pattern matching inspection is determined from the pattern, and the pattern or chip on the entire surface of the wafer is inspected with the determined sensitivity.
演算処理手段は、検査中に良品率が所定の閾値以下に低下した場合、検査中のパターン又はチップの画像を用いて学習処理を再度行い新しいリファレンス画像を作成し、又は、学習処理でパターンを学習した後に均一なパターンを探し、均一なパターン部分であれば、パターン検査以外の、ピッチ検査などの検査でウェハの検査を行うか、あるいは均一パターン部分でパターンマッチング検査とピッチ検査を同時に行ない、ピッチ検査の結果からパターンマッチング検査の感度を決定し、決定した感度でウェハ全面のパターン又はチップを検査することを特徴とするウェハのパターン検査装置。 Means for inputting an inspection image of a wafer pattern or chip to be inspected, means for comparing the input inspection image with a pre-stored reference image, and determination means for determining the quality of the wafer based on the comparison result A wafer pattern inspection apparatus comprising:
When the non-defective product rate falls below a predetermined threshold value during the inspection, the arithmetic processing means creates a new reference image by performing the learning process again using the image of the pattern or chip under inspection, or the pattern by the learning process. After learning, search for a uniform pattern, and if it is a uniform pattern part, inspect the wafer by inspections other than pattern inspection, such as pitch inspection, or perform pattern matching inspection and pitch inspection simultaneously on the uniform pattern part, A wafer pattern inspection apparatus which determines the sensitivity of pattern matching inspection from the result of pitch inspection and inspects the pattern or chip on the entire wafer surface with the determined sensitivity.
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| CN2009801402786A CN102177429B (en) | 2008-10-16 | 2009-09-30 | Method and device for inspecting wafer pattern |
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| JP2008286708A JP5460023B2 (en) | 2008-10-16 | 2008-11-07 | Wafer pattern inspection method and apparatus |
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| KR (1) | KR20110090901A (en) |
| CN (1) | CN102177429B (en) |
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| JP2023135089A (en) * | 2022-03-15 | 2023-09-28 | トヨタ自動車株式会社 | Inspection equipment and inspection method |
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| JP5941782B2 (en) * | 2012-07-27 | 2016-06-29 | 株式会社日立ハイテクノロジーズ | Matching processing apparatus, matching processing method, and inspection apparatus using the same |
| WO2014038419A1 (en) * | 2012-09-05 | 2014-03-13 | コニカミノルタ株式会社 | Optical property measurement device, program and control device |
| KR101661023B1 (en) * | 2014-07-23 | 2016-09-29 | 에스엔유 프리시젼 주식회사 | Method for detecting defect of pattern |
| US10186028B2 (en) * | 2015-12-09 | 2019-01-22 | Kla-Tencor Corporation | Defect signal to noise enhancement by reducing die to die process noise |
| CN105702597B (en) * | 2016-02-05 | 2019-03-19 | 东方晶源微电子科技(北京)有限公司 | Multi-stage or multi-chamber inspection system |
| US10192302B2 (en) * | 2016-05-25 | 2019-01-29 | Kla-Tencor Corporation | Combined patch and design-based defect detection |
| JP6964031B2 (en) * | 2018-03-27 | 2021-11-10 | Tasmit株式会社 | Pattern edge detection method |
| WO2020071234A1 (en) * | 2018-10-05 | 2020-04-09 | 日本電産株式会社 | Image processing device, image processing method, appearance inspection system, and computer program |
| CN114121704A (en) * | 2021-11-22 | 2022-03-01 | 江苏维普光电科技有限公司 | Method for acquiring DIE distribution of semiconductor wafer |
| CN119918481A (en) * | 2025-04-03 | 2025-05-02 | 博越微电子(江苏)有限公司 | A method and system for inspecting symmetrical structure inside a chip |
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| JP2010117132A (en) | 2010-05-27 |
| TW201024716A (en) | 2010-07-01 |
| JP5460023B2 (en) | 2014-04-02 |
| KR20110090901A (en) | 2011-08-10 |
| CN102177429B (en) | 2013-12-04 |
| TWI480541B (en) | 2015-04-11 |
| CN102177429A (en) | 2011-09-07 |
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