Source: http://www.google.com/patents/US20080162065?ie=ISO-8859-1
Timestamp: 2015-04-26 17:31:04
Document Index: 445997819

Matched Legal Cases: ['art. 12', 'art. 20', 'Application No. 2004', 'art� 61', 'art� 62', 'art� 63', 'art� 64', 'arts 61', 'art� 61', 'art� 62', 'art� 62', 'art� 63', 'art� 64', 'art� 61', 'art� 63']

Patent US20080162065 - Pattern inspection apparatus - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsThe defect confirmation screen of a pattern inspection apparatus that allows the user to create a recipe and check defects easily and quickly includes a �map display part� where a wafer map is displayed, an �image display part� where a list of defect images is displayed, a �list display part�...http://www.google.com/patents/US20080162065?utm_source=gb-gplus-sharePatent US20080162065 - Pattern inspection apparatusAdvanced Patent SearchPublication numberUS20080162065 A1Publication typeApplicationApplication numberUS 12/073,083Publication dateJul 3, 2008Filing dateFeb 29, 2008Priority dateDec 17, 2004Also published asUS7355693, US7599054, US20060133661Publication number073083, 12073083, US 2008/0162065 A1, US 2008/162065 A1, US 20080162065 A1, US 20080162065A1, US 2008162065 A1, US 2008162065A1, US-A1-20080162065, US-A1-2008162065, US2008/0162065A1, US2008/162065A1, US20080162065 A1, US20080162065A1, US2008162065 A1, US2008162065A1InventorsMasayoshi Takeda, Hirokazu ItoOriginal AssigneeHitachi High-Tecnologies CorporationExport CitationBiBTeX, EndNote, RefManReferenced by (4), Classifications (10), Legal Events (1) External Links: USPTO, USPTO Assignment, EspacenetPattern inspection apparatus
US 20080162065 A1Abstract
The defect confirmation screen of a pattern inspection apparatus that allows the user to create a recipe and check defects easily and quickly includes a �map display part� where a wafer map is displayed, an �image display part� where a list of defect images is displayed, a �list display part� where detailed information on defects is displayed and set, and a �graph display part� where a graph is displayed for selected defect items. Those display parts cooperate with each other and change the defect images, defect information list, and defect graph according to selected map information. A classification code, a clustering condition, and a display filter entered using the information described above are registered in a recipe.
11. A pattern inspection apparatus comprising:
substrate holding means for holding a substrate on which a pattern is formed; application means for applying a laser beam, a beam, or a charged particle beam to the substrate held by said substrate holding means; detection means for detecting a signal generated from the substrate by the application; storage means for imaging and storing the signal detected by said detection means; comparison means for comparing the image stored in said storage means with an another image formed from a pattern identical in design; determination means for determining if defects are detected in the pattern based on the comparison result of said comparison means; display means having a map display part where positions of defects on the substrate are displayed as a map, an image display part where defect images are displayed, a list display part where a list of defect information is displayed, and a graph display part where statistical information on selected defect items is displayed as a graph; and area selection means for selecting an area included in the map displayed in said map display part, wherein, when a map area is selected by said area selection means, a list of defect images of defects in the selected map area is displayed in said image display part and a list of defect information on defects in the selected map area is displayed in said list display part. 12. The pattern inspection apparatus according to claim 11, further comprising image selection means for selecting an image displayed in said image display part wherein, when an image is selected by said image selection means and a position of a defect in said map display part corresponding to the image are highlighted.
13. The pattern inspection apparatus according to claim 11, further comprising defect information selection means for selecting defect information displayed in said list display part wherein, when defect information is selected by said defect information selection means, a position of a defect in said map display part corresponding to the defect information and a defect image in said image display part corresponding to the defect information are highlighted.
14. The pattern inspection apparatus according to claim 11, further comprising a function for plotting a group of defects, to which a predetermined classification code is assigned, in a coordinate system whose axes indicate a plurality of items representing characteristics of the defects, for displaying a boundary line for including plotted points according to a predetermined ratio, and for registering an area surrounded by the boundary line into a recipe as a condition for assigning the classification code.
15. The pattern inspection apparatus according to claim 14, further comprising means for changing the boundary line via dragging.
16. The pattern inspection apparatus according to claim 11 wherein, when a radius and a number of elements are entered as a clustering condition and when there are continuous defects, each of which has defects no fewer than the number of elements within the radius, within a distance of the radius from a defect that is a center, a cluster number is assigned to each of the defects.
17. The pattern inspection apparatus according to claim 14, further comprising a function for confirming defects displayed in said image display part after executing a review condition registered in the recipe.
18. The pattern inspection apparatus according to claim 14, further comprising a function for saving defect images displayed in said image display part after executing a review condition registered in the recipe.
19. A pattern inspection apparatus comprising:
substrate holding means for holding a substrate on which a pattern is formed; application means for applying a laser beam, a beam, or a charged particle beam to the substrate held by said substrate holding means; detection means for detecting a signal generated from the substrate by the application; storage means for imaging and storing the signal detected by said detection means; comparison means for comparing the image stored in said storage means with an another image formed from a pattern identical in design; determination means for determining if defects are detected in the pattern based on the comparison result of said comparison means; display means having a map display part where positions of defects on the substrate are displayed as a map, an image display part where defect images are displayed, a list display part where a list of defect information is displayed, and a graph display part where statistical information on selected defect items is displayed as a graph; and area selection means for selecting an area included in the map displayed in said map display part, wherein a selected map area is displayed in said graph display part. 20. The pattern inspection apparatus according to claim 19, further comprising image selection means for selecting an image displayed in said image display part wherein, when an image is selected by said image selection means, a position of a defect in said map display part corresponding to the image and a display part in said graph display part to which a defect corresponding to the image belongs is highlighted.
21. The pattern inspection apparatus according to claim 19, further comprising graph selection means for selecting a display part in said graph display part wherein, when a part of the graph is selected by said graph selection means, a position of a defect in said map display part corresponding to a defect belonging to the selected part of the graph, a defect image in said image display part corresponding to a defect included in the selected part of the graph, and a defect included in the selected part of the graph are highlighted.
22. The pattern inspection apparatus according to claim 19, further comprising a function for plotting a group of defects, to which a predetermined classification code is assigned, in a coordinate system whose axes indicate a plurality of items representing characteristics of the defects, for displaying a boundary line for including plotted points according to a predetermined ratio, and for registering an area surrounded by the boundary line into a recipe as a condition for assigning the classification code.
23. The pattern inspection apparatus according to claim 22, further comprising means for changing the boundary line via dragging.
24. The pattern inspection apparatus according to claim 19 wherein, when a radius and a number of elements are entered as a clustering condition and when there are continuous defects, each of which has defects no fewer than the number of elements within the radius, within a distance of the radius from a defect that is a center, a cluster number is assigned to each of the defects.
25. The pattern inspection apparatus according to claim 19, further comprising means for setting au upper limit value and/or a lower limit value for the graph displayed in said graph display part and a function for registering the upper limit value and/or the lower limit value in a recipe as a filtering condition.
26. The pattern inspection apparatus according to claim 22, further comprising a function for confirming defects displayed in said image display part after executing a review condition registered in the recipe.
27. The pattern inspection apparatus according to claim 22, further comprising a function for saving defect images displayed in said image display part after executing a review condition registered in the recipe.
This application is a Continuation of U.S. application Ser. No. 11/298,749, filed Dec. 12, 2005, claiming priority of Japanese Application No. 2004-366501, filed Dec. 17, 2004, the entire contents of each of which are hereby incorporated by reference.
A diffusion/re-supply type thermal field-emission electron source is used for the electron gun 10. As compared with a conventional tungsten (W) filament electron source or a cold field-emission electron source, this electron gun 10 supplies a stable electron beam current and therefore gives an electron beam image with a smaller brightness variation. In addition, the electron gun 10, which allows a large electron beam current to be set, can make a high-speed inspection as will be described later. The primary electron beam 19 is induced from the electron gun 10 by applying voltage across the electron gun 10 and the electron beam induction electrodes 11. The primary electron beam 19 is accelerated by applying a large negative potential to the electron gun 10. This causes the primary electron beam 19.to be supplied into the direction of the stage 30 with an energy corresponding to the potential. After converged by the capacitor lens 12 and narrowed by the object lens 16, the primary electron beam 19 is directed to the inspected-substrate 9 (semiconductor wafer, chip, or substrate having micro-patterns such as liquid crystals or masks) mounted on the X-Y stages 31 and 32 on the stage 30. The scan signal generator 44, which generates the scan signal and the blanking signal, is connected to the blanking polarizer 13, and the lens power supply 45 is connected to the capacitor lens 12 and the object lens 16, respectively. A negative voltage can be applied to the inspected-substrate 9 by a retarding power supply 36. By adjusting the voltage of the retarding power supply 36, the primary electron beam can be decelerated and the electron beam exposure energy applied to the inspected-substrate 9 can be adjusted to an optimum value without changing the potential of the electron gun 10.
FIG. 5 is a diagram showing an example of the defect confirmation screen displayed on the monitor 50 shown in FIG. 1. The defect confirmation screen has four display parts. The first part is a �map display part� 61 where the map of a wafer and a die is displayed. The second part is an �image display part� 62 where the images of defects selected from the map are displayed. The third part is a �list display part� 63 where the list of defect information selected from the map is displayed and the defect information is set. The fourth part is a �graph display part� 64 where statistical information on the various defect items of the defects selected from the map is displayed as a graph. The display contents of the display parts 61-64 vary as the user performs operation in each display part, thereby enabling the user to check defects and to create a recipe quickly and easily.
FIG. 6 shows an example of data configuration of a recipe. As an example, the product class data and the process data are hierarchically structured. The product class data is �wafer information� and �die layout�. The �wafer information� is information such as the wafer diameter and the wafer type (orientation flat type or notch type). The �die layout� is information on the wafer transfer unit indicating the shot size, the number of shots, the size of the die in the shot, and the number of dies.
Next, the following shows an example of process data. The process data includes �beam application condition�, �alignment�, �inspection area�, �inspection condition�, and �review condition�. The �beam application condition� indicates the retarding voltage for the electron beam to be applied to the wafer. At inspection time, this voltage value is set to acquire an image. The �alignment� indicates correction data for correcting an error generated when the wafer is transported into the sample room. An example of correction data is a die number, alignment coordinates in the die layout, and die origin offset data. The �inspection area� indicates an area used for wafer inspection. For example, the area is managed by the coordinates of the start point and the end point of the area. The �inspection condition� indicates an image processing filter, threshold, and image brightness and contrast that are applied to the actual inspection. An example of the inspection condition is a smoothing filter for reducing the noise of an image at inspection time. The �review condition� indicates a condition for observing defects after the inspection. An example of the review condition is a beam application condition, a cluster condition, a defect classification condition, and filter condition for the observation.
The process data is linked structurally to a production class. For example, when a production class has process A and process B and when process B is read and the die layout is changed, the die layout of process A is also changed. On the other hand, when the alignment data of process B is changed (for example, the alignment die is changed), process A is not affected. This recipe structure allows the same process to be changed at the same time. In a structure in which each process data unit has product class data, each of process A and process B can have its own �wafer information� and �die layout� information to which a change is made independently.
Next, the following describes the data structure of the result of wafer inspection. This data structure is defined as �inspection result data�. FIG. 7 shows an example of the data structure of inspection result and defect information. The inspection result data includes �defect information�, �recipe information�, and �runtime information�. The �recipe information� indicates information on the recipe used for the inspection. As an example, the recipe information includes all data stored in the recipe.
The �inspection information� indicates various types of data generated by the wafer inspection. For example, the �inspection information� includes the number of defects, the defect density for the inspection area, the inspection time, and the inspection date and time of day. The �defect information� indicates defect data detected by the image processing apparatus by comparing the inspection data with the reference data. For example, the �defect information� includes the �defect coordinates�, �defect address�, �defect area�, �defect size�, �aspect ratio�, �classification code�, �cluster number�, �inspection method�, �shading difference�, �defect image information�, and �defect validity flag� all of which are related to the defect ID. There are three types of �defect coordinates�: stage coordinates, in-die coordinates, and in-shot coordinates. The �defect address� indicates the die address and the shot address where the defect was detected. The �defect area� indicates the area of the defect. The �defect size� indicates the size of the defect in the X direction and the Y direction. The �aspect ratio� indicates the width-to-height ratio of the defect. There are two types of �classification codes�: an automatic classification code and a manual classification code. The automatic classification code is a code classified according to the classification condition specified by the recipe. The �cluster number� is a number generated as a result of clustering according to the cluster condition specified by the recipe. The �inspection method� indicates an inspection method by which the defect was detected. When the defect was detected both by cell comparison and die comparison, the defect is treated as a mixed defect. The �shading difference� indicates the difference in brightness of the defect between the defect determination part and the reference part. For example, a black defect is a negative value and a white defect is a positive value. The �defect image information� is image information linked to the defect image. For example, the defect image address is set as the detect image information. The �defect validity flag� is information indicating whether the defect is valid or invalid. For example, if the user wants to display or select only a defect whose defect area is equal to or smaller than a predetermined value, the validity flag is turned off for a defect whose defect area is larger than the predetermined value.
The �map display part�, �image display part�, �list display part�, and �graph display part� cooperate with each other based on the defect information selected in each display part.
For example, those display parts are implemented as a �map process�, an �image process�, a �graph process�, and a �list process� which are independent of each other and have one shared defect information saving memory area as shown in FIG. 8. Of course, each process has its own defect information saving memory area. As an example of inter-process communication, the processes are connected by a message server. Each process is connected to the message server via a socket. Therefore, each process can be connected to the message server without worrying about other processes.
The user can also specify that one or more of the display parts be excluded from the cooperation with other parts. For example, if the user always wants to display all defects in the �list display part�, the cooperation function can be turned off only for the �list display part�. The size and the display position of each of those screens can be changed freely. For example, the user can drag the edge of each part to change the display size, and drag a display part to another position to change the display position in the screen. The changed size and position can be stored as the starting coordinates and size. The setting is effective at the next startup and can be reset to the default starting coordinates and size any time the user wants. The ability to freely change the screen size and the display position provides the user with an easy-to-use screen.
The following describes each screen part in detail. First, the �map display part� 61 will be described. In the �map display part�, the whole wafer map is drawn based on the wafer information and the defect information. At least the wafer outline and the die are created based on the wafer information to build the whole wafer screen. In addition, the in-die inspection area, if drawn, could make the actually inspected area clearer. The drawn map has the following three major modes as shown in the map drawing mode shown in FIG. 9A.
The modes can be switched by the buttons. The display indicating which mode is currently used, if shown, makes the screen easier to use. In this example, (1) is assigned to the �Wafer� button, (2) is assigned to the �Die� button, and (3) is assigned to the �Shot� button. Those buttons may be changed to a combo box or radio buttons.
The operations can be switched by the buttons. The display indicating which map operation is currently executed, if shown, makes the screen easier to use. In this example, (1) is assigned to the �Arrow� button, (2) is assigned to the �Magnifying glass+Square� button, and (3) is assigned to the �Magnifying glass� button. Those buttons may be changed to a combo box or radio buttons. Combining the three map modes with the three operations makes the relation of the wafer map information and the defect information easier to understand. For example, if the user wants to observe multiple defects that which concentrate in a particular part of the wafer, all at a time, the user can select map mode (1) and map operation (2) to select all concentrated defects.
The user specifies a start point and an end point in the map by dragging on the screen as shown in FIG. 10 to notify the defects in the selected area to the �image display part�, �list display part�, and �graph display part� for displaying the information on the defects in the area.
The user specifies a point and a radius in the map by dragging on the screen as shown in FIG. 11 to notify the defects in the selected area to the �image display part�, �list display part�, and �graph display part� for displaying the information on the defects in the area.
The user specifies a die in the map by clicking on it as shown in FIG. 12 to notify the defects in the selected die to the �image display part�, �list display part�, and �graph display part� for displaying the information on the defects in the die.
Next, the following describes the �image display part� 62. In the �image display part� 62, the image of at least one defect notified from the map is displayed. Any size of a display image can be specified, for example, by the number of pixels. Displayed images are those stored in the image processing unit (hereinafter called an inspection images). The images may be those output internally or externally during the inspection. An image re-acquired after the inspection can also be displayed. Because one image to hundreds of thousands of images can be displayed, the scrollbar can be provided to allow the user to move through the display part easily. Instead of the scrollbar, tabs can also be provided to allow the user to easily move through the display part.
When the user selects a defect displayed in the image display part, the selection is notified also to the �map display part�, �list display part�, and �graph display part�. In response to the notification, the corresponding defect in the map is highlighted in the �map display part�. In addition, in response to the notification, the information on the corresponding defect is highlighted in the �list display part�. In addition, the component part of the graph, to which the corresponding defect belongs, is highlighted in the �graph display part�. Instead of a highlight display, it is also possible to change the display color or to display a navigation line.
Next, the following describes the �list display part� 63. The function of the �list display part� is divided roughly into the following two functions:
The function to display defect information list displays detailed information on at least one defect notified from the map display part. The user can select the detailed information items of the defects to be displayed. Because the display list can contain one entry to hundreds of thousands of entries, the toolbar can be provided to allow the user to move through the display part easily. Instead of the toolbar, tabs can also be provided to allow the user to easily move through the display part. By selecting items of the list, the list can be sorted in ascending order or descending order by the selected items. The �select� item is provided as a list item other than the defect information. When there is a setting item to be applied only to a part of the defects obtained from the map display part, this �select� checkbox can be used to apply information only to the defects checked by this �select� checkbox. For example, when a classification code is set at a time or a clustering group is set, it is sometimes desired to assign the same classification code and the clustering number to the defects other than specific defects. In such a case, this �select� item button is pressed to inactivate the sort function of the other defect information but to activate the all-select and all-deselect function.
The user wants to specify a classification code individually for each item in some case while, in some other case, to specify the same code for all the selected defects. To meet this need, the function to specify a classification code for multiple defects at a time is provided. To specify a classification code at a time, the user checks the �All� checkbox and enters a classification code. Then, the entered classification code is assigned to all the �selected� defects.
When the user selects a defect from the displayed list, the selection is notified to the �map display part�, �image display part�, and �graph display part�. In response to the notification, the corresponding defect is highlighted in the map in the �map display part�. In addition, in response to the notification, the edge of the image of the corresponding defect is highlighted in the �image display part�. In addition, the component part of the graph, to which the corresponding defect belongs, is highlighted in the �graph display part�. Instead of a highlight display, it is also possible to change the display color or to display a navigation line.
Next, the following describes the �graph display part� 64. The function of the �graph display part� is divided roughly into the following two functions:
The function to graphically display defect information is used to display a graph with the axes of the graph indicating the specified defect information items and the number of displayed defects. A bar graph or a line graph can be displayed according to the user's selection. The defect information to be displayed in the graph can be specified by the combo box. The items that can be displayed are all defect information including �defect ID�, �coordinates�, �size�, and �shading difference�. Instead of the combo box, radio buttons or pre-set buttons can also be used to select defect information to be displayed. To scale the graph, the �Magnifying glass� button of the �map display part� can be used also in the �graph display part�. The �Magnifying glass� button is used to scale a specific part of the graph. The scaled graph information is held until the next time the �Magnifying glass� button is pressed.
The function to set a defect display filter for the displayed map is used to set filtering information on the defects to be displayed in the map using the graph display function. This entry function allows the user to graphically enter filter information from a graph. When the �Enter graph� button is pressed, the user can enter the upper limit and the lower limit. As the user drags the upper and lower limits, the display in the �map display part� 61 is changed accordingly and the defect distribution is changed. The user enters the upper limit and the lower limit, for example, by clicking the right button of the mouse on the graph to set the upper limit, and the left button to set the lower limit, with the �Enter graph� button held. As shown in FIG. 13, the upper limit and lower limit boundary lines are drawn in the corresponding parts each time the user clicks the mouse. At the same time the upper and lower limits of the graph are set, the number of defects displayed in the �list display part� 63 is also changed.
The �Display filter� button can be used to confirm the executed filter condition. As shown in FIG. 14, a filter condition entered from the graph can be confirmed by the �Display condition dialog�. This function allows the user to edit or re-execute a filter condition visually entered from the graph. This function also allows the user to display and execute a filter condition, which is difficult to enter from the graph, for more efficient execution of a display filter. For example, the user can specify two parameters, a radius and the number of elements, to set up a clustering condition. When there is a set of defects satisfying the specified cluster condition, that is, when there are defects, each of which has defects no fewer than the specified number of elements within the specified radius, within the distance of the specified radius from one particular defect that is the center, a cluster number is assigned to each of those defects. At this time, it is also possible to assign cluster numbers, one for each die, to a die, a shot, or a wafer by selecting the range where the defect search is made. In addition, by specifying two parameters, that is, in-die defect-to-defect distance or in-shot defect-to-defect distance and the number of elements, the same cluster number can be assigned to the reticle defects detected in the same die-coordinates or shot coordinates. That is, when there are defects, each of which has defects no fewer than the specified number of elements within the specified radius in the die coordinates or shot coordinates, within the distance of the specified radius from one particular defect that is the center, a cluster number is assigned to each of those defects.
First, the cooperative operation started in the �map display part� is executed as follows. When the user selects a defect in the map, the map process notifies the selected defect ID to the �image process�, �graph process�, and �list process� via broadcasting or a file. The �map process�, �image process�, and �list process� highlight the notified defect ID. The �graph process� highlights the graph part to which the selected defect ID belongs.
Second, the cooperative operation started in the �image display part� is executed as follows. When the user selects a defect from the image display part, the image process notifies the selected defect ID to the �map process�, �graph process�, and �list process� via broadcasting or a file. The �map process�, �image process�, and �list process� highlight the notified defect ID. The �graph process� highlights the graph part to which the selected defect ID belongs.
Third, the cooperative operation started in the �list display part� is executed as follows. When the user selects a defect from the list display part, the list process notifies the selected defect ID to the �map process�, �image process�, and �graph process� via broadcasting or a file. The �map process�, �image process�, and �list process� highlight the notified defect ID. The �graph process� highlights the graph part to which the selected defect ID belongs.
Fourth, the cooperative operation started in the �graph display part� is executed as follows. When the user selects a defect from the graph display part, the graph process notifies all defect IDs corresponding to the selected graph display part to the �map process�, �image process�, and �list process� via broadcasting or a file. The �map process�, �image process�, and �list process� highlight all notified defect IDs. The �graph process� highlights the graph part to which the selected defect ID belongs.
The user can select multiple defects from the �map display part�, �image display part�, and �list display part�. The following describes the relation among data in that case.
First, the selection of multiple defects from the �map display part� is triggered by the mouse drag operation in a part of the defect distribution map where multiple defects are included. An area can be selected by entering the �start point/end point� or �center/radius�. When a defect selection area is created in the defect distribution map, the �map process� calculates the stage coordinates corresponding to the area and the number of the die including the area. For the defects in the die whose number is calculated, the map process calculates whether the defects are within the selected area based on the stage coordinates. The process notifies the IDs of defects, which are determined to be in the area, to the �image process�, �list process�, and �graph process� via broadcasting or a file. The �map process�, �image process�, and �list process� highlight all notified defect IDs. The �graph process� highlights the graph part to which the selected defect IDs belong. Instead of highlighting the graph part in the graph display part, it is also possible to change the color according to the number of notified defects corresponding to the graph or to provide an area within the graph display part where the number of selections is displayed.
Second, the selection of multiple defects from the �image display part� is triggered by the mouse drag operation, or by the mouse click operation with the Shift button and the Ctrl button held on the keyboard, in a part of the image list where multiple defects are included. Each time a defect selected from the image display part is updated, the defect ID is notified to the �map process�, �list process�, and �graph process�. In response to the notification, the processes update the display based on the notified defect ID.
Third, the selection of multiple defects from the �list display part� is triggered by the mouse click operation, or by the mouse click operation with the Shift button and the Ctrl button held on the keyboard, in a part of the list where multiple defects are included. Each time a defect selected from the list display part is updated, the defect ID is notified to the �map process�, �image process�, and �graph process�. In response to the notification, the processes update the display based on the notified defect ID.
The die overlap function and the shot overlap function in the defect distribution map are available as an extended function of defect confirmation. FIG. 15 shows a defect die map generated by overlapping all inspected dies using the in-die coordinates of the �defect coordinates� of the defect information. FIG. 16 shows a defect shot map generated by overlapping all inspected shots using the in-shot coordinates of the �defect coordinates� of the defect information. Although all dies and all shots are overlapped in those examples, it is also possible to create a defect map of only the selected dies and shots rather than all inspected dies and shots. Because one die is created in the X direction, and two dies in the Y direction, in one shot in the example shown in the figure, FIG. 16 shows the map of one shot (two dies). This overlap function allows the user to find the tendency and distribution of defects that are not found only by checking the wafer map and to easily detect the defects detected in the same area of different dies or different shots. The cooperative operation of the display parts using this die overlap function and the shot overlap function is the same as that for the normal defect distribution map.
For example, when the characteristic defect information is �shading difference�, �size�, �area�, and �aspect ratio (width-to-height ratio)� as shown in FIG. 17A, the �shading difference�, �size�, �area�, and �aspect ratio� items of the defects assigned to the classification code 1 are added up and the variance of each item is calculated. After that, at least one item is automatically selected in ascending sequence of variances beginning with the lowest variance. In this example, two items are selected and the defects are classified two-dimensionally. A classification area is specified using a square or an ellipse so that the specified classification code 1 is assigned to more than the specified classification percent of the selected defects. The specified classification percent, which has the default value of 3σ, is a parameter that can be changed. The classification area determined in this manner is registered in the recipe as the definition of the classification code 1 and, from this time on, the classification code 1 is automatically assigned to a defect that will belong to this area. The same processing is performed for the classification code 2 as shown in FIG. 17B to create a classification area. If multiple classification codes are assigned to a defect, the code is determined according to the predetermined classification code priority.
The user can graphically confirm and easily change those �classification areas� in the graph. To change a classification area, the user dynamically drags the line that forms the classification area of the graph displayed in the right half of FIG. 17A or FIG. 17B. The user can also specify classification code priority for each recipe and, in addition, can select a square for the shape of a classification area although the default is an ellipse. If �in-die coordinates� and �in-shot coordinates� are added to the axis components of this classification area, a �reticle defect� that may be detected in the same coordinates of other dies or in the same coordinates of other shots can also be recognized easily.
Those three processing functions are executed after the inspection to set up a hierarchically structured defect image sample condition in the recipe, as shown in FIG. 18, to help the user to check the defects highly efficiently after the inspection. This hierarchically structured defect image sample condition is used when the following are automatically set by the recipe as shown in FIG. 18: �classification code� information that is assigned automatically to a defect, which is plotted in a special area associated with some defect characteristics, based on the information shown in FIG. 17; �cluster number� that is assigned to each of the defects, each of which has defects not fewer than the specified number of elements within the specified radius, from one particular defect that is the center; and �defect validity flag� that is assigned for selecting only valid defects. For example, the hierarchically structured defect image sample condition described above is used to select only the defects with a particular classification code from cluster defects, to which a cluster number is assigned, based on the valid defects. It is possible to select only an arbitrary number of defects, which are to be observed or whose defect images are to be obtained, from the selected defects. Similarly, only those defects with no cluster number are selected from defects, to which a particular classification code is assigned, based on the valid defects. It is possible to select only an arbitrary number of defects, which are to be observed or whose defect images are to be obtained, from the selected defects. A hierarchically structured defect image sample condition like this can be used not only as an image sample condition but also in defect confirmation. Therefore, the condition is registered in the recipe and at the same time registered externally as a review condition file to allow the user to simply load it as a review condition when loading another recipe.
Referenced byCiting PatentFiling datePublication dateApplicantTitleUS8312401 *Jan 13, 2011Nov 13, 2012Elitetech Technology Co., Ltd.Method for smart defect screen and sampleUS20120185818 *Jan 13, 2011Jul 19, 2012Iyun LeuMethod for smart defect screen and sampleWO2012006221A1 *Jun 30, 2011Jan 12, 2012Rudolph Technologies, Inc.Scratch detection method and apparatusWO2013140302A1 *Mar 13, 2013Sep 26, 2013Kla-Tencor CorporationMethod, computer system and apparatus for recipe generation for automated inspection semiconductor devices* Cited by examinerClassifications U.S. Classification702/82International ClassificationG01N23/225, H01L21/66, G01N21/956, G06F19/00, G01N37/00Cooperative ClassificationG01N21/8851, G01N21/95607, G01N2021/8416European ClassificationG01N21/956ALegal EventsDateCodeEventDescriptionMar 6, 2013FPAYFee paymentYear of fee payment: 4RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services