Abstract:
To make it possible to produce inspection conditions for optimizing various inspection conditions by extracting DOIs efficiently and instructing them reliably in a state where a few DOIs are hidden among a large number of nuisances. According to the present invention, a semiconductor wafer is inspected, images of defects detected by the inspection are shown on a screen, and an input interface is provided through which any given defect can be selected from among the defects whose images are shown. The inspection is conducted in such a way that the inspection conditions are adjusted to enhance capabilities for detecting the defect instructed by a user.

Description:
BACKGROUND OF THE INVENTION  
       [0001]     1. Field of the Invention  
         [0002]     The present invention relates to a technology for inspecting semiconductor wafers. In particular, it relates to a method and an apparatus which can be applied effectively to various condition-producing methods for defect judgment, defect image processing, defect classification, etc. of the inspection apparatus.  
         [0003]     2. Description of the Prior Art  
         [0004]     As electronic products are getting smaller and having more functionality, semiconductors are also becoming considerably smaller, and new semiconductor products are being introduced on the market one after another. On the other hand, in semiconductor manufacturing processes, inline defect inspections of the semiconductor wafers are conducted. As a semiconductor becomes smaller, a defect causing a failure in a device, namely, a defect of interest (DOI) becomes smaller. To cope with this, more and more highly sensitive defect inspections are being conducted. As a result, many unnecessary defects (nuisances) such as microscopic asperities on the wafer surface are also detected, causing a small number of DOIs being hidden among a large number of nuisances.  
         [0005]     Accordingly, it becomes important to reliably detect the DOIs alone with respect to a new device. In order to achieve it, a condition-producing method that can properly and easily set various inspection conditions for defect judgment, defect image processing, defect classification, etc. of an inspection apparatus is indispensable.  
         [0006]     For example, U.S. Pat. No. 6,178,257 discloses an inspection apparatus comprising a classifier capable of obtaining defect images and classifying them by using data stored in advance in a database. Further, for example, JP2003-515942T discloses a data processing system wherein a user instructs how to classify defects and the system sets the classification conditions and classifies them based on the instruction and shows the classified result.  
         [0007]     A method according to the above U.S. Pat. No. 6,178,257 does not show whether or not the classification of defects is instructed in advance. In order to detect a DOI without fail, it is necessary to instruct the DOI reliably. However, it is not easy to find a few DOIs alone among a lot of nuisances and instruct them. What actually happens is that either a user is forced to check all the defects one by one and instruct them or, at the result of instructing some of the defects only, the DOI is missed and optimization of the inspection conditions cannot be achieved.  
         [0008]     Also, according to the above JP2002-515942T, a user is supposed to instruct how to classify defects. However, a specific procedure for the instruction is not shown, either.  
       SUMMARY OF THE INVENTION  
       [0009]     The present invention relates to a method and an apparatus for inspection which enable inspection-condition producing to optimize various inspection conditions for defect judgment, defect image processing, defect classification, etc. by extracting DOIs efficiently and instructing them reliably even where a few DOIs are hidden among a large number of nuisances in a defect inspection.  
         [0010]     Namely, according to the inspection method of the one aspect of the present invention, a semiconductor wafer is inspected and one or more images of the defects detected in the inspection are shown on a screen. A user selects one or more DOIs from among the shown defects. By using the selected defect as a reference, indicators are given to other defects, and one or more images of the defects to which indicators are given are shown on the screen. By referencing indicators, the user instructs one or more DOIs from among the defects shown. Optimum values of various inspection conditions of the inspection apparatus for defect judgment, defect image processing, defect classification, and so on are calculated so that the selection ratio of the instructed defect will be higher. The obtained optimum values are set in an inspection recipe, and the inspection is conducted hereafter according to the optimum inspection conditions thus set.  
         [0011]     According to the aspect of the invention, when the user select on DOI from among the defect images shown on the screen, indicators are given to all other defects by using such a DOI as a reference. Therefore, by referencing the indicators, a defect whose image feature is similar to the previously selected DOI can easily be extracted. Accordingly, it becomes possible to instruct DOIs efficiently and reliably. Further, since DOIs can reliably be instructed, it becomes possible to optimize various inspection conditions for defect judgment, defect image processing, defect classification, and so on of the inspection apparatus. Further, since the inspection can be conducted with optimum inspection conditions, even an ordinary user can make the most of capabilities of the apparatus to detect DOIs like an expert does.  
         [0012]     These and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention, as illustrated in the accompanying drawings. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0013]      FIG. 1  shows an example of a DOI search screen;  
         [0014]      FIG. 2  shows an example of a DOI search screen  2 ;  
         [0015]      FIG. 3  shows an example of a wafer reference screen;  
         [0016]      FIG. 4  shows an example of a wafer reference screen  2 ;  
         [0017]      FIG. 5  shows an example of an album referencing screen;  
         [0018]      FIG. 6  shows an example of another album reference screen;  
         [0019]      FIG. 7  shows another example of an album reference screen;  
         [0020]      FIG. 8  shows still another example of an album reference screen;  
         [0021]      FIG. 9  shows an example of a wafer select screen;  
         [0022]      FIG. 10  shows an example of prescribed processing for dividing defects into groups;  
         [0023]      FIG. 11  shows an example of prescribed processing for dividing defects into groups;  
         [0024]      FIG. 12  shows an example of a DOI extract screen;  
         [0025]      FIG. 13  shows another example of a DOI extract screen;  
         [0026]      FIG. 14  shows an example of a procedure of an inspection method including producing inspection conditions;  
         [0027]      FIG. 15  shows an example of a configuration of an inspection apparatus;  
         [0028]      FIG. 16  shows an example of a detailed configuration of a defect judging section;  
         [0029]      FIG. 17  shows another example of a detailed configuration of a defect judging section;  
         [0030]      FIG. 18  shows still another example of a detailed configuration of a defect judging section; and  
         [0031]      FIG. 19  shows an example of prescribed processing for automatically adjusting conditions. 
     
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS  
       [0032]     Now, referring to the drawings, embodiments of the present invention will be described.  
       Embodiment  1   
       [0033]      FIG. 1  shows an example of a DOI search screen which is one of the screens provided by a user interface for producing inspection conditions according to the present invention. When a condition producing button  101  on the screen is clicked, the DOI search screen is shown. There are a wafer select tab  102 , a DOI search tab  103 , and a DOI extract tab  104  on the screen. When the wafer select tab  102  is clicked, the wafer select screen is shown.  
         [0034]      FIG. 9  shows an example of the wafer select screen. Shown on the screen is a list  901  of semiconductor wafers selectable as subjects for which conditions are made. On the list  901 , information about one wafer is shown on each line. The wafer information shown includes a type name, a process name, a lot name, a wafer name, and so on. It is assumed that a wafer to be shown is inspected in advance by an inspection apparatus, an image of the portion which is judged as a defect in the defect judgment is extracted, a feature quantity of an image of each defect is calculated by image processing, and the feature quantity together with the above wafer information are inputted to the user interface. When a line of a wafer for which inspection conditions are to be made, namely, A type BB process CCC lot DDDD wafer  902  in  FIG. 9 , is clicked and an open button  903  is clicked, the wafer for which the inspection conditions are made is confirmed. When the DOI search tab  103  is clicked, the DOI search screen ( FIG. 1 ) is shown.  
         [0035]     All the defects  108  are divided into a defect group  1   109 , a defect group  2   110 , a defect group  3   111 , and a defect group  4   112 , and shown as a defect-group division tree  105 . Further, each of the defect group  1   109 , defect group  2   110 , defect group  3   111 , and defect group  4   112  is plotted in a feature-quantity space diagram  106 . A representative defect  1   113 , a representative defect  2   114 , a representative defect  3   115 , and a representative defect  4   116  of the respective defect groups are determined by prescribed processing and are shown in the feature-quantity space diagram  106 . Further, a defect image  1   117 , a defect image  2   118 , a defect image  3   119 , and a defect image  4   120  of the respective representative defects are shown. A user checks each representative defect and determines a defect group which may include a DOI. For example, if the user determines that the DOI is included in the defect group  1 , he or she double-clicks the defect image  1   117 . As a result, a DOI select screen  2  is shown.  
         [0036]      FIG. 10  shows an example of prescribed processing for dividing defects into groups and determines a representative defect. Since feature quantities for all the defects are given in advance, it is possible to plot all the defects  1002  in a feature quantity space  1001 . Two feature quantities, for example, are selected from among the given feature quantities and a feature quantity plane  1003  defined by them is set. The two feature quantities maybe selected, for example, in the order of greater variance. Alternatively, an axis with grater variance may be defined by performing a quadrature (orthogonalized) (orthogonal) projection using a known main component analysis. With respect to these two feature quantities, defects are each divided into two groups, namely, four defect groups  1004 . When dividing the defects into two groups, a known discrimination analysis, for example, may be used. Alternatively, a known clustering method such as K-means method may be used to divide defects into groups. Also, the number of groups is not limited to four, and it may be any given number. The defect nearest to a barycenter of the defect group  1005  after division is regarded as its representative defect  1006 . The representative defect is not necessarily the one nearest to the barycenter, and it may be a defect nearest to the center. Alternatively, it may be determined by other methods. With respect to each of the defect group  1005  after division, the above processing is repeated until one defect is left in the defect group. With such processing, the defect-group division tree  105  is made.  
         [0037]      FIG. 2  shows an example of the DOI select screen  2 . The defect group  1   109  is divided into a defect group  11   201 , a defect group  12   202 , a defect group  13   203 , and a defect group  14   204  by prescribed processing and shown as a defect-group division tree  105 . Further, respective defects of the defect group  11   201 , defect group  12   202 , defect group  13   203 , and defect group  14   204  are plotted in the feature-quantity space diagram  106 . A representative defect  11   205 , a representative defect  12   206 , a representative defect  13   207 , and a representative defect  14   208  of respective defect groups are determined by prescribed processing and shown in the feature-quantity space diagram  106 . Further, a defective image  11   209 , a defective image  12   210 , a defective image  13   211 , and a defective image  14   212  of the respective representative defects are shown. The user checks each representative defect and determines a defect group which may include a DOI. If one of the representative defects is the DOI, the user selects it and clicks a DOI decide button  213 . The selected defect is recorded as the DOI.  
         [0038]     Further, on the DOI search screen ( FIG. 1 ) and DOI search screen  2  ( FIG. 2 ), a first feature-quantity button  122  and a second feature-quantity button  125  may be provided. When the first feature-quantity button  122  is clicked, a feature-quantity select menu  123  is shown. When a feature quantity is selected from the feature-quantity select menu  123 , the feature quantity is shown on the horizontal axis  124  of the feature quantity space diagram  106 . Similarly, when the second feature-quantity button  125  is clicked, the feature-quantity select menu  123  is shown. When a feature quantity is selected from the feature-quantity select menu  123 , the feature quantity is shown on the vertical axis  126  of the feature-quantity space diagram  106 .  
         [0039]     Further, a feature-quantity weight button  121  may be provided in the DOI search window ( FIG. 1 ) and DOI search window  2  ( FIG. 2 ). When the feature-quantity weight button  121  is clicked, the feature-quantity weight window  127  is shown. In the feature-quantity weight window  127 , a weight entry field  128  for each feature quantity is provided. The user enters a weighting value in the weight entry field  128  and clicks an OK button  130 . The weighting value thus entered is used when defects are divided by prescribed processing.  
         [0040]     Further, on the DOI search screen ( FIG. 1 ), a wafer reference button  129  may be provided. When the wafer reference button is clicked, a wafer referencing screen is shown.  
         [0041]      FIG. 3  shows an example of the wafer reference screen. On the screen, a list  301  of semiconductor wafers that can be selected as wafers to be referenced is shown. Information about one wafer is shown on each line of the list  301 . Information about a wafer to be shown includes a type name, a process name, a lot name, and a wafer name. It is assumed that the wafer to be shown is inspected in advance by an inspection apparatus, an image of its portion which is judged as a defect by defect judgement is extracted, a feature quantity of the image of each defect is calculated by image processing, a DOI is extracted, and the feature quantity and extracted DOI are inputted to a user interface together with the wafer information described above. When a line of a wafer to be referenced (I type JJ process KKK lot LLLL wafer  302 , in  FIG. 3 ) is clicked, and an open button  903  is clicked, a wafer to be referenced is confirmed and a wafer reference screen  2  is shown.  
         [0042]      FIG. 4  shows an example of the wafer reference screen  2 . All the defects  108  are divided into a defect group  1   109 , a defect group  2   110 , a defect group  3   111 , and a defect group  4   112 , and shown as a defect-group division tree  105 . Further, defects of the defect group  1   109 , defect group  2   110 , defect group  3   111 , and defect group  4   112  are plotted in the feature-quantity space diagram  106 . A boundary line  1   401 , a boundary line  2   401 , and a boundary line  3   403  of respective defect groups are shown in the feature-quantity space diagram  106 . Further, a defect image  1   117 , a defect image  2   118 , a defect image  3   119 , and a defect image  4   120  of respective defect groups are shown. It is possible to scroll each defect image, and the user selects a DOI by checking each defect image and clicks a DOI decide button  213 . The selected defect is recorded as the DOI.  
         [0043]      FIG. 11  shows another example of prescribed processing for dividing defects into groups and determining a representative defect. The feature quantities about all the defects are given in advance. Therefore, all the defects  1002  can be plotted in the feature-quantity space  1001 . A boundary area  1101  of the DOI of the referenced wafer given is superimposed over the feature-quantity space  1001 . If the boundary area of the DOI and the distribution area of all the defects are not aligned, the boundary area of the DOI is adjusted. Being based on the boundary area  1102  after the adjustment, all the defects are divided into defect groups. The defect nearest to the barycenter of a defect group after division is regarded as a representative defect  1103  of the defect group. A defect-group division tree  105  is determined.  
         [0044]     Further, in the DOI search screen ( FIG. 1 ), an album reference button  130  may be provided. When the album reference button  130  is clicked, an album reference screen is shown.  
         [0045]      FIG. 5  shows an example of the album reference screen. On the screen, a defect image  501  that can be selected as a subject for album referencing is shown. It is assumed that the defect to be shown is inspected in advance by the inspection apparatus, an image of the portion judged as an defect by the defect judgment is extracted, a feature quantity of the image of each defect is calculated by image processing, extracted as a DOI, and the defect image and feature quantity are inputted to the user interface. When the image of the defect for which an album is referenced (a broken wire  1   502 , in  FIG. 5 ) is clicked and a defect select button  503  is clicked, a subject defect of the album referencing is confirmed and the subject defect  504  is plotted in the feature-quantity space diagram  106 . In the same way as described above, the user checks defect groups whose subject defect  504  is plotted and its representative defect, and determines the defect group which may include a DOI. Then, the user double-clicks a defect image corresponding such a defect group. As a result, the DOI select screen  2  ( FIG. 2 ) is shown. By checking each representative defect, the user determines a defect group which may include a DOI. If one of the representative defects is the DOI, the user selects it and clicks the DOI decide button  213 . The selected defect is recorded as the DOI.  
         [0046]      FIG. 6  shows another example of the album reference screen. On the screen of  FIG. 5 , defect images  501  that can be selected as subjects for album referencing are shown. It is assumed that the defect to be shown is inspected in advance by the inspection apparatus, an image of the portion which is judged as a defect by the defect judgment is extracted, the feature quantity of the image of each defect is calculated by image processing and extracted as a DOI, and the defect image and feature quantity are inputted to the user interface. When an image of the defect for which album referencing is to be conducted (a broken wire  1   502 , in  FIG. 6 ) is clicked and the defect select button  503  is clicked, the subject defect for album referencing is confirmed and the screen of  FIG. 6  is shown. The subject defect  504  is plotted in the feature-quantity space diagram  106 . All the defects are plotted in the feature-quantity space diagram. All the defects are sorted in the rθ coordinate system by using the subject defect  504  as a reference, and the defect image  601  is shown. The defect image can be scrolled in the rθ directions. The user selects a DOI by checking each defect image, and clicks the DOI decide button  213 . The selected defect is recorded as the DOI.  
         [0047]      FIG. 7  shows another example of album referencing. On the screen, a defect image  501  which can be selected as a subject for album referencing is shown. It is assumed that the defect to be shown is inspected in advance by the inspection apparatus, an image of a portion which is judged as a defect by the defect judgment is extracted, a feature quantity of the image of each defect is calculated by image processing, extracted as a DOI, and both the defect image and feature quantity are inputted to the user interface. When the image of the defect for which album referencing is to be conducted (a broken wire  1   502 , in  FIG. 7 ) is clicked and the defect select button  503  is clicked, a subject defect for album referencing is confirmed. Using the subject defect as a reference, all the defects are arranged according to the closeness to the subject defect in the feature quantity space, and the defect image  701  is shown. The defect image can be scrolled, and the user selects a DOI by checking each defect image and clicks the DOI decide button  213 . The selected defect is recorded as the DOI.  
         [0048]      FIG. 8  shows another example of album referencing. A defect image  501  which can be selected as a subject for album referencing is shown on the screen. It is assumed that the defect to be shown is inspected in advance by the inspection apparatus, an image of a portion which is judged as a defect by defect judgment is extracted, a feature quantity of the image of each defect is calculated by image processing, extracted as a DOI, and the defect image and feature quantity are inputted to the user interface. When an image of the defect for which album referencing is conducted (a broken wire  1   502 , in  FIG. 8 ) is clicked and the defect select button  503  is clicked, a subject defect for album referencing is confirmed. Each feature quantity of the subject defect is shown on a feature quantity display bar  801 . Using the subject defect as a reference, defects are arranged according to the closeness to the subject defect in the feature quantity space and the defect image  802  is shown. Further, each feature quantity of the defect  803  at the left end of the defect image  802  is shown on the feature-quantity display bar  804 . The user can change the feature quantity on the feature-quantity display bar  804 . Using the changed feature quantity as a reference, defects are renewed and arranged according to the closeness to the subject defect in the feature quantity space, and the defect image  802  is also renewed and displayed. The user selects a DOI by checking each defect image and clicks the DOI decide button  213 . The selected defect is recorded as the DOI.  
         [0049]     When the DOI selection is over, the DOI is extracted. When a DOI extract tab  104  is clicked on the DOI search screen ( FIG. 1 ), DOI search screen  2  ( FIG. 2 ), wafer reference screen  2  ( FIG. 4 ), and album reference screens (FIGS.  5  to  8 ), a DOI extract screen is shown.  
         [0050]      FIG. 12  shows an example of the DOI extract screen. All the defects are plotted in the feature-quantity space diagram  106 . There are provided a first feature-quantity button  122  and a second feature-quantity button  125 . When the first feature-quantity button  122  is clicked, a feature-quantity select menu  123  is shown. When a feature quantity is selected from the feature-quantity select menu  123 , the feature quantity is shown on the horizontal axis  124  in the feature-quantity space diagram  106 . In the same way, when the second feature-quantity button  125  is clicked, the feature-quantity select menu  123  is shown.  
         [0051]     When a feature quantity is selected from the feature-quantity select menu  123 , the feature quantity is shown on the vertical axis  126  of the feature-quantity space diagram  106 . Also, the searched DOI  1201  is plotted in the feature-quantity space diagram  106 . A boundary line  1   1202 , a boundary line  2   1203 , a boundary line  3   1204 , and a boundary line  4   1205  are shown in the upper, lower, left, and right directions of the searched DOI  1201 . Each boundary line is movable in the upper and lower, or left and right directions. When the user clicks and selects one of the boundary lines, an image  1206  of the defect inside and close to the boundary line and an image  1207  of the defect outside and close to the boundary line are shown. In  FIG. 12 , the boundary line  4   1205  is selected, the image  1206  of the defect inside and close to the boundary line is shown on the left of the boundary line  1208  and the image  1207  of the defect outside and close to the boundary line is shown on the right of the boundary line  1208 .  
         [0052]     When the user moves the boundary line  4   1205 , the defect close to the boundary line changes accordingly. Therefore, the image of the defect shown also changes. The user checks the defects shown, and moves the boundary line  4   1205  so that a defect judged as a DOI is inside the boundary line. This is similarly done with respect to the upper, lower, left, and right boundary lines. Further, as required, the first and second feature quantities are selected again and the above processing is similarly performed. When the above processing has been performed with respect to all the feature quantities, the DOI decide button  1209  is clicked and all the DOIs are confirmed.  
         [0053]     Another example of the DOI extract screen is shown. If the wafer reference has been selected during the DOI search, when the DOI extract tab  104  is clicked on the wafer reference screen  2  ( FIG. 4 ), the DOI extract screen  2  is shown.  
         [0054]      FIG. 13  shows another example of the DOI extract screen. An upper limit  1302  and a lower limit  1303  of the feature quantity with respect to the DOI of the referenced wafer are shown on the feature-quantity display bar  1301 . A left cursor  1304  and a right cursor  1305  of the feature-quantity display bar  1301  are movable. When the user clicks and selects one of the cursors of the feature-quantity display bar, an image  1306  of the defect inside and close to the cursor and an image  1307  of the defect outside and close to the cursor are shown. When the user moves the cursor, the defect close to the cursor changes accordingly. Therefore, the image of the defect shown also changes. The user checks the defect shown, and moves the cursor so that the defect judged as a DOI is inside the cursors The same processing is performed with respect to right and left cursors of all the feature quantities. When the above processing has been performed with respect to all the feature quantities, the DOI decide button  1209  is clicked to confirm all the DOIs.  
         [0055]     Using the DOI extracted by the above process as instruction data, defect classification is performed based on prescribed classification conditions and the evaluation value of the capability to detect DOIs is calculated. The evaluation value is calculated, for example, by the following expression. 
 
Evaluation value=DOI detection rate−Constant×Nuisance rate 
 
         [0056]     Various conditions such as defect judgment, defect image processing, and defect classification are automatically adjusted by prescribed processing so that the above evaluation value reaches a maximum. Thus, the condition presenting of the inspection is achieved.  
         [0057]      FIG. 19  shows an example of prescribed processing for automatically adjusting various conditions. For example, in the image processing  1901 , suppose x coordinate  1902  of the image is on the horizontal axis and the brightness difference  1903  is on the vertical axis, and a threshold  1904  is set with respect to the brightness difference  1903 . If it is regarded that the area above the threshold  1904  is a defect portion  1905 , the range of the x coordinate  1902  of the corresponding image is a feature quantity, which is the size  1906  of the defect. When the threshold value  1904  is changed, the portion corresponding to the defect portion  1905  is changed. Accordingly, the feature quantity, namely, the size  1906  of the defect, which is the range of the x coordinate  1902  of the corresponding image is changed. By this threshold change  1907 , the distribution of the defect groups in the feature quantity space  1908  is changed.  
         [0058]     In the processing of defect classification  1909 , the distribution of the frequency  1917  with respect to the feature quantity selected in the feature quantity selection  1910  is changed by the above threshold change  1907 . Accordingly, in the processing of the threshold calculation  1911 , the threshold  1914  for differentiation between the DOI  1912  and nuisance  1913  changes. Accordingly, the detection result  1918  of the DOI  1912  and nuisance  1913  is changed. Accordingly, in the evaluation value calculation  1915 , the evaluation value  1916  is changed. The above processing is repeatedly and sequentially optimized so that the evaluation value  1916  reaches a maximum.  
         [0059]     To sum up, an example of the process of the inspection method including the inspection-condition making will be shown in  FIG. 14 . The whole process comprises two steps of inspection-condition producing  1401  and a normal inspection  1402 . In the inspection-condition producing  1401 , defect judgment  1403  is performed on a semiconductor wafer to obtain a defect image  1404 . The image processing  1405  is performed on the obtained defect image  1404  to extract a feature quantity  1406  of the defect. By using the obtained feature quantity  1406 , DOI search  1407  is performed. In the DOI search  1407 , defects are divided into groups according to the feature quantity and defect image display  1408  is executed. Then, the user refers to the defect image shown, and selects a representative DOI  1409  in the DOI selection  1422 . By using the representative DOI  1409  as a reference, DOI extraction  1410  is performed.  
         [0060]     In the DOI extraction  1410 , an indicator obtained from the feature quantity with respect to other defects by using the selected representative DOI  1409  as a reference is added and the defect image display  1411  is executed. Then, the user refers to the defect image shown and performs DOI instruction  1412  to obtain a DOI group  1413 . The inspection-condition optimization  1414  for calculating the optimum value of each inspection condition for defect judgement, image processing, and defect classification is executed so that the obtained DOI group  1413  may be most properly classified in the defect classification to obtain an optimum inspection condition  1415 . In the normal inspection  1402 , the obtained inspection condition  1415  is set in an inspection recipe and defect judgment  1416  is performed on a semiconductor wafer to obtain a defect image  1417 . Image processing  1418  is performed on the obtained defect image  1417  to extract the feature quantity  1419  of the defect. By executing the defect classification  1420  using the obtained feature quantity  1419 , a detected DOI  1421  is obtained.  
         [0061]     The best defect-classification result about the subject wafer is obtained when the step of the inspection-condition producing  1401  is over. Therefore, the step of the inspection-condition producing  1401  may be regarded as a procedure for the inspection method.  
         [0062]     Further, in the step of the inspection-condition producing  1401 , instead of the DOI extraction  1410 , the DOI search  1407  may be repeated to select the required number of DOIs.  
         [0063]     Further, if there are two or more types of DOIs, the DOI search  1407  and DOI extraction  1410  may be repeated as many times as the number of types of DOIs.  
         [0064]      FIG. 15  shows an example of the configuration of the inspection apparatus according to the present invention. The procedure is the one shown in  FIG. 14 . This inspection apparatus comprises: a defect judging section  1501  judging a defect of a semiconductor wafer and extracting a defect image; an image processing section  1502  processing the image of the defect and extracting its feature quantity; a defect classifying section  1503  calculating the feature quantity and classifying defects; a defect-indicator calculating section  1504  calculating the feature quantity and adding (giving) an indicator to the defect(s); a condition optimizing section  1505  calculating the inspection conditions, feature quantity of the defect, and defect classification to calculate an optimum condition; a data storing section  1506  storing the inspection condition(s), defect image(s), feature quantity of the defect, and defect classification; and a user interface section  1507  to show the defect image and feature quantity of the defect on a screen and to which a user inputs a defect classification instruction and feature quantity designation. Those sections are connected with one another so that the data can be exchanged among them as required. Further, the components other than the defect judging section  1501  may be connected with one another inside the inspection-condition producing server  1508  and connected with the detect judging section  1501  outside the inspection-condition producing server  1508 .  
         [0065]      FIG. 16  shows an example of a detailed configuration of the defect judging section  1501 . The defect judging section  1501  comprises: an electron beam source  1601  producing electron beams  1602 ; a deflector  1603  deflecting the electron beams  1602  from the electron beam source  1601  in the x direction; an objective lens  1604  converging the electron beams  1602  to a semiconductor wafer  1605 ; a stage  1606  moving the semiconductor wafer  1605  in the Y direction upon deflection of the electron beams  1602 ; a detector  1608  detecting secondary electrons etc.  1607  from the semiconductor wafer  1605 ; an A/D converter  1609  analog-to-digital converting the detected signals into digital images; an image processing circuit  1610  comprising a plurality of processors comparing the detected digital image with a digital image of a place where the image is expected to be originally the same and judges the place as a defect candidate when a difference is found and electric circuits such as an FPGA; a detection-condition setting section  1611  setting conditions of the portions related to forming images such as the electron beam source  1601 , deflector  1602 , objective lens  1604 , detector  1608 , and stage  1606 ; a judging-condition setting section  1612  setting conditions of judging defects for the image processing circuit; and an overall control section  1613  controlling the whole system.  
         [0066]      FIG. 17  shows another example of the detailed configuration of the defect judging section  1501 . The defect judging section  1501  comprises: alight source  1712 ; an objective lens  1704  converging light beams from the light source  1712  to a semiconductor wafer  1705 , a stage  1706  moving the semiconductor wafer  1705  in the Y direction; an image sensor  1714  detecting reflected light from the semiconductor wafer  1705  and obtaining an analog-to-digital converted detected image  1715 ; a memory  1716  storing the detected digital image and outputting the stored image  1717 ; an image processing circuit  1710  comprising a plurality of processors comparing the detected image  1715  with a stored image  1717  and judges the image as a defect candidate and an electric circuit such as an FPGA; a detection-condition setting section  1718  setting the conditions of the portions related to forming images such as the light source  1712 , objective lens  1704 , image sensor  1714 , and the stage  1706 ; a judging-condition setting section  1719  for setting conditions of judging defects for the image processing circuit; and an overall control section  1720  for controlling the whole system.  
         [0067]      FIG. 18  shows another example of the detailed configuration of the defect judging section  1501 . The defect judging section  1501  comprises: a stage  1801  on which a subject  1811  is placed and displacement coordinates of the subject  1811  are measured; a stage driving section  1802  driving the stage  1801 ; a stage control section  1803  controlling the stage driving section  1802  based on the displacement coordinates of the stage  1801  measured from the stage  1801 ; an oblique illumination optical system  1804  obliquely illuminating the subject  1811  placed on the stage  1801 ; a detection optical system  1807  comprising a collective lens  1805  collecting scattered light beams (diffracted light of a lower-order other than zero-order) from the surface of the subject  1811  and a photoelectric converter  1806  comprising a TDI, a CCD sensor, etc.; an illumination control section  1808  controlling amount of light irradiated to the subject  1811  by the oblique illumination optical system  1804 , an illuminating angle, etc; a judging circuit (inspection algorithm circuit)  1809  aligning an inspected image signal obtained from the photoelectric converter  1806  and the standard image signal (reference image signal) obtained from a neighboring chip or a cell, comparing the aligned detected-image signal with the reference image signal to extract a difference image, judging the extracted difference image by using a prescribed threshold set in advance to detect an image signal showing a defect, and judging the defect based on the image signal showing the detected defect; and a CPU  1810  performing various processing on the defect judged by the judging circuit  1809  based on a stage coordinate system obtained from the stage control section  1803 .  
         [0068]     The invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiment is therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.  
                                                                                                                                                                                                                                                                             FIG. 1         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                                             Boundary line                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4                    106                                 Feature quantity space                    108   All       109   Defect group 1       110   Defect group 2       111   Defect group 3       112   Defect group 4                                             Defect image                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4               121   Weight feature quantity       122   First feature quantity       123   Feature-quantity select menu                                             Second feature quantity                                             Second feature quantity                                             Gray level difference                                             Gray level value                                             Size X                                             Size Y                                             First feature quantity               125   Second feature quantity                                             Second feature quantity               127   Feature-quantity weighting window                                             Gray level difference                                             Gray level value                                             Size X                                             Size Y                                             Cancel               129   Reference wafer       130   Reference album       213   Decide DOI                                             Save                                             End                 FIG. 2         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                    106                                 Feature quantity space                    108   All       109   Defect group 1       110   Defect group 2       111   Defect group 3       112   Defect group 4                                             Boundary line                                             Defect group 11                                             Defect group 12                                             Defect group 13                                             Defect group 14               121   Weight feature quantity       122   First feature quantity                                             First feature quantity               125   Second feature quantity                                             Second feature quantity               201   Defect group 11       202   Defect group 12       203   Defect group 13       204   Defect group 14                                             Defect image                                             Defect group 11                                             Defect group 12                                             Defect group 13                                             Defect group 14               213   Decide DOI                                             Save                                             End                 FIG. 3         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                    106                                 Feature quantity space                    108   All       109   Defect group 1       110   Defect group 2       111   Defect group 3       112   Defect group 4                                             Boundary line                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4               121   Weight feature quantity       122   First feature quantity                                             First feature quantity               125   Second feature quantity                                             Second feature quantity               129   Reference wafer                                             Reference album                                             Type                                             Process                                             Lot                                             Wafer               903   Open                                             Save                 FIG. 4         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4                    106                                 Feature quantity space                    108   All       109   Defect group 1       110   Defect group 2       111   Defect group 3       112   Defect group 4                                             Defect image                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4                                             Gray level difference                                             Gray level difference                                             Gray level value                                             Gray level value               121   weight feature quantity       129   Reference wafer                                             Reference album               213   Decide DOI                                             Save                                             End                 FIG. 5         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                    106                                 Feature quantity space                    108   All       109   Defect group 1       110   Defect group 2       111   Defect group 3       112   Defect group 4                                             Boundary line                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4               121   Weight feature quantity                                             First feature quantity                                             First feature quantity                                             Second feature quantity                                             Second feature quantity               129   Reference wafer       130   Reference album                                             Defect image                                             Broken wire 1                                             Broken wire 2                                             Foreign material 1                                             Foreign material 2               503   Select defect                                             Save                                             End                 FIG. 6         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                    106                                 Feature quantity space                                                              Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4               121   weight feature quantity                                             First feature quantity                                             First feature quantity                                             Second feature quantity                                             Second feature quantity               129   Reference wafer       130   Reference album                                             Defect image                                             Defect 1                                             Defect 2                                             Defect 3                                             Defect 4               213   Decide DOI                                             Save                                             End                 FIG. 7         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer               121   Weight feature quantity       129   Reference wafer       130   Reference album       213   Decide DOI                                             Album DOI image                                             Broken wire 1                                             Broken wire 2                                             Broken wire 3                                             Broken wire 4               503   Select defect                                             End                                             Defect image                                             Defect 1                                             Defect 2                                             Defect 3                                             Defect 4                                             Save                                             End                 FIG. 8         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer               121   Weight feature quantity       129   Reference wafer       130   Reference album       213   Decide DOI                                             Album DOI image                                             Broken wire 1                                             Broken wire 2                                             Broken wire 3                                             Gray level difference                                             Gray level value                                             Area               503   Select defect                                             End                                             Defect image                                             Defect 1                                             Defect 2                                             Defect 3                                             Close                                             Far                                             Gray level difference                                             Gray level value                                             Area                                             Save                                             End                 FIG. 9         101   Produce condition       103   Search DOI       903   Open                                             Select wafer                                             Extract DOI                                             Wafer for which condition is produced                                             Type                                             Process                                             Lot                                             Wafer                                             Save                 FIG. 10                                      1001                                 Defect groups&#39; feature quantity space                                                              Define feature quantity axis                                             Divide into four groups                                             Regard barycenter as representative                                             Select one group                                             Repeat until 1 group = 1 defect                                             Defect-group division tree                                             All                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4                                             Defect group 11                                             Defect group 12                                             Defect group 13                                             Defect group 14                                             Defect group 1111111                                             Defect group 1111112                                             Defect group 1111113                                             Defect group 1111114                                             Defect group 111111111                                             Defect group 111111112                                             Defect group 111111113                                             Defect group 111111114                 FIG. 11                                      1001                                 Defect groups&#39; feature quantity space                                                              Superimpose boundary lines of reference data                                             Adjust boundary line                                             Regard barycenter as representative                                             Defect-group division tree                                             All                                             Defect group 1                                             Defect group 2                                             Defect group 3                                             Defect group 4                 FIG. 12         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                                    106                                 Feature quantity space                    122   First feature quantity                                             First feature quantity               125   Second feature quantity                                             Second feature quantity               1209   Decide DOI                                             Defect image                                             Defect 1                                             Defect 2                                             Defect 3                                             Defect 4                                             Save                                             End                 FIG. 13         101   Produce condition       102   Select wafer       103   Search DOI       104   Extract DOI                                             A type                                             BB process                                             CCC lot                                             DDDD wafer                                             Defect image                                             Gray level difference                                             Gray level value                                             Area                                             Defect image                                             Defect 1                                             Defect 2                                             Defect 3                                             Close                                             Far               121   Weight feature quantity       129   Reference wafer       130   Reference album       1209   Decide DOI                                             Save                                             End                 FIG. 14         1401   Producing inspection condition       1402   Normal inspection       1403   Defect judgment       1404   Defect image       1405   Image processing       1406   Feature quantity       1407   DOI search       1408   Defect image display       1409   Representative DOI       1410   DOI extraction       1411   Defect image display       1412   DOI instruction       1413   DOI group       1414   Inspection-condition optimization       1415   Inspection condition       1416   Defect judgment       1417   defect image       1418   Image processing       1419   Feature quantity       1420   Defect classification       1421   Detected DOI       1422   DOI selection         FIG. 15         1501   Defect judging section       1502   Image processing section       1503   Defect classifying section       1504   Defect-indicator calculating section       1505   Condition optimizing section       1506   Data storing section       1507   User interface section       1508   Inspection-condition producing server         FIG. 16         1601   Electron beam source       1602   Electron beam       1603   Deflector       1604   Objective lens       1605   Semiconductor wafer       1606   Stage       1607   Secondary electron etc.       1608   Detector       1609   A/D converter       1610   Image processing circuit       1611   Inspection-condition setting section       1612   Judgment-condition setting section       1613   Overall control section         FIG. 17         1704   Objective lens       1705   Semiconductor wafer       1706   Stage       1710   Image processing circuit       1712   Light source       1714   Image sensor       1715   Detected image       1716   Memory       1717   Stored image       1718   Inspection-condition setting section       1719   Judgment-condition setting section       1720   Overall control section         FIG. 18         1802   Stage driving section       1803   Stage control section       1808   Illumination control section       1809   Judging circuit         FIG. 19         1901   Image processing       1902   x coordinate of image       1903   Brightness difference       1904   Threshold       1905   Defect portion       1906   Size       1907   Threshold change                                             Defect portion                                             Brightness difference                                             Threshold                                             Size                                             x coordinate of image               1908   Defect groups&#39; feature quantity space                                             Feature quantity 1                                             Feature quantity 2                                             Feature quantity 3               1909   Defect classification       1910   Feature quantity selection                                             Frequency                                             Feature quantity                                             Nuisance               1911   Threshold calculation       1913   Nuisance       1914   Threshold       1917   Frequency                                             Optimize by sequential repetition               1915   Evaluation value calculation       1916   Evaluation value = DOI detectivity −           Constant × Nuisance rate       1918   Detection result                                             Number of defects