JPH06232018A - Monitoring system for manufacturing line, and manufacturing line - Google Patents

Abstract

PURPOSE:To predict the final yield of a product as the ratio of nondefective product works to all product works by substituting intermediate inspection results actually obtained from each intermediate inspecting device into a functional expression indicating the latest correlation between the intermediate inspection data and final inspection data. CONSTITUTION:A data analyzing station 1 prepares a correlation diagram for predicting yield by plotting the number of foreign matters in an inspection process B on the axis of abscissa and displays the diagram on a display 4. At the same time, a functional expression and coefficient of correlation between the number of foreign matters and yield are calculated and displayed on the display 4. After displaying the functional expression, etc., a foreign matter inspecting device 2 actually inspects a semiconductor wafer selected as an object for prediction for foreign matters as an intermediate inspection. When the actually obtained foreign matter inspected results are plotted on the axis of abscissa of the graph of the functional expression, the yield of the semiconductor wafer can be easily predicted from the graph.

Description

Detailed Description of the Invention

[0001]

INDUSTRIAL APPLICABILITY The present invention makes it possible to predict the final yield, grade, etc. for a product work in the process of production by performing an intermediate inspection for each product work on the production line. The present invention relates to a manufacturing line monitoring system, and further to a manufacturing line to which such a manufacturing line monitoring system is integrally added.

[0002]

2. Description of the Related Art In recent years, semiconductor products generally have a very fine processing dimension accuracy of about 1 μm (0.001 mm) or less, and the manufacturing process is hundreds of processes, and many manufacturing processes take several months to complete. However, there is a possibility that various defects may occur in the semiconductor product in each of all manufacturing steps in the process of manufacturing. For example, there is a possibility that foreign matter may be mixed into the semiconductor wafer, or some kind of defect or defective thin film formation (hereinafter, foreign matter mixed in, defective, defective thin film formation, etc. is referred to as an intermediate inspection defect). is there. This intermediate inspection failure later causes a chip failure.However, since the size of the intermediate inspection failure generally is fine, the quality cannot be easily judged by visual inspection, and the quality is finally determined by the final inspection. It is the first to be known. In other words, once a semiconductor wafer has been put into the production line, the workers and the manufacturing staff need to know the yield, that is, the number of non-defective chips acquired for the semiconductor wafer, for several months until the manufacturing is completed. It is something that is not known as Heki.

In consideration of the above circumstances, in order to manage semiconductor wafers in the process of being manufactured, it is actually practiced to carry out an intermediate inspection on each semiconductor wafer in each specific intermediate manufacturing process. Is the reality. Specifically, some semiconductor wafers or some semiconductor wafers are subjected to an intermediate inspection in each of several specific intermediate manufacturing steps, and each of the semiconductor wafers undergoes a manufacturing step under a certain control standard. It is manufactured so as to be sequentially interposed.
By the way, in the final inspection process as the final manufacturing process, the final inspection is performed on all the chips on each semiconductor wafer, and the number of non-defective chips at that time is regarded as the yield.
In order to improve the yield, the analysis of the cause of the defect and the extraction of the defective manufacturing process are performed from the final inspection result. Appropriate measures are taken for the clarified defective factors and defective manufacturing processes, thereby improving the yield.

Incidentally, in documents related to this type of technology, for example, Japanese Patent Laid-Open No. 3-44054, intermediate inspection data and final inspection data for a product work are analyzed at a workstation in order to specify a manufacturing process relating to a defect. Therefore, appropriate measures are taken for the identified defective manufacturing process.

[0005]

However, according to the above-mentioned publication, although the defective manufacturing process can be specified by the analysis of the inspection data, the yield at the final manufacturing stage cannot be predicted, so that , Assuming yield prediction,
Even for the final target yield that is arbitrarily set, it is impossible to set a control standard in production control.

Even if the intermediate inspection is carried out, since the intermediate inspection is performed in several tens of manufacturing processes for hundreds of lots of products per day at the semiconductor manufacturing site, the result of the intermediate inspection is manually performed. The reality is that analysis is no longer possible. Therefore, it is conceivable to use a workstation to manage the intermediate inspection results in each manufacturing process for each product type and lot as a database. When the intermediate inspection results are managed as a database, not only the new intermediate inspection results generated every day can be stored, but also a huge amount of inspection results can be stored for a certain period. Further, by analyzing the intermediate inspection result and the final inspection result, it is possible to support the failure analysis of the product which has become defective in the final inspection. For example, by matching the final inspection failure with the intermediate inspection results of each manufacturing process, an intermediate manufacturing process that has a high correlation with the final inspection failure is found, and the inspection frequency is reviewed with the manufacturing process as the priority measure. By reviewing the management standards, it is possible to reduce defects. However, these analyzes are all after the final inspection result of the product, and how much the product currently in process can be obtained as a good product at the final inspection, that is,
How much the yield will be is unknown.

[0007] A first object of the present invention is to obtain a product work in a completed state in order by sequentially passing through each manufacturing process as a production line for each product work. There is a production line monitoring system and a production line that can predict the final yield as a percentage. A second object of the present invention is to obtain a set target number of non-defective product work pieces in order to sequentially obtain finished product work pieces by sequentially passing through each manufacturing process as a production line. This is to provide a production line monitoring system and a production line capable of controlling additional input, stoppage of production, and production suspension of the work. A third object of the present invention is to predict the occurrence rate of a defective category of product works when sequentially obtaining finished product works by sequentially passing each manufacturing process as a manufacturing line. It is to provide the production line monitoring system and the production line. A fourth object of the present invention is to set the final yield as predictable when sequentially obtaining finished product workpieces by sequentially passing through various manufacturing processes as a manufacturing line. Based on the result of comparison with the final yield, a production line monitoring system and a production line capable of controlling whether or not production of a product work on the production line can be continued thereafter are provided. A fifth object of the present invention is to monitor a manufacturing line which can predict the final grade of a product work when sequentially obtaining finished product works by sequentially passing through various manufacturing processes as a manufacturing line. It is to provide the system and the production line. A sixth object of the present invention is to grade each product work based on an intermediate inspection result when sequentially obtaining finished product works by sequentially passing through each manufacturing process as a manufacturing line. After that, the production line monitoring system and the production line capable of performing production control according to the grade are provided. A seventh object of the present invention is to predict the occurrence rate of a defective category on a semiconductor wafer when sequentially obtaining finished product works by sequentially passing through each manufacturing process as a manufacturing line. To provide a production line with a possible production line monitoring system.

[0008]

[Means for Solving the Problem] The first purpose is to provide one or more intermediate inspection devices for performing an intermediate inspection on a product work in each intermediate manufacturing process, and a final inspection for performing a final inspection on a product work in a final manufacturing process. An inspection device, an intermediate inspection database that stores the intermediate inspection data from each of the intermediate inspection devices as updatable, a final inspection database that stores the final inspection data from the final inspection device as updatable, the intermediate inspection database, and the final inspection database. From each inspection database,
A yield prediction database that stores the latest inspection data required for yield prediction as updatable, and the intermediate inspection device,
After accommodating each of the final inspection device, intermediate inspection database, final inspection database and yield prediction database,
The latest inspection data stored in the yield prediction database is used as the yield prediction data, and the intermediate inspection data, which is analyzed from the yield prediction data, is added to the functional formula showing the latest correlation between the final inspection data and the intermediate inspection. A data analysis station that predicts the final yield by substituting the intermediate inspection results that are currently obtained from each device, and a display device that displays various data related to data analysis in a state accommodated in the data analysis station And at least the above, and is achieved by adding the production line monitoring system thus configured to the production line.

The second purpose is to provide one or more intermediate inspection devices for performing an intermediate inspection on a product work in each intermediate manufacturing process, a final inspection device for performing a final inspection on a product work in a final manufacturing process, and the above intermediate. An intermediate inspection database that stores the intermediate inspection data from each inspection device as updatable,
A final inspection database that stores final inspection data from the final inspection device as updatable, and a yield that stores the latest inspection data required for yield prediction from each of the intermediate inspection database and final inspection database as updatable. Prediction database, above intermediate inspection device, final inspection device,
The intermediate inspection data, which contains the intermediate inspection database, the final inspection database, and the yield prediction database, and is analyzed from the yield prediction data, using the latest inspection data stored in the yield prediction database as the yield prediction data. , A data analysis station that predicts the final yield and the number of non-defective product workpieces obtained by substituting the intermediate inspection results currently obtained from each intermediate inspection device into the functional expression showing the latest correlation between the final inspection data. A display device for displaying various data relating to data analysis in a state of being housed in the data analysis station, and the final yield and the number of non-defective product work acquisitions and the set target non-defective product work acquisition number from the data analysis station. Originally, additional input / stop control of unfinished product work to the production line, unfinished This is achieved by configuring at least a production management station that controls production suspension in the production process of the product work in the ready state, and is also achieved by adding the production line monitoring system as described above to the production line. To be done.

The third object is to provide one or more intermediate inspection devices for performing an intermediate inspection on a product work in each intermediate manufacturing process, a final inspection device for performing a final inspection on a product work in a final manufacturing process, and the above intermediate. An intermediate inspection database that stores the intermediate inspection data from each inspection device as updatable,
The final inspection database that stores the final inspection data from the final inspection device as updatable, and the latest inspection data required for predicting the defective category occurrence rate of product work from each of the above intermediate inspection database and final inspection database are updated. The failure category occurrence rate prediction database stored as OK, the intermediate inspection apparatus, the final inspection apparatus, the intermediate inspection database, the final inspection database, and the failure category occurrence rate prediction database are stored in the failure category occurrence rate database. The latest inspection data is used as the defect category occurrence rate prediction data, and the intermediate inspection apparatus is added to the function formula showing the latest correlation between the number of intermediate inspection defective product works and the defect categories analyzed from the defect category occurrence rate prediction data. The intermediate inspection defective products that are actually obtained from each At least a data analysis station that predicts the occurrence rate of defective categories of product works by substituting the number of jobs, and a display device that displays various data related to data analysis in a state accommodated in the data analysis station. Achieved by configuring to include,
Further, it is achieved by adding the production line monitoring system thus configured to the production line.

The fourth object is to provide at least one intermediate inspection device for performing an intermediate inspection on a product work in each intermediate manufacturing process, a final inspection device for performing a final inspection on a product work in the final manufacturing process, and the above intermediate. An intermediate inspection database that stores the intermediate inspection data from each inspection device as updatable,
A final inspection database that stores final inspection data from the final inspection device as updatable, and a yield that stores the latest inspection data required for yield prediction from each of the intermediate inspection database and final inspection database as updatable. Prediction database, above intermediate inspection device, final inspection device,
The intermediate inspection data, which contains the intermediate inspection database, the final inspection database, and the yield prediction database, and is analyzed from the yield prediction data, using the latest inspection data stored in the yield prediction database as the yield prediction data. , A data analysis station that predicts the final yield by substituting the intermediate inspection results currently obtained from each of the intermediate inspection devices into a functional expression indicating the latest correlation between the final inspection data, and the data analysis station. Manufacturing of unfinished product workpieces based on the result of comparison between the display device that displays various data related to data analysis and the final yield setting target final yield from the above data analysis station At least a production control station for controlling whether or not to continue manufacturing on the line. It is accomplished by configuring also achieved by allowed to adding a manufacturing line monitoring system comprising in this way the production line.

The fifth object is to provide at least one intermediate inspection device for performing an intermediate inspection of a product work in each intermediate manufacturing process, a final inspection device for performing a final inspection of a product work in a final manufacturing process, and the intermediate product. An intermediate inspection database that stores the intermediate inspection data from each inspection device as updatable,
A final inspection database that stores the final inspection data from the final inspection device as updatable, and a grade prediction database that stores the latest inspection data required for grade prediction from each of the above intermediate inspection database and final inspection database as updatable And accommodating each of the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database and grade prediction database, the latest inspection data stored in the grade prediction database is used as grade prediction data, A data analysis station that predicts the final grade by substituting the intermediate inspection results currently obtained from each intermediate inspection device into the functional formula showing the latest correlation between the analyzed intermediate inspection data and final inspection data. And the data analysis It is achieved by including at least a display device that displays various data related to data analysis in a state of being accommodated in the application, and adding the production line monitoring system thus configured to the production line. Is achieved in.

The sixth object relates to the intermediate inspection by analyzing the intermediate inspection device for performing the intermediate inspection on the product work in the intermediate manufacturing process and the intermediate inspection data actually obtained from the intermediate inspection device. It should include at least a data analysis station that determines the quality level of a product work as a grade, and a production management station that performs production management for each product work thereafter according to the grade corresponding to the product work from the data analysis station. This is achieved by constructing the system, and also by adding the production line monitoring system thus configured to the production line.

The seventh object is to provide at least one intermediate inspection device for performing an intermediate inspection for each chip on a semiconductor wafer in each intermediate manufacturing process and a final inspection for each chip on a semiconductor wafer in a final manufacturing process. A final inspection device to perform, an intermediate inspection database that stores the intermediate inspection data from the intermediate inspection device together with the chip identification data as updatable,
It is necessary for predicting the defect category occurrence rate on the semiconductor wafer from the final inspection database that stores the final inspection data from the final inspection device together with the chip identification data as updatable, and the intermediate inspection database and the final inspection database. In addition to accommodating each of the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database, and defect category incidence prediction database, the defect category incidence database that stores the latest inspection data that can be updated The latest inspection data stored in the rate prediction database is used as the defect category occurrence rate prediction data, and the functional expression showing the latest correlation between the number of intermediate inspection defective chips and the defect category analyzed from the defect category occurrence rate prediction data. In addition, the The data analysis station that predicts the incidence of defective categories on a semiconductor wafer by substituting the number of defective chips for intermediate inspection, and various data related to data analysis displayed in the data analysis station It is achieved by including at least the display device described above, and by adding the production line monitoring system thus formed to the production line.

[0015]

[Function] An intermediate inspection database that stores the intermediate inspection data from each of one or more intermediate inspection devices that perform an intermediate inspection on a product work in each intermediate manufacturing process as updatable, and a final inspection for the product work in the final manufacturing process. A final inspection database that stores the final inspection data from the final inspection device that can be updated, and a step that stores the latest inspection data required for yield prediction from each of the intermediate inspection database and the final inspection database that can be updated. In addition to the foreign exchange prediction database, at the data analysis station,
The latest inspection data stored in the yield prediction database is used as the yield prediction data, and the intermediate inspection data, which is analyzed from the yield prediction data, is added to the functional formula showing the latest correlation between the final inspection data and the intermediate inspection. By substituting the intermediate inspection result actually obtained from each device, the final yield of the product work can be predicted.

[0016]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below with reference to FIGS. [First Embodiment] First, a manufacturing line monitoring system relating to yield prediction will be described. FIG. 1 shows a basic system configuration thereof. In this example, a semiconductor device manufacturing line is assumed to be applied, and in this case, the data analysis station 1 as a central component has an intermediate inspection database 5, a final inspection database 7, a yield prediction database 6, and a display 4. The intermediate inspection device 2 and the final inspection device 3 are configured to be housed. Of these, the intermediate inspection apparatus 2 is in the clean room 8 and functions to perform an intermediate inspection on a semiconductor wafer in a specific intermediate manufacturing step among a plurality of manufacturing steps 9 constituting a manufacturing line. At the time of the intermediate inspection, the inspector decides the inspection process name, measurement product name,
After the lot number, the inspection date and time, etc. are input, and the cassette containing the semiconductor wafer to be inspected is set in the intermediate inspection apparatus 2, the intermediate inspection is performed on the semiconductor wafer. ing. At that time, the wafer number recognition device 12 installed near the intermediate inspection device 2 recognizes the wafer number of the semiconductor wafer, so that the intermediate inspection data (intermediate inspection result) can be obtained. ing. In the intermediate inspection device 2,
It has a function to detect the coordinates of the intermediate inspection defect position on the semiconductor wafer and the size of the intermediate inspection defect, and a function to measure the number of intermediate inspection defects, and the intermediate inspection including information related to these detections and measurements. The data is temporarily transferred to the data analysis station 1 via the communication line 10 together with the externally input data, and then stored in the intermediate inspection database 5 as updatable. In the intermediate inspection database 5, the externally input data and the intermediate inspection data are inspection / manufacturing processes, lot numbers and inspection dates and times as product unit data for each product type, and the wafer number of the semiconductor wafer belonging to the lot and the number of intermediate inspection defects. The intermediate inspection failure position is collectively managed as a wafer unit data in a hierarchical state.

On the other hand, the final inspection apparatus 3 is also in the clean room 8 and is provided for each of the chips on the semiconductor wafer in the final manufacturing process among the plurality of manufacturing processes 9 constituting the manufacturing line. For the final inspection, the inspector inputs the inspection process name, measurement type name, lot number, inspection date and time, and the semiconductor wafer to be inspected is stored. The intermediate inspection is performed on each of the chips on the semiconductor wafer with the cassette set in the final inspection device 3. At that time, the wafer number recognition device 13 installed near the final inspection device 3 recognizes the wafer number of the semiconductor wafer, so that the final inspection data (final inspection result) can be obtained. ing. As in the case of the intermediate inspection device 2, the final inspection data from the final inspection device 3 is once transferred to the data analysis station 1 via the communication line 11 together with the external input data, and then stored in the final inspection database 5 as updatable. There is something. Now, in the final inspection database 7, like the intermediate inspection database 5, the external input data and final inspection data are the product type, lot number, and inspection date and time as P inspection lot unit data, and the wafers of the semiconductor wafers belonging to the lot. The number and the final inspection data of all the chips in the wafer are collectively managed in a hierarchical state as P inspection wafer unit data. Incidentally, the "P test" here means a probe test.

The product type unit data and the P inspection wafer unit data will be described in more detail with reference to FIG.
(A) and (B) show the data structure as the product type unit data 14 and the P inspection wafer unit data 15, respectively. As shown in the drawing, the product type unit data 14 is largely classified into product types such as product type A, product type B, ... In the intermediate inspection database 5, and lots inspected for each product type are used as lot number data. It is stored in a hierarchical state. Further, as shown in the P inspection wafer unit data 15, data for each semiconductor wafer belonging to the lot is stored in a hierarchical state in each lot. Therefore, in order to retrieve the data of a certain semiconductor wafer unit, the data, the lot number and the wafer number are designated from the data analysis station 1, and the data of the semiconductor wafer unit is transferred from the intermediate inspection database 5 to the data analysis station 1. It can be read. The data structure in the final inspection database 7 is basically the same as that of the intermediate inspection database 5. In the final inspection database 7, the P inspection lot unit data 15 is the product type unit data 14, and the P inspection wafer unit data is It corresponds to each wafer unit data. Therefore, when the product type, the lot number and the wafer number are designated by the data analysis station 1, the data of a desired semiconductor wafer unit can be read from the final inspection database 7 onto the data analysis station 1.

Now, in connection with the intermediate inspection database 5 and the final inspection database 7, the yield prediction database 6 provided for yield prediction will be described. Product unit data in database 5 and P in final inspection database 7
The inspection lot unit data is stored in correspondence with each other, and as reference data for yield prediction, the number of intermediate inspection defects, the function formula for yield prediction, the correlation coefficient, the number of intermediate inspection defects, and the defect category function. Expressions and the like are managed in a hierarchical manner. FIGS. 3A and 3B show the data structure in the yield prediction database 6. As illustrated, the wafer unit data table 16 for the product type A and the lot number BB as the wafer unit data 15 and the P inspection wafer unit data table 17 for the product type A and the lot number BB are given as examples. These data tables can be retrieved from the intermediate inspection database 5 and the final inspection database 7 by the data analysis station 1 using the product type A and the lot number BB as keys, and stored in the yield prediction database 6. By comparing the wafer unit data table 16 and the P inspection wafer unit data table 17 by the data analysis station 1, and checking the correlation between the inspection process and the yield data of the wafers having the same wafer number, the functional expression and the correlation coefficient are obtained. Although it is calculated, if the correlation coefficient is calculated to be 0.6 or more at that time, it can be said that the correlation is statistically high. That is, it can be seen that the number of intermediate inspection defects in the process greatly affects the yield of products. Therefore, in the process, since the correlation coefficient of the functional formula for prediction based on the number of defects in the intermediate inspection result is high, the prediction accuracy of the final yield can be improved accordingly. Here, with reference to FIG. 4, an example of the registration processing method of the intermediate inspection data and the final inspection data in the intermediate inspection database and the final inspection database will be described with a delay. Since the registration processing of the intermediate inspection data is performed in exactly the same manner as that of the final inspection data, only the registration processing of the intermediate inspection data will be described below. That is, in the intermediate inspection, the intermediate inspection apparatus 2 performs the intermediate inspection on the semiconductor wafer or on each of the chips on the semiconductor wafer. The data is transmitted to the data analysis station 1 via the line 10 and is registered in the intermediate inspection database 5 under the control of the data analysis station 1 in a predetermined manner. Since the storage capacity of the intermediate inspection database 5 is limited, whether or not it is necessary to delete the intermediate inspection data having the oldest inspection date among the intermediate inspection data registered in the intermediate inspection database 5 thereafter. If it is necessary to delete the intermediate inspection data, the intermediate inspection data is deleted, and then the data file is updated, whereby the registration process is ended. If it is not necessary to delete it, the data file is updated as it is and the registration process is ended.

Next, a data analysis method for yield prediction will be described assuming that a foreign matter inspection is performed as an intermediate inspection and a probe inspection is performed as a final inspection.
Under the control of the data analysis station 1, foreign matter inspection data and probe inspection data required for the prediction are registered in advance in the intermediate inspection database 5 and the final inspection database 7 in fixed amounts in order to perform the yield prediction. Need to be present. Specifically, as the amount of inspection data, for example, it is necessary that the inspection data for the last one or two months have been registered. With the inspection data required for yield prediction registered, the data analysis station 1 collates the data of the same product type and the same lot number from each of the intermediate inspection database 5 and the final inspection database 7, This is registered in the yield prediction database 6 as yield prediction data, and then the data analysis station 1 is first performing the yield prediction process. FIG. 5 shows a flow of the yield prediction process. In this case, first, the product type name (assuming a semiconductor wafer in this example) as the yield prediction target is input from the data analysis station 1, and subsequently, the number of lots for creating the yield prediction functional expression is changed. Is entered. For example, if 4 lots are input as the lot number, the foreign substance inspection data and probe inspection data for the latest 4 lots of the product type are collated and used as yield prediction data. Further, the name of the manufacturing process in which the foreign matter inspection is performed is input. If, for example, the manufacturing process B is input as the manufacturing process name, it is assumed that predetermined data is collated in the yield prediction database 6. Has become. That is, the number of foreign matters corresponding to the inspection process B in the wafer unit data table 16 and the P inspection wafer unit data table 1
The yield data in 7 is compared with the data for 4 lots. 4 in the data analysis station 1
A correlation diagram for yield prediction in which the number of foreign substances in the inspection process B for the lot is plotted on the horizontal axis and the yield is plotted on the vertical axis is displayed on the display 4 at that time. As a result, the functional expression and the correlation coefficient relating to the number of foreign matters and the yield are calculated together and then displayed on the display 4. FIG. 6 shows the display screen 18 on the display 4 at that time. On the display screen 18, the function formula 20, the correlation coefficient 32, and the correlation diagram (the function formula line 21 constitutes a part of the correlation diagram). In addition to the above, the title 19, the product type name 22, the lot number 23, and the other inspection process display list 24 are additionally displayed.

After the functional equation 20 is created and displayed, the foreign matter inspection apparatus 2 actually performs the foreign matter inspection on the semiconductor wafer to be predicted as an intermediate inspection. The foreign matter inspection result at that time is used as a function. The yield can be easily predicted from the function formula line 21 by substituting it on the horizontal axis of the formula line 21. Referring to FIG. 6, for example, the yield prediction method for the inspection process B will be described. By plotting data for several lots of the same product type, the horizontal axis represents the number of foreign substances and the vertical axis represents the probe inspection yield. , A function formula line 21 indicating the relationship between the number of foreign matters and the inspection yield is defined.
After that, if the actual foreign matter inspection result for the yield prediction target is substituted on the horizontal axis of the function equation line 21 as the number of foreign matters, the predicted yield is calculated from the function equation 20 using the value as a variable. Calculated by the display screen 1 shown in FIG. 7 as a predicted yield display screen layout.
8 can be displayed on the screen. Here, as a specific example of calculating the predicted yield by substituting the number of foreign substances as the result of the intermediate inspection into the functional expression (y = f (x)) 20, for example, the functional expression is y = a + bx (a , B: constant, x: variable)
If the number of foreign matters (variable x) as the result of the intermediate inspection is 10, the predicted yield y in this case can be calculated as (a + 10b) × 100%. Incidentally, since the product name 22, lot number 23 and other inspection process list 24 are also displayed on the display screen 18 on the display 4 shown in FIG. 6, the display is selectively updated by, for example, a mouse. By that,
It is possible to switch to another display screen immediately. For example, if the product type name 22 is designated by a mouse, the correlation diagram for yield prediction for other product types can be displayed immediately. In the data analysis station 1, the lot as the yield prediction target is transported to the final inspection process, and the final inspection device 3 performs the probe inspection to obtain the actual yield and the defect category distribution data for the lot. When obtained, the final inspection data of the oldest inspection date and time in the final inspection database 7 is deleted, and the new final inspection data is registered in the final inspection database 7. With this registration update, the data analysis station 1 matches the intermediate inspection data and the final inspection inspection data for the lot to generate new yield prediction data, and also registers it in the yield prediction database 6, while The oldest yield prediction data in the yield prediction database 6 is deleted. Therefore, even if the yield is improved due to process improvement, etc., the yield prediction data is also updated accordingly,
It is possible to always maintain a highly accurate predicted yield.

[Example 2] By the way, it is conceivable to positively utilize the predicted yield for production control. FIG. 8 shows the system configuration of the manufacturing line monitoring system at that time. First, the analysis described in Example 1 is performed to calculate the predicted yield and the predicted number of products to be obtained.
These are to be transferred from the data analysis station 1 to the production control station 25 via the communication line 26. At the production control station 25, production instructions such as additional input of semiconductor wafers and production suspension are performed based on the information.

As a concrete production control, reduction of delivery delay will be described. FIG. 9 compares the flow of processes from the introduction of a product to the shipment of the conventional system and the production line monitoring system according to the present invention. Is shown.
For example, assuming that a customer orders N products for a certain product, in the conventional case, the production management department makes a judgment based on the past record of the same product,
The quantity that would have been obtained approximately N as the estimated number of acquisitions had been put into the production line. Therefore, if some trouble occurs during manufacturing and only N-K good products are obtained as a result of probe inspection,
Since products were newly added to the manufacturing line to make up for the deficiency of K pieces, it can be understood that the delivery date is already delayed by the time the deficiency is obtained as a good product. However, in the case of the manufacturing line monitoring system according to the present invention, after the product is put into the manufacturing line, the foreign matter inspection is performed in the middle of the manufacturing process, so that the product is analyzed by the analysis described in the first embodiment. Since the predicted yield and the predicted acquisition number are obtained, the production management station 25 can give necessary instructions for production management in consideration of the information and the number N of orders. That is, when the number of predicted acquisitions is NK as a result of the foreign matter inspection, the production control station 25
Can instruct the production control department to add new products to the manufacturing line to make up for the shortage of K pieces, so even if the shortage is completed, as many products as the number of orders will be delivered within the delivery date. It can be shipped.

[Embodiment 3] Although the reduction of the delivery delay has been described above, the reduction of the surplus non-defective products can also be dealt with. FIG. 10 shows the process flow from the product insertion to the shipment, which takes into consideration the reduction of surplus non-defective products.
It is shown in comparison with the conventional system and the production line monitoring system according to the present invention. For example, assuming a case where a customer orders N products for a certain product, in the past, in order to prevent shortage due to a sudden trouble as described in Example 2 in the past, due to the strict adherence to delivery time, Judging from the yield record for the same product, the product was put on the manufacturing line so that a good product was obtained in an amount larger than the number of orders. Therefore, when N + K non-defective products are obtained as a result of the probe inspection, the K surplus products are discarded and become scrap costs.
However, in the case of the manufacturing line monitoring system according to the present invention, after the product is put into the manufacturing line, the foreign matter inspection is performed in the middle of the manufacturing process, so that the product is analyzed by the analysis described in the first embodiment. Since the predicted yield and the predicted acquisition number are obtained, the production management station 25 considers the information and the ordered number N,
It is possible to give necessary instructions for production control. That is, if it is assumed that the number of predicted acquisitions is N + K as a result of the foreign matter inspection, the production management station 25 informs the production management station 25 to suspend the production of K products that may become surplus products at that time. It is possible to instruct the production control department. By continuing the production of products other than the production suspension, the surplus non-defective products can be suppressed to the minimum with respect to the ordered number N, so that the scrap cost can be reduced. At that time, the manufacturing process in which the foreign substance inspection is performed is a common process, and the product whose production is suspended in the manufacturing process can be continuously diverted to another product, so that the effect of reducing the material cost can also be obtained. Is.

[Embodiment 4] Further, the foreign matter number management will be described. FIG. 11 shows a management processing flow at that time. In this case, if the type and the foreign substance inspection process name as the foreign substance number management target and the probe inspection yield to be obtained as a target are input to the data analysis station 1, the data analysis station 1 Based on these data, the yield prediction database 6 is searched in the same manner as the procedure shown in Example 1, and a correlation diagram of the inspection process and the yield data of the product type is created, and the functional expression and the phase relationship are obtained. The number is to be calculated. After that, by substituting the yield desired to be obtained as a target into the functional expression, the maximum number of foreign particles allowed to achieve the yield is calculated. 9 is a display screen showing a correlation coefficient and a correlation coefficient. The target yield 27 is set in the correlation diagram with the maximum number of foreign substances as the foreign substance number management upper limit line 28. Now, with the target yield 27 set, foreign matter inspection is actually performed by the foreign matter inspection device 2 in the inspection process for the product subject to foreign matter number management, and the foreign matter inspection result is the data analysis station 1 The data analysis station 1 analyzes the inspection result and determines whether the detected number of foreign substances exceeds the foreign substance number management upper limit line 28. If the result of the determination is that the foreign matter number is within the foreign matter number management upper limit line 28, the target yield 27 is achievable at the time of the process, and the subsequent process is instructed, but the foreign matter number is the foreign matter number management upper limit. Line 2
If it exceeds 8, it is judged that the target yield 27 cannot be achieved even if the process is continued thereafter, and further, disposal is instructed. In this way, if the number of foreign substances is managed, the manufacturing process can be stopped at that time for the product that cannot achieve the target yield, so that no unnecessary manufacturing process is performed thereafter. It is also done. The target yield 27 can be set arbitrarily by selecting the target yield setting 29 with the mouse.

[Fifth Embodiment] Further, the defect category analysis will be described. FIG. 13 shows an analysis processing flow in that case. When the type and lot number to be analyzed are input to the data analysis station 1, the data analysis station 1 searches the yield prediction database 6 and, as shown in FIGS. 3 (A) and 3 (B), The wafer unit data table 16 and the P inspection wafer unit data table 17 of the product type and the lot are displayed on the display 4. After that, each inspection process of the wafer unit data table 16 is represented by P on the horizontal axis.
Correlation charts are created by plotting each defect category in the inspection wafer unit data table 17 on the vertical axis.
4 shows, as an example, a correlation diagram between the number of foreign particles in the inspection process C and the number of defects in the defect category A in the probe inspection. Next, the function formulas and correlation coefficients of each correlation diagram are calculated and then displayed together. In this manner, by selecting the other defect category list 30 with the mouse, the correlation relating to each combination is known, for example, the inspection process B and the defect category C, or the inspection process B and the defect category R. From this, it is understood that if there is a combination having a large correlation, it is highly likely that the process is the cause of the defective category. From the above results, it is clarified that some measures need to be taken for the specific process in order to reduce a certain defect category.

[Sixth Embodiment] Here, a manufacturing line monitoring system including a plurality of intermediate inspection devices will be described. FIG. 15 shows a system configuration of a manufacturing line monitoring system including a plurality of intermediate inspection devices. is there. As shown in the figure, two intermediate inspection devices 2 are installed in the clean room 8, but an intermediate inspection is performed on a certain product.
When the yield is predicted from the result, first, the intermediate inspection device 2 of the first unit performs an intermediate inspection on the product. From the result, the predicted yield is calculated by using the yield prediction correlation diagram shown in FIG. 6. Next, an intermediate inspection is performed on the same product by another intermediate inspection device 2, and other inspection items are also determined. Similarly, the predicted yield is calculated. Therefore, when the predicted yield value of each of the plurality of intermediate inspection devices 2 is analyzed by the data analysis station 1, the predicted yield more highly accurate than the yield predicted from only one intermediate inspection device can be obtained. It is a thing. In this way, by arranging a combination of different inspection types as the plurality of intermediate inspection devices 2 (for example, a combination of a foreign substance inspection and a visual inspection, a combination of a foreign substance inspection and a dimensional inspection), the accuracy in the predicted yield is improved. It can be further improved.

[Embodiment 7] Further, the foreign substance content analysis will be described. When the foreign substance inspection apparatus performs the foreign substance inspection, the detected foreign substances are classified into S, M, and L in ascending order according to their size. Although it has a function of classifying into three types, FIG. 16 shows the distribution of foreign matters by size of wafers in a certain product type and lot. Even if the total number of foreign particles suddenly increases, it can be estimated that some kind of abnormality has occurred, but by classifying the foreign particles into three types according to their size, and analyzing them, for example, only S-size foreign particles will increase rapidly. If so, it is estimated that the amount of fine dust may have increased, or L
It is possible to estimate the cause of the increase in foreign matter specifically by taking into account that if the size of foreign matter increases rapidly, it is highly possible that a very serious trouble has occurred, and effective countermeasures can be taken. In addition, the final analysis database 7 is searched by the data analysis station 1, and the correlation between foreign particle sizes is also checked, such as the correlation between S-sized foreign particles and yield, or the correlation between L-sized foreign particles and defective category D. Is also possible.

[Embodiment 8] Another example of the foreign matter content analysis will be described. In the foreign matter inspection apparatus, when performing the foreign matter inspection, information on the size of each foreign matter and the generation position on the semiconductor wafer are given. It is possible to take in information using two-dimensional coordinates of (X, Y). FIG. 17 shows foreign substance data for the types and lots. For foreign substances on the same semiconductor wafer, the foreign substance numbers are sequentially written from 1 and the data of the size, the X coordinate, and the Y coordinate are written respectively, but the data analysis station 1 manages the generation position coordinates for all the foreign substances. Therefore, if the final inspection database 7 is searched and the final inspection data of the same product type and the same lot are made to correspond to each other, it is determined whether or not the chip at the coordinates where the foreign matter is generated is defective in the probe inspection. Further, it is also checked which defect category the chip having the foreign substance occurrence coordinates belongs to.

[Embodiment 9] Here, the grade classification of products will be described. FIG. 18 shows a control chart for grade classification of products based on the number of foreign matters. As illustrated, for example, the A rank management standard 31, the B rank management standard 35, and the C rank management standard 3 set on the horizontal axis.
6 and the number of foreign matter actually detected from the product by the intermediate inspection, for example, if the number of foreign matter is less than A, A
Graded products from the intermediate inspection results as rank B products when there are more than A pieces and less than B pieces as rank products, and as C rank products when there are more than B pieces and less than C pieces. It is about going. If graded products are classified according to their grade, such as express products and sample products, the grades of the products can be adjusted within the manufacturing line if they are sorted during the manufacturing process. For products with low grade and low yield, it can be effectively used as a sample product to reduce waste.

[Embodiment 10] In the above embodiments, the semiconductor wafer is mainly assumed as a product, but of course, it can be applied to other products. As an example of the optical disk device, one of the optical disks is
In a CD-ROM (Read Only Memory) as a seed, information data to be written in the CD-ROM is obtained in advance from a customer, and one metal master (stamper) on which the information is recorded is created. Has become. The products are duplicated by the number of orders by plastic injection molding using the stamper.However, each duplicated product is actually read and tested, and until the number of errors is checked, it is a good product. Whether or not it is unknown. In addition, since the stamper is different for each title, it is difficult to quickly supplement the missing item. Therefore, in the past, in order to complete the delivery within the delivery date, more than the number of orders was produced, and the surplus product was discarded, resulting in unavoidable damage costs. However, according to the manufacturing line monitoring system of the present invention, although the number of orders is first duplicated, it is possible to review it during the manufacturing process. That is, the appearance inspection of the product is performed as an intermediate inspection, and the predicted yield is calculated from the functional formula of the correlation between the result and the final yield, but if a shortage is likely to occur as a result, an additional injection instruction should be issued. By doing so, it is possible to ship the products for the number of orders within the delivery date while minimizing the damage cost.

[Embodiment 11] Lastly, the product distribution will be described. Even if semiconductor products called memories such as DRAM and SRAM are manufactured by exactly the same process, the operation speed is determined by the final inspection. There are variations in electrical characteristics such as. Specifically, the operating speed is 50
There are variations such as ns, 80ns and 100ns, but at that time, products with high operating speed are treated as high grade products,
Since the demand is high even at a high price, it is desired to manufacture more high grade products. Therefore, professional
For electrical inspection, while measuring electrical characteristics such as operating speed, after that, the electrical characteristics are measured in the final inspection in the state where the chips are cut from the semiconductor wafer into products, and the correlation of those values is analyzed. In addition, it is possible to create a correlation diagram. The correlation diagram is shown in FIG. 19. Based on the correlation diagram, a pro-
If the test is performed as an intermediate test and the operation speed is measured, by substituting the result into the correlation equation,
The operation speed in the final inspection can be predicted. Based on the result of the prediction, the lot is graded and the high grade is
Lots with a large number of products should be preferentially manufactured.

Thus, by predicting the grade of the lot in advance, the lot satisfying the customer's demand grade can be preferentially introduced into the production line, and the high grade demand can be satisfied by the high grade.
In order to meet the requirements for drottes and low grades, by introducing low grade lots, it is possible to properly introduce them. Further, if the correlation coefficient is sufficiently large, the grade can be predicted from the result by performing a partial sampling inspection without inspecting all the operation speeds in the intermediate inspection. Due to the drastic reduction, the delivery time can be shortened.

[0034]

As described above, according to the first and the eighth aspects, when the product workpieces are sequentially passed through the various manufacturing steps as the production line, the finished product workpieces are sequentially obtained. In the case where the manufacturing line monitoring system and the manufacturing line capable of predicting the final yield as a ratio of non-defective product work to all product works are according to claims 2 and 9, each product work is a manufacturing line and each manufacturing process is performed. Production line monitoring system that can control additional input, stoppage, and production suspension of product work in order to obtain the set target number of good product work when sequentially obtaining finished product work. According to claims 3 and 10, each of the product workpieces sequentially goes through each of the various manufacturing steps as a manufacturing line. Therefore, when the finished product works are sequentially obtained, the manufacturing line monitoring system and the manufacturing line capable of predicting the occurrence rate of the defective category of the product works are the manufacturing lines according to claims 4 and 11. When sequentially obtaining finished product workpieces by sequentially passing through various manufacturing processes, the final yield can be predicted, and product workpieces on the manufacturing line can be based on the result of comparison between this and the set target final yield. When the manufacturing line monitoring system and manufacturing line capable of controlling whether or not the manufacturing of
The manufacturing line monitoring system and the manufacturing line capable of predicting the final grade of the product work when sequentially obtaining the finished product work by sequentially passing through each of the various manufacturing processes as a manufacturing line. , 13 according to each of the product work, sequentially through each manufacturing process as a production line, when sequentially obtaining the finished product work, grade each product work based on the intermediate inspection result,
Thereafter, the manufacturing line monitoring system and the manufacturing line capable of performing the production management according to the grade are completed according to claims 7 and 14, and the product workpieces are sequentially passed through various manufacturing steps as the manufacturing line. When sequentially obtaining product works in a state, a production line monitoring system and a production line capable of predicting the incidence of defective categories on a semiconductor wafer are obtained.

[Brief description of drawings]

FIG. 1 is a diagram showing a basic system configuration of a manufacturing line monitoring system related to yield prediction.

2A and 2B are product type data in the intermediate inspection database and P in the final inspection database, respectively.
The figure which shows the data structure as inspection wafer unit data

3 (A) and 3 (B) are views showing a data structure in a yield prediction database.

FIG. 4 is a diagram showing a registration process flow of intermediate inspection data and final inspection data in an intermediate inspection database and a final inspection database.

FIG. 5 is a diagram showing a flow of yield prediction processing.

FIG. 6 is a diagram showing a display screen on which a correlation diagram for yield prediction, a function formula, and a correlation coefficient are displayed.

FIG. 7 is a diagram showing a predicted yield display screen layout.

FIG. 8 is a diagram showing a system configuration of a manufacturing line monitoring system in which a predicted yield can be used for production management.

FIG. 9 is a diagram showing a process flow from the time when a product is input to the time when the product is shipped, in consideration of reduction of delivery delay, in comparison between the conventional system and the production line monitoring system according to the present invention.

FIG. 10 is a flow chart of a process from the input of a product to the shipment in consideration of reduction of surplus non-defective products.
The figure which shows in comparison the conventional system and the manufacturing line monitoring system by this invention.

FIG. 11 is a diagram showing a management processing flow for foreign matter number management.

FIG. 12 is a view showing a display screen on which a correlation diagram for managing the number of foreign matters, a functional formula, and a correlation coefficient are displayed.

FIG. 13 is a diagram showing an analysis processing flow for defect category analysis.

FIG. 14 is a diagram showing a display screen showing a foreign substance inspection data and a correlation diagram of defect categories in probe inspection, a function formula, and a correlation coefficient for defect category analysis.

FIG. 15 is a diagram showing a system configuration of a manufacturing line monitoring system including a plurality of intermediate inspection devices.

FIG. 16 is a diagram showing the distribution of particle size by wafer size in a certain type and lot for particle content analysis.

FIG. 17 is a diagram for another example of foreign matter content analysis;
Diagram showing the size and location of foreign matter in a product type and lot

FIG. 18 is a diagram showing a correlation diagram for classifying products based on the number of foreign matters.

FIG. 19 is a diagram showing a correlation diagram for product distribution.

[Explanation of symbols]

1 ... Data analysis station, 2 ... Intermediate inspection device, 3 ...
Final inspection device, 4 ... Display, 5 ... Intermediate inspection database, 6 ... Yield prediction database, 7 ... Final inspection database, 8 ... Clean room, 9 ... Manufacturing process, 10 ...
Communication line, 11 ... Communication line, 12 ... Wafer number recognition device, 13 ... Wafer number recognition device

Claims (14)

[Claims] 1. When each unfinished product work is sequentially processed through various manufacturing steps as a production line, one or more intermediate manufacturing steps are performed in order to sequentially obtain finished product work in the final manufacturing process. A production line monitoring system for predicting the final yield as a ratio of non-defective product work to the total product work based on the intermediate inspection result for the product work and the final inspection result in the final manufacturing process. One or more intermediate inspection devices that perform intermediate inspection on product workpieces in each manufacturing process, final inspection device that performs final inspection on product workpieces in the final manufacturing process, and intermediate inspection data from each of the above intermediate inspection devices can be updated. An intermediate inspection database that stores the final inspection data from the final inspection device as updatable, and an intermediate inspection database that stores the intermediate inspection database Yield prediction database that stores the latest inspection data required for yield prediction from each of the inspection database and the final inspection database as updatable,
In addition to accommodating the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database, and yield prediction database, the latest inspection data stored in the yield prediction database is used as yield prediction data, and the yield prediction is performed. The final yield is predicted by substituting the intermediate inspection result currently obtained from each intermediate inspection device into the functional expression showing the latest correlation between the intermediate inspection data and the final inspection data analyzed from the data. A manufacturing line monitoring system including at least a data analysis station and a display device for displaying various data relating to data analysis while being housed in the data analysis station. 2. The unfinished product workpieces are sequentially passed through various manufacturing steps as a manufacturing line so that the finished product workpieces can be sequentially obtained in the final manufacturing step by one or more intermediate manufacturing steps. A production line monitoring system for predicting the final yield as a ratio of non-defective product work to the total product work based on the intermediate inspection result for the product work and the final inspection result in the final manufacturing process. One or more intermediate inspection devices that perform intermediate inspection on product workpieces in each manufacturing process, final inspection device that performs final inspection on product workpieces in the final manufacturing process, and intermediate inspection data from each of the above intermediate inspection devices can be updated. An intermediate inspection database that stores the final inspection data from the final inspection device as updatable, and an intermediate inspection database that stores the intermediate inspection database Yield prediction database that stores the latest inspection data required for yield prediction from each of the inspection database and the final inspection database as updatable,
In addition to accommodating the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database, and yield prediction database, the latest inspection data stored in the yield prediction database is used as yield prediction data, and the yield prediction is performed. By substituting the intermediate inspection results currently obtained from each intermediate inspection device into the functional formula showing the latest correlation between the intermediate inspection data and the final inspection data analyzed from the data, the final yield and the non-defective product A data analysis station that predicts the number of workpieces to be acquired, a display device that displays various data related to the data analysis in the state of being housed in the data analysis station, and the final yield and the number of non-defective product workpieces acquired from the data analysis station. Based on the number of acquisitions of non-defective product work, set to the production line of unfinished product work Add-on / turned stop control, at least including the manufacturing line monitoring system production and management station, a to manufacture hold control in the production process of the product work unfinished state. 3. The unfinished product workpieces are sequentially passed through various manufacturing steps as a manufacturing line, so that when the finished product workpieces are sequentially obtained in the final manufacturing step, one or more intermediate manufacturing steps are performed. It is a manufacturing line monitoring system that predicts the occurrence rate of defective category of product work based on the intermediate inspection result for the product work and the final inspection result in the final manufacturing process. On the other hand, one or more intermediate inspection devices that perform intermediate inspections, a final inspection device that performs final inspections on product workpieces in the final manufacturing process, and an intermediate inspection database that stores intermediate inspection data from each of the intermediate inspection devices as updatable. , The final inspection database that stores the final inspection data from the final inspection device as updatable, the intermediate inspection database, and the final inspection database. From each inspection database, a defect category occurrence rate prediction database that stores the latest inspection data required for prediction of the defect category occurrence rate of product work as updatable, the intermediate inspection device, the final inspection device,
In addition to accommodating each of the intermediate inspection database, final inspection database, and defect category incidence prediction database,
The latest inspection data stored in the defect category incidence prediction database is used as the defect category incidence prediction data, and analyzed from the defect category incidence prediction data,
Data analysis to predict the occurrence rate of defective categories in product work by substituting the intermediate inspection results currently obtained from each intermediate inspection device into the function formula showing the latest correlation between intermediate inspection results and defective categories. Station,
A manufacturing line monitoring system including at least a display device for displaying various data relating to data analysis while being accommodated in the data analysis station. 4. The unfinished product workpieces are sequentially passed through various manufacturing steps as a manufacturing line so that the finished product workpieces are sequentially obtained in the final manufacturing step by one or more intermediate manufacturing steps. A production line monitoring system for predicting the final yield as a ratio of non-defective product work to the total product work based on the intermediate inspection result for the product work and the final inspection result in the final manufacturing process. One or more intermediate inspection devices that perform intermediate inspection on product workpieces in each manufacturing process, final inspection device that performs final inspection on product workpieces in the final manufacturing process, and intermediate inspection data from each of the above intermediate inspection devices can be updated. An intermediate inspection database that stores the final inspection data from the final inspection device as updatable, and an intermediate inspection database that stores the intermediate inspection database Yield prediction database that stores the latest inspection data required for yield prediction from each of the inspection database and the final inspection database as updatable,
In addition to accommodating the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database, and yield prediction database, the latest inspection data stored in the yield prediction database is used as yield prediction data, and the yield prediction is performed. The final yield is predicted by substituting the intermediate inspection result currently obtained from each intermediate inspection device into the functional expression showing the latest correlation between the intermediate inspection data and the final inspection data analyzed from the data. Based on a comparison result between the data analysis station, a display device for displaying various data related to the data analysis in a state of being housed in the data analysis station, and a final target setting target final yield from the data analysis station. , A production management system that controls whether or not to continue manufacturing unfinished product workpieces on the manufacturing line. Including at least a production line monitoring system and Shon, a. 5. The unfinished product workpieces are sequentially passed through various manufacturing steps as a manufacturing line so that the finished product workpieces are sequentially obtained in the final manufacturing step by one or more intermediate manufacturing steps. It is a manufacturing line monitoring system for predicting the final grade of product work based on the intermediate inspection result for the product work and the final inspection result in the final manufacturing process. And one or more intermediate inspection devices, a final inspection device that performs a final inspection on a product work in the final manufacturing process, an intermediate inspection database that stores the intermediate inspection data from each of the intermediate inspection devices as updatable,
A final inspection database that stores the final inspection data from the final inspection device as updatable, and a grade prediction database that stores the latest inspection data required for grade prediction from each of the above intermediate inspection database and final inspection database as updatable And accommodating each of the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database and grade prediction database, the latest inspection data stored in the grade prediction database is used as grade prediction data, A data analysis station that predicts the final grade by substituting the intermediate inspection results currently obtained from each intermediate inspection device into the functional formula showing the latest correlation between the analyzed intermediate inspection data and final inspection data. And the data analysis While it is accommodated in Deployment, including at least a production line monitoring system and display device, the for displaying various data relating to the data analysis. 6. The unfinished product workpieces are sequentially passed through various manufacturing processes as a manufacturing line, so that when the finished product workpieces are sequentially obtained in the final manufacturing process, the product workpieces in the intermediate manufacturing process are processed. It is a manufacturing line monitoring system that grades each product work based on the quality of the intermediate inspection result, and then performs production control according to the grade. An inspection device, a data analysis station that determines the quality level of a product work related to the intermediate inspection as a grade by analyzing the intermediate inspection data currently obtained from the intermediate inspection device, and a product from the data analysis station From now on, production control will be performed for each product work according to the grade corresponding to the work A production line monitoring system including at least a production control station. 7. An unfinished semiconductor wafer is sequentially passed through various manufacturing steps as a manufacturing line so that the semiconductor wafers in an intermediate manufacturing step can be obtained when sequentially obtaining the completed semiconductor wafers in the final manufacturing step. A manufacturing line monitoring system for predicting a failure category occurrence rate on a semiconductor wafer based on an intermediate inspection result for each chip and a final inspection result for each chip on a semiconductor wafer in a final manufacturing process, One or more intermediate inspection devices that perform an intermediate inspection on each chip on a semiconductor wafer in each intermediate manufacturing process, a final inspection device that performs a final inspection on each chip on a semiconductor wafer in a final manufacturing process, and the above intermediate inspection device Intermediate inspection database that stores the intermediate inspection data from the device along with the chip identification data as updatable, and the final inspection device The final inspection database that stores the final inspection data from the device together with the chip identification data as updatable, and the latest inspections required for predicting the defect category occurrence rate on the semiconductor wafer from the intermediate inspection database and the final inspection database. A defect category incidence prediction database that stores data as updatable,
In addition to accommodating each of the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database, and defect category incidence prediction database, the latest inspection data stored in the defect category incidence prediction database is used as defect category incidence prediction data. As a function formula showing the latest correlation between the number of defective chips in the intermediate inspection and the defective categories analyzed from the defective category occurrence rate prediction data,
By substituting the number of defective chips actually obtained from each of the intermediate inspection devices, a data analysis station that predicts the occurrence rate of defective categories on a semiconductor wafer, and a state housed in the data analysis station, A manufacturing line monitoring system including at least a display device that displays various data relating to data analysis. 8. The product work in each of one or more intermediate manufacturing processes is sequentially obtained in the final manufacturing process by sequentially passing each manufacturing process of each unfinished product work. Intermediate inspection results,
Based on the final inspection result in the final manufacturing process, a manufacturing line equipped with a function for predicting the final yield as a ratio of non-defective product work to all product work,
For a manufacturing line consisting of various manufacturing processes, one or more intermediate inspection devices that perform intermediate inspections on product workpieces in each intermediate manufacturing process, final inspection devices that perform final inspections on product workpieces in the final manufacturing process, and the above intermediate An intermediate inspection database that stores the intermediate inspection data from each inspection device as updatable, a final inspection database that stores the final inspection data from the final inspection device as updatable, the intermediate inspection database, from each of the final inspection databases, Yield prediction database that stores the latest inspection data required for yield prediction as updatable, and after accommodating each of the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database and yield prediction database, The latest inspection data stored in the yield prediction database is used as yield prediction data. By substituting the intermediate inspection result currently obtained from each intermediate inspection device into the functional expression showing the latest correlation between the intermediate inspection data and the final inspection data analyzed from the yield prediction data, the final yield A production line including at least a data analysis station for predicting the above and a display device for displaying various data relating to the data analysis in a state accommodated in the data analysis station. 9. The product work in each of one or more intermediate manufacturing processes is sequentially obtained in the final manufacturing process by sequentially passing each unfinished product work through each manufacturing process. Intermediate inspection results,
Based on the final inspection result in the final manufacturing process, a manufacturing line equipped with a function for predicting the final yield as a ratio of non-defective product work to all product work,
For a manufacturing line consisting of various manufacturing processes, one or more intermediate inspection devices that perform intermediate inspections on product workpieces in each intermediate manufacturing process, final inspection devices that perform final inspections on product workpieces in the final manufacturing process, and the above intermediate An intermediate inspection database that stores the intermediate inspection data from each inspection device as updatable, a final inspection database that stores the final inspection data from the final inspection device as updatable, the intermediate inspection database, from each of the final inspection databases, Yield prediction database that stores the latest inspection data required for yield prediction as updatable, and after accommodating each of the above-mentioned intermediate inspection device, final inspection device, intermediate inspection database, final inspection database and yield prediction database, The latest inspection data stored in the yield prediction database is used as yield prediction data. By substituting the intermediate inspection result currently obtained from each intermediate inspection device into the functional expression showing the latest correlation between the intermediate inspection data and the final inspection data analyzed from the yield prediction data, the final yield And a non-defective product, a data analysis station that predicts the number of workpieces to be acquired, a display device that displays various data relating to the data analysis in a state of being housed in the data analysis station, a final yield from the data analysis station, and a non-defective product Number of workpieces acquired and setting target Good product production management that controls the input / stop of addition of unfinished product workpieces to the manufacturing line and the production suspension control in the manufacturing process of unfinished product workpieces based on the number of workpieces acquired A production line including a production line monitoring system including at least a station. 10. The product work in each of one or more intermediate manufacturing processes is sequentially obtained in the final manufacturing process by sequentially passing each manufacturing process of each unfinished product work. Based on the intermediate inspection result and the final inspection result in the final manufacturing process, it is a manufacturing line equipped with a function to predict the occurrence rate of the defective category of product work. , One or more intermediate inspection devices that perform an intermediate inspection on the product work in each intermediate manufacturing process, and a final inspection device that performs a final inspection on the product work in the final manufacturing process,
From the intermediate inspection database that stores the intermediate inspection data from each of the intermediate inspection devices as updatable, the final inspection database that stores the final inspection data from the final inspection device as updatable, from the intermediate inspection database and the final inspection database respectively , A defect category incidence prediction database that stores the latest inspection data required to predict the defect category incidence of product work as updatable, and the intermediate inspection device, final inspection device, intermediate inspection database,
In addition to accommodating each of the final inspection database and the defect category incidence prediction database, the latest inspection data stored in the defect category incidence prediction database was analyzed as the defect category incidence prediction data as the defect category incidence prediction data. , The number of intermediate inspection defects and the latest correlation between defect categories are substituted into the function formula that shows the latest intermediate inspection defect numbers obtained from each intermediate inspection device to predict the incidence of defective categories in product work. A manufacturing line monitoring system that includes at least a data analysis station and a display device that displays various data related to the data analysis while being housed in the data analysis station. 11. The product work in each of one or more intermediate manufacturing processes is sequentially obtained in the final manufacturing process by sequentially passing each manufacturing process of each unfinished product work. It is a manufacturing line equipped with a function to predict the final yield as the ratio of non-defective product work to the total product work based on the intermediate inspection result and the final inspection result in the final manufacturing process. For a production line consisting of processes, one or more intermediate inspection devices that perform intermediate inspections on product workpieces in each intermediate manufacturing process, final inspection devices that perform final inspections on product workpieces in the final manufacturing process, and the intermediate inspection device described above. Intermediate inspection database that stores the intermediate inspection data from each as updatable and the final inspection data that stores the final inspection data from the final inspection device as updatable. Inspection database, a yield prediction database that stores the latest inspection data required for yield prediction from each of the intermediate inspection database and final inspection database as updatable, and the intermediate inspection device, final inspection device, and intermediate inspection The database, the final inspection database, and the yield prediction database are each accommodated, and the latest inspection data stored in the yield prediction database is used as the yield prediction data. A data analysis station that predicts the final yield by substituting the intermediate inspection results currently obtained from each intermediate inspection device into a functional expression indicating the latest correlation between inspection data, and the data analysis station Display device that displays various data related to data analysis, and the data solution Setting the final yield from the station Based on the result of comparison with the target final yield, the production management station that controls whether or not to continue manufacturing the unfinished product workpiece on the production line. A manufacturing line including at least a manufacturing line monitoring system. 12. The unfinished product workpieces are sequentially passed through various manufacturing processes, so that when the finished product workpieces are sequentially obtained in the final manufacturing process, the product workpieces in each of one or more intermediate manufacturing processes are processed. It is a manufacturing line equipped with a function to predict the final grade of a product work based on the intermediate inspection result and the final inspection result in the final manufacturing process. It is possible to update one or more intermediate inspection devices that perform intermediate inspections on product workpieces in each process, final inspection devices that perform final inspections on product workpieces in the final manufacturing process, and intermediate inspection data from each of the above-mentioned intermediate inspection devices. The intermediate inspection database that is stored, the final inspection database that stores the final inspection data from the final inspection device as updatable, and the intermediate inspection data described above. Database, final inspection database, grade prediction database that stores the latest inspection data required for grade prediction as updatable, the above intermediate inspection device, final inspection device, intermediate inspection database, final inspection database and grade prediction database In addition to accommodating each, the latest inspection data stored in the grade prediction database as the grade prediction data, the functional formula showing the latest correlation between the intermediate inspection data and the final inspection data analyzed from the grade prediction data. , A data analysis station that predicts the final grade by substituting the intermediate inspection results currently obtained from each of the intermediate inspection devices, and various data related to data analysis is displayed in a state accommodated in the data analysis station. And at least a display device Production line forming line monitoring system is being added. 13. An intermediate inspection result for a product work in an intermediate manufacturing process when sequentially obtaining a product work in a completed state in a final manufacturing process by sequentially passing each unfinished product work through each manufacturing process. Grade each product work based on the quality level,
After that, a production line in which production control is performed according to the grade, and for a production line including various production processes, an intermediate inspection device that performs an intermediate inspection of a product work in the intermediate production process, and the intermediate inspection device By analyzing the obtained intermediate inspection data, the data analysis station that determines the quality level of the product work related to the intermediate inspection as a grade, and the grade corresponding to the product work from the data analysis station, A production line including a production line monitoring system including at least a production control station for controlling production of each product work. 14. The semiconductor wafer in an unfinished state is sequentially subjected to various manufacturing steps to sequentially obtain semiconductor wafers in a finished state in a final manufacturing step, with respect to each chip on the semiconductor wafer in an intermediate manufacturing step. A manufacturing line equipped with a function for predicting a failure category occurrence rate on a semiconductor wafer based on an intermediate inspection result and a final inspection result for each chip on a semiconductor wafer in a final manufacturing process. One or more intermediate inspection devices that perform an intermediate inspection on each chip on a semiconductor wafer in each intermediate manufacturing process for a manufacturing line consisting of manufacturing processes;
A final inspection device that performs a final inspection on each chip on the semiconductor wafer in the final manufacturing process, an intermediate inspection database that stores the intermediate inspection data from the intermediate inspection device together with the chip identification data as updatable, and a final inspection device. The final inspection database that stores the final inspection data together with the chip identification data as updatable, and the latest inspection data required for predicting the defect category occurrence rate on the semiconductor wafer from each of the intermediate inspection database and the final inspection database. The defect category occurrence rate prediction database that is stored as updatable, the intermediate inspection apparatus, the final inspection apparatus, the intermediate inspection database, the final inspection database, and the defect category occurrence rate prediction database are stored in the defect category occurrence rate prediction database. Latest inspection day As defective category occurrence rate prediction data, the number of intermediate inspection defective chips analyzed from the defective category occurrence rate prediction data, a function formula showing the latest correlation between defective categories, is actually obtained from each intermediate inspection device. A data analysis station that predicts the occurrence rate of failure categories on a semiconductor wafer by substituting the number of defective chips for intermediate inspection, and various data related to data analysis is displayed in a state of being housed in the data analysis station. A production line including a production line monitoring system including at least a display device.