JP2005033090A - Device status discrimination system and manufacturing process stabilization system in manufacturing process - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To detect abnormality which occurs in an important process formed of a plurality of processors at an early stage and to remove a factor caused by the device in a manufacturing process. <P>SOLUTION: A device status discrimination system of the manufacturing process where a plurality of processors are arranged in the same process is provided with a difference information generation means 4 formed of comparators 41, 42 and 43 generating difference information on measurement signals 11, 21 and 31 output from the respective processors 1, 2 and 3, and a status discrimination means 5 formed of logic circuits 51, 52 and 53 discriminating the status of the processors 1, 2 and 3 by synthetically determining a plurality of pieces of difference information generated in the difference information generation means 4. Thus, the abnormal device can be correctly specified at the early stage. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

The present invention relates to a production system in a device manufacturing factory for semiconductors and the like, and particularly monitors equipment fluctuations and process fluctuations constantly from equipment monitoring signals collected from manufacturing equipment and measurement data collected from inspection equipment, and fluctuations are recognized. The present invention relates to an apparatus state determination system and a manufacturing process stabilization system in a manufacturing process for realizing high-quality production by correcting the state of the apparatus and process.

The semiconductor manufacturing process involves many manufacturing apparatuses and processes, and stable operation of the manufacturing process is an important issue.

However, during manufacturing, degradation and abnormalities in manufacturing equipment and inspection equipment, process fluctuations,
If a defect or the like due to foreign matter such as dust occurs, the yield of the product is reduced. In order to eliminate these defects, in the manufacturing process, equipment that monitors and controls the state of the equipment is provided at various points in the process, and inspection processes that inspect the presence or absence of foreign substances with a foreign substance inspection machine are provided. The device is prevented from flowing into subsequent processes.

For example, constantly monitoring trends in product inspection data and facility work data collected from the production line, assessing the presence or absence of such abnormalities, providing warnings or countermeasures,
There has been proposed a production management calculation system that improves the yield of products by preventing the reduction of quality variations and the occurrence of mass defects (see, for example, Patent Document 1).

In addition, a semiconductor manufacturing process stabilization support system that achieves a desired target value by compressing variation by adjusting process parameters by obtaining a causal relationship between actual data from a manufacturing apparatus and an inspection result from an inspection apparatus. It has been proposed (see, for example, Patent Document 2).
Japanese Patent Laid-Open No. 9-50949 JP 2000-252179 A

The normal range of the signal that monitors the output of the device is the upper control level (Upper Control Level).
Limit) and the lower control level (Lower Control Limit).

However, even if the production system observes an output exceeding the normal control range and issues an abnormal warning signal, it is rare to trust the warning signal 100% and stop the device. In many cases, the state of the apparatus is checked to check whether there is any abnormality, and if it is abnormal, a judgment is made as to whether it is temporarily stopped or if it is normal.

This is because even if there is no abnormality in the main body of the apparatus, a false alarm may be issued due to an abnormality such as a sensor failure or the influence of noise.

The risk of leaving defects abnormally and the risk of failure of the production line after trusting misinformation are back-to-back, and such a judgment is burdensome to workers. This burden increases as the number of devices increases.

Even if the output signal of the production apparatus is within the normal range, the output may tend to change or fluctuate in a certain cycle due to process state changes or fluctuations. In this case, the characteristics of the manufactured device will be affected and varied by such process changes.

Therefore, even for devices of the same lot that are processed under the same environment and the same conditions, in the case of a device that is processed by a plurality of processing apparatuses, the result is that the characteristics vary despite the same processing conditions. In this case, if it is not possible to deal with the process abnormality upstream of the process, the quality / defective product is finally determined by the inspection of the downstream process.
At that time, the abnormality will be found.

For example, the history information of which device in which process has passed through a device with frequent defects is collected and edited into transition information for each unit and lot to determine which device in which process has a specific problem. To do. Then, after confirming whether or not there is an abnormality, a process or a device having a problem is temporarily stopped. However, the more downstream the process is, the more complex information including the fluctuation of the upstream process is included, so even with database search and extraction, statistical calculation of causal relations and analysis techniques, etc. From the data, it is difficult to definitively identify the cause of the fluctuation in question.

Since a large amount of defects due to the apparatus abnormality causes a large loss, it is necessary to detect the abnormality as accurately as possible in the upstream process. In particular, the tact-based process can be said to be a bottleneck process that uses multiple devices to reduce time. However, it is a bottleneck to detect abnormalities that occur in this important process at an early stage and remove the factors caused by the device. While preventing a reduction in the operating rate due to a process down, it improves the accuracy of locating the cause process when the characteristic variation is caused by factors other than the bottleneck process.

The present invention pays attention to the fact that, in a manufacturing process using a plurality of processing apparatuses, the difficulty of control that increases due to the plurality of processing apparatuses can be solved by utilizing means that can be configured because of the plurality. The first object of the present invention is to provide a device state determination system that can accurately identify an abnormal device by configuring a mutual monitoring system with a plurality of signals of the same type. In addition, the second object is to synchronize the data correlation calculation system that performs failure analysis of the entire manufacturing process and the apparatus state determination system in a synchronized manner, thereby accurately extracting problems in the manufacturing process using information that excludes equipment-caused factors. It is an object of the present invention to provide a manufacturing process stabilization system that can be executed.

The apparatus state determination system of the present invention is applied to a manufacturing process in which a plurality of processing apparatuses are arranged in the same process. That is, a difference information generating unit that generates difference information between observation signals output from each processing device, and a state of each processing device by comprehensively determining a plurality of difference information generated by the difference information generating unit And a state discriminating means for discriminating between.

In this way, by configuring a mutual monitoring system with a plurality of observation signals of the same type, it is possible to determine the state of a single processing device (specifically, determination of abnormality) using a plurality of observation signals. As a result, it is possible to distinguish against noise. Specifically, for example, when an error occurs in the difference information between the processing device 1 and the processing device 2 by the state determination unit even though the processing device 2 is outputting normally due to an external factor such as noise. But
If the difference information between the processing device 2 and the processing device 3 is normal, the processing device 2 can be regarded as normal. Accordingly, it is possible to determine a state that is resistant to noise and has high reliability, and it is possible to accurately identify an abnormal device at an early stage. From the viewpoint of information theory, an error correction function can be provided by using redundant information. Thereby, it is possible to prevent defects caused by the apparatus at an upstream stage of the process, and it is possible to reduce a burden when an operator monitors the apparatus.

In addition, when the observation signal is physical information to be directly controlled, a noise component may be included. Therefore, in the present invention, the noise component is removed from the observation signal before taking the difference.

In addition, when the observation signal is different from the information to be directly controlled, but is one or more observation information related to the control target, the information to be controlled with the plurality of observation information output from the processing device. It is good also as a structure further provided with the correlation calculating means which performs a correlation analysis. And information comprehensively estimated from this correlation calculation means,
It is regarded as an observation signal representing the state of the controlled object and output to the difference information generating means. In this way, even if the observation signal is a physical quantity that cannot be directly measured, the state can be estimated by relating a plurality of measurement information that can be measured.

Moreover, it is good also as a structure further provided with the filter calculation means which performs a filter process with respect to the estimated information after carrying out the correlation analysis by the said observation information or the said correlation calculation means. Then, the estimated information filtered by the filter calculating means is output to the difference information generating means. As described above, by performing the filter processing by the filter calculation means, it is possible to extract a signal while suppressing the influence of noise and fluctuation.

In addition, the apparatus state determination system of the present invention, in a manufacturing process in which a plurality of processing devices are arranged in the same process, provides difference information between observation signals output from each processing device and difference information between the observation signal and a reference signal. It is characterized by comprising difference information generating means to be generated and state determining means for determining the state of each processing device by comprehensively combining the difference information generated by the difference information generating means. Yes.

As described above, by using the difference information between the observation signals and the difference information between the observation signal and the reference signal in combination, it is strong against noise and can be distinguished with high accuracy. This makes it possible to identify an accurate device at an early stage. From the viewpoint of information theory, an error correction function can be provided by using redundant information. Thereby, it is possible to prevent defects caused by the apparatus at an upstream stage of the process, and it is possible to reduce a burden when an operator monitors the apparatus.

In this case, the state discriminating means discriminates the state of each processing device by a combination of a plurality of logics such as an OR circuit, an AND circuit, and a NOT circuit. Specifically, when the inspection period of the processing apparatus is short, the final stage logic is combined with an AND circuit, and when the processing apparatus inspection period is long, the final stage logic is combined with an OR circuit. Join. That is, if the inspection period of the processing equipment is short,
Since there is a high possibility that an abnormality can be found by inspection, it is possible to perform state determination with an emphasis on prevention of warning error due to malfunction by taking a logical product. In addition, when the inspection period of the processing equipment is long, the risk of an abnormality occurring between inspections increases, so a state that emphasizes reducing the risk of missing an abnormality by taking a logical OR. Discrimination becomes possible.

The manufacturing process stabilization system of the present invention is applied to a manufacturing process that is processed by a plurality of processing devices and inspection devices and is finally sent to a payout process. Managing data such as system and manufacturing condition management data for collecting and managing the manufacturing conditions of the plurality of processing apparatuses, inspection data acquired from the inspection apparatus, and characteristic data measured in the characteristic inspection downstream of the manufacturing process And a data correlation calculation system that analyzes the correlation based on various data managed by the process information management system and extracts the cause when an abnormality occurs in the manufacturing process. . Then, the data correlation calculation system acquires the device abnormality information determined by the device state determination system,
It is characterized by excluding factors caused by the apparatus from downstream process information including a plurality of abnormal factors.

In this way, the data correlation calculation system that performs failure analysis of the entire manufacturing process and the apparatus state determination system can be linked in synchronization, and the problem extraction of the manufacturing process can be performed with high accuracy by using information that excludes the factor caused by the equipment. Thus, stabilization of the manufacturing process can be realized, and stable operation of the apparatus and improvement in the yield of manufactured products can be achieved.

As described above, according to the present invention, in a manufacturing process using a plurality of processing devices, an abnormal device can be accurately identified early by configuring a mutual monitoring system with a plurality of signals of the same type. It becomes possible. Thereby, it is possible to prevent defects caused by the apparatus at an upstream stage of the process, and it is possible to reduce a burden when an operator monitors the apparatus. In addition, by synchronizing the data correlation operation system that performs failure analysis of the entire manufacturing process and the apparatus state determination system, it is possible to accurately extract problems in the manufacturing process with information that excludes the factors caused by the equipment. Therefore, stabilization of the manufacturing process can be realized, and stable operation of the apparatus and improvement in the yield of manufactured products can be achieved.

  Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a block diagram showing a logical configuration of an apparatus state determination system according to Embodiment 1 of the present invention. In the first embodiment, a case will be described in which this apparatus state determination system is applied to a manufacturing process in which three processing apparatuses 1, 2, and 3 are installed in a certain process.

That is, this apparatus state determination system includes comparators 41, 42, 43 that generate difference information between the observation signals 11, 21, 31 output from the processing apparatuses 1, 2, 3.
And a logical product circuit (hereinafter, referred to as “AND”) for discriminating the states of the processing devices 1, 2 and 3 by comprehensively judging a plurality of pieces of difference information generated by the difference information generating unit 4. It is referred to as an “AND circuit”.) State discriminating means 5 comprising 51, 52, 53 is provided.

Comparators 41, 42, and 43 mutually compare arbitrary two observation signals, and output a signal when the deviation reaches preset values ε1, ε2, and ε3. Specifically, the comparator 41 compares the observation signal 11 of the processing device 1 and the observation signal 21 of the processing device 2 with each other, and a signal is generated when any of the observation signals 11 or 21 changes. Is output. Similarly, the comparator 42 outputs a signal when either the observation signal 21 of the processing device 2 or the observation signal 31 of the processing device 3 changes, and the comparator 43 outputs the observation signal 11 of the processing device 1. A signal is output when any of the observation signals 31 of the processor 3 changes.

The AND circuits 51, 52 and 53 take an arbitrary two signals from the comparators 41, 42 and 43 as inputs and perform a logical product and output the result as an abnormal signal. Specifically, the AND circuit 51 calculates the logical product of the signal output of the comparator 41 and the signal output of the comparator 42 and outputs the result as an abnormality of the processing device 2. The AND circuit 52
Takes the logical product of the signal output of the comparator 42 and the signal output of the comparator 43, and outputs the result as an abnormality of the processing device 3. Further, the AND circuit 53 includes a comparator 4
1 and the signal output of the comparator 43 are ANDed, and the result is processed by the processor 1
Is output as an error.

For example, if the signals of the comparator 1 and the comparator 2 are output together, AND AND
Since the abnormality of the processing device 2 is output from the circuit 51, it can be specified that an abnormality has occurred in the observation signal 21 of the processing device 2.

Further, although the processing device 2 outputs the normal observation signal 21, the difference information between the processing device 1 and the processing device 2 exceeds ε1 in the comparator 41 due to external factors such as noise. Even when a signal is output, if the difference information between the processing device 2 and the processing device 3 is normal (ε2 or less), no signal is output from the comparator 42, and therefore the output of the AND circuit 51 is also at the L level. Will remain. Therefore, in this case, the processing apparatus 2 can be regarded as normal.

FIG. 2 shows an example of the temporal change of the observation signals 11, 21, 31 output from the processing devices 1, 2, 3, respectively. Each of the processing devices 1, 2, and 3 is managed as a single device within a management range of ± 3σ, and is set to issue a warning when it exceeds 3σ.

From FIG. 2, it can be said that all are in the normal range in the single state, but only the information signal 21 tends to decrease in output. In this state, when the characteristics of the manufactured device are examined, it becomes a factor that causes characteristic variation as a machine difference of the processing apparatus.

On the other hand, according to the apparatus state discrimination system shown in FIG.
Since a mutual monitoring system is formed between the two, when only one of them exhibits a different behavior, it can be easily found.

When applied to the observation signals 11, 21, 31 shown in FIG. 2, when the output deviation allowable values ε1, ε2, ε3 are all 3σ, after time 15,
| 11-21 | ≧ 3σ and | 21-31 | ≧ 3σ
Are observed together, the abnormality of the processing apparatus 2 can be detected early.

1 may be a production facility such as a processing machine or an inspection machine that inspects the state of the workpiece. Further, the information output from the processing device may be a physical analog signal, or may be discrete data acquired at an arbitrary sampling period. Further, as a means for generating a differential signal, hardware such as a comparator as shown in FIG. 1 can be used. However, analog information is A / D converted and taken into a computer as numerical information. May be created.

As described above, by configuring a mutual monitoring system of a plurality of observation signals, it is possible to find an abnormal state of the processing device early, but when errors such as noise and fluctuation are superimposed on the observation signal, If these signals are used directly, there is a risk that a warning will be issued even though it is not actually abnormal. Therefore, if the difference signal is taken after removing noise such as removing high-frequency components from the observed signal components, taking a moving average, or performing smoothing processing, the reliability of abnormality diagnosis is further improved. .

  Next, noise removal filtering means will be described.

When the variable representing the process is x and the noise component is w, the observed signal y is
y = cx + w. Here, c is a conversion coefficient from the physical quantity x of the process to the measured quantity y. By applying a discrete FFT to y, separating a signal component and a noise component in the frequency domain, and performing an inverse FFT transform, a signal with the noise component cut can be obtained.

If the noise component is random and does not include a frequency feature, the observation noise is minimized by minimizing the square of the error between the observed value and the measured value in the real-time domain using a statistical filtering technique such as the Kalman filter. What is necessary is just to extract the signal except the influence of w and the fluctuation of process x itself. FIG. 3 shows an example in which the process state x is estimated from the observed value y including noise using a Kalman filter.

By the way, if the process information that you want to control can not be measured directly, make information that estimated the state of the process using one or more secondary information that seems to be related, using the difference information between the estimated signals It is possible to determine the abnormal state of the processing device.

FIG. 4 is an example in which the correlation between five measurable signals from x0 to x4 and the characteristic value y after processing is examined. In FIG. 4, y and x0, y and x1, y and x2, y and x3,
The individual correlations between y and x4 are shown in FIG. 5 as y and x0, x1, x2, x3, x4.
y = a0 * x0 + a1 * x1 + a2 * x2 + a3 * x3 + a4 * x4 + w
As shown in the figure, the cases of being connected by the linear multiple regression equation are compared.

As described above, even if the physical quantity cannot be directly measured, the state can be estimated by associating it with a plurality of pieces of information that can be measured.

In the case of a plurality of observation signals, the accuracy of the estimated value may deteriorate due to fluctuations individually included in x0, x1, x2, x3, and x4 and the influence of observation noise w. In this case, the partial regression coefficients a0, a1, a2, a3, a4 obtained by multiple regression are sequentially corrected, and the characteristic value y and the predicted values a0 · x0 + a1 · x1 + a2 · x2 + a3 · x
Statistical extraction that minimizes the square of the error with 3 + a4 · x4 + w enables signal extraction with suppressed effects of noise and fluctuations.

That is, as shown in FIG. 6, five types of observation signals xa0 to xa4, xb0 to xb4, and xc0 to xc4 are observed from three processing devices (not shown), and correlation calculation means A, B, and C for performing correlation analysis. Thus, the partial regression coefficients a0, a1, a2, a3, a4 are obtained in relation to the characteristic value y. This partial regression coefficient a0, a1, a2
, A3, a4 are calculated by the filter operation units Fa, Fb, Fc every time new sampling data is acquired, and are corrected with time as shown in FIG. In this way, by dynamically correcting the prediction model, it is possible to suppress process variations that cannot be directly measured, and it is possible to perform abnormality determination with higher reliability. Thereafter, the signals ya ′, yb ′, yc ′ output from the respective filter operation units Fa, Fb, Fc are input to the respective comparators 41 ′, 42 ′, 43 ′ of the difference information generating means 4 ′ to input the respective signals. ya
Difference information between ', yb' and yc 'is generated, and each AND circuit 5 of the state discriminating means 5 is generated.
1, 52, 53 to determine whether the device is abnormal.

FIG. 8 is a block diagram showing a logical configuration of the apparatus state determination system according to the second embodiment of the present invention. FIGS. 9 and 10 are logical configurations of the apparatus state determination system according to the third embodiment of the present invention. FIG.

The apparatus state determination system according to the second and third embodiments includes information signals 11a and 21a of two processing apparatuses 1a and 2a and a reference signal 31a that the two processing apparatuses 1a and 2a refer to in common. Here, the combination of the information signals 11a and 21a and the reference signal 31a will be described with reference to the apparatus state determination system of the second embodiment shown in FIG. This combination is the same in the apparatus state determination system according to the third embodiment shown in FIG. 9 and FIG.

That is, the comparator 41A constituting the difference information generating unit 4A compares the observation signal 11a of the processing device 1a with the reference signal 31a, and outputs a signal when a change occurs in the observation signal 11a. Further, the comparator 42A constituting the difference information generating means 4A compares the observation signal 11a of the processing device 1a with the observation signal 21a of the processing device 2a, and any one of the observation signals 11a or 21a changes. Output a signal when it occurs. The comparator 43A constituting the difference information generating unit 4A compares the observation signal 21a of the processing device 2a with the reference signal 31a, and outputs a signal when a change occurs in the observation signal 21a.

The two AND circuits 51A and 52A constituting the state discriminating means 5A take an arbitrary two signals from the comparators 41A, 42A and 43A as inputs and perform a logical product.
The result is output as an abnormal signal. Specifically, the AND circuit 51A performs a logical product of the signal output of the comparator 41A and the signal output of the comparator 42A, and outputs the result as an abnormality of the processing device 1a. The AND circuit 52A takes a logical product of the signal output of the comparator 42A and the signal output of the comparator 43A, and outputs the result as an abnormality of the processing device 2A.

On the other hand, in the apparatus state determination system of the second embodiment shown in FIGS. 9 and 10, the state determination means 5B to 5E are AND circuits or logical sum circuits (hereinafter referred to as “OR circuits”).
Or a negative circuit (hereinafter referred to as “NOT circuit”). However, what kind of logic is combined depends on the processing device 1
a and 2a and the failure rates of the comparators 4B to 4E, and the conditions such as the periodic inspection interval of the processing devices 1a and 2a can be determined by policy.

For example, when the interval between the periodic inspections of the processing apparatuses 1a and 2a is short, there is a high possibility that an abnormality can be found by the inspection, and thus a warning error due to a malfunction should be prevented.
Therefore, as the abnormality determination logic of the processing device 1a, as shown in FIGS. 9A and 9B, warning errors due to malfunctions are obtained by combining the final stage logic of the state determination means 5B and 5C with an AND circuit. It becomes possible to determine the state with an emphasis on prevention. On the other hand, when the periodic inspection of the processing apparatuses 1a and 2a is long, the risk of an abnormality occurring between inspections increases, so that the final stage as shown in FIGS. 10 (a) and 10 (b). By combining logic with an OR circuit, the determination becomes more sensitive and the risk of missing an abnormality can be reduced.

As described above, the apparatus state determination system of the present invention is characterized in that a mutual monitoring system is configured by a plurality of observation signals of the same type. Advantages of configuring such a mutual monitoring system are as follows. Is briefly described here.

When making an abnormality judgment for each processing device, the tolerance ε from the reference value can be reduced to increase the sensitivity of the judgment. However, if the tolerance ε is reduced, it becomes more sensitive to noise and generates more warnings. The problem occurs. On the other hand, if a mutual monitoring system is configured with a plurality of observation signals of the same type as in the present invention, a difference in tendency from other processing devices can be detected by mutual monitoring, so it is not necessary to unnecessarily reduce the allowable deviation. An abnormal tendency can be detected early.

For example, referring to the example shown in FIG. 2, when abnormality determination is performed for each processing apparatus as in the prior art, the information signals 11 and 31 that tend to rise with time and the information signal 21 that tends to fall are discriminated. However, according to the present invention, such a difference in tendency can also be discriminated, and a difference in characteristics due to a difference in processing apparatus can be predicted. Thereby, it is possible not only to stop the abnormal processing apparatus, but also to give an opportunity to cancel or correct the characteristics in the subsequent steps for a substrate processed by a processing apparatus having a different tendency.

That is, according to the apparatus state determination system of the present invention, there is an advantage that it is resistant to noise and can be determined with high sensitivity, and an opportunity for recovery in subsequent processes can be provided.

Next, a manufacturing process stabilization system using the apparatus state determination system having the above configuration will be described.

In FIG. 11, three processing apparatuses A1, A2, and A3 are used in the process A, two processing apparatuses B1 and B2 are used in the process B, and three inspection apparatuses K1, K2, and K3 are used in the inspection process K. The manufacturing process is shown.

In such a manufacturing process, the objects to be processed from W11 to W12 are time t1.
Are sent to the processing devices A1, A2 and A3 for processing, and then at time t2, the processing device B
1 and B2, and processed in parallel by inspection devices K1 to K3 after time t3. Further, the process inspection system (not shown) acquires and stores the inspection results as shown in FIG. 12 from the CIM and the inspection apparatuses K1, K2, and K3 (not shown).

Here, if there is no apparatus status determination system of the present invention, if a defect is observed in the characteristic values YL1-5 and YL1-6 in the final process payout inspection, the use history pattern of the apparatus until then is examined. As a result, when it is recognized that an abnormality has occurred after passing through the processing device A2 and the processing device B1, the states of the processing devices A2 and B1 are examined.
In addition to temporarily disabling the use of these devices, measures such as stopping the shipment of wafers processed by this device will be taken.

FIG. 13 is a block diagram showing the configuration of the manufacturing process stabilization system of the present invention.

The manufacturing process stabilization system of the present invention can be broadly divided into the apparatus state determination system 101, the process information management system 102, and the data correlation calculation system 10 configured as described above.
It is composed of three.

As described above, the apparatus state determination system 101 includes a plurality of processing apparatuses A1 and A2.
, A3 based on the observation signal (or the observation signal and the reference signal), the processing device A1
, A2 and A3.

The process information management system 102 includes manufacturing condition management data M for collecting and managing manufacturing conditions of the processing apparatuses A1, A2, and A3, inspection data X acquired from the inspection apparatuses K1, K2, and K3, and downstream of the manufacturing process. This is a system that manages data such as characteristic data Y measured by characteristic inspection.

The data correlation calculation system 103 analyzes the correlation between the characteristic data Y, the manufacturing conditions M, and the inspection data X based on the information from the process information management system 102, and causes a factor when an abnormality occurs in the manufacturing process. It is a system to extract. here,
The manufacturing condition management data M includes recipe information for each of the processing apparatuses A1, A2, and A3 and history information about which apparatus the manufacturing lot and substrate have passed.

In the above configuration, in the present invention, by sending the information of the device state determination system 101 to the data correlation calculation system 103, the abnormality caused by the device can be removed at an early stage of the process, and it occurs due to factors other than the device abnormality. It is possible to identify the cause with high accuracy for process defects and characteristic variations.

It is a block diagram which shows the logic structure of the apparatus state determination system concerning Embodiment 1 of this invention. It is a graph which shows the time-sequential change of the information observed from a processing apparatus. It is a graph which compares and shows the time series observation information containing noise, and the time series information which removed the noise. It is the graph which investigated the correlation with a characteristic value, and temporal transition with respect to several observation information. It is the correlation graph related with the characteristic value y by multiple regression with respect to several observation information, and the graph which represented the time transition of the characteristic value y by the comparison with an actual measurement value using the said multiple regression model. It is a block diagram which shows the logic structure which provided the correlation calculating means and the filter calculating part between the processing apparatus and the difference information generation means. It is a graph which shows the case where the partial regression coefficient of a regression model is changed dynamically with time. It is a block diagram which shows the logic structure of the apparatus state determination system concerning Embodiment 2 of this invention. It is a block diagram which shows the logic structure of the apparatus state discrimination | determination system concerning Embodiment 3 of this invention, and has shown an example which combined several logic, such as AND circuit, OR circuit, and NOT circuit. It is a block diagram which shows the logic structure of the apparatus state discrimination | determination system concerning Embodiment 3 of this invention, and has shown the other example which combined several logic, such as AND circuit, OR circuit, and NOT circuit. It is explanatory drawing which shows the flow of the manufacturing process which consists of a some processing apparatus and test | inspection apparatus. It is explanatory drawing which shows an example of the data managed with the process information management system. It is a block diagram of the manufacturing process stabilization system which combined the apparatus state discrimination | determination system and the process information management system.

Explanation of symbols

1, 2, 3, 1a, 2a, 3a Processing unit 11, 21, 31, 11a, 21a, 32a Information signal 4, 4 ', 4A to 4E Difference information generating means 41, 42, 43, 41', 42 ', 43 'Comparator 41A-41E, 42A-42E, 43A-43E Comparator 5 State discriminating means 51, 52, 53 Logic circuit
DESCRIPTION OF SYMBOLS 101 Apparatus state discrimination system 102 Process information management system 103 Data correlation calculation system

Claims (8)

An apparatus state determination system for a manufacturing process in which a plurality of processing apparatuses are deployed in the same process,
Difference information generating means for generating difference information between observation signals output from each processing device;
An apparatus state determination system comprising: state determination means for determining the state of each processing apparatus by comprehensively determining a plurality of difference information generated by the difference information generation means. The apparatus state determination system according to claim 1, wherein the observation signal is physical information to be directly controlled, and is a signal from which a noise component is removed before taking a difference. The observation signal is one or more pieces of observation information that is different from information to be directly controlled but is related to a control target,
Correlation calculating means for performing correlation analysis between the plurality of observation information output from the processing device and information to be controlled is further provided,
2. The apparatus state determination system according to claim 1, wherein information comprehensively estimated from the correlation calculation unit is regarded as an observation signal representing a state of a control target and is output to the difference information generation unit. The observation information is discrete sequential sampling information including observation noise,
Filter observation means for applying a filter process to the observation information or the estimation information after correlation analysis by the correlation calculation means,
4. The apparatus state determination system according to claim 3, wherein the estimated information filtered by the filter calculating means is output to the difference information generating means. An apparatus state determination system for a manufacturing process in which a plurality of processing apparatuses are deployed in the same process,
Difference information generating means for generating difference information between observation signals output from each processing device and difference information between the observation signals and a reference signal;
An apparatus state determination system comprising: state determination means for determining the state of each processing apparatus by comprehensively determining a combination of both pieces of difference information generated by the difference information generation means. 6. The apparatus state determination system according to claim 5, wherein the state determination unit determines the state of each processing apparatus by a combination of a plurality of logics such as an OR circuit, an AND circuit, and a NOT circuit. When the inspection period of the processing apparatus is short, the state determination means combines the final stage logic with an AND circuit, and when the inspection period of the processing apparatus is long, the final stage logic is an OR circuit. The apparatus state determination system according to claim 6, wherein the apparatus state determination system is combined. A stabilization system for a manufacturing process that is processed by a plurality of processing devices and inspection devices and is finally sent to a dispensing process,
The apparatus state determination system according to any one of claims 1 to 7,
Process information managing data such as manufacturing condition management data that collects and manages manufacturing conditions of the plurality of processing apparatuses, inspection data acquired from the inspection apparatus, and characteristic data measured in a characteristic inspection downstream of the manufacturing process A management system;
Analyzing correlation based on various data managed by the process information management system, and comprising a data correlation calculation system that extracts the factor when an abnormality occurs in the manufacturing process,
The data correlation calculation system acquires apparatus abnormality information determined by the apparatus state determination system, and removes a factor caused by the apparatus from downstream process information including a plurality of abnormality factors. Stabilization system.

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