JP4649837B2 - Data analysis method, device manufacturing method and system - Google Patents

Description

  In the process of manufacturing an electronic device (hereinafter simply referred to as an electronic device or a device) such as a semiconductor element, a liquid crystal display element, an imaging element such as a CCD, a plasma display element, or a thin film magnetic head, the present invention Data analysis method suitable for analysis of measurement data obtained from an object (electronic device), etc., and device manufacturing method and device manufacturing that can appropriately perform such data analysis and appropriately manufacture an electronic device About the system.

In the production line of electronic devices, in order to quickly detect and respond to manufacturing defects, and to efficiently manufacture devices with excellent characteristics, this improves the operating rate of equipment. In order to improve the yield, information collection / analysis devices, diagnostic systems, device support systems, and the like have been introduced.
In such a diagnosis system and apparatus support system, various data are collected from a manufacturing apparatus such as an exposure apparatus and a process processing apparatus, an inspection apparatus and a measurement apparatus, and the data is analyzed by a server apparatus or the like. And control parameters are adjusted. Thus, for example, processing such as analysis and grasping of the operating status of the apparatus, detection of anomaly by statistically analyzing the trend of the apparatus, and prevention of occurrence of anomaly by predicting the future from the trend of the apparatus, etc. (For example, refer to Patent Document 1).

Japanese Patent No. 336436

However, the data (hereinafter referred to as measurement data) obtained from the respective apparatuses and devices as described above are generally complex data and signals that are generally affected by various components and noise. That is, such measurement data includes components such as an offset component, a trend component, a periodic component (frequency component), and a random component. Also, regarding the periodic component, from the component having periodicity with respect to the time axis, the periodicity in the processing order direction of sequentially processed wafers, the periodicity in the processing order direction of sequentially processed lots, or There are various periodicities in various directions, such as periodicity in the processing order direction of shots (devices) that are sequentially processed. Therefore, the observed measurement data is data of a very complicated component structure, and its analysis is difficult.
As a result, conventionally, there is a problem that the measurement data cannot be properly analyzed and the measurement data cannot be effectively used.

The present invention has been made in view of such problems, and an object of the present invention is to provide a data analysis method capable of easily and appropriately analyzing measurement data relating to device manufacturing.
Another object of the present invention is to provide a device manufacturing method and a device manufacturing system capable of appropriately manufacturing such a device by appropriately performing such data analysis.

  In order to achieve the above object, the data analysis method of the present invention detects a periodic component from measurement data related to a device or a device manufacturing apparatus (step S110), and detects the detected periodic component (step S120) or the measurement. The cause of the characteristic indicated by the measurement data is estimated based on the remaining component (step S140) obtained by removing the periodic component from the data (see FIG. 10).

Preferably, an event having the same period as the detected periodic component is detected, and the cause of the characteristic indicated by the measurement data is estimated for the event.
Preferably, the period component is detected by setting a provisional period that is a candidate period, detecting the correlation of the measurement data separated from the provisional period, and when the correlation is higher than a predetermined value, It is detected that the measurement data has periodicity with the provisional period as a period.

Suitably, the said periodicity includes the periodicity in the time passage which made arbitrary time a unit.
Preferably, the measurement data is data measured in relation to wafer processing, and the periodicity includes periodicity in the wafer processing order with an arbitrary number of wafers as a unit.
Further preferably, the measurement data is data measured in relation to a process for processing a wafer for each lot, and the periodicity is a periodicity in the processing order of the lots with an arbitrary number of lots as a unit. including.

Preferably, a trend component is detected from the measurement data, the periodic component and the trend component are removed from the measurement data, and a random component is extracted. Based on the random component, characteristics of the measurement data It is characterized by estimating the cause.
Preferably, the cause of abnormality of the device manufacturing apparatus or the device is estimated based on the measurement data.

  By detecting the periodic component from the measurement data, it is possible to easily estimate the cause of the characteristics of the measurement data such as abnormality (for example, a feature indicating abnormality) from the detected periodic component. Also, the remaining measurement data from which the periodic component is removed (the remaining component including the random component) is simpler than the case of including the periodic component, that is, the characteristics of the random component and the like are clarified, The cause of the characteristic indicated by the measurement data can be easily estimated.

  The device manufacturing method according to the present invention is a method for manufacturing a desired device, and measures data related to the device or device manufacturing apparatus, detects a periodic component from the measured data, and detects the detected periodic component. Alternatively, the cause of the characteristic indicated by the measurement data is estimated based on the residual component obtained by removing the periodic component from the measurement data, and the device is manufactured based on the cause of the characteristic of the estimated measurement data. It is characterized by controlling conditions.

  The device manufacturing system according to the present invention is a system for manufacturing a desired device, and includes a device manufacturing apparatus, data measuring means for measuring data related to the device manufacturing apparatus or the device, and a cycle based on the measured data. A period component detecting means for detecting a component, a cause estimating means for estimating a cause of the characteristic indicated by the measurement data based on the detected periodic component or a residual component obtained by removing the periodic component from the measurement data; Control means for controlling manufacturing conditions of the device based on the estimated cause of the characteristic of the measurement data.

  In this column, the reference numerals of the corresponding components shown in the attached drawings are shown for each component, but this is only for easy understanding and does not relate to the present invention. It is not intended to indicate that the means is limited to the embodiments described below with reference to the accompanying drawings.

ADVANTAGE OF THE INVENTION According to this invention, the data analysis method which can analyze data easily and appropriately can be provided by detecting a periodic component from the measurement data regarding manufacture of a device.
In addition, it is possible to provide a device manufacturing method and a device manufacturing system capable of appropriately manufacturing such a device by appropriately performing such data analysis.

An embodiment of the present invention will be described with reference to FIGS.
FIG. 1 is a block diagram showing a configuration of an exposure apparatus system 1 according to an embodiment of the present invention.
As shown in FIG. 1, the exposure apparatus system 1 includes an exposure apparatus 10, a track 20, a laser 30, an inline measuring instrument (inspection apparatus) 40, an offline measuring instrument (inspection apparatus) 50, an apparatus support system 60, and a communication network 70. Have.

The device support system 60 includes a server 61, a terminal device 62, and a remote terminal device 63. The communication network 70 includes a first network 71, a second network 72, and a gate device 73.
The exposure apparatus system 1 has a plurality of device manufacturing lines, and a plurality of exposure apparatuses 10, tracks 20, lasers 30, and inline measuring instruments 40 are provided corresponding to each line, for example. A plurality of offline measuring instruments 50 are provided separately from those production lines.

First, the configuration of each part of the exposure apparatus system 1 will be described in order.
The exposure apparatus 10 projects an image of a desired pattern formed on the reticle onto a substrate (wafer) coated with a photosensitive material, and transfers the pattern onto the wafer. The exposure apparatus 10 of the present embodiment is an exposure apparatus having an off-axis alignment optical system that detects a predetermined reference pattern of a wafer by image processing.

The overall configuration of the exposure apparatus will be described with reference to FIGS.
In the following description, the XYZ orthogonal coordinate system shown in FIG. 2 is set, and the positional relationship of each member will be described with reference to this XYZ orthogonal coordinate system. The XYZ orthogonal coordinate system is set such that the X axis and the Z axis are parallel to the paper surface, and the Y axis is set to a direction perpendicular to the paper surface. In the XYZ coordinate system in the figure, the XY plane is actually set to a plane parallel to the horizontal plane, and the Z-axis is set vertically upward.

  In the exposure apparatus 10, as shown in FIG. 2, the exposure light EL emitted from an illumination optical system (not shown) is irradiated to the pattern area PA formed on the reticle R through the condenser lens 101 with a uniform illuminance distribution. The As the exposure light EL, for example, g-line (436 nm), i-line (365 nm), light emitted from a KrF excimer laser (248 nm), ArF excimer laser (193 nm), or F2 excimer laser (193 nm) is used. .

  The reticle R is held on a reticle stage 102, and the reticle stage 102 is supported so that it can move and rotate in a two-dimensional plane on the base 103. A main control system 115 that controls the operation of the entire apparatus controls the operation of the reticle stage 102 via the drive device 104 on the base 103. The reticle R is positioned with respect to the optical axis AX of the projection lens PL by detecting a reticle alignment mark (not shown) formed around the reticle R by a reticle alignment system including a mirror 105, an objective lens 106, and a mark detection system 107. The

The exposure light EL that has passed through the pattern area PA of the reticle R is incident on, for example, a telecentric projection lens PL on both sides (or one side) and projected onto each shot area on the wafer (substrate) W. The projection lens PL has the best aberration correction with respect to the wavelength of the exposure light EL, and the reticle R and the wafer W are conjugated with each other under the wavelength. The illumination light EL is Keller illumination and is formed as a light source image at the center in the pupil EP of the projection lens PL.
The projection lens PL has a plurality of optical elements such as lenses. As the glass material of the optical element, an optical material such as quartz or fluorite is used according to the wavelength of the exposure light EL.

  The wafer W is placed on the wafer stage 109 via the wafer holder 108. On the wafer holder 108, a reference mark 110 used for baseline measurement or the like is provided. Wafer stage 109 is an XY stage that two-dimensionally positions wafer W in a plane perpendicular to optical axis AX of projection lens PL, and wafer W is positioned in a direction (Z direction) parallel to optical axis AX of projection lens PL. A stage for rotating the wafer W slightly, a stage for adjusting the inclination of the wafer W with respect to the XY plane by changing an angle with respect to the Z axis, and the like.

An L-shaped moving mirror 111 is attached to one end of the upper surface of the wafer stage 109, and a laser interferometer 112 is disposed at a position facing the mirror surface of the moving mirror 111. Although illustrated in a simplified manner in FIG. 2, the movable mirror 111 includes a plane mirror having a reflecting surface perpendicular to the X axis and a plane mirror having a reflecting surface perpendicular to the Y axis.
The laser interferometer 112 includes two X-axis laser interferometers that irradiate the moving mirror 111 along the X axis and a Y axis that irradiates the moving mirror 111 along the Y axis. The X coordinate and Y coordinate of the wafer stage 9 are measured by one laser interferometer for the X axis and one laser interferometer for the Y axis. Further, the rotation angle of the wafer stage 109 in the XY plane is measured based on the difference between the measurement values of the two X-axis laser interferometers.

A position measurement signal PDS indicating the X coordinate, the Y coordinate, and the rotation angle measured by the laser interferometer 112 is supplied to the stage controller 113. The stage controller 113 controls the position of the wafer stage 109 via the drive system 114 according to the position measurement signal PDS under the control of the main control system 115.
Further, the position measurement information PDS is output to the main control system 115. The main control system 115 outputs a control signal for controlling the position of the wafer stage 109 to the stage controller 113 while monitoring the supplied position measurement signal PDS.
Further, the position measurement signal PDS output from the laser interference system 112 is output to a laser step alignment (LSA) arithmetic unit 125 described later.

The exposure apparatus 100 includes a laser light source 116, a beam shaping optical system 117, a mirror 118, a lens system 119, a mirror 120, a beam splitter 121, an objective lens 122, a mirror 123, a light receiving element 124, an LSA arithmetic unit 125, and a projection lens PL. A TTL type alignment optical system having the above as a constituent member.
The laser light source 116 is a light source such as a He—Ne laser, for example, and emits a non-photosensitive laser beam LB with respect to the photoresist applied on the wafer W with red light (for example, wavelength 632.8 nm). . The laser beam LB passes through a beam shaping optical system 117 including a cylindrical lens and the like, and enters the objective lens 122 via a mirror 118, a lens system 119, a mirror 120, and a beam splitter 121. The laser beam LB transmitted through the objective lens 122 is reflected by a mirror 123 provided below the reticle R and obliquely with respect to the XY plane, and enters the periphery of the field of view of the projection lens PL in parallel with the optical axis AX. Then, the wafer W is irradiated vertically through the center of the pupil EP of the projection lens PL.

The laser beam LB is focused as slit-shaped spot light SP0 in the space in the optical path between the objective lens 122 and the projection lens PL by the action of the beam shaping optical system 117.
The projection lens PL re-images the spot light SP0 on the wafer W as a spot SP.
The mirror 123 is fixed so as to be outside the periphery of the pattern area PA of the reticle R and in the field of view of the projection lens PL. Accordingly, the slit-shaped spot light SP formed on the wafer W is located outside the projected image of the pattern area PA.

  In order to detect the mark on the wafer W by the spot light SP, the wafer stage 109 is moved horizontally with respect to the spot light SP in the XY plane. When the spot light SP relatively scans the mark, specularly reflected light, scattered light, diffracted light, and the like are generated from the mark, and the amount of light changes depending on the relative position of the mark and the spot light SP. Such optical information travels backward along the light transmission path of the laser beam LB, and reaches the light receiving element 124 via the projection lens PL, the mirror 123, the objective lens 122, and the beam splitter 121. The light receiving surface of the light receiving element 124 is disposed on a pupil image plane EP ′ substantially conjugate with the pupil EP of the projection lens PL, has a non-sensitive area with respect to specularly reflected light from the mark, and receives only scattered light and diffracted light.

  FIG. 3 is a diagram showing the distribution of light information from the mark on the wafer W on the pupil EP (or the pupil image plane EP ′). Above and below (Y-axis direction) the specularly reflected light D0 extending in a slit shape in the X-axis direction at the center of the pupil EP, positive first-order diffracted light + D1, second-order diffracted light + D2, and negative first-order diffracted light -D1, respectively. The second-order diffracted light -D2 is arranged, and scattered light ± Dr from the mark edge is positioned on the left and right (X-axis direction) of the regular reflection light D0. This is described in detail in, for example, Japanese Patent Laid-Open No. 61-128106, and detailed description thereof is omitted. However, the diffracted light ± D1, ± D2 is generated only when the mark is a diffraction grating mark.

In order to receive the optical information from the mark having the distribution shown in FIG. 3, the light receiving element 124 has four independent light receiving surfaces 124a, 124b, 124c,. The light receiving surfaces 124a and 124b receive scattered light ± Dr, and the light receiving surfaces 124c and 124d receive diffracted light ± D1 and ± D2.
FIG. 4 is a view showing a light receiving surface of the light receiving element 124. If the numerical aperture (NA) on the wafer W side of the projection lens PL is large and the third-order diffracted light generated from the diffraction grating mark also passes through the pupil EP, the light-receiving surfaces 124c and 124d have their third-order diffracted light. It is good to make it large enough to receive light.

  Each photoelectric signal from the light receiving element 124 is input to the LSA arithmetic unit 125 together with the position measurement signal PDS output from the laser interferometer 112, and the mark position information AP1 is generated. The LSA arithmetic unit 125 samples and stores the photoelectric signal waveform from the light receiving element 124 when the wafer mark is scanned with respect to the spot light SP, based on the position measurement signal PDS, and analyzes the waveform to analyze the mark. The mark position information AP1 is output as the coordinate position of the wafer stage 109 when the center coincides with the center of the spot light SP.

In the exposure apparatus shown in FIG. 2, only one set of TTL type alignment systems (116, 117, 118, 119, 120, 121, 122, 123, and 124) is shown, but is orthogonal to the paper surface. Another set is provided in the direction (Y-axis direction), and similar spot light is formed in the projection image plane. The extension lines in the longitudinal direction of these two spot lights are directed toward the optical axis AX.
Also, the solid line shown in the optical path of the TTL alignment optical system in FIG. 2 represents the imaging relationship with the wafer W, and the broken line represents the conjugate relationship with the pupil EP.

  Further, the exposure apparatus 10 includes an off-axis alignment optical system (hereinafter referred to as an alignment sensor) on the side of the projection optical system PL. This Arament sensor is an FIA (Field Image Alignment) type alignment sensor that detects signal position information (including image processing) by imaging a signal (n-dimensional signal) obtained by imaging the vicinity of an alignment mark on the substrate surface. It is.

In the exposure apparatus 100, the alignment sensor performs search alignment measurement and fine alignment measurement.
The search alignment measurement is a process of detecting a plurality of search alignment marks formed on the wafer and detecting a rotation amount of the wafer with respect to the wafer holder and a positional deviation in the XY plane. In this embodiment, as a signal processing method for search alignment measurement, a template matching method is used in which a predetermined pattern corresponding to the template is detected using a preset reference pattern (template).

The fine alignment measurement is a process for detecting an alignment mark for fine alignment formed corresponding to a shot area and finally positioning each exposure shot. In the present embodiment, as an image processing method for fine alignment, a technique (edge measurement technique) for extracting the edge of a mark and detecting its position is used.
Note that the image processing method in both the search alignment measurement and the fine alignment measurement is not limited to the method of the present embodiment, and each of them is a template matching method, an edge measurement method, or another image processing method. It may be.
The observation magnification at the time of the search alignment measurement and the observation magnification at the time of fine alignment measurement may be equal to each other, or the magnification at the time of fine alignment may be set higher than the magnification at the time of search alignment. Also good.

The alignment sensor includes a halogen lamp 126 that emits irradiation light for illuminating the wafer W, a condenser lens 127 that condenses the illumination light emitted from the halogen lamp 126 on one end of an optical fiber 128, and a waveguide for the illumination light. Optical fiber 128 to be included.
The reason why the halogen lamp 126 is used as the light source of the illumination light is that the wavelength range of the illumination light emitted from the halogen lamp 126 is 500 to 800 nm, and the wavelength range in which the photoresist coated on the upper surface of the wafer W is not exposed. This is because the wavelength band is wide and the influence of the wavelength characteristic of the reflectance on the surface of the wafer W can be reduced.

  Illumination light emitted from the optical fiber 128 passes through a filter 129 that cuts a photosensitive wavelength (short wavelength) region and an infrared wavelength region of the photoresist applied on the wafer W, and passes through the lens system 130 to be half. The mirror 131 is reached. The illumination light reflected by the half mirror 131 is reflected almost parallel to the X-axis direction by the mirror 132, and then enters the objective lens 133. Further, the field of the projection lens PL is formed around the lower part of the projection lens PL. It is reflected by a prism (mirror) 34 fixed so as not to be shielded from light, and irradiates the wafer W vertically.

  Although not shown, an appropriate illumination field stop is provided at a position conjugate with the wafer W with respect to the objective lens 133 in the optical path from the emission end of the optical fiber 28 to the objective lens 133. The objective lens 133 is set to a telecentric system, and an image of the exit end of the optical fiber 128 is formed on the surface 133a of the aperture stop (same as the pupil), and Koehler illumination is performed. The optical axis of the objective lens 133 is determined to be vertical on the wafer W so that the mark position does not shift due to the tilt of the optical axis when the mark is detected.

The reflected light from the wafer W is imaged on the index plate 136 by the lens system 135 via the prism 134, the objective lens 133, the mirror 132, and the half mirror 131. The index plate 136 is arranged conjugate with the wafer W by the objective lens 133 and the lens system 135, and is linearly extended in the X-axis direction and the Y-axis direction in a rectangular transparent window as shown in FIG. Index marks 136a, 136b, 136c, and 136d.
Therefore, the mark image of the wafer W is formed in the transparent window 136e of the index plate 136. The mark image of the wafer W and the index marks 136a, 136b, 136c, 136d are the relay systems 137, 139 and the mirror. An image is formed on the image sensor 140 via 138.

  The image sensor 140 (photoelectric conversion means, photoelectric conversion element) converts an image incident on the imaging surface into a photoelectric signal (image signal, image data, data, signal). For example, a two-dimensional CCD is used. A signal (n-dimensional signal) output from the image sensor 140 is input to the FIA calculation unit 141 together with the position measurement signal PDS from the laser interferometer 112.

In the present embodiment, the image sensor 140 obtains a two-dimensional image signal and inputs it to the FIA arithmetic unit 141 for use. In template matching performed during the search alignment process, signals obtained by the two-dimensional CCD are integrated (projected) in the non-measurement direction and used as a one-dimensional projection signal for measurement in the measurement direction.
Note that the format of the signal obtained by the image sensor 140 and the signal to be processed in the subsequent signal processing is not limited to the example of the present embodiment. At the time of template matching, two-dimensional image processing may be performed and a two-dimensional signal may be used for measurement. Alternatively, a three-dimensional image signal may be obtained and three-dimensional image processing may be performed. More specifically, the CCD signal is expanded in n dimensions (n is an integer of n ≧ 1) to generate, for example, an n-dimensional cosine component signal, an n-dimensional sine signal, or an n-order frequency signal. The present invention can also be applied to a device that performs position measurement using an n-dimensional signal.
In the description of the present specification, the term “image”, “image signal”, “image information”, “pattern signal”, and the like are similarly applied to not only a two-dimensional image but also such an n-dimensional signal (an n-dimensional image signal or the above-described one). As well as signals developed from image signals).

  The FIA arithmetic unit 141 detects an alignment mark from the input image signal, and obtains a deviation of the mark image with respect to the index marks 136a to 136d of the alignment mark. Then, the mark center detection position of the wafer stage 109 when the mark image formed on the wafer W is accurately positioned at the center of the index marks 136a to 136d from the stop position of the wafer stage 109 represented by the position measurement signal PDS. Information AP2 concerning is output.

  The FIA arithmetic unit 141 detects a position of a predetermined alignment mark image and a deviation thereof during each alignment process of search alignment and fine alignment. In the present embodiment, a template matching method is used during search alignment, and an edge detection processing method is used during fine alignment to detect mark position and displacement.

Each component of the exposure apparatus 10 operates in cooperation based on the control of the main control system 115. The main control system 115 controls each part of the exposure apparatus 10 as described above.
The main control system 115 communicates with a server 61 of the device support system 60 described later via the communication network 70. Then, operation history data, process program (process condition data, sometimes referred to as a recipe), apparatus setup state data, measurement data at each of the above-mentioned parts, that is, alignment measurement data, mark signal waveform trace data, etc. To the server 61.
The main control system is controlled in operating conditions based on the control information obtained by the server 61 of the device support system 60 based on the data described above, or the operation is stopped or interrupted.
The schematic configuration of the exposure apparatus 10 has been described above.

Returning to the exposure apparatus system 1 shown in FIG. 1, the track 20 is a transfer system for sequentially transferring wafers in each line. The track 20 is controlled by, for example, a track server (not shown) in the exposure apparatus system 1.
The laser 30 is a light source that provides exposure light to the exposure apparatus 10 of each line.
The in-line measuring instrument 40 is a sensor incorporated in the exposure apparatus 10, the track 20, or the laser 30, and is a sensor that measures information such as the temperature, humidity, and atmospheric pressure of the apparatus atmosphere. Data measured by the inline measuring instrument 40 is output to the server 61 of the apparatus support system 60 based on a data transfer method described later.
The off-line measuring instrument 50 is a measuring tool that is not directly incorporated in the device manufacturing line, and is, for example, an overlay measuring apparatus or a line width measuring apparatus.

The apparatus support system 60 collects various data from various apparatuses such as the exposure apparatus 10, the track 20, the laser 30, the in-line measuring instrument 40, and the offline measuring instrument 50 through the network 70, analyzes the data, and analyzes, for example, an apparatus abnormality Grasp the state of etc. Further, when there is an abnormality in the apparatus, the cause is detected based on the analysis result. Further, the process of each production line of the exposure apparatus system 1 is controlled based on the state of each apparatus.
For this purpose, the server 61 of the apparatus support system 60 first collects data from each apparatus such as the exposure apparatus 10, the track 20, the laser 30, the inline measuring instrument 40, and the offline measuring instrument 50, and stores and manages this data in a database. . Then, using the stored data, analysis or diagnosis of the operating state of the apparatus or line is performed. In addition, if necessary, the cause of the device failure is estimated. Further, based on the result, processing such as automatic correction control of each device, report creation / notification, and the like is performed.

  In the server 61 of the device support system 60, for example, functional modules as shown in FIG. 6 are developed by software or hardware, and various device support operations described later are executed.

The data collection unit 210 of the server 61 includes an exposure apparatus data acquisition unit 211 that collects data from the exposure apparatus 10, a track data acquisition unit 212 that collects data from the track 20, a laser data acquisition unit 213 that collects data from the laser 30, An in-line measuring instrument data acquisition unit 214 that collects data from the in-line measuring instrument 40 and an offline measuring instrument data acquisition unit 215 that collects data from the off-line measuring instrument 50 are included.
By these data acquisition units 211 to 215, an event log file, a sequence log file, an error log file, and an operation history log are transmitted from each apparatus of the exposure apparatus system 1 including the above-described exposure apparatus 10 via the communication network 70. Files, measurement result files, parameter setting files, diagnostic result files, various signal waveform files such as alignment, and other various trace data and log files are collected.

  The exposure process DB 220 is a database that accumulates data collected by the data collection unit 210. The data stored in the exposure process DB 220 is appropriately used by an application 250 (to be described later) and used for support processing of the exposure apparatus. Also, access is made from a terminal device 62 and a remote terminal device 63 which will be described later. In general, the exposure apparatus 10 generates a huge amount of data compared to other process apparatuses, and such a huge database is efficiently managed by the exposure process DB 220.

  The common software tool 230 is a tool that is commonly used when the server 61 performs a desired operation. For example, functions such as access to data collected by the data collection unit 210 or data stored in the exposure process DB 220, remote connection via a communication network, and the like are provided as the common tool.

The interface 240 is an interface for the server 61 to communicate with other devices and to input / output data and commands with workers.
Specifically, the interface 240 provides a communication environment in which the server 61 is connected to another apparatus such as the exposure apparatus 10 via the communication network 70 to transfer data. In addition, a remote network connection environment that enables access from the terminal device 62 connected via the communication network 70 is provided. In addition, a human interface environment is provided in which instructions and data are input / output from a worker in a suitable form.

The application 250 is a program that realizes a function for the server 61 to actually support the exposure apparatus 10 and the like in the exposure apparatus system 1.
As illustrated, the server 61 of this embodiment includes an apparatus / process analysis function 251, a report / notification function 252, an e-mail diagnosis function 253, an automatic diagnosis function 254, a PP management function 255, and an automatic correction control function 256. An application to be realized is provided.

The apparatus / process analysis function 251 analyzes data stored in the exposure process DB 220 and outputs the analysis result in the form of a graph or the like.
The apparatus / process analysis function 251 analyzes data by a data analysis method such as detection of a periodic component related to the present invention. The specific contents of this data analysis method will be described in detail later.
In addition to data analysis according to the present invention, the apparatus / process analysis function 251 performs aggregation processing, statistical processing, and the like of data stored in the exposure process DB 220.
For example, the analysis apparatus / process analysis function 251 totalizes the number of errors for each unit of the apparatus and outputs an error total graph as shown in FIG.
The error total graph shown in FIG. 7 is a graph that displays the number of error occurrences for each exposure apparatus 10 in a predetermined period for each error type (for each error occurrence unit). By looking at this graph, it is possible to grasp at a glance which unit of which exposure apparatus has a problem. That is, the dependency of the error on the device and the recipe (process program) can be analyzed, and the trouble handling time can be shortened.

Further, the apparatus / process analysis function 251 aggregates, for example, the processing time for each processing step and outputs a productivity graph as shown in FIG.
The productivity graph shown in FIG. 8 is a graph showing the wafer exchange time, alignment time, and exposure time for each wafer in the lot. From this graph, it can be seen that there are wafers with a long exchange time from time to time, and there is waste in wafer transfer. That is, from such a graph, the usage status of the apparatus can be grasped, and a measure for improving the productivity efficiency can be examined.

Further, the apparatus / process analysis function 251 outputs a graph showing the control state of the atmospheric pressure as shown in FIG. 9 by, for example, totaling the target atmospheric pressure and the actual atmospheric pressure in the lens chamber.
FIG. 9 is a plot in which the target air pressures of the two lens chambers (the A chamber and the B chamber) and the measured actual air pressure are overlaid. You can see that it is following. The environment of the exposure apparatus 10 can be grasped from such a graph. That is, the correlation between the device performance and the environmental variation can be obtained, and the time for investigating the cause of the process abnormality can be shortened and the frequency of device adjustment can be optimized.

  By operating the apparatus / process analysis function 251 in this way, the burden of graph creation when data is organized and analyzed is reduced. And analysis efficiency improves and a downtime can be shortened.

The report / notification function 252 outputs the data analysis result or abnormality cause estimation result, etc., performed by the apparatus / process analysis function 251 to, for example, the terminal device 62 or the remote terminal device 63 where the worker is present via the communication network 70. To do.
Further, the report / notification function 252 automatically generates a report indicating the operation state of each apparatus of the exposure apparatus system 1 in units of months, weeks, or days, and outputs it to a predetermined output destination set in advance. . The report content is management data for maintaining an appropriate operation state of the apparatus, such as MTBF, MTBI, or a failure factor-specific histogram.

  The e-mail diagnosis function 253 is a function for transmitting output contents of an automatic diagnosis function 254 described later to a remote terminal device 63 at a remote location via a communication network. As a result, it is possible to monitor the performance of each apparatus of the exposure apparatus system 1 at the remote terminal apparatus 63, grasp the malfunction or failure, determine the failed part, and the like. As a result, it is possible to diagnose and adjust the exposure apparatus 10 and the like from a remote location. Further, by regularly monitoring the operation history and log data, preventive maintenance of the apparatus can be performed.

The automatic diagnosis function 254 is a function that analyzes data sent from various devices and automatically detects an abnormality in the operation status of the device. The automatic diagnosis function 254 also performs data analysis / analysis and estimation of the cause of abnormality using the data analysis method according to the present invention. The data analysis / analysis and the method for estimating the cause of abnormality will be described in detail later.
In addition, the automatic diagnosis function 254 performs automatic diagnosis such as error number diagnosis, maintenance data diagnosis, or production data diagnosis.
In the error number diagnosis, an apparatus trouble and a defective process are found from the number of occurrences of errors in the stage, loader, alignment, and the like of the exposure apparatus 10.
Maintenance data diagnosis optimizes maintenance frequency and consumables replacement time by monitoring changes in various measurement results such as the stage, imaging system, illumination system, alignment, and AF of the exposure apparatus 10 Is what you do.
The production data diagnosis is for early detection of process abnormality and prevention of defective product production by monitoring alignment measurement results, focus control data, and the like.
With such an automatic diagnosis function 254, downtime can be shortened and abnormalities during production can be detected at an early stage or at an appropriate timing, and the number of rework wafers can be reduced.

The recipe (PP) management function 255 is a function for managing a recipe that describes actual processing conditions in a process apparatus such as the exposure apparatus 10.
In the exposure apparatus system 1, recipes applied to the exposure apparatus 10 are centrally managed in the server 61, and can be downloaded or uploaded from the server 61 to each exposure apparatus 10. For this purpose, the PP management function 255 provides an environment in which an operator can create a recipe on the server 61. In other words, the PP management function 255 provides an environment, tools, and the like that allow a worker to access the server 61 from an office PC or the like via the communication network 70 to create and edit recipes (desktop recipe editing). function).
The PP management function 255 provides an environment for optimizing the recipe. Usually, the worker edits and optimizes the recipe based on the analysis result and diagnosis result by the above-described apparatus / process analysis function 251 and automatic diagnosis function 254, for example. However, when editing a recipe, there are cases where it is desired to check the validity of the processing conditions. The PP management function 255 provides the worker with a simulation environment for checking the validity of such conditions. More specifically, the PP management function 255 provides an exposure processing simulation environment based on a set recipe, and thereby, for example, overlay, image formation, and throughput evaluation can be performed.

The automatic correction control function 256 is a function that performs feedback or feedforward correction control based on data sent from various apparatuses, and stabilizes the functions and operations of the apparatus.
The automatic correction control function 256 according to the present embodiment roughly performs two correction controls: a correction control for a change in the environment and the apparatus state, and a correction control for a process.

Compensation control for changes in the environment and equipment status stabilizes equipment performance by performing compensation control for changes in the environment such as temperature, atmospheric pressure, and humidity, and changes in equipment status such as exposure equipment, tracks, and lasers. Is intended.
Specifically, for example, the following controls are performed.
First, the focus surface of the exposure apparatus 10 is predicted and controlled from change data of atmospheric pressure, temperature, and humidity to improve surface stability (long-term focus stabilization).
In addition, the optimal path light quantity is predicted and controlled from the change data of laser, air pressure, temperature, and humidity to improve the CD stability between the wafers (inter-wafer ΔCD stabilization).
Further, finely adjusting (correcting) the amount of light for each shot for hitting in the vicinity of the wafer due to non-uniformity of the PEB temperature to improve the stability of ΔCD in the wafer (stabilization of ΔCD in the wafer).
It also measures temperature changes at the loader / track interface, predicts wafer expansion / contraction during exposure, applies alignment correction, and improves stacking accuracy (stabilization of stacking between wafers).

The correction control for the process predicts the fluctuation caused by the process and the fluctuation due to the combination of the exposure apparatus, the track, the laser, etc., and corrects and controls various operating conditions based on this. This is intended to stabilize the performance. ,
Specifically, the following control is performed.
For example, correction parameters of SDM (distortion matching) and GCM (grid matching) are optimized to improve overlay accuracy (matching accuracy between machine matching overlays).
In addition, the actual throughput is calculated by each recipe (process program) and the actual throughput between the exposure apparatus and the track, and the throughput reduction unit is specified and countermeasures are supported (productivity improvement by the throughput simulator). .
In addition, the alignment measurement algorithm is automatically selected for each process to improve the overlay accuracy (alignment measurement algorithm automatic measurement).
Further, lens circumference correction control optimized for the mask pattern is performed (lens aberration correction control).

  The operation screens for these application-level functions are constructed by a web browser, and all functions can be used from anywhere without remote / local distinction.

  The terminal device 62 of the device support system 60 is a terminal device for an operator to access the server 61 in a factory, for example. The terminal device 62 is connected to the first network 71 of the communication network 70, and is connected to the server 61 via the first network 71.

The remote terminal device 63 of the apparatus support system 60 is a terminal device for the parties concerned to access the server 61 from, for example, an office outside the factory or a vendor of the exposure apparatus 10. The remote terminal device 63 is connected to the server 61 via the second network 72, the gate device 73, and the first network 71 and using the function of the interface 240 of the server 61.
The above is the configuration of the device support system 60.

  The communication network 70 is a network for connecting each apparatus of the exposure apparatus system 1. The first network 71 of the communication network 70 is a communication network in a factory, for example, and includes a server 61 and a terminal device 62 of the apparatus support system 60, an exposure apparatus 10, a track 20, a laser 30, an inline measuring instrument 40, and offline measurement. Connect the device 50 or the like. The second network 72 of the communication network 70 is, for example, a communication network outside the factory, a network managed by the vendor of the exposure apparatus 10, or the like. As illustrated, the second network 72 and the first network 71 are connected by a gate device 73 having a firewall function, for example.

Next, a data analysis method according to the present invention in the exposure apparatus system 1 having such a configuration will be described with reference to FIGS. Note that the data analysis method described below is implemented in the apparatus / process analysis function 251 or the automatic diagnosis function 254 of the server 61 described above.
First, an outline flow of the data analysis method will be described with reference to FIG.
FIG. 11 is a flowchart showing the flow of the data analysis method according to the present invention.
In the measurement data analysis, first, it is checked whether or not the measurement data has periodicity (step S110). If periodicity is recognized in the measurement data, the cause of the abnormality is estimated based on the detected periodic component (step S120). If the cause of the error is found from the periodic component (step S130), the data analysis process ends (step S160).
If the cause of the error is not found from the periodic component (step S130), the trend component and the periodic component are subtracted from the measurement data, the random component is extracted, and the measurement data is analyzed (step S140).
If it is determined in step S110 that the measurement data has no periodicity, the trend data is subtracted from the measurement data, the random component is extracted, and the measurement data is analyzed (step S150).

Next, each process will be described in detail.
First, a method for detecting the periodicity of measurement data and estimating the cause of abnormality will be described.
In detecting periodicity, measurement data is applied to various periodicities such as time periodicity, intra-lot wafer periodicity, and lot injection periodicity, and the degree of periodicity correlation is calculated. When the degree of correlation is higher than a predetermined threshold, it is determined that there is periodicity, and the cause of the abnormality is estimated from the type and period of the period.
If at least two points (samples) are not included in one cycle, the waveform is not reproduced. Therefore, it is necessary to perform data sampling with a sense that the reciprocal of the double frequency of the highest frequency included in the signal. .

Time periodicity indicates periodicity in units of time such as year, month, week, day, hour, minute and second.
The time periodicity is detected by giving a period T to the function f (x) as shown in Equation (1) in units of years, months, days, hours, minutes, seconds, etc., and calculating the degree of periodicity correlation. calculate. As the degree of correlation, any one of formulas (2) to (4) is used. Equation (3) is obtained by subtracting an average value from Equation (2) in order to remove this influence when an offset occurs in units of periods. Also, equation (4) is normalized with each standard deviation in order to remove the influence of amplitude fluctuations in units of cycles with respect to equation (3). When it is desired to make a determination with a certain threshold, the correlation value of equation (4) is used.
When the degree of periodicity correlation exceeds a predetermined threshold, it is determined that there is periodicity, and the minimum integer T satisfying Expression (1) is regarded as the period of the function f (x).
A factor that coincides with this time period T is estimated to be the cause of the abnormality.

The intra-lot wafer periodicity indicates the periodicity in units of wafers in a lot, such as the first wafer in the lot, the last wafer, or every one or several wafers.
In the detection of the wafer periodicity in the lot, as in the time periodicity described above, a period T is given to the function f (x) in units of wafers as shown in Expression (1), and Expressions (2) to ( Based on 4), the degree of periodic correlation is calculated.
When the degree of periodicity correlation exceeds a predetermined threshold, it is determined that there is periodicity and the measurement data is analyzed.
Specifically, for example, when a line width variation occurs for each wafer, it is estimated that the problem is caused by using two types of C / D pods (A, B) in parallel. In addition, when the overlay fluctuation occurs for each wafer, it is estimated that the problem is caused by the CMP in two ways of cutting (right and left). Further, when the overlay fluctuation occurs only in the first wafer, it is estimated that the deformation is caused by a temperature difference between the C / D and the exposure apparatus, a temperature difference between the wafer and the holder, or the like.

The lot insertion periodicity indicates a periodicity in units of lots to be input.
Similarly to the time periodicity described above, the lot insertion periodicity is also detected by giving a period T in units of lots to the function f (x) as shown in the equation (1) using the lot to be input as a unit. The degree of periodic correlation is calculated based on (2) to (4).
When the degree of periodicity correlation exceeds a predetermined threshold, it is determined that there is periodicity, and the minimum integer T satisfying Expression (1) is regarded as the period of the function f (x).
Then, it is estimated that the factor that coincides with the lot insertion period T is the cause of the abnormality.

Next, a method for extracting a random component in consideration of trend characteristics from measurement data and estimating the cause of the abnormality will be described.
In this embodiment, in order to extract a random component, the regression equation which added the trend property is used. That is, in order to consider temporal variation in the regression equation, a time variable is incorporated in the form of an exponential function as shown in Equation (5).

In Equation (5), T is a trend variable and D is a regression coefficient. E is the Napier number (the base of the natural logarithm) and is approximated by 2.71828. When the objective variable is expected to increase or decrease over time as the background of the measurement data, the introduction of such a trend variable is effective.
As the regression equation, linear approximation, polynomial approximation or the like is used, and it is obtained by the least square method.
Random components are extracted on the basis of fitting an appropriate regression equation that takes into account such trend characteristics, the measurement data is analyzed, and the cause of the abnormality is estimated. In addition, when periodicity is recognized in measurement data, both a trend component and a periodic component are removed with respect to measurement data, a random component is extracted, and an abnormal cause is estimated.

For example, for the AF follow-up error measurement data, a trend component unique to the apparatus due to AF long-term fluctuation is subtracted, and further, a periodic component due to apparatus / environment fluctuation is subtracted. Then, the measurement data thus obtained is analyzed. Specifically, for example, when an offset is present from a certain time, an abnormality caused by the apparatus is estimated, and when a random component is equal to or larger than a predetermined threshold, an abnormality caused by a process is estimated.
Specifically, for example, an apparatus as shown in FIG. 11C is obtained by subtracting a trend component unique to the apparatus as shown in FIG. 11B from the AF follow-up error measurement data as shown in FIG. As a result of subtracting periodic components due to environmental fluctuations, random components as shown in FIG. 11D are detected. Therefore, the measurement data is analyzed using the random component data.
At this time, for example, as shown in FIG. 12, by graphing the number of AF follow-up errors occurring for each recipe name and device name, it is easy to determine whether the cause of the error is caused by the process or the device. In FIG. 12, the X axis is the recipe (process program) name, the Y axis is the device name, and the X axis is the number of errors.

  In addition, as shown in Expression (5), the trend component may not be applied to the regression equation, and the random component may be extracted by applying the regression equation to the result obtained by subtracting the trend component from the measurement data in advance. .

Next, the operation of the exposure apparatus system 1 having such a configuration, that is, the flow of processing when the exposure apparatus system 1 is actually operated will be briefly described.
First, data measured in the exposure apparatus 10 is transferred from each exposure apparatus 10 to the server 61 by the function of the data collection unit 210 of the server 61. The measurement and collection of data in the exposure apparatus 10 are performed irregularly when the exposure apparatus 10 is operated regularly and regularly while the exposure apparatus 10 is operating normally, or when an abnormality occurs in the exposure apparatus 10. There are cases.
After the data is collected, analysis and automatic diagnosis are performed by the device / process analysis function 251 and the automatic diagnosis function 254 of the server 61, for example. Here, at least processing such as detection of the periodic component of the measurement data as described above and detection of a random component based on a regression formula that takes into account the trend of the measurement data is performed. In a system that automatically estimates the cause of an abnormality, the cause of the abnormality is estimated based on the detected periodic component or random component.

Next, the obtained analysis result (periodic component or random component) and the result of automatic diagnosis (abnormal state, cause of abnormality, etc.) are sent to the terminal device 62 of the worker in the office or the like by the e-mail diagnosis function 253. Forward.
The operator confirms the transferred result, accesses the server 61 as necessary, and browses the data in a graph form, for example, by the functions of the report / notification function 251 and the report / notification function 252 of the server 61. And grasp the situation. Further, if necessary, processing such as estimation of the cause of abnormality is performed based on information such as analysis results and graphs.
Based on the result, the operator can correct, change, or adjust the exposure process recipe (process program), adjust the parameters of the exposure apparatus 10, adjust the unit, replace parts, etc., for example, to eliminate the cause of the abnormality. Take. In the system that automatically estimates the cause of the abnormality, the recipe may be automatically corrected based on the estimated cause of the abnormality.

  By operating the exposure apparatus system 1 in this way, the state of the exposure apparatus 10 or an abnormal state can be quickly taken up by the server 61, and the data can be easily and appropriately analyzed to estimate the cause of the abnormality, for example. it can. Further, based on the result, the recipe (process program) can be appropriately corrected as necessary. Therefore, it is possible to appropriately cope with the occurrence of an abnormal state, and efficient production of devices and the like becomes possible.

In addition, this Embodiment was described in order to make an understanding of this invention easy, and does not limit this invention at all. Each element disclosed in the present embodiment includes all design changes and equivalents belonging to the technical scope of the present invention, and various suitable modifications are possible.
For example, the present invention is not limited to a system including an exposure apparatus. The present invention can also be applied to any process processing apparatus used in the electronic device manufacturing process.

FIG. 1 is a view showing the arrangement of an exposure apparatus system according to an embodiment of the present invention. FIG. 2 is a view showing the arrangement of the exposure apparatus of the exposure apparatus system shown in FIG. FIG. 3 is a view showing the distribution of optical information from the mark on the wafer on the pupil image plane of the TTL type alignment system of the exposure apparatus shown in FIG. FIG. 4 is a view showing a light receiving surface of a light receiving element of the TTL alignment system of the exposure apparatus shown in FIG. FIG. 5 is a sectional view of the finger plate of the off-axis alignment optical system of the exposure apparatus shown in FIG. FIG. 6 is a diagram showing a functional configuration of a server of the exposure apparatus system shown in FIG. FIG. 7 is a diagram showing an error total graph by the device / process analysis function of the server function shown in FIG. FIG. 8 is a diagram showing a productivity graph by the device / process analysis function of the server function shown in FIG. FIG. 9 is a diagram showing a device environment graph by the device / process analysis function of the server function shown in FIG. FIG. 10 is a flowchart showing a data analysis method in the exposure apparatus system shown in FIG. FIG. 11 is a diagram for explaining a specific example of data analysis by the data analysis method shown in FIG. 12 is a diagram illustrating an example of a data analysis result obtained by the data analysis method illustrated in FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Exposure apparatus system 10 ... Exposure apparatus 101 ... Condenser lens 102 ... Reticle stage 103 ... Base 104 ... Drive apparatus 105 ... Mirror 106 ... Objective lens 107 ... Mark detection system 108 ... Wafer holder 109 ... Wafer stage 110 ... Reference mark 111 ... Moving mirror 112 ... Laser interferometer 113 ... Stage controller 114 ... Drive system 115 ... Main control system 116 ... Laser light source 117 ... Beam shaping optical system 118, 120, 123 ... Mirror 119 ... Lens system 121 ... Beam splitter 122 ... Objective lens 124 Light receiving element 125 LSA arithmetic unit 126 Halogen lamp 127 Condenser lens 128 Optical fiber 129 Filter 130, 135 Lens system 131 Half mirror 132, 138 Mirror 133 ... Objective lens 134 ... Prism (mirror)
136 ... Finger mark 137, 139 ... Relay system 140 ... Image sensor 141 ... FIA arithmetic unit 20 ... Track 30 ... Laser 40 ... Inline measuring device 50 ... Offline measuring device 60 ... Device support system 61 ... Server 210 ... Data collecting unit 211 ... Exposure device data acquisition unit 212 ... Track data acquisition unit 213 ... Laser data acquisition unit 214 ... Inline measuring device data acquisition unit 215 ... Offline measuring device data acquisition unit 220 ... Exposure process DB
230 ... Common software tool 240 ... Interface 250 ... Application 251 ... Device / process analysis function 252 ... Report / notification function 253 ... E-mail diagnosis function 254 ... Automatic diagnosis function 255 ... PP management function 256 ... Automatic correction control function 62 ... Terminal Device 63 ... Remote terminal device 70 ... Communication network 71 ... First network 72 ... Second network 73 ... Gate device

Claims (10)

Detect periodic components from measurement data related to devices or device manufacturing equipment,
A trend component is detected from the measurement data,
Removing the detected periodic component and the detected trend component from the measurement data to extract a random component;
A data analysis method for estimating the cause of the characteristic indicated by the measurement data based on at least the extracted random component ,
The data analysis method is characterized in that the measurement data is AF follow-up error measurement data, and when the extracted random component is offset from a specific time, it is estimated that the abnormality is caused by the apparatus . Detect periodic components from measurement data related to devices or device manufacturing equipment,
A trend component is detected from the measurement data,
Removing the detected periodic component and the detected trend component from the measurement data to extract a random component;
A data analysis method for estimating the cause of the characteristic indicated by the measurement data based on at least the extracted random component ,
The data analysis method is characterized in that the measurement data is AF follow-up error measurement data, and when the extracted random component is equal to or greater than a predetermined threshold, it is estimated that the abnormality is caused by a process. Furthermore, the cause of the characteristic indicated by the measurement data is estimated based on the detected periodic component or a residual component obtained by removing the periodic component from the measurement data.
The data analysis method according to claim 1 or 2 . An event having the same period as the detected periodic component is detected, and the event is estimated as a cause of the characteristic indicated by the measurement data.
The data analysis method according to claim 1 . Detection of the periodic component is
Set a temporary cycle sequentially,
Detecting the correlation of the measurement data away from the provisional period,
When the correlation is higher than a predetermined value, it is detected that the measurement data has a periodicity with the provisional period as a period.
The data analysis method according to claim 1 . Based on the measurement data, the cause of abnormality of the device manufacturing apparatus or the device is estimated.
The data analysis method according to claim 1 . A method of manufacturing a desired device, comprising:
Measure data on the device or device manufacturing equipment,
A periodic component is detected from the measured data,
A trend component is detected from the measurement data,
Removing the detected periodic component and the detected trend component from the measurement data to extract a random component;
Based on at least the extracted random component, estimate the cause of the characteristic indicated by the measurement data,
A device manufacturing method for controlling manufacturing conditions of the device based on a cause of the estimated characteristic of the measurement data ,
The device manufacturing method , wherein the measurement data is measurement data of an AF tracking error, and when the extracted random component is offset from a specific time, it is estimated that the abnormality is caused by the apparatus . A method of manufacturing a desired device, comprising:
Measure data on the device or device manufacturing equipment,
A periodic component is detected from the measured data,
A trend component is detected from the measurement data,
Removing the detected periodic component and the detected trend component from the measurement data to extract a random component;
Based on at least the extracted random component, estimate the cause of the characteristic indicated by the measurement data,
A device manufacturing method for controlling manufacturing conditions of the device based on a cause of the estimated characteristic of the measurement data ,
The device manufacturing method, wherein the measurement data is AF follow-up error measurement data, and when the extracted random component is equal to or greater than a predetermined threshold, it is estimated that the abnormality is caused by a process. A system for manufacturing a desired device,
Device manufacturing equipment;
Data measuring means for measuring data relating to the device manufacturing apparatus or the device;
Periodic component detection means for detecting a periodic component from the measured data;
Trend component detecting means for detecting a trend component from the measurement data;
Based on a random component extracted by removing the detected periodic component and the detected trend component from the measurement data, cause estimation means for estimating the cause of the characteristic indicated by the measurement data;
A device manufacturing system comprising: control means for controlling manufacturing conditions of the device based on the cause of the characteristics of the estimated measurement data ,
The data measuring means measures AF follow-up error measurement data,
In the device manufacturing system , the cause estimating means estimates that the extracted random component is abnormal due to an apparatus when an offset is added from a specific time . A system for manufacturing a desired device,
Device manufacturing equipment;
Data measuring means for measuring data relating to the device manufacturing apparatus or the device;
Periodic component detection means for detecting a periodic component from the measured data;
Trend component detecting means for detecting a trend component from the measurement data;
Based on a random component extracted by removing the detected periodic component and the detected trend component from the measurement data, cause estimation means for estimating the cause of the characteristic indicated by the measurement data;
A device manufacturing system comprising: control means for controlling manufacturing conditions of the device based on a cause of the characteristics of the estimated measurement data ,
The data measuring means measures AF follow-up error measurement data,
The cause estimation unit estimates that the abnormality is caused by a process when the extracted random component is equal to or greater than a predetermined threshold.

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