Method for diagnosing a malfunction in a control device, diagnostic device, control device, lithography device, method for manufacturing articles, and program

Abstract

To provide technique favorable to diagnosis for failure portion of a control device having a plurality of actuators and a plurality of sensors.SOLUTION: There is provided a method for diagnosing a failure portion of a control device including: a plurality of actuators that impart thrust to an object; a plurality of sensors that detect state quantities of the object; and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, the method comprises: a first step of comparing a first signal output from each of the plurality of sensors in a state in which the plurality of actuators and the plurality of sensors are considered to be normal, and a second signal output from each of the plurality of sensors; and a second step of diagnosing a device including at least one of an actuator in a faulty state and a sensor in a faulty state as the failure portion based on a comparison result of the first step.SELECTED DRAWING: Figure 5

Description

Technical Field

[0005]

[0001] The present invention relates to a method for diagnosing a failure location of a control device, a diagnostic device, a control device, a lithography device, a method for manufacturing an article, and a program.

Background Art

[0002] Generally, a control device has an actuator that applies a thrust to an object (control target) and a sensor that measures a state quantity of such an object, determines an operation amount of the actuator according to an output signal of the sensor, and controls the state quantity of the object. For example, an active vibration isolation table, which is one of the control devices, has a plurality of acceleration sensors provided on a surface plate and a linear motor, and determines an operation amount of the linear motor based on an output signal of the acceleration sensors to control the acceleration of the surface plate. <00,00010>

[0003] Failures of sensors and actuators used in a control device are factors that reduce the control accuracy of an object. When an active vibration isolation table is used in an exposure device, failures of sensors (acceleration sensors) and actuators lead to a decrease in exposure accuracy and the production of defective products. Therefore, it is necessary to quickly detect (judge) and repair failures (failure locations) of sensors and actuators.

[0004] Therefore, techniques for detecting failures of sensors and actuators used in a control device have been proposed (see Patent Documents 1 and 2). Patent Document 1 discloses a technique for determining whether a sensor is faulty or an actuator is faulty by newly providing a detection unit for detecting an actuator failure. Patent Document 2 discloses a technique for obtaining transfer characteristics of sensors and actuators and estimating a failure location based on the transfer characteristics of individual sensors and individual actuators.

Prior Art Documents

Patent Documents

[0005] [[ID=?]]

Patent Document 1

[0006] However, the technology disclosed in Patent Document 1 requires a detection unit to detect actuator failures, which leads to increased costs and a more complex device configuration. Furthermore, the technology disclosed in Patent Document 2 involves vibrating the object (controlled object) when determining its transmission characteristics, which temporarily reduces the control accuracy of the object. For example, if the control device is used in an exposure apparatus, defective products will be produced while the object is being vibrated, forcing the apparatus to be stopped and reducing productivity.

[0007] This invention has been made in view of the problems of the prior art, and its exemplary objective is to provide a technique advantageous for diagnosing the location of a failure in a control device having multiple actuators and multiple sensors. [Means for solving the problem]

[0008] To achieve the above objective, one aspect of the present invention is a method for diagnosing a fault in a control device having a plurality of actuators that provide thrust to an object, a plurality of sensors that detect state quantities of the object, and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, wherein the method compares a first signal output from each of the plurality of sensors when the plurality of actuators and the plurality of sensors are considered to be normal with a second signal output from each of the plurality of sensors when the control device is in use. This allows us to obtain a pattern consisting of information indicating whether the output of each of the aforementioned sensors is normal or abnormal. The first step and the aforementioned first step The pattern obtained Based on this, a device including at least one of the actuators and sensors that is in a faulty state is selected from the plurality of actuators and the plurality of sensors as the faulty location. identificationThe second step involves having Furthermore, the second signal is a signal that can be acquired without stopping the control device in order to acquire the second signal, and in the second step, the device is identified from the plurality of actuators and the plurality of sensors by comparing a table showing the correspondence between a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal and the fault location with the pattern obtained in the first step. It is characterized by doing so.

[0009] Further objects or other aspects of the present invention will be revealed by embodiments described below with reference to the accompanying drawings. [Effects of the Invention]

[0010] According to the present invention, for example, it is possible to provide a technique that is advantageous for diagnosing the location of a failure in a control device having multiple actuators and multiple sensors. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic diagram showing the configuration of an active vibration isolation table as one aspect of the present invention. [Figure 2] This diagram shows the flow of determining the control amount of a linear motor from the signal output from an acceleration sensor. [Figure 3] This is a control block diagram for an active vibration isolation table. [Figure 4] This is a schematic diagram showing the configuration of the output recording unit and the abnormality diagnosis unit. [Figure 5] This is a schematic diagram showing the configuration of the fault diagnosis unit. [Figure 6] This figure shows an example of an abnormality diagnosis table. [Figure 7] This is a flowchart to explain the process of the fault diagnosis unit. [Figure 8] This figure shows the acceleration data recorded in the first recording unit and the second recording unit, respectively. [Figure 9] This figure shows the acceleration data recorded in the first recording unit and the second recording unit, respectively. [Figure 10] This is a schematic diagram showing the configuration of an exposure apparatus as one aspect of the present invention. [Modes for carrying out the invention]

[0012] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the invention according to the claims. Although a plurality of features are described in the embodiments, not all of these plurality of features are essential for the invention, and the plurality of features may be arbitrarily combined. Further, in the accompanying drawings, the same or similar configurations are denoted by the same reference numerals, and redundant descriptions are omitted.

[0013] FIG. 1 is a schematic diagram showing the configuration of an active vibration isolation table 1 as one aspect of the present invention. The active vibration isolation table 1 is a control device that performs four-axis control with respect to the Z-axis, the pitch axis around the X-axis, the roll axis around the Y-axis, and the twist (Phi) axis.

[0014] The active vibration isolation table 1 includes a surface plate 100, a plurality of acceleration sensors, in this embodiment, four acceleration sensors 101 to 104, and a plurality of linear motors, in this embodiment, four linear motors 105 to 108. The acceleration sensors 101 to 104 are provided at the four corners of the surface plate 100, and measure (detect) the acceleration in the Z direction of the active vibration isolation table 1 (surface plate 100) as a state quantity of the control target (object). The linear motors 105 to 108 function as actuators that drive the surface plate 100 by applying a thrust in the Z direction to the surface plate 100.

[0015] FIG. 2 is a block diagram showing a flow for determining the operation amounts of linear motors 105 to 108 from the signals output from acceleration sensors 101 to 104. As shown in FIG. 2, first, the accelerations in the Z direction of the active vibration isolation table 1 are measured by each of the acceleration sensors 101 to 104, and the output signals thereof are input to the calculation unit 200. Next, in the calculation unit 200, accelerations related to the Z axis, pitch axis, roll axis, and twist axis of the active vibration isolation table 1 are calculated from the output signals from the acceleration sensors 101 to 104 via the mode conversion matrix 201. Then, in the controllers 202 to 205 related to each axis including a PID controller and a filter, the operation amounts Z', Pitch', Roll', and Phi' related to each axis are determined. Then, the operation amounts Z', Pitch', Roll', and Phi' related to each axis are input to the thrust distribution matrix 206 to determine the respective operation amounts of the linear motors 105 to 108.

[0016] FIG. 3 is a control block diagram of the active vibration isolation table 1. The controller 300 supplies current to the linear motors 105 to 108 based on the operation amounts determined by the calculation unit 200, and drives the surface plate 100 by applying a thrust to the surface plate 100 from the linear motors 105 to 108. The acceleration sensors 101 to 104 provided on the surface plate 100 measure the acceleration of the active vibration isolation table 1 (surface plate 100), and feedback the output signals thereof to the calculation unit 200. Note that the controller 300 also functions as a diagnostic device for diagnosing a failure location of the active vibration isolation table 1 (control device) as will be described later.

[0017] Also, the accelerations (output signals) measured by the acceleration sensors 101 to 104 are also input to the output recording units 301 to 304 and recorded by the output recording units 301 to 304. The accelerations recorded by the output recording units 301 to 304 are input to the abnormality diagnostic units 305 to 308 as signals. The abnormality diagnostic units 305 to 308 diagnose the presence or absence of an abnormality in the acceleration of the active vibration isolation table 1 (surface plate 100) based on the signals input from the output recording units 301 to 304, and input the diagnosis results to the failure diagnosis unit 309.

[0018] Figure 4 is a schematic diagram showing the configuration of the output recording unit 301 and the abnormal diagnosis unit 305. Since the configuration of each of the output recording units 301 to 304 and each of the abnormal diagnosis units 305 to 308 are the same, the output recording unit 301 and the abnormal diagnosis unit 305 will be used as examples in this explanation. The output recording unit 301 includes a switch 400, a first recording unit 401, and a second recording unit 402. The abnormal diagnosis unit 305 includes a first extraction unit 500, a second extraction unit 501, and a comparison unit 502.

[0019] In the output recording unit 301, by setting (controlling) the switch 400, the acceleration (output signal) measured by the acceleration sensor 101 can be recorded as acceleration data in the first recording unit 401 or the second recording unit 402. Both the first recording unit 401 and the second recording unit 402 can record acceleration data for any desired time (period).

[0020] In this embodiment, acceleration data (first signal) is recorded in the first recording unit 401 for an arbitrary period of time when the acceleration sensors 101 to 104 and linear motors 105 to 108 are not malfunctioning (initial state), such as immediately after the active vibration isolation table 1 is installed (during assembly). Here, the state in which the acceleration sensors 101 to 104 and linear motors 105 to 108 are not malfunctioning means a state in which the acceleration sensors 101 to 104 and linear motors 105 to 108 are considered to be normal, that is, a state in which they are compensated to be normal. Note that the acceleration data recorded in the first recording unit 401 is not limited to actual data, but may also be acceleration data obtained from a simulation in an ideal state in which the active vibration isolation table 1 has no malfunctions. Furthermore, the arbitrary period of time may be a fixed period such as 1 minute, or, if the active vibration isolation table 1 is used in an exposure apparatus, it may be the period for exposing one substrate. Next, when the active vibration isolation table 1 is in operation (in use), the switch 400 is switched to continuously record the acceleration measured by the acceleration sensor 101 as acceleration data (second signal) in the second recording unit 402. Then, the acceleration data recorded in the first recording unit 401 and the second recording unit 402 are input to the abnormality diagnosis unit 305 to diagnose whether there is an abnormality in the acceleration of the active vibration isolation table 1 (base plate 100). Here, since the acceleration data recorded in the first recording unit 401 is reference data, the acceleration data may be recorded (updated) again depending on the device status of the active vibration isolation table 1 (for example, when the acceleration sensor 101 is repaired or replaced).

[0021] The acceleration data recorded in the first recording unit 401 is input to the first extraction unit 500. The first extraction unit 500 extracts (extracts) features from the acceleration data input from the first recording unit 401, such as the instantaneous value of acceleration (output signal) or statistical values ​​such as the maximum value, mean value, and standard deviation over a predetermined period. Similarly, the acceleration data recorded in the second recording unit 402 is input to the second extraction unit 501. The second extraction unit 501 extracts (extracts) features from the acceleration data input from the second recording unit 402, such as the instantaneous value of acceleration (output signal) or statistical values ​​such as the maximum value, mean value, and standard deviation over a predetermined period.

[0022] Note that the features extracted by the first extraction unit 500 and the features extracted by the second extraction unit 501 do not need to be the same. For example, the first extraction unit 500 divides the acceleration data recorded by the first recording unit 401 into 1-second intervals, finds the maximum value for each 1-second interval, and calculates the sum of the mean and standard deviation from these maximum values ​​to obtain the features. On the other hand, the second extraction unit 501 may find the maximum value for each 1-second interval from the acceleration data recorded by the second recording unit 402 and use that as the features.

[0023] The comparison unit 502 has the function of comparing acceleration data (first signal) recorded by the first recording unit 401 with acceleration data (second signal) recorded by the second recording unit 402. In this embodiment, the comparison unit 502 determines (diagnoses) whether the output of the acceleration sensor 101 is normal or abnormal by comparing the feature quantity extracted by the first extraction unit 500 with the feature quantity extracted by the second extraction unit 501. For example, if the feature quantity extracted by the second extraction unit 501 is smaller than the feature quantity extracted by the first extraction unit 500, the comparison unit 502 outputs "0" to indicate that the output of the acceleration sensor 101 is normal. On the other hand, if the feature quantity extracted by the second extraction unit 501 is greater than or equal to the feature quantity extracted by the first extraction unit 500, the comparison unit 502 outputs "1" to indicate that the output of the acceleration sensor 101 is abnormal.

[0024] Furthermore, the comparison unit 502 may determine (diagnose) whether the output of the acceleration sensor 101 is normal or abnormal by comparing the difference between the feature quantity extracted by the first extraction unit 500 and the feature quantity extracted by the second extraction unit 501 with a threshold. For example, if the difference between the feature quantity extracted by the first extraction unit 500 and the feature quantity extracted by the second extraction unit 501 is less than the threshold, the comparison unit 502 outputs "0" to indicate that the output of the acceleration sensor 101 is normal. On the other hand, if the difference between the feature quantity extracted by the first extraction unit 500 and the feature quantity extracted by the second extraction unit 501 is greater than or equal to the threshold, the comparison unit 502 outputs "1" to indicate that the output of the acceleration sensor 101 is abnormal.

[0025] The diagnostic result (comparison result) from the comparison unit 502 is input to the fault diagnosis unit 309. Figure 5 is a schematic diagram showing the configuration of the fault diagnosis unit 309. The fault diagnosis unit 309 includes a diagnostic unit 600 and an abnormality diagnosis table 601. Figure 6 is a diagram showing an example of the abnormality diagnosis table 601. The abnormality diagnosis table 601 is a table consisting of information indicating whether the output of each of the acceleration sensors 101 to 104 is normal or abnormal. Specifically, the abnormality diagnosis table 601 is a table showing the correspondence between the abnormality diagnosis pattern, which consists of a binary code of "0" and "1" output from the abnormality diagnosis units 305 to 308, and the fault location. As shown in Figure 6, in this embodiment, the abnormality diagnosis table 601 is an abnormality diagnosis pattern (vector) for each fault location obtained in advance by testing. It is recorded as JPEG0007911877000001.jpg108.

[0026] Referring to Figure 7, the processing in the fault diagnosis unit 309 (diagnosis unit 600), that is, the process of diagnosing the fault location of the active vibration isolation table 1 (diagnosis process), will be explained.

[0027] First, in S701, the diagnostic unit 600 determines whether one or more of the abnormality diagnostic units 305 to 308 have diagnosed the output of the acceleration sensor as abnormal (whether they are outputting "1" to indicate an abnormality). If one or more abnormality diagnostic units have not diagnosed the output of the acceleration sensor as abnormal (i.e., the output of acceleration sensors 101 to 104 is normal), S701 is repeated. On the other hand, if one or more abnormality diagnostic units have diagnosed the output of the acceleration sensor as abnormal, the process proceeds to S702.

[0028] In S702, the diagnostic unit 600 obtains an abnormality diagnosis pattern (vector) from the outputs of the abnormality diagnosis units 305 to 308, which consists of information indicating whether the output of each of the acceleration sensors 101 to 104 is normal or abnormal. Retrieve JPEG0007911877000002.jpg86.

[0029] In S703, the diagnostic unit 600 checks the i-th abnormality diagnostic pattern of the abnormality diagnostic table 601. JPEG0007911877000003.jpg97 and the anomaly diagnosis pattern obtained with S702 We will calculate the similarity to JPEG0007911877000004.jpg87. The similarity can be calculated using, for example, the cosine similarity (cos similarity) shown in the following formula.

[0030] JPEG0007911877000005.jpg2277

[0031] In S704, the diagnostic unit 600 records the similarity score obtained in S703.

[0032] In S705, the diagnostic unit 600 determines whether it has recorded the similarity for all abnormal diagnosis patterns included in the abnormal diagnosis table 601. If it has not recorded the similarity for all abnormal diagnosis patterns included in the abnormal diagnosis table 601, steps S703 to S705 are repeated. On the other hand, if it has recorded the similarity for all abnormal diagnosis patterns included in the abnormal diagnosis table 601, the process proceeds to S706.

[0033] In S706, the diagnostic unit 600 diagnoses (estimates) the location of a failure in the active vibration isolation table 1 from the acceleration sensors 101 to 104 and the linear motors 105 to 108, based on the similarity recorded in S704. In other words, based on the abnormality diagnosis pattern obtained in S702, it identifies a data bus from the acceleration sensors 101 to 104 and the linear motors 105 to 108 that contains at least one of the acceleration sensors in a faulty state and the sensor in a faulty state. For example, the diagnostic unit 600 diagnoses the device corresponding to the abnormality diagnosis pattern with the highest similarity among all the abnormality diagnosis patterns included in the abnormality diagnosis table 601 as the location of the failure. Alternatively, the diagnostic unit 600 may diagnose the devices corresponding to each of multiple abnormality diagnosis patterns with high similarity among all the abnormality diagnosis patterns included in the abnormality diagnosis table 601, for example, multiple abnormality diagnosis patterns with similarity above a threshold, as the location of the failure.

[0034] Thus, according to this embodiment, it is possible to diagnose failures (location of failures) in acceleration sensors and linear motors without requiring a new detection unit to detect failures in linear motors (actuators). Furthermore, since failures in acceleration sensors and linear motors can be diagnosed without stopping the active vibration isolation table 1, a decrease in productivity can be suppressed (prevented). Therefore, it is possible to provide a technology that is advantageous for diagnosing the location of failures in an active vibration isolation table 1 (control device) having multiple acceleration sensors (sensors) and multiple linear motors (actuators).

[0035] Next, a specific example of the diagnostic process in the fault diagnosis unit 309 (diagnosis unit 600) is shown. Figure 8 shows the acceleration data output from each of the acceleration sensors 101 to 104 and recorded by the first recording unit 401, and the acceleration data recorded by the second recording unit 402. Note that the acceleration data recorded by the second recording unit 402 is the acceleration data when one of the four acceleration sensors 101 to 104, acceleration sensor 103, is faulty.

[0036] In the first extraction unit 500, the sum of the average value and standard deviation of the maximum values ​​obtained by dividing the acceleration data recorded by the first recording unit 401 into 1-second intervals is used as a feature. In the second extraction unit 501, the maximum value obtained by dividing the acceleration data recorded by the second recording unit 402 into 1-second intervals is used as a feature. In the example shown in Figure 8, for acceleration sensors 101, 102, and 104, the feature values ​​extracted by the second extraction unit 501 are smaller than the feature values ​​extracted by the first extraction unit 500. Therefore, the anomaly diagnosis units 305, 306, and 308 output "0" to indicate that the outputs of acceleration sensors 101, 102, and 104 are normal. On the other hand, for acceleration sensor 103, the feature value extracted by the second extraction unit 501 is greater than or equal to the feature value extracted by the first extraction unit 500, so the anomaly diagnosis unit 307 outputs "1" to indicate that the output of acceleration sensor 103 is abnormal. As a result, the abnormality diagnosis units 305 to 308 output "0", "0", "1", and "0" as an abnormality diagnosis pattern, which are then input to the fault diagnosis unit 309.

[0037] The diagnostic unit 600 determines the similarity between the abnormal diagnosis pattern input from the abnormal diagnosis units 305 to 308 and each of the multiple abnormal diagnosis patterns included in the abnormal diagnosis table 601 shown in Figure 6. In this embodiment, among the multiple abnormal diagnosis patterns included in the abnormal diagnosis table 601, the abnormal diagnosis pattern in which the acceleration sensor 103 is the fault location is determined. The image has the highest similarity to JPEG0007911877000006.jpg98. Therefore, the diagnostic unit 600 diagnoses the acceleration sensor 103, which is the device corresponding to the abnormality diagnosis pattern with the highest similarity, as the faulty part.

[0038] Furthermore, another specific example of the diagnostic process in the fault diagnosis unit 309 (diagnosis unit 600) is shown. Figure 9 shows the acceleration data output from each of the acceleration sensors 101 to 104 and recorded by the first recording unit 401, and the acceleration data recorded by the second recording unit 402. Note that the acceleration data recorded by the second recording unit 402 is the acceleration data when one of the four linear motors 105 to 108, linear motor 105, is faulty.

[0039] In the example shown in Figure 9, the abnormality diagnosis units 305, 306, and 308 output "1" to indicate that the outputs of acceleration sensors 101, 102, and 104 are abnormal. On the other hand, the abnormality diagnosis unit 307 outputs "0" to indicate that the output of acceleration sensor 103 is normal. As a result, the abnormality diagnosis units 305 to 308 output "1", "1", "0", and "1" as an abnormality diagnosis pattern, which is input to the fault diagnosis unit 309.

[0040] The diagnostic unit 600 determines the similarity between the abnormal diagnosis pattern input from the abnormal diagnosis units 305 to 308 and each of the multiple abnormal diagnosis patterns included in the abnormal diagnosis table 601 shown in Figure 6. In this embodiment, among the multiple abnormal diagnosis patterns included in the abnormal diagnosis table 601, the abnormal diagnosis pattern in which the linear motor 105 is the fault location is determined. The image has the highest similarity to JPEG0007911877000007.jpg98. Therefore, the fault diagnosis unit 309 diagnoses the linear motor 105, which is the device corresponding to the abnormality diagnosis pattern with the highest similarity, as the fault location.

[0041] In this embodiment, acceleration data is divided into 1-second intervals to diagnose the fault location of the active vibration isolation table 1, and therefore it is assumed that multiple acceleration sensors will not fail within 1 second. Consequently, if multiple acceleration sensors fail within 1 second, there is a possibility of misdiagnosing the fault location. However, since the probability of multiple acceleration sensors failing within 1 second is low, the actual possibility of misdiagnosing the fault location is extremely low. Furthermore, it is also possible to reduce the possibility of misdiagnosing the fault location by dividing the acceleration data into intervals shorter than 1 second.

[0042] The active vibration isolation table 1 (control device) can be used in an exposure apparatus. Figure 10 is a schematic diagram showing the configuration of an exposure apparatus EXA using the active vibration isolation table 1. The exposure apparatus EXA is a lithography apparatus used, for example, in the lithography process of various devices, and is used to form patterns on a substrate. The exposure apparatus EXA performs an exposure process that exposes the substrate W via a master plate R and transfers the pattern of the master plate R to the substrate W. In this embodiment, the exposure apparatus EXA is a scanning type exposure apparatus (scanner) that exposes the substrate W while scanning the master plate R and the substrate W relatively in the scanning direction (scanning exposure) and transfers the pattern of the master plate R onto the substrate.

[0043] As shown in Figure 10, the exposure apparatus EXA includes a stage platen 692, a substrate stage 690, a lens barrel platen 696, a damper 698, a projection optical system 697, an illumination optical system 699, a master plate platen 694, and a master plate stage 695. In this embodiment, the direction perpendicular to the plane of Figure 10 is defined as the scanning direction, and the horizontal direction within the plane of Figure 10 is defined as the step direction. Furthermore, a coordinate system is defined in which the scanning direction is the Y-axis, the direction intersecting the scanning direction, in particular the step direction perpendicular to the scanning direction, is defined as the X-axis, and the direction perpendicular to the X and Y axes is defined as the Z-axis.

[0044] The stage platen 692 is supported on the floor 691 via an active vibration isolation table 1. A substrate stage 690 for holding the substrate W is movably mounted on the stage platen 692. The lens barrel platen 696 is supported on the floor 691 via a damper 698. The lens barrel platen 696 is equipped with a projection optical system 697 and a master plate platen 694. A master plate stage 695 for holding the master plate R is movably (slidably) mounted on the master plate platen 694. An illumination optical system 699 is provided above the master plate stage 695.

[0045] During exposure, light emitted from a light source (not shown) illuminates the master plate R by the illumination optical system 699. The pattern of the master plate R is projected onto the substrate W by the projection optical system 697. At this time, the master plate stage 695 and the substrate stage 690 scan the master plate R and the substrate W relative to each other in the scanning direction. The stage plate 692 on which the substrate stage 690 is mounted is supported by the active vibration isolation table 1. Therefore, the exposure apparatus EXA can provide devices (articles such as semiconductor elements, magnetic storage media, and liquid crystal display elements) economically with high throughput.

[0046] The method for manufacturing an article in the embodiment of the present invention is suitable for manufacturing articles such as devices (semiconductor elements, magnetic storage media, liquid crystal display elements, etc.). Such a manufacturing method includes the steps of forming a pattern on a substrate using an exposure apparatus EXA, processing (treating) the substrate on which the pattern has been formed, and manufacturing an article from the processed substrate. Such a manufacturing method may also include other well-known steps (oxidation, film formation, vapor deposition, doping, planarization, etching, resist stripping, dicing, bonding, packaging, etc.). The method for manufacturing an article in this embodiment is advantageous compared to conventional methods in at least one of the performance, quality, productivity, and production cost of the article.

[0047] The present invention can also be realized by supplying a program that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that implements one or more functions.

[0048] This disclosure includes methods for diagnosing failures in control devices, diagnostic devices, control devices, lithography devices, methods for manufacturing articles, and programs.

[0049] (Item 1) A method for diagnosing a fault in a control device having a plurality of actuators that provide thrust to an object, a plurality of sensors that detect state quantities of the object, and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, A first step of comparing a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use. Based on the comparison results in the first step, the second step involves diagnosing a device that includes at least one of the actuators and sensors in a faulty state as the faulty location, A method characterized by having the following:

[0050] (Item 2) In the first step, by comparing the first signal and the second signal, a pattern consisting of information indicating whether the output of each of the multiple sensors is normal or abnormal is obtained. The method according to item 1, characterized in that, in the second step, the device is identified from the plurality of actuators and the plurality of sensors based on the pattern obtained in the first step.

[0051] (Item 3) The method for item 2, characterized in that, in the first step, feature quantities are extracted from the first signal and the second signal, and the feature quantities extracted from the first signal and the feature quantities extracted from the second signal are compared to determine whether the output of each of the multiple sensors is normal or abnormal.

[0052] (Item 4) The method for item 2, characterized in that, in the first step, feature quantities are extracted from the first signal and the second signal, and the difference between the feature quantities extracted from the first signal and the feature quantities extracted from the second signal is compared with a threshold to determine whether the output of each of the multiple sensors is normal or abnormal.

[0053] (Item 5) The method according to item 3 or 4, characterized in that the feature quantity includes instantaneous values ​​or statistical values ​​over a predetermined period of time of signals output from each of the plurality of sensors.

[0054] (Item 6) The method for any one of items 2 to 5, characterized in that, in the second step, the device is identified from the plurality of actuators and the plurality of sensors by comparing a table showing the correspondence between a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal and the fault location with the pattern obtained in the first step.

[0055] (Item 7) The method according to any one of items 1 to 6, characterized in that the state in which the plurality of actuators and the plurality of sensors are deemed to be normal is the initial state at the time of assembly of the control device.

[0056] (Item 8) A diagnostic device for diagnosing a fault in a control device having a plurality of actuators that provide thrust to an object, a plurality of sensors that detect state quantities of the object, and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, A comparison unit compares a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use. Based on the comparison results from the comparison unit, the diagnostic unit diagnoses a device containing at least one of the actuators and sensors that are in a faulty state as the faulty location. A diagnostic device characterized by having the following features.

[0057] (Item 9) A control device for controlling an object, Multiple actuators that provide thrust to the object, Multiple sensors for detecting the state quantities of the object, A controller that controls the plurality of actuators based on signals output from the plurality of sensors, A comparison unit compares a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use. Based on the comparison results from the comparison unit, a diagnostic unit diagnoses a device containing at least one of the actuators and sensors that is malfunctioning as a faulty location. A control device characterized by having the following features.

[0058] (Item 10) A lithography apparatus for forming patterns on a substrate, A vibration isolation table supporting a surface plate on which a stage for holding the substrate is provided, Multiple actuators that provide thrust to the vibration isolation table, Multiple sensors for detecting the state quantities of the vibration isolation table, A controller that controls the plurality of actuators based on signals output from the plurality of sensors, A comparison unit compares a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the lithography apparatus is in use. Based on the comparison results from the comparison unit, a diagnostic unit diagnoses a device containing at least one of the actuators and sensors that is malfunctioning as a faulty location. A lithography apparatus characterized by having [a certain feature].

[0059] (Item 11) A step of forming a pattern on a substrate using the lithography apparatus described in item 10, A step of manufacturing an article by processing the substrate on which the pattern has been formed in the above step, A method for manufacturing an article, characterized by having the following:

[0060] (Item 12) A program that causes a computer to execute a method for diagnosing a fault in a control device having a plurality of actuators that provide thrust to an object, a plurality of sensors that detect state quantities of the object, and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, To the aforementioned computer, A first step of comparing a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use. Based on the comparison results in the first step, the second step involves diagnosing which actuators and sensors are malfunctioning from among the plurality of actuators and sensors as the faulty parts. A program characterized by causing the execution of a specific action.

[0061] The invention is not limited to the embodiments described above, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, claims are attached to disclose the scope of the invention. [Explanation of Symbols]

[0062] 1: Active vibration isolation table 100: Surface plate 101~104: Acceleration sensor 105~108: Linear motor 200: Calculation unit 300: Controller 305~308: Anomaly diagnosis unit 309: Fault diagnosis unit

Claims

1. A method for diagnosing a fault in a control device having a plurality of actuators that provide thrust to an object, a plurality of sensors that detect state quantities of the object, and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, A first step involves comparing a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are considered to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use, thereby obtaining a pattern consisting of information indicating whether the output of each of the multiple sensors is normal or abnormal. A second step involves identifying a device from the plurality of actuators and the plurality of sensors that includes at least one of a faulty actuator and a faulty sensor as the faulty location, based on the pattern obtained in the first step. It has, The second signal is a signal that can be acquired without stopping the control device in order to acquire the second signal. The method is characterized in that, in the second step, the device is identified from the plurality of actuators and the plurality of sensors by comparing a table showing the correspondence between a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal and the fault location with the pattern obtained in the first step.

2. The method according to claim 1, characterized in that, in the first step, feature quantities are extracted from the first signal and the second signal, and the feature quantities extracted from the first signal and the feature quantities extracted from the second signal are compared to determine whether the output of each of the plurality of sensors is normal or abnormal.

3. The method according to claim 1, characterized in that, in the first step, feature quantities are extracted from the first signal and the second signal, and the difference between the feature quantity extracted from the first signal and the feature quantity extracted from the second signal is compared with a threshold to determine whether the output of each of the plurality of sensors is normal or abnormal.

4. The method according to 2 or 3, characterized in that the feature quantities include instantaneous values ​​or statistical values ​​over a predetermined period of time of signals output from each of the plurality of sensors.

5. The method according to claim 1, characterized in that the state in which the plurality of actuators and the plurality of sensors are deemed to be normal is the initial state at the time of assembly of the control device.

6. A diagnostic device for diagnosing a fault in a control device having a plurality of actuators that provide thrust to an object, a plurality of sensors that detect state quantities of the object, and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, A comparison unit compares a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use. A diagnostic unit that, based on the comparison results from the comparison unit, obtains a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal, and based on the obtained pattern, identifies a device from the plurality of actuators and the plurality of sensors that includes at least one of a faulty actuator and a faulty sensor as the faulty location. It has, The second signal is a signal that can be acquired without stopping the control device in order to acquire the second signal. The diagnostic device is characterized by identifying the device from the plurality of actuators and the plurality of sensors by comparing the obtained pattern with a table showing the correspondence between a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal and the fault location.

7. A control device for controlling an object, Multiple actuators that provide thrust to the object, Multiple sensors for detecting the state quantities of the object, A controller that controls the plurality of actuators based on signals output from the plurality of sensors, A comparison unit compares a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use. Based on the comparison results from the comparison unit, a diagnostic unit obtains a pattern consisting of information indicating whether the output of each of the multiple sensors is normal or abnormal, and based on the obtained pattern, identifies a device from the multiple actuators and multiple sensors that includes at least one of a malfunctioning actuator and a malfunctioning sensor as a faulty location. It has, The second signal is a signal that can be acquired without stopping the control device in order to acquire the second signal. The control device is characterized in that the diagnostic unit identifies the device from the plurality of actuators and plurality of sensors by comparing the obtained pattern with a table showing the correspondence between a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal and the fault location.

8. A lithography apparatus for forming patterns on a substrate, A vibration isolation table supporting a surface plate on which a stage for holding the substrate is provided, Multiple actuators that provide thrust to the vibration isolation table, Multiple sensors for detecting the state quantities of the vibration isolation table, A controller that controls the plurality of actuators based on signals output from the plurality of sensors, A comparison unit compares a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are deemed to be functioning normally with a second signal output from each of the multiple sensors when the lithography apparatus is in use. A diagnostic unit that, based on the comparison results in the comparison unit, obtains a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal, and based on the obtained pattern, identifies a device from the plurality of actuators and the plurality of sensors that includes at least one of a faulty actuator and a faulty sensor as a faulty location. It has, The second signal is a signal that can be acquired without stopping the control device in order to acquire the second signal. The lithography apparatus is characterized in that the diagnostic unit identifies the device from the plurality of actuators and the plurality of sensors by comparing the obtained pattern with a table showing the correspondence between a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal and the fault location.

9. A step of forming a pattern on a substrate using the lithography apparatus described in claim 8, A step of manufacturing an article by processing the substrate on which the pattern has been formed in the above step, A method for manufacturing an article, characterized by having the following:

10. A program that causes a computer to execute a method for diagnosing a fault in a control device having a plurality of actuators that provide thrust to an object, a plurality of sensors that detect state quantities of the object, and a controller that controls the plurality of actuators based on signals output from the plurality of sensors, To the aforementioned computer, A first step involves comparing a first signal output from each of the multiple sensors when the multiple actuators and the multiple sensors are considered to be functioning normally with a second signal output from each of the multiple sensors when the control device is in use, thereby obtaining a pattern consisting of information indicating whether the output of each of the multiple sensors is normal or abnormal. A second step involves identifying the faulty actuator and the faulty sensor from the plurality of actuators and sensors based on the pattern obtained in the first step, as the faulty location. Make it run, The second signal is a signal that can be acquired without stopping the control device in order to acquire the second signal. The program is characterized in that, in the second step, it identifies the device from the plurality of actuators and the plurality of sensors by comparing a table showing the correspondence between a pattern consisting of information indicating whether the output of each of the plurality of sensors is normal or abnormal and the fault location with the pattern obtained in the first step.

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