Abnormal discharge detection method and control device

Abstract

Minute abnormal discharge is detected based on the processed image.SOLUTION: The control device 40 acquires a gray scale image in which an image of a frame belonging to a time-series evaluation target range for detecting minute abnormal discharge is expressed in gray scale based on the moving image obtained by photographing the inside of the processing container 11, and performs a flattening process of adjusting the contrast on the gray scale image. Further, the controller 40 acquires a binarized image in which a difference section specified as a foreground with respect to a background in the flattened image to be processed and a section other than the difference section are represented by different pixel values by the background difference method. Further, the control device 40 performs a closing process and an opening process at least once on the binarized image, and outputs a discharge image for detecting minute abnormal discharge.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to an abnormal discharge detection method and a control device. [Background technology]

[0002] A substrate processing apparatus is known that performs plasma processing on a substrate placed on a mounting table. The substrate processing apparatus detects abnormal discharges, such as arc discharges, that occur in a processing chamber during plasma processing by monitoring electrical signals generated when the abnormal discharges act on an electrical circuit installed in the processing chamber (see, for example, Patent Document 1).

[0003] Furthermore, in recent years, with the miniaturization of semiconductor devices manufactured in substrate processing equipment, the conditions for plasma processing have become more delicate, making it necessary to detect even minute abnormal discharges that are difficult to detect with the above-mentioned electrical signals. Such minute abnormal discharges are accompanied by light emission, albeit weak, and therefore the light emission is observed with the naked eye. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-33726 Summary of the Invention [Problem to be solved by the invention]

[0005] The technology according to the present disclosure detects minute abnormal discharges based on the processed image. [Means for solving the problem]

[0006] One aspect of the technology disclosed herein is an abnormal discharge detection method for detecting minute abnormal discharges that occur inside a processing vessel where plasma processing is performed, the method comprising the steps of: acquiring a video of the inside of the processing vessel; acquiring a grayscale image based on the video, in which images of frames belonging to a time-series evaluation range for detecting the minute abnormal discharges are represented in grayscale; performing a flattening process on the grayscale image to adjust the contrast, thereby generating a flattened image; acquiring a binary image using a background subtraction method to represent difference areas identified as foreground against the background in the flattened image and areas other than the difference areas with different pixel values; and performing a first expansion process, a closing process in which the first expansion process is followed by a first contraction process, and an opening process in which a second contraction process is followed by a second expansion process, on the binary image at least once, thereby outputting a discharge image for detecting the minute abnormal discharges. [Effects of the Invention]

[0007] According to the technology of the present disclosure, it is possible to detect minute abnormal discharges based on the processed image. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram illustrating a schematic configuration of a substrate abnormality detection system including a control device according to an embodiment of the technology disclosed herein. [Figure 2] FIG. 2 is a cross-sectional view schematically showing the configuration of the film forming apparatus of FIG. [Figure 3] 3 is a diagram for explaining an image of the inside of the processing vessel taken by the camera in FIG. 2. FIG. [Figure 4] 2 is a block diagram schematically illustrating a hardware configuration of the control device of FIG. 1. FIG. [Figure 5] 2 is a flowchart showing the procedure of a process for detecting an abnormal minute discharge executed by the control device of FIG. 1. [Figure 6] 6 is a diagram for explaining the processing contents of S501, S504, and S505 in FIG. 5. [Figure 7] 6A and 6B are diagrams for explaining the expansion process and the contraction process in S505 of FIG. 5. [Figure 8] FIG. 6 is a diagram showing an example of a discharge image to be excluded in S506 of FIG. 5. [Figure 9] 10 is a flowchart showing another procedure of the abnormal minor discharge detection process executed by the control device of FIG. DETAILED DESCRIPTION OF THE INVENTION

[0009] Conventionally, abnormal discharges such as arc discharges that occur within a processing vessel during plasma processing have been detected by monitoring the electrical signals that are generated when the abnormal discharge acts on an electrical circuit installed within the processing vessel.

[0010] Furthermore, in recent years, with the miniaturization of semiconductor devices manufactured in substrate processing equipment, the conditions for plasma processing have become more delicate, making it necessary to detect even minute abnormal discharges that are difficult to detect with the above-mentioned electrical signals. Such minute abnormal discharges are accompanied by light emission, albeit weak, and therefore the light emission is observed with the naked eye.

[0011] However, it is not realistic for workers to constantly visually monitor for the irregularly occurring light emitted by abnormal discharges, as this places a heavy burden on the workers. Furthermore, visual monitoring can lead to the light being overlooked.

[0012] In contrast, the technology disclosed herein outputs a discharge image for detecting minute abnormal discharges based on a video captured inside a processing vessel. Specifically, a grayscale image is acquired by representing, in grayscale, images of frames belonging to a time-series evaluation range for detecting minute abnormal discharges based on the video captured inside the processing vessel, and a flattening process is performed to adjust the contrast of the grayscale image. Furthermore, a background subtraction method is performed using multiple flattened images acquired by the flattening process to acquire a binary image in which difference areas identified as foregrounds against the background in the flattened image to be processed and areas other than the difference areas are represented by different pixel values. Furthermore, a closing process and an opening process are performed at least once on this binary image to output a discharge image for detecting minute abnormal discharges. Note that the minute abnormal discharge in this embodiment refers to an abnormal discharge so minute that the above-mentioned electrical signal is below the detection limit.

[0013] Hereinafter, an embodiment of the technology according to the present disclosure will be described with reference to the drawings.

[0014] Fig. 1 is a block diagram showing a schematic configuration of a substrate abnormality detection system 1 including a control device 40 according to an embodiment of the technology disclosed herein. In Fig. 1, the substrate abnormality detection system 1 is made up of a film forming apparatus 10, a camera 22, and a control device 40 for controlling image processing of moving images acquired by the camera 22 and detection of abnormal discharge. In the substrate abnormality detection system 1, the control device 40 controls a series of processes, such as performing a micro-abnormal discharge detection process shown in Fig. 5, which will be described later, using the moving images transmitted from the camera 22, and outputting a discharge image for detecting micro-abnormal discharges in a processing chamber of the film forming apparatus 10.

[0015] Fig. 2 is a cross-sectional view schematically showing the configuration of the film formation apparatus 10 of Fig. 1. The film formation apparatus 10 of Fig. 2 is an inductively coupled plasma processing apparatus (substrate processing apparatus). The film formation apparatus 10 performs a film formation process to form a protective film or the like on a rectangular substrate, for example, a glass substrate G (hereinafter referred to as "substrate G") for an FPD (Flat Panel Display), using plasma generated from a processing gas.

[0016] The film forming apparatus 10 includes a rectangular cylindrical processing chamber 11 made of a conductive material, and the processing chamber 11 accommodates a substrate G. The upper portion of the processing chamber 11 is airtightly sealed by a window member 12. Inside the processing chamber 11, a mounting table 13 on which the substrate G is placed is disposed at the lower portion, and the mounting table 13 faces the window member 12. In the processing chamber 11, a processing space U is formed between the mounting table 13 and the window member 12. In the processing space U, plasma is generated from a processing gas, as will be described later.

[0017] An electrostatic chuck (not shown) is provided on the top surface of the mounting table 13. The substrate G placed on the mounting table 13 is attracted and held to the mounting table 13 by the electrostatic chuck. A temperature control mechanism such as a chiller and a heat transfer gas supply mechanism (neither of which are shown) are provided inside the mounting table 13 to control the temperature of the placed substrate G. The mounting table 13 is installed on the bottom surface of the processing chamber 11 via an insulating frame 14.

[0018] A metal frame 15 is provided at the upper end of the side wall of the processing vessel 11, and a side wall portion 16 is installed on the upper surface of the metal frame 15. The side wall portion 16 supports a top plate 17, and the top plate 17 covers the window member 12 from above. A sealing member 18 such as an O-ring is provided between the side wall of the processing vessel 11 and the metal frame 15 to keep the processing space U airtight.

[0019] One side wall of the processing vessel 11 is provided with a loading / unloading port 19 for loading / unloading the substrate G into / out of the processing space U, and a gate valve 20 for opening / closing the loading / unloading port 19. In addition, another side wall of the processing vessel 11 is provided with a monitoring window 21 (observation window) in which an optically transparent member is airtightly fitted, and a camera 22 for monitoring the inside of the processing vessel 11 through the monitoring window 21 is provided outside the processing vessel 11 adjacent to the film forming apparatus 10. The camera 22 may be provided as a part of the film forming apparatus 10. The camera 22 transmits a video of the inside of the processing vessel 11 that it has captured to the control device 40. In this embodiment, the image captured by the camera 22 is a video, not a still image.

[0020] The window member 12 is made of a conductor, for example, metal, has a rectangular shape, and is divided into a plurality of segments 23, with a partition member 24 made of an insulator disposed between each of the adjacent segments 23. The partition members 24 separate the adjacent segments 23 and electrically insulate them from one another.

[0021] In the film forming apparatus 10, the space surrounded by the window member 12, the side wall portion 16, and the top plate 17 constitutes an antenna chamber 25. In the antenna chamber 25, an inductive coupling antenna 26 is disposed so as to face the substrate G on the mounting table 13 across the window member 12. The inductive coupling antenna 26 is disposed across the regions facing the respective segments 23 as a whole, and is formed in a spiral shape so as to wrap around in the circumferential direction of the window member 12, but the shape of the inductive coupling antenna 26 is not limited to a spiral shape.

[0022] Each divided piece 23 has a number of gas holes 27 formed therein, which open toward the processing space U. A gas supply pipe 28 is connected to each divided piece 23, and the gas supply pipe 28 is connected to a gas supply device 29. A gas diffusion chamber 30 is formed inside each divided piece 23, and the gas supply device 29 introduces processing gas into the gas diffusion chamber 30 via the gas supply pipe 28. The processing gas introduced into the gas diffusion chamber 30 is supplied to the processing space U through the gas holes 27.

[0023] In the film forming apparatus 10, a high-frequency power supply 32 is connected to the inductively coupled antenna 26 via a matching box 31. The high-frequency power supply 32 supplies high-frequency power for generating plasma, for example, 13.56 MHz, to the inductively coupled antenna 26. As a result, eddy currents are induced in each of the segments 23 constituting the window member 12, circulating from the upper surface (the inductively coupled antenna 26 side) to the lower surface (the processing space U side). These eddy currents form an inductive electric field in the processing space U. This inductive electric field then excites the processing gas supplied to the processing space U to generate plasma. Note that, although the above-described embodiment has been described as being made of a conductor such as metal, the window member 12 may also be made of a dielectric. In this case, the electric field formed by the inductively coupled antenna 26 penetrates the window member 12 and directly acts on the processing gas to generate plasma. Furthermore, the gas diffusion chamber, gas holes, etc. are formed, for example, in a support beam supporting the dielectric.

[0024] Furthermore, a high-frequency power supply 34 is connected to the mounting table 13 via a matching box 33. The high-frequency power supply 34 supplies, for example, 3.2 MHz high-frequency bias power to the mounting table 13. This allows various ions in the plasma in the processing space U to be attracted to the substrate G, thereby performing a film formation process to form various films on the substrate G. Note that the film formation apparatus 10 may also perform an etching process on the substrate G by attracting various ions to the substrate G. In this case, the film formation apparatus 10 functions as an etching apparatus.

[0025] Furthermore, in the film forming apparatus 10, an exhaust port 35 is formed on the bottom surface of the processing vessel 11. An exhaust device 36, such as a turbo molecular pump or a dry pump, is connected to this exhaust port 35. When performing a film forming process, the exhaust device 36 maintains the processing space U at a pressure lower than atmospheric pressure. The film forming apparatus 10 is also provided with an apparatus control unit 37. The apparatus control unit 37 is made up of a computer having at least a CPU and a memory, and the memory stores a recipe (program) for performing processes, such as film forming processes, on the substrate G. The recipe also includes information for performing processes on the substrate G inside the processing vessel 11. The apparatus control unit 37 controls the execution of the processes performed on the substrate.

[0026] Fig. 3 is a diagram for explaining an image of the inside of the processing vessel 11 captured by the camera 22 in Fig. 2. Note that Fig. 3 shows a captured image of one frame among a plurality of frames constituting a moving image captured by the camera 22.

[0027] As described above, the camera 22 captures images of the interior of the processing vessel 11 through the monitoring window 21, for example, while processing is being performed on the substrate G placed on the mounting table 13, to obtain a video including the captured image shown in FIG. 3. The captured image in FIG. 3 includes structural components inside the processing vessel 11, such as the mounting table 13 and the substrate G placed on the mounting table 13. For ease of understanding, the thickness of the substrate G is exaggerated in FIG. 3. The camera 22 then transmits the video to the control device 40. Note that, in this embodiment, a configuration in which the camera 22 directly transmits the video to the control device 40 will be described; however, the camera 22 may also transmit the video to the control device 40 via the device control unit 37 of the film forming apparatus 10.

[0028] Fig. 4 is a block diagram showing a schematic hardware configuration of the control device 40 shown in Fig. 1. The control device 40 is, for example, a personal computer. The control device 40 includes a CPU 41, a ROM 42, a RAM 43, an HDD 44, a communication I / F 45, an input / output I / F 46, an output device 47, and an input device 48, which are connected to each other via a system bus 49 so as to be able to communicate with each other.

[0029] The CPU 41 is a microprocessor that performs overall control of the control device 40. Specifically, the CPU 41 reads out programs stored in the ROM 42 or HDD 44, and executes the programs deployed on the RAM 43. The ROM 42 stores the programs and the like to be executed by the CPU 41. The RAM 43 is used as the main memory of the CPU 41, and is also used as an area for temporarily storing programs and data.

[0030] The HDD 44 stores various data and programs executed by the CPU 41. In the present embodiment, a configuration is described in which the control device 40 includes an HDD as an example of a storage device, but the control device 40 may include a storage device other than an HDD, such as an SSD.

[0031] The communication I / F 45 is an interface through which the control device 40 communicates with external devices. For example, the communication I / F 45 receives video captured by the camera 22 from the camera 22. Note that communication via the communication I / F 45 is realized by various communication technologies, whether wireless or wired. The input / output I / F 46 is connected to an output device 47, such as a display that displays various information and a speaker that outputs audio, and an input device 48, such as a mouse and a keyboard, that the user uses.

[0032] Next, a process for detecting a small abnormal discharge inside the processing chamber 11 of the film forming apparatus 10 will be described.

[0033] FIG. 5 is a flowchart showing the procedure of the abnormal micro-discharge detection process executed by the control device 40 of FIG. 1. The abnormal micro-discharge detection process of FIG. 5 is realized by the CPU 41 executing a program stored in the ROM 42 or the HDD 44. The abnormal micro-discharge detection process of FIG. 5 is executed, for example, when the control device 40 receives an instruction from an operator to start the abnormal micro-discharge detection process after the process performed on the substrate G, such as a film formation process, inside the processing vessel 11 is completed. In this embodiment, a recipe used when the film formation apparatus 10 performs the process on the substrate G is stored in advance in a storage device (built-in or external) of the device control unit 37. The recipe stored in the storage device is loaded into the memory of the device control unit 37 when the process on the substrate G is performed. This recipe includes, for example, the time when plasma generation starts in the process performed on the substrate G and the time corresponding to the state when the plasma is extinguished in the processing vessel 11.

[0034] 5, first, the CPU 41 acquires a video of the interior of the processing vessel 11 captured by the camera 22 from the camera 22 (S501). This video is a video captured at least from immediately before the start of processing on the substrate G to the end of the processing, and is composed of multiple frame images, such as frame image 61 in FIG. 6(A). In this embodiment, the video captured by the camera 22 is described as a video obtained by color photography, as an example. The CPU 41 also acquires a recipe stored in the storage device of the device control unit 37 from the device control unit 37. Note that the timing of acquiring the recipe is not limited to this timing, and the control device 40 may acquire the recipe from the device control unit 37 in advance before starting the processing. Note that in S501, the video may be associated with a time included in the recipe. Therefore, the control device 40 does not necessarily need to acquire all information of the recipe, but only needs to acquire information that can associate the video with a time included in the recipe.

[0035] Next, the CPU 41 converts the image of each frame constituting this moving image into a grayscale image (S502), thereby obtaining a plurality of grayscale images in which the images of the frames belonging to the time-series evaluation range for detecting minute abnormal discharges are each expressed in grayscale.

[0036] Next, the CPU 41 performs a flattening process on the acquired grayscale images to adjust the contrast of each image (S503). The flattening process, for example, applies an adaptive histogram averaging algorithm to convert grayscale images that are biased toward a narrow brightness range into a wide brightness range. That is, the image is divided into several blocks, and the histogram distribution, which indicates brightness within each block, is processed to be uniform. This flattening process results in multiple flattened images in which the contrast is flattened by brightening dark areas and darkening bright areas compared to the average. That is, flattened images in which intermediate contrasts are more clearly defined are acquired.

[0037] Next, the CPU 41 acquires a binarized image of the foreground, separated as a difference by a background subtraction method based on these flattened images (S504). Examples of the background subtraction method include MOG (Mixture of Gaussians). Specifically, the CPU 41 sets a statistical distribution of pixel values ​​that can be taken as background for each pixel in the flattened image based on the multiple flattened images. Then, for each pixel constituting the flattened image to be processed, the CPU 41 determines whether it is background or not based on the statistical pixel value distribution, and extracts pixels that are not background as foreground. The foreground relative to the background in the flattened image to be processed is identified as a difference portion. At this time, for example, by binarization, foreground pixels are output as white. Note that while the above description has been given using MOG, this is not a limitation. For example, a flattened image to be processed among multiple flattened images may be compared with another flattened image corresponding to a frame immediately preceding the frame corresponding to the flattened image in the video. In this case, the CPU 41 generates a binary image in which the difference between the flattened image and the other flattened images is represented by different pixel values ​​from the other areas. In the present embodiment, as an example, a binary image is generated in which the difference is represented by "1" (white) and the other areas are represented by "0" (black). In this manner, in the present embodiment, the CPU 41 generates multiple binary images by processing all of the flattened images generated in S503. Next, the process proceeds to S505. In S504, the difference between the flattened image and the other flattened images may be extracted using a background subtraction method and then grayscaled. The extracted difference may be grayscaled to generate a grayscale image, and the grayscale image may then be binarized to generate a binary image. The binary image 62 in FIG. 6B is an example of the binary image generated in S504. The binary image 62 includes a difference area (white area in FIG. 6B) corresponding to the discharge area. FIG. 6(C) is an enlarged view of this difference region.

[0038] Here, because the light emitted by minute abnormal discharges is weak, it is not possible to accurately distinguish between difference points identified as the foreground in the flattened image to be processed and non-difference points, and gaps or holes may appear in the collection of multiple difference points (difference areas) corresponding to the discharge areas in the binarized image, and even protruding noise may occur (see, for example, Figure 6(C)). Therefore, it is difficult to accurately obtain information about the shape, size, and number of discharge areas from such a binarized image, and this can lead to misidentification of discharge areas, particularly in a configuration in which discharge areas are automatically detected from a binarized image using software.

[0039] Therefore, in this embodiment, in S505, the CPU 41 performs morphology processing on each of the multiple binarized images acquired in S504. Specifically, the CPU 41 performs closing processing on the binarized images to fill gaps and holes in the differential regions and shape the differential regions, and then performs opening processing on the binarized images that have already undergone the closing processing to remove noise from the differential regions. In this embodiment, the closing processing and the opening processing are performed at least once in the morphology processing. Furthermore, if minute abnormal discharges occur in multiple regions inside the processing vessel 11, the closing processing individually shapes each set of multiple difference locations corresponding to the multiple regions in the binarized images. Note that in the morphology processing of S505, the closing processing may be performed after the opening processing.

[0040] By the above-described morphology processing, for example, a differential region having gaps or holes as shown in FIG. 6(C) is shaped as shown in FIG. 6(D). Note that in the closing processing, a binarized image is dilated and then eroded. Note that in the opening processing, a binarized image is eroded and then dilated. In the dilation processing, for example, as shown in FIG. 7(A), a kernel 72 is arranged to include a pixel 71 to be converted, and if there is even one pixel in the kernel 72 with a pixel value of "1" (white), the pixel value of the pixel 71 to be converted is converted to "1." On the other hand, in the erosion processing, for example, as shown in FIG. 7(B), a kernel 74 is arranged to include a pixel 73 to be converted, and if there is even one pixel in the kernel 74 with a pixel value of "0" (black), the pixel value of the pixel 73 to be converted is converted to "0." Note that in this embodiment, the size of the kernel applied in the closing processing and the size of the kernel applied in the opening processing may be the same, but they may be different sizes to achieve appropriate shaping of the differential region. By the process of S505 described above, a plurality of morphology-processed binarized images (hereinafter referred to as "discharge images") are obtained.

[0041] Next, the CPU 41 performs an erroneous detection countermeasure process (S506). In the erroneous detection countermeasure process, discharge images that may be a cause of erroneous determination of a small abnormal discharge are excluded from the plurality of discharge images obtained in S505. For example, the CPU 41 excludes, from the plurality of discharge images obtained in S505, discharge images corresponding to the time before plasma generation begins and discharge images corresponding to the time after the plasma disappears in the process performed on the substrate G based on the recipe acquired in S501. The CPU 41 also excludes, from the plurality of discharge images obtained in S505, discharge images in which the number of difference regions, which are sets of difference points, exceeds a predetermined reference number, for example, 10 (see, for example, discharge image 81 in FIG. 8A). Furthermore, the CPU 41 excludes, from the plurality of discharge images obtained in S505, discharge images in which the size of all difference regions, which are sets of difference points, exceeds a predetermined reference size (see, for example, discharge image 82 in FIG. 8B).

[0042] Next, the CPU 41 determines whether or not there is a minute abnormal discharge using the discharge images not excluded in S506 (S507). In S507, for example, if the CPU 41 detects a discharge image including a difference region of a predetermined size or less from the plurality of discharge images to be determined, the CPU 41 notifies the worker of time information corresponding to the discharge image and coordinate information of the difference region in the discharge image. This allows the worker to easily identify the time and location of the minute abnormal discharge. Note that in S507, the discharge image not excluded in S506 may be input to a trained model that has trained binarized images including a region corresponding to the minute abnormal discharge, to determine whether or not there is a minute abnormal discharge. This trained model may, for example, notify the worker of the presence or absence of the minute abnormal discharge. Furthermore, as described above, if the CPU 41 detects a discharge image including a difference region of a predetermined size or less from the plurality of discharge images to be determined, the trained model also outputs time information corresponding to the discharge image and coordinate information of the difference region in the discharge image. When the processing of S507 is completed, this process ends.

[0043] According to this embodiment, a grayscale image is obtained by expressing in grayscale images of frames belonging to a time-series evaluation range for detecting minute abnormal discharges based on a moving image captured inside the processing vessel 11, and then a flattening process is performed on the grayscale image to adjust the contrast. Such flattening process broadens the gradation of the grayscale image, thereby emphasizing the discharge region and providing a flattened image that makes it easy to capture the shape of the discharge region.

[0044] Furthermore, a background subtraction method using MOG separates the background and foreground in the flattened image to be processed, and a binarized image is obtained in which difference areas identified as the foreground relative to the background are represented by different pixel values ​​from areas other than the difference areas. A closing process is then performed on this binarized image to fill in gaps and holes in the difference area and reshape the difference area. An opening process is then performed to remove noise from the difference area. This allows the shape of the difference area to approach the shape of the original discharge area, making it possible to obtain an image in which minute abnormal discharges can be detected. Furthermore, by obtaining an image in which minute abnormal discharges can be detected, it is possible to detect minute abnormal discharges that act on electrical circuits and generate electrical signals that cannot be detected.

[0045] Furthermore, in this embodiment, when minute abnormal discharges occur in multiple regions inside the processing vessel 11, the closing process individually shapes the multiple difference regions in the binarized image, thereby making it possible to individually identify the multiple regions where minute abnormal discharges occur.

[0046] Furthermore, in this embodiment, based on the recipe acquired in S501, discharge images corresponding to the time before plasma generation starts in the process performed on the substrate G and discharge images corresponding to the time after the plasma disappears are excluded from the multiple discharge images obtained in S505. In other words, the objects for determining the presence or absence of minute abnormal discharge are narrowed down to discharge images corresponding to timings when minute abnormal discharge may occur. This reduces the load of the process for determining the presence or absence of minute abnormal discharge.

[0047] Furthermore, in this embodiment, discharge images in which the number of difference regions, which are sets of difference locations, exceeds a predetermined reference number are excluded from the multiple discharge images obtained in S505. Here, when the conditions for processing the substrate G are changed, a large amount of discharge occurs, so it is meaningless to determine the presence or absence of minute abnormal discharge from a discharge image corresponding to this case, but the discharge image corresponding to this case contains a large number of difference regions, which are sets of difference locations. Therefore, by excluding discharge images in which the number of difference regions exceeds a predetermined reference number from the multiple discharge images obtained in S505, the load of the process for determining the presence or absence of minute abnormal discharge can be reduced.

[0048] Furthermore, in this embodiment, discharge images in which the size of all differential regions, which are a collection of differential locations, exceeds a predetermined reference size are excluded from the multiple discharge images obtained in S505. Here, when the conditions for processing the substrate G are changed, a relatively large discharge may occur, and it is meaningless to determine the presence or absence of a small abnormal discharge from a discharge image corresponding to this case, but the size of the differential regions, which are a collection of differential locations, becomes large in the discharge image corresponding to this case. Therefore, by excluding discharge images in which the size of all differential regions exceeds a predetermined reference size from the multiple discharge images output, the load of the process for determining the presence or absence of a small abnormal discharge can be further reduced.

[0049] Furthermore, in this embodiment, the size of the kernel applied in the closing process is made different from the size of the kernel applied in the opening process. Here, the size of the kernel used to properly fill gaps and holes in the differential domain in the closing process is not necessarily the same as the size of the kernel used to properly remove noise in the differential domain in the opening process. Therefore, by making the size of the kernel used in the closing process different from the size of the kernel used in the opening process, it is possible to both properly fill gaps and holes in the differential domain and properly remove noise in the differential domain.

[0050] Furthermore, in this embodiment, the control device 40 acquires a video after completing the processing performed on the substrate G, and can analyze the conditions of any minute abnormal discharges that occur during the processing, and use the analysis results for the next processing.

[0051] Although the preferred embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments, and various modifications and changes are possible within the scope of the gist of the present disclosure.

[0052] For example, in the above-described embodiment, the video captured by camera 22 is described as a video obtained by color photography, but this is not limited to this configuration. For example, the video captured by camera 22 may be a video obtained by monochrome photography. In such a configuration, a grayscale image can be directly obtained from the video obtained by monochrome photography, so the step of converting to a grayscale image (S502) can be omitted, which in turn reduces the overall processing load for detecting minute abnormal discharges.

[0053] Furthermore, in the above-described embodiment, a configuration has been described in which, in S506, discharge images corresponding to the time before plasma generation begins in the processing performed on the substrate G and discharge images corresponding to the time after the plasma has disappeared are excluded. However, this configuration is not limited to this. For example, before performing S502 or S503, based on the recipe acquired in S501, frame images corresponding to the time before plasma generation begins in the processing performed on the substrate G and frame images corresponding to the time after the plasma has disappeared may be excluded from the processing target from among the multiple frame images constituting the moving image. In other words, the targets of the grayscale conversion and flattening processes are narrowed down to frame images corresponding to timings at which minute abnormal discharges may occur among the multiple frame images constituting the moving image. This reduces the processing load after the grayscale conversion and flattening processes.

[0054] Furthermore, in the above-described embodiment, the control device 40 is configured as a separate entity from the film forming apparatus 10, but this configuration is not limiting. For example, the film forming apparatus 10 may have the functions of the control device 40. In this case, the device control unit 37 of the film forming apparatus 10 executes a process equivalent to the above-described abnormal micro-discharge detection process. Even with such a configuration, the same effects as those of the above-described embodiment can be achieved.

[0055] Furthermore, in the above-described embodiment, the processing vessel 11 has been described as having a rectangular cylindrical shape, but the shape of the processing vessel 11 is not limited to a rectangular cylindrical shape. For example, the processing vessel 11 may have another shape, such as a cylindrical shape.

[0056] Furthermore, in the above-described embodiment, the control device 40 has been described as being configured to acquire a video of the interior of the processing vessel 11 after the processing performed on the substrate G has been completed, but the timing of acquiring the video is not limited to this timing. For example, the control device 40 may acquire a video of the interior of the processing vessel 11 from the camera 22 in real time while the processing performed on the substrate G is being performed. Note that in a configuration in which a video is acquired in real time while the processing performed on the substrate G is being performed, the procedure for the abnormal micro discharge detection process differs from the flowchart of FIG. 5 described above. For this reason, the procedure for the abnormal micro discharge detection process in a configuration in which a video is acquired in real time while the processing performed on the substrate G is being performed will be described with reference to FIG. 9. In the following, the differences from the abnormal micro discharge detection process of FIG. 5 described above will be particularly described.

[0057] 9 is a flowchart showing another procedure of the abnormal micro discharge detection process executed by the control device 40 of FIG. 1. Note that, like the abnormal micro discharge detection process of FIG. 5 described above, the abnormal micro discharge detection process of FIG. 9 is also realized by the CPU 41 executing a program stored in the ROM 42 or the HDD 44. In this embodiment, the camera 22 captures images of the inside of the processing vessel 11 before the start of processing on the substrate G, and transmits the video obtained by this capture to the control device 40 in real time. The abnormal micro discharge detection process of FIG. 9 is executed, for example, when the control device 40 receives an instruction to start the abnormal micro discharge detection process from an operator after the camera 22 starts capturing images of the inside of the processing vessel 11 and before the start of processing on the substrate G. Note that the abnormal micro discharge detection process may be started automatically based on a recipe.

[0058] 9, the CPU 41 acquires, from the camera 22, an image of the latest frame constituting a moving image of the inside of the processing vessel 11 captured by the camera 22 (S901).

[0059] Next, the CPU 41 grayscales the acquired frame image (S902). As a result, a grayscale image is acquired, in which the acquired frame image is expressed in grayscale. Note that if the camera 22 is performing monochrome photography and the frame image transmitted from the camera 22 is a grayscale image, the CPU 41 may skip S902.

[0060] Next, the CPU 41 performs the above-described flattening process on the acquired grayscale image (S903). The method of the flattening process is the same as the method described in S503 above. By the process of S903, a flattened image in which intermediate contrast is made clearer is acquired. The flattened image acquired in S903 is held in the RAM 43 or the like until this process is completed, and is used to generate a binarized image by a background subtraction method in S904, which will be described later.

[0061] Next, the CPU 41 acquires a binarized image using a background subtraction method based on the plurality of flattened images acquired in S903 (S904). The method for acquiring a binarized image using the background subtraction method is the same as the method described in S504 above. The process of S904 generates a binarized image in which difference portions identified as foregrounds relative to the background in the flattened image to be processed and portions other than the difference portions are represented by different pixel values.

[0062] Next, the CPU 41 performs morphology processing on the binarized image acquired in S904 (S905). The morphology processing method is the same as the method described in S505 above. By the processing of S905, a discharge image, which is a binarized image that has been subjected to morphology processing, is acquired.

[0063] Next, the CPU 41 determines whether or not to exclude the discharge image acquired in S905 from the evaluation target (S906). In S906, similar to S506 described above, if it is determined that this discharge image is a discharge image corresponding to the time before plasma generation starts and a discharge image corresponding to the time after the plasma disappears in the process performed on the substrate G based on the recipe acquired in S501, or if the number of difference regions, which are a collection of difference points in this discharge image, exceeds a predetermined reference number, or if the size of all difference regions, which are a collection of difference points in this discharge image, exceeds a predetermined reference size, it is determined that this discharge image is to be excluded from the evaluation target. If it is determined that this discharge image is to be excluded from the evaluation target, the process proceeds to S909 described later. On the other hand, if none of the above applies, it is determined that this discharge image is not to be excluded from the evaluation target, and the process proceeds to S907.

[0064] In S907, the CPU 41 uses this discharge image to determine whether or not there is a minute abnormal discharge. The method for determining whether or not there is a minute abnormal discharge is the same as the method described above in S507. If it is determined that no minute abnormal discharge has occurred, the process proceeds to S909, which will be described later. If it is determined that a minute abnormal discharge has occurred, the process proceeds to S908.

[0065] In S908, the CPU 41 performs countermeasure control for the minute abnormal discharge. Examples of this countermeasure control include control to instruct the apparatus control unit 37 of the film forming apparatus 10 to stop the processing performed on the substrate G, control to cause the output device 47 to display a warning message notifying the occurrence of the minute abnormal discharge, and control to cause the output device 47 to output a warning sound or voice notifying the occurrence of the minute abnormal discharge.

[0066] Next, the CPU 41 determines whether or not to terminate this process (S909). In S909, for example, when the control device 40 receives an instruction to terminate this process from an operator, or when it detects that the processing performed on the substrate G has been completed based on the time included in the recipe, it is determined that this process should be terminated, and the process ends. Note that if the process is terminated in response to an instruction to terminate from an operator, the process continues even after the plasma is extinguished until the instruction to terminate is received. On the other hand, if none of the above applies, it is determined that this process should not be terminated, and the process returns to S901, where processing is performed on the image of the next frame. Note that processing on the image of the next frame may be started before a NO determination is obtained in S909.

[0067] 9 described above, since video is acquired during the execution of the processing performed on the substrate G, it is possible to determine whether or not there is a minute abnormal discharge during the execution of the processing performed on the substrate G, and if a minute abnormal discharge is detected, it is possible to notify an operator that a minute abnormal discharge has occurred. As a result, it is possible to take measures such as stopping the processing performed on the substrate G, and it is possible to minimize problems caused by the occurrence of a minute abnormal discharge.

[0068] In this embodiment, the substrate processing apparatus has been described as being applied to a film forming apparatus, but the present invention is not limited to this, as long as it is an apparatus that uses plasma. The present invention may also be applied to a substrate processing apparatus that performs other processes, such as an etching apparatus or an ashing apparatus, as long as it is an apparatus that performs a process of performing plasma processing on a substrate placed on a mounting table. In other words, the processing performed on the substrate is not limited to film forming processing, but may also be etching processing, ashing processing, or other processing. Furthermore, in this embodiment, the present invention has been described as being applied to an inductively coupled plasma apparatus as the substrate processing apparatus, but the present invention is not limited to this, and other types of plasma apparatus may also be used, such as a capacitively coupled plasma apparatus or a microwave plasma apparatus. [Explanation of symbols]

[0069] 10 Film deposition equipment 11 Processing container 21 Observation Window 22 Camera 37 Device control section 38 Lift Pin 40 Control device 41 CPU

Claims

1. An abnormal discharge detection method for detecting minute abnormal discharge occurring inside a processing vessel in which plasma processing is performed, comprising: acquiring a video of the inside of the processing vessel; acquiring, based on the video, grayscale images representing, in grayscale, images of frames that belong to a time-series evaluation range for detecting at least the minute abnormal discharge; performing a flattening process on the grayscale image to adjust the contrast and generate a flattened image; obtaining a binarized image in which difference portions identified as foregrounds relative to the background in the flattened image by a background subtraction method and portions other than the difference portions are expressed with different pixel values; An abnormal discharge detection method comprising a step of performing a first expansion process, a closing process in which a first contraction process is performed following the first expansion process, and an opening process in which a second contraction process is performed following the second contraction process, on the binary image at least once each, and outputting a discharge image for detecting the minute abnormal discharge.

2. 2. The abnormal discharge detection method according to claim 1, wherein the minute abnormal discharge acts on an electric circuit for performing the plasma processing, generating an electric signal below a detection limit.

3. The abnormal discharge detection method described in claim 1, wherein, when the minute abnormal discharge occurs in multiple areas inside the processing vessel, the closing process individually shapes each of the sets of multiple difference points corresponding to the multiple areas in the binary image.

4. The abnormal discharge detection method according to claim 3 , wherein the plurality of areas where the minute abnormal discharge has occurred are individually identified from the discharge image obtained by individually shaping the plurality of sets of difference portions.

5. 2. The abnormal discharge detection method according to claim 1, wherein in the step of acquiring the grayscale image or the step of generating the flattened image, based on a recipe used to perform the plasma processing, from among the images of the multiple frames constituting the video, images of frames corresponding to before plasma generation starts and images of frames corresponding to after plasma extinction are excluded from the processing target.

6. The abnormal discharge detection method described in claim 1, further comprising a step of excluding, from the plurality of discharge images output in the output step, the discharge images corresponding to before plasma generation begins and the discharge images corresponding to after plasma extinction based on a recipe used to perform the plasma processing.

7. The abnormal discharge detection method according to claim 1, further comprising a step of excluding, from the plurality of discharge images output in the outputting step, discharge images in which the number of difference regions, which are sets of difference points, exceeds a predetermined reference number.

8. The abnormal discharge detection method according to claim 1, further comprising a step of excluding, from the plurality of discharge images output in the outputting step, discharge images in which the size of all difference regions, which are a collection of the difference points, exceeds a predetermined reference size.

9. The abnormal discharge detection method according to claim 1 , wherein in the outputting step, the opening process is performed after the closing process is performed.

10. The abnormal discharge detection method according to claim 1 , wherein a size of the kernel applied in the closing process is different from a size of the kernel applied in the opening process.

11. The abnormal discharge detection method according to claim 1 , wherein the video is a video obtained by color photography.

12. The abnormal discharge detection method according to claim 1 , wherein the moving image is a moving image obtained by monochrome photography.

13. The abnormal discharge detection method according to claim 1 , wherein the step of acquiring the moving image acquires the moving image after the plasma processing is completed.

14. The abnormal discharge detection method according to claim 1 , wherein the step of acquiring the moving image acquires the moving image while the plasma processing is being performed.

15. A control device for detecting minute abnormal discharges occurring inside a processing vessel in which plasma processing is performed, acquiring a video of the inside of the processing vessel; acquiring, based on the video, grayscale images representing, in grayscale, images of frames that belong to a time-series evaluation range for detecting the minute abnormal discharge; performing a flattening process on the grayscale image to adjust the contrast and generate a flattened image; obtaining a binarized image in which difference portions identified as foregrounds relative to the background in the flattened image by a background subtraction method and portions other than the difference portions are expressed with different pixel values; A control device that performs a process of performing a first expansion process, a closing process in which a first contraction process is performed following the first expansion process, and an opening process in which a second contraction process is performed following the second contraction process, on the binary image at least once each, and outputs a discharge image for detecting the minute abnormal discharge.

16. The control device according to claim 15 , wherein the control device is a device separate from the substrate processing apparatus including the processing vessel.

17. The control device according to claim 15 , wherein a substrate processing apparatus including the processing vessel includes the control device.

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