Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
  • G01N21/84—Systems specially adapted for particular applications
  • G01N21/88—Investigating the presence of flaws or contamination
  • G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
  • G01N21/892—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the flaw, defect or object feature examined

Definitions

• the present invention relates to an information processing system, an information processing method, and an information processing program.
• Optical films are used in displays such as liquid crystal display devices.
• Webs for optical films and the like are composed of a laminate of multiple webs.
• the manufacturing process for such optical films and the like requires strict control over defects that occur in the web.
• Patent Document 1 describes technology related to defects that occur in webs.
• a laminate of multiple webs may include an opaque web, such as a protector, separator, or anti-glare film. Detecting defects in a laminate that includes an opaque web can be difficult. Therefore, it would be desirable to be able to more easily analyze defects present in a laminate that includes an opaque web.
• the present invention was made in consideration of the above circumstances, and aims to provide an information processing system, information processing method, and information processing program that can more easily analyze defects present in laminates that include opaque webs.
• An information processing system comprising: an acquisition unit that acquires first feature information relating to feature points present in a first web and second feature information relating to feature points present in a laminate formed by laminating an opaque second web onto the first web; a comparison unit that compares the acquired first feature information with the acquired second feature information; and an output unit that outputs comparison information relating to the comparison result between the first feature information and the second feature information.
• An information processing system as described in (1) above further comprising an alignment unit that associates feature points present on the first web with feature points present on the laminate based on their relative positions, and the comparison unit uses the results of the association to compare the first feature point information with the second feature point information.
• the second web includes at least one of a protector, a separator, or an anti-glare film.
• An information processing method including: acquiring first feature point information relating to feature points present in a first web; and second feature point information relating to feature points present in a laminate formed by laminating an opaque second web on the first web; comparing the acquired first feature point information with the acquired second feature point information; and outputting comparison information relating to the comparison result between the first feature point information and the second feature point information.
• the first feature information and the second feature information are compared, and comparison information regarding the comparison results is output.
• This allows, for example, a manufacturing manager to easily grasp which feature points present in a laminate including an opaque second web remain from the state of the first web, making it easier to analyze defects present in a laminate including an opaque web.
• FIG. 1 is a schematic diagram illustrating an application example of an information processing system according to a first embodiment.
• FIG. 2 is a cross-sectional view showing an example of the configuration of a first stack and a second stack shown in FIG. 1 .
• FIG. 2 is a schematic diagram showing an example of the configuration of the inspection device shown in FIG. 1 .
• FIG. 3B is another schematic diagram showing the configuration of the inspection device shown in FIG. 3A.
• FIG. 3B is a schematic diagram showing another configuration of the inspection device shown in FIG. 3A.
• FIG. 3B is a schematic diagram showing another configuration of the inspection device shown in FIG. 3A.
• FIG. 7 is a diagram for explaining a result of comparing first feature point information with second feature point information by the control unit shown in FIG. 6 .
• FIG. 2 is a flowchart illustrating an example of a process executed by the information processing system illustrated in FIG. 1 .
• 11 is a subroutine flowchart of the process of step S33 shown in FIG. 10.
• 10 is a subroutine flowchart executed by an information processing system according to a second embodiment.
• FIG. 13 is a diagram illustrating an example of a probability density function calculated by the kernel density estimation shown in FIG. 12 .
• FIG. 11 is a cross-sectional view showing an example of the configuration of a stack to which an information processing system according to a third embodiment is applied.
• 15A to 15C are schematic diagrams illustrating an example of a manufacturing process for the laminate shown in FIG. 14.
• FIG. 1 is a schematic diagram illustrating an application example of an information processing system 50 according to the first embodiment.
• the information processing system 50 is configured, for example, by a server.
• the information processing system 50 is connected to a terminal device 70 in a factory 100 via a network.
• the network is a communication line such as a data communication network. Some networks may use a wired LAN or a wireless LAN.
• the wireless LAN is, for example, a LAN conforming to the IEEE 802.11 standard.
• the information processing system 50 may be connected to another factory via the network.
• a manufacturing apparatus 2000 manufactures a first laminate 80A into a second laminate 80B.
• the second laminate 80B is wound, for example, into a roll.
• the first laminate 80A corresponds to a specific example of a first web of the present invention
• the second laminate 80B corresponds to a specific example of a laminate of the present invention.
• feature points present in the second laminate 80B are optical feature points present in the web, specifically, spots that are optically different from their surroundings. Note that when determining optical differences from their surroundings, a predetermined threshold may be set, and those exceeding that threshold may be considered feature points.
• Feature points present in the web may also be referred to as web defects, malfunctions, or failures. Feature points include, for example, defects caused by poor adhesion when bonding multiple webs together and defects caused by axial unevenness. Multiple webs are bonded together using, for example, ultrasonic welding. For example, tens to tens of thousands of feature points can be detected from image data captured of a single second laminate 80B. The total length of the second laminate 80B is, for example, several hundred meters to several kilometers. Note that multiple defects, malfunctions, and failures within a specified area (for example, a 10 mm square) may be considered a single feature point.
• Camera 92 is positioned, for example, at a location where it receives specularly reflected light from light source 91. Camera 92 may also be positioned to avoid specularly reflected light from light source 91, i.e., at a location where it receives diffused light from second laminate 80B.
• the analysis unit 93 acquires image data for one area a1 and performs mathematical processing on the image data for area a1.
• Mathematical processing includes, for example, preprocessing, enhancement processing, signal processing, and image feature extraction.
• Enhancement processes include, for example, Sobel filters, Scharr filters, Laplacian filters, Gabor filters, and Canny algorithms.
• Signal processing includes, for example, basic statistics, square root of the sum of squares, difference, sum, product, ratio, distance matrix calculation, differential and integral calculus, thresholding, Fourier transform, wavelet transform, and peak detection.
• Basic statistics include, for example, maximum, minimum, mean, median, standard deviation, variance, and quartile.
• Thresholding includes, for example, binarization and adaptive binarization.
• Peak detection includes, for example, detection of peak value, peak number, or half-width.
• the analysis unit 93 performs mathematical processing on the image data of area a1, and then performs threshold processing on the values obtained from this processing.
• Threshold processing is a process that determines whether or not an object is a feature point based on a predetermined threshold, and also determines the size of the feature point, etc.
• Figure 3C shows an example of a transmission-type inspection device 90.
• a light source 91 is positioned opposite a camera 92, with the second laminate 80B in between.
• the CPU 71 controls the above components and performs various calculations in accordance with programs stored in the ROM 72 or storage 74.
• ROM 72 stores various programs and data.
• RAM 73 serves as a working area for temporarily storing programs and data.
• Storage 74 stores various programs, including the operating system, and various data. For example, applications for displaying various information sent from information processing system 50 are installed in storage 74.
• the operation reception unit 77 includes, for example, a touch sensor, a pointing device such as a mouse, or a keyboard.
• the operation reception unit 77 receives various operations from the user.
• the display unit 160 and the operation reception unit 77 may form a touch panel by overlaying a touch sensor serving as the operation reception unit 77 on the display surface serving as the display unit 76.
• the terminal device 70 may generate the second feature information by performing image analysis on the image data of the second laminate 80B captured by the inspection device 90.
• the terminal device 70 may, for example, transmit the inspection data including the second feature information to the information processing system 50.
• the terminal device 70 further transmits inspection data of the first stack 80A to the information processing system 50.
• This inspection data includes first feature point information regarding feature points present in the first stack 80A.
• the feature points present in the first stack 80A are optically detected, for example, by an inspection device similar to the above-mentioned inspection device 90.
• Inspection data for the first laminate 80A may be transmitted to the information processing system 50 from another terminal device.
• the other terminal device may be, for example, a terminal device at the factory where the first laminate 80A was manufactured.
• the information processing system 50 compares the first feature point information and second feature point information received from the terminal device 70 and classifies each feature point into three types: first-type feature points, second-type feature points, and third-type feature points.
• FIG. 5 is a table for explaining the first, second, and third type feature points.
• the multiple feature points present in the first laminate 80A can be classified, for example, into first type feature points and third type feature points.
• the feature points present in the second laminate 80B can be classified, for example, into second type feature points and third type feature points.
• the third type characteristic points are characteristic points that exist in both the first laminate 80A and the second laminate 80B.
• the third type characteristic points are characteristic points that are generated in a process prior to the manufacturing process of the first laminate 80A and that remain in the second laminate 80B.
• These third type characteristic points are characteristic points that are relatively likely to affect processes after the lamination process of the fourth web 84. Note that the shape and size of the third type characteristic points may change during the lamination process of the fourth web 84 compared to when they existed in the first laminate 80A. Depending on the lamination process, additional failures may occur.
• the information processing system 50 classifies and stores the feature points present in the first stack 80A and the feature points present in the second stack 80B as first-type feature points, second-type feature points, and third-type feature points. By storing the feature points as first-type feature points and third-type feature points, it is possible to determine whether the feature points of the first stack 80A remain in the second stack 80B or have disappeared.
• FIG. 6 is a block diagram showing a schematic configuration of the information processing system 50.
• the information processing system 50 includes, for example, a control unit 51, a storage unit 52, and a communication unit 53.
• the control unit 51 includes, for example, a CPU and memories such as RAM and ROM.
• the CPU is composed of a multi-core processor that controls the above-mentioned units and executes various arithmetic processes in accordance with a program.
• Each function of the information processing system 50 is realized by the CPU executing the corresponding program. The specific functions of the control unit 51 will be described later.
• Figure 7B shows an example of a lot list.
• the lot list includes information such as the lot ID, product name, delivery destination user ID, manufacturing conditions, size, and manufacturing date for each lot.
• the information processing system 50 functions as an acquisition unit 511, an alignment unit 512, a comparison unit 513, and an output unit 514 by the control unit 51 reading a program stored in the memory unit 52 and executing processing.
• the acquisition unit 511 acquires first feature point information and second feature point information.
• the first feature point information is information about feature points present in the first stack 80A.
• the first feature point information includes, for example, information about the feature point ID, position, area, length, width, maximum brightness, minimum brightness, division, and presence or absence of concentrated points for each of the multiple feature points present in the first stack 80A.
• the second feature point information is information relating to the feature points present in the second laminate 80B.
• the second feature point information includes, for example, information relating to the feature point ID, position, area, length, width, maximum brightness, minimum brightness, division, and presence or absence of concentrated dots for each of the multiple feature points present in the second laminate 80B.
• the first feature point information and second feature point information include at least information regarding the position of each feature point.
• the position of the feature point is expressed, for example, as XY coordinates based on a predetermined position on each web.
• the acquisition unit 511 acquires the first feature point information and second feature point information from, for example, the terminal device 70.
• the acquisition unit 511 may also acquire the first feature point information and second feature point information from the storage unit 52.
• the acquisition unit 511 may further acquire third feature point information.
• the third feature point information is information relating to feature points present on the fourth web 84.
• the third feature point information includes, for example, information relating to the feature point ID, position, area, length, width, maximum brightness, minimum brightness, classification, and the presence or absence of concentrated dots for each of the multiple feature points present on the fourth web 84.
• Figure 9 shows an example of the comparison results between the first feature point information and the second feature point information.
• the comparison unit 513 for example, integrates and compares the feature points present in the first stack 80A and the feature points present in the second stack 80B.
• the comparison unit 513 for example, assigns new feature point IDs to all of the integrated feature points.
• the comparison unit 513 for example, classifies the feature points for each feature point ID into first, second, or third type feature points.
• the comparison results may include information regarding the accuracy of the classification of first, second, and third type feature points.
• FIG. 10 is a flowchart showing an example of the procedure for processing to output comparison information executed in the information processing system 50.
• the processing of the information processing system 50 shown in the flowchart in FIG. 10 is stored as a program in the storage unit 52 of the information processing system 50, and is executed by the CPU controlling each unit.
• the information processing system 50 further performs noise removal processing as preprocessing for each inspection data.
• the noise removal processing includes, for example, removal of low-intensity feature points, removal of extremely small feature points, and removal of continuous dots.
• the noise removal processing may also include removal of concentrated dots in the width direction. Concentrated dots in the width direction occur, for example, at the leading and trailing ends of the first stack 80A and the second stack 80B.
• Step S33 The information processing system 50 performs preprocessing on each piece of inspection data, and then performs alignment processing between the coordinate system of the first stack 80A and the coordinate system of the second stack 80B.
• Figure 11 is a subroutine flowchart showing the alignment process in step S33.
• the information processing system 50 first roughly adjusts the XY coordinates of the feature points of the first stack 80A and the second stack 80B as follows. For example, the information processing system 50 first shifts the coordinate position of a predetermined feature point of the first stack 80A by a predetermined amount. Next, the information processing system 50 calculates distances L1 to Lm between the predetermined feature point of the first stack 80A and the corresponding feature point of the second stack 80B, and selects the shift amount (x1, y1) whose sum is the smallest. The information processing system 50 may use an average value instead of the sum.
• the information processing system 50 sequentially shifts the coordinate position of a predetermined feature point of the first stack 80A from (-shift_x, -shift_y) to (+shift_x, +shift_y) around the central shift amount (0, 0) in increments of a fixed coarse adjustment shift amount a. It then calculates distances L1 to Lm from the coordinate position of the predetermined feature point of the first stack 80A to feature points 1 to m of the second stack 80B. It then selects the shift amount (x1, y1) from (-shift_x, -shift_y) to (+shift_x, +shift_y) that results in the smallest sum of distances L1 to Lm.
• the information processing system 50 may use different units for the X direction and the Y direction for the coarse adjustment shift amount a.
• Steps S404 to S406 the information processing system 50 fine-tunes the XY coordinates of the feature points of each of the first stack 80A and the second stack 80B and selects a shift amount (x2, y2).
• the information processing system 50 selects the shift amount (x2, y2) in substantially the same manner as in steps S401 to S403 described above.
• Steps S404 to S406 differ from steps S401 to S403, for example, in the following respects:
• the fine-adjustment shift amount b in step S404 is smaller than the coarse-adjustment shift amount a.
• the shift amount (x1, y1) selected in step S403 is used as the center shift amount in step S405.
• the fine-adjustment shift amount b is sufficiently smaller than the coarse-adjustment shift amount a, for example, 0.1 mm, which is one order of magnitude smaller.
• Step S407 The information processing system 50 performs coordinate transformation processing on all of the feature points of the first stack 80A using the shift amount (x2, y2) selected in step S406.
• Step S408 The information processing system 50 calculates the distances L1 to Lm after the coordinate transformation in step S407 and checks whether the sum of the distances L1 to Lm is less than a predetermined threshold value. If the sum is equal to or greater than the predetermined threshold value, the information processing system 50 may determine that the coordinate transformation process in step S407 is inappropriate.
• Step S409 If the alignment is inappropriate, i.e., if the answer is YES, the information processing system 50 ends the process. If the alignment is inappropriate, the information processing system 50 may display an error message on the display unit 76 or record in the test data DB a message indicating that calculation is not possible. On the other hand, if the alignment is appropriate, i.e., if the answer is NO, the information processing system 50 ends the process of FIG. 11, returns to the process of FIG. 10, and executes the processes from step S34 onwards.
• the information processing system 50 further uses third feature point information regarding feature points present in the fourth web 84. This makes it possible to classify the feature points present in the first laminate 80A and the feature points present in the second laminate 80B into first-type feature points, second-type feature points, and third-type feature points with greater accuracy.
• Steps S453 to S455 The information processing system 50 compares the two obtained probability density functions and performs correspondence based on the density distribution. Then, the information processing system 50 calculates a transformation matrix based on the correspondence result and performs coordinate transformation of the X and Y coordinates for the feature points of the first stack 80A.
• the first web of the present invention includes an opaque optical film such as a polarizer, but the first web may also include other opaque webs.
• the first web may include, for example, a steel plate or an anti-glare film.
• the first web may also be transparent.
• a transparent first web has, for example, a haze of 2% or less.
• a transparent first web is, for example, a transparent optical film, a hard coat, an anti-reflection layer, or a liquid crystal layer.
• the second web of the present invention may include, for example, an opaque optical film such as a polarizer, a plastic film, a steel plate, paper, etc.
• the means and methods for performing various processes in the information processing system 50 according to the above-described embodiment can be realized by either dedicated hardware circuits or a programmed computer.
• the above programs may be provided, for example, by computer-readable recording media such as USB memory or DVD-ROM, or may be provided online via a network such as the Internet.
• the programs recorded on the computer-readable recording media are typically transferred to and stored in a storage unit such as a hard disk.
• the above programs may be provided as standalone application software, or may be incorporated into the software of a device as one of its functions.
• DVD is an abbreviation for Digital Versatile Disc.

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