Method and system for simulating yield of slit thin film material and computer readable storage medium

Abstract

The invention belongs to the technical field of thin film production, and discloses a method and system for simulating the yield of a slit thin film material and a computer readable storage medium, and the method comprises the following steps: firstly, detecting a thin film by adopting an optical defect detector to obtain defect data; preprocessing the defect data to obtain preprocessed data; obtaining an evaluation score of each cutting area according to a preset cutting size and the pre-processing data; and finally, calculating a simulation yield according to the evaluation score, and generating an abnormal map at the same time. The problems that in the current yield simulation process, evaluation of each defect on a thin film material cannot be achieved, an abnormal area is missed, and large-area small defects are not missed are solved, full-defect calculation can be achieved, the accuracy of the simulation yield is high, a guidance basis is provided for subsequent cutting, and the optimal cutting mode can be obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of thin film production, and in particular, relates to a method for simulating the yield of thin film materials after slitting, a system thereof, and a computer-readable storage medium. Background Art

[0002] Film is an organic layer made from polymer resin as the matrix material through processing, molding, post-processing and other steps. For example, optical film, plastic film, polyester film, etc., has been widely used in the electronics, machinery, printing and other industries. The processing and molding process of film materials is the key to producing high-quality films. Due to problems with the film preparation process, various defects may appear after the film is formed. In the post-processing stage of film materials, the film needs to be cut into the required size and shape to facilitate subsequent processing by downstream clients. However, different cutting sizes and cutting methods will cause defects to appear on different sheets. The existing traditional method is to use the back-end manual inspection method to manually inspect the cut film before making the actual judgment. This is time-consuming and requires a lot of personnel. It is easy to miss inspections, and the existing method cannot evaluate every defect.

[0003] For example, patent publication number CN113188862A discloses a method for simulating the yield of polarizing film rolls. This method, when producing polarizing film rolls, uses defect data generated by an automated optical inspection system to simulate and calculate the yield of a specific cut polarizing film based on the defect's location, size, and severity. Cutting parameters can be set to avoid flashing edges and areas with high defect counts, thereby improving the yield of the actual cut product. However, in the defect data screening process, this method matches defect type with defect attributes such as length, width, and area as screening criteria, classifying defects as in-specification or out-of-specification defects (i.e., undesirable defects). This results in a situation where, in actual operation, defects that are smaller than the selected defects, far exceeding the normal cut size, are present, such as if there are five in-specification defects per meter, but dozens or even hundreds of them per meter, but these are not in the selected size, the abnormal area will be missed and the abnormality will be missed. Summary of the Invention

[0004] The present invention aims to solve the problem that the current yield simulation process cannot evaluate every defect on the thin film material and abnormal areas are missed. It provides a method for simulating the yield of the thin film material after cutting. The method can give an evaluation score for the defects of each cutting area by preprocessing the defect data. There is no problem of missing small defects in large areas, and the calculation of all defects is achieved. The simulation yield is highly accurate, providing a guiding basis for subsequent cutting to obtain the best cutting method.

[0005] At the same time, the present invention also provides a system and a computer-readable storage medium that can implement the above-mentioned method for simulating the yield of thin film materials after slitting.

[0006] The present invention is achieved through the following technical solution: A method for simulating the yield of thin film materials after slitting, comprising the following steps: S1. Use an optical defect detector to inspect the film and obtain defect data; S2. Preprocess the defect data to obtain preprocessed data; S3. Obtain the evaluation score of each cutting area according to the preset cutting size and preprocessed data; S4. Calculate the simulation yield based on the evaluation score and generate an anomaly map.

[0007] The defect data contains at least the following indicator features: defect location, length, width, area, aspect ratio, fill ratio and light-dark area ratio.

[0008] The preprocessing is a process of classifying various indicator features in the defect data and dividing them into different levels according to the different data ranges.

[0009] According to the preset cutting size and pre-processing data, the number of defects in each cutting area and their corresponding grades are obtained, and the evaluation score of each cutting area is calculated based on the preset grade points. When the evaluation score is greater than or equal to the preset score, the corresponding cropping area is “NG”; when the evaluation score is less than the preset score, the corresponding cropping area is “OK”.

[0010] The simulation yield is the number of “OK” / the total number of cuts.

[0011] The abnormality map is an image in which "NG" areas are drawn on the inspection map of the entire film roll.

[0012] A system for simulating the yield rate of thin film materials after slitting includes a memory, a processor, and a computer program stored and running on the processor. When the processor executes the computer program, the method for simulating the yield rate of thin film materials after slitting as described above is implemented.

[0013] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for simulating the yield of thin film materials after slitting.

[0014] Compared with the prior art, the present invention has the following advantages and beneficial effects: (1) The present invention utilizes the index characteristics of the acquired defect data, and through classification, grading, and preset grade integration, can obtain the calculation of all defects in different cutting areas under any cutting method, without missing defects due to unselected defects, and can improve the accuracy of yield simulation to obtain the best cutting method.

[0015] (2) Since the method of the present invention gives an evaluation score to the defects of the cutting area to determine whether the corresponding cutting area meets the requirements of good products ("NG" is a defective product, and "OK" is a good product), the present invention can be applied to cutting settings of any size and any method, and can also perform covering and shielding of any length during the cutting process, and has a wide range of applications.

[0016] (3) The present invention can obtain the yield of each cutting area, the number of good products in the cutting area, the number of good products of the cut film material, and the yield of the cut film material.

[0017] (4) Since the present invention can realize the calculation of all defects and the scores of all defects are simulated by the algorithm, it is also possible to obtain an abnormal map of the NG position and realize the image display of the abnormal position of cutting, thereby improving the controllability for subsequent cutting. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of the process of the present invention.

[0019] Figure 2 This is an information coordinate diagram of defect data in Example 2 of the present invention.

[0020] Figure 3 The scores of different defects in Example 2 of the present invention are defined.

[0021] Figure 4 This is an anomaly map of the thin film material in Example 2 of the present invention. DETAILED DESCRIPTION

[0022] The present invention will be further described in detail below with reference to the examples, but the embodiments of the present invention are not limited thereto.

[0023] Example 1: This embodiment is a method for simulating the yield of thin film materials after slitting.

[0024] like Figure 1 As shown, the method of this embodiment is to pre-process the defect data of the thin film material detected by the optical defect detector, and then select different cutting sizes in the yield simulation system to score and evaluate different defects in the cutting area, and finally generate a simulated yield and produce an abnormality map at the same time.

[0025] The process can be further summarized as follows: Step 1: Defective data detection Before the film material is formed and wound, an optical defect detector is fixedly installed on the production line to inspect the continuously conveyed film material. Examples of optical defect detectors include ISRA, FUTEC, or MEC. The defect data that can be obtained include the following indicator characteristics: defect location, length, width, area, aspect ratio, fill ratio, and light-dark area ratio, etc.

[0026] Step 2: Data processing The above defect data obtained by the optical defect detector is input into the computer for preprocessing. Preprocessing is the process of classifying the various indicator features in the defect data and dividing them into different levels according to their data ranges.

[0027] In one possible embodiment, classification and grading can be performed in the following manner: 1) When the defect index characteristics meet the following requirements: length > 0.6mm, width > 0.6mm, area > 0.2mm 2 , when the filling ratio is ≥30%, the defect is marked as level 10; 2) When the defect index characteristics meet the following requirements: 0.1mm≤length≤0.6mm, 0.1mm≤width≤0.6mm, 0.2mm 2 ≥Area>0.1mm 2 , when the aspect ratio is 20%<80%, the defect is marked as level 9; 3) When the defect index characteristics meet the following requirements: light-dark area ratio ≤ 0.1%, the defect is identified as level 8; 4) When the defect meets the following indicator characteristics: length < 0.1mm, width < 0.1mm, the defect is identified as level 7.

[0028] It should be noted that the classification and grading of the various indicator features involved in the data processing process can be achieved based on known software systems (such as MaxEye). It only requires inputting the data of the various indicator features to be classified and the number of levels to be divided. All data can be automatically statistically calculated and classified, and graded as needed.

[0029] Step 3: Yield simulation In the yield simulation system, by inputting the preset cutting size and defect data as well as the processed data corresponding to the defect data, the number of defects in each cutting area and the corresponding level of the defects can be obtained. Here, the preset level points are required. For example, level 8 corresponds to 100 points, level 5 corresponds to 5 points, and so on. Based on the aforementioned number of defects and defect level points, the evaluation score of each cutting area can be calculated.

[0030] When the evaluation score is greater than or equal to the preset score, the corresponding cutting area is marked as "NG", indicating that the cutting area is defective. When the evaluation score is less than the preset score, the corresponding cutting area is “OK”, indicating that the cutting area is a good product.

[0031] By counting all cut areas, we can obtain the total number of cuts, the number of "Good" and "Not Good" results for the entire film material. The simulated yield of the film material is calculated as the simulated yield "Good" number divided by the total number of cuts. Furthermore, images of "Good" areas can be plotted on the inspection map of the entire film roll, thereby generating an anomaly map.

[0032] It should be noted that the points corresponding to the levels described in this embodiment can be generated according to the system software, and the preset scores are preset based on production experience and downstream usage experience.

[0033] Example 2: This embodiment is an example of film cutting using the method for simulating the yield of film material after slitting described in Example 1.

[0034] The whole roll of film material is continuously passed through the optical defect detector to detect the defect data, and the data obtained by the detection is imported into the software system for pre-processing data to obtain the following Figure 2 The information coordinate diagram shown.

[0035] Depend on Figure 2 As shown, the defect data is classified into categories such as "*", "+", "■", "●", etc., and is displayed on the corresponding film map according to the coordinate position of the defect data.

[0036] For the convenience of calculation, this embodiment uses the cutting simulation calculation based on 2m in the longitudinal direction and the full width in the transverse direction. If the whole roll is calculated as 1000 meters, the whole roll of film material can be cut into 500 parts. After cutting, the evaluation scores of different cutting areas are obtained. The definition of the scores of different types of defects can be found in Figure 3 shown.

[0037] In this embodiment, the preset score is 100 points. When the sum of the scores of the number of defects in the cutting area exceeds the preset score, the cutting area is displayed as "NG", otherwise it is "OK", and the cutting yield of the film material is obtained. At the same time, the position of the "NG" is drawn on the map of the entire roll of film material, as shown in FIG. Figure 4 As shown in the figure, the shaded part is the "NG" position.

[0038] Example 3: This embodiment is a system for simulating the yield rate of thin film materials after slitting.

[0039] The device mainly consists of a memory, a processor and a computer program stored and running on the processor. When the processor executes the computer program, the method for simulating the yield of thin film materials after slitting described in Example 1 is implemented.

[0040] Example 4: This embodiment is a computer-readable storage medium.

[0041] The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for simulating the yield rate of thin film materials after slitting described in Example 1 is implemented.

[0042] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification or equivalent change made to the above embodiment based on the technical essence of the present invention shall fall within the scope of protection of the present invention.

Claims

1. A method for simulating the yield of thin film materials after slitting, characterized in that: The following steps are involved: S1. Use an optical defect detector to inspect the film and obtain defect data; S2. Preprocess the defect data to obtain preprocessed data; S3. Obtain the evaluation score of each cutting area according to the preset cutting size and preprocessed data; S4. Calculate the simulation yield based on the evaluation score and generate an anomaly map.

2. The method according to claim 1, wherein: The defect data contains at least the following indicator features: defect location, length, width, area, aspect ratio, fill ratio and light-dark area ratio.

3. The method according to claim 1, wherein: The preprocessing is a process of classifying various indicator features in the defect data and dividing them into different levels according to the different data ranges.

4. The method according to claim 3, wherein: According to the preset cutting size and pre-processing data, the number of defects in each cutting area and their corresponding grades are obtained, and the evaluation score of each cutting area is calculated according to the preset grade points.

5. The method according to claim 4, characterized in that: When the evaluation score is ≥ the preset score, the corresponding cropping area is "NG"; when the evaluation score is < the preset score, the corresponding cropping area is "OK".

6. The method according to claim 5, characterized in that: The simulation yield is the number of "OK" / the total number of cuts.

7. The method according to claim 5, characterized in that: The abnormality map is an image that depicts the "NG" area on the inspection map of the entire roll of film.

8. A system for simulating the yield of thin film materials after slitting, characterized by: The method comprises a memory, a processor and a computer program stored and run on the processor, wherein when the processor executes the computer program, the method for simulating the yield rate of thin film materials after slitting as claimed in any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for simulating the yield rate of thin film materials after slitting according to any one of claims 1 to 7 is implemented.

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