Manufacturing inspection systems, manufacturing inspection methods, manufacturing inspection equipment, and programs

Abstract

The system measures the object being inspected non-destructively and automatically determines whether or not it meets the specified standards. [Solution] A manufacturing inspection system that measures an inspection target, which is a product, by fluorescent fingerprint measurement in the product manufacturing process and outputs a manufacturing inspection result, comprising: a spectrofluorometer for measuring the fluorescent fingerprint data of the inspection target; a fluorescent fingerprint data calculation unit for analyzing the measured fluorescent fingerprint data using a predetermined calculation method; an acceptance criteria storage unit for storing acceptance criteria for product specifications formulated from one or more design specification ranges defined in the product design information and manufacturing specification ranges defined in the manufacturing information; and an acceptance / rejection determination unit for determining acceptance or rejection by comparing the results analyzed by the fluorescent fingerprint data calculation unit with the acceptance criteria.

Description

Technical Field

[0001] The present disclosure relates to a manufacturing inspection system, a manufacturing inspection method, a manufacturing inspection apparatus, and a program.

Background Art

[0002] In the transition to a resource recycling society, an increase in the usage rate of recycled materials in resin products and the like is required.

[0003] In recent years, techniques for analyzing components, states, etc. of inspection targets using machine learning and the like have been developed.

[0004] In Patent Document 1, a resin film is used as an example of a target T for obtaining inductive information in machine learning, and the principal component scores 1 and 2 of the fluorescence fingerprint for the resin film, information regarding a UV absorber that may be included in a predetermined resin film, and information regarding the heating state of this resin film are learned as teacher data. An information processing apparatus is disclosed that analyzes the fluorescence fingerprint based on the principal component scores generated by the machine learning model and thereby analyzes the presence or absence of a UV absorber and the heating state in the target T.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] In the transition to a resource recycling society, an increase in the usage rate of recycled materials in resin products and the like is required. In such a situation, it is required to prove what percentage of recycled materials are actually contained in each product.

[0007] The information processing device described in Patent Document 1 performs analysis on various objects and outputs the results, but it is assumed that the operator will determine whether or not the predetermined criteria are met.

[0008] This disclosure aims to provide a method for non-destructively measuring an object to be inspected and automatically determining whether or not it meets predetermined criteria. [Means for solving the problem]

[0009] The manufacturing inspection system disclosed herein measures an inspection target, which is a product, by fluorescent fingerprint measurement during the product manufacturing process and outputs a manufacturing inspection result, and comprises: a spectrofluorometer for measuring the fluorescent fingerprint data of the inspection target; a fluorescent fingerprint data calculation unit for analyzing the measured fluorescent fingerprint data using a predetermined calculation method; an acceptance criteria storage unit for storing acceptance criteria for product specifications formulated from one or more design specification ranges defined in the product design information and manufacturing specification ranges defined in the manufacturing information; and an acceptance / rejection determination unit for determining acceptance or rejection by comparing the results analyzed by the fluorescent fingerprint data calculation unit with the acceptance criteria. [Effects of the Invention]

[0010] According to this disclosure, the object to be inspected can be measured non-destructively, and it can be automatically determined whether or not it meets predetermined standards. [Brief explanation of the drawing]

[0011] [Figure 1] This is a diagram showing the manufacturing inspection system of Example 1. [Figure 2] This is a flowchart showing the manufacturing inspection method for Example 1. [Figure 3] This is a configuration diagram showing the hardware of the manufacturing inspection system in Example 1. [Figure 4A] This graph shows the fluorescence fingerprint data of the subject of the examination (1). [Figure 4B] This graph shows the fluorescence fingerprint data of the subject of the examination (2). [Figure 5A] This table shows the principal component scores for test subject (1) and test subject (2). [Figure 5B] A graph showing the distributions of the inspection targets (1) and (2) regarding two main components. [Figure 5C] A graph showing the relationship between the fluorescence fingerprint data after preprocessing and the proportion of recycled materials contained in the resin material. [Figure 6] A diagram showing an example of the screen of the display device of Example 1. [Figure 7] A configuration diagram showing the manufacturing inspection system of Example 2. [Figure 8] A flowchart showing the manufacturing inspection method of Example 2. [Figure 9] A configuration diagram showing the manufacturing inspection system of Example 3. [Figure 10] A flowchart showing the manufacturing inspection method of Example 3.

MODE FOR CARRYING OUT THE INVENTION

[0012] Hereinafter, examples of the present disclosure will be described with reference to the drawings.

EXAMPLE

[0013] FIG. 1 is a configuration diagram showing the manufacturing inspection system of Example 1.

[0014] The manufacturing inspection system 100 shown in this figure includes a fluorescence fingerprint data calculation unit 1, a pass / fail criterion storage unit 2, a pass / fail determination unit 3, a pass / fail information storage unit 4, an output unit 5, and a non-conformance cause analysis unit 6. The manufacturing inspection system 100 may also be referred to as a "manufacturing inspection device". The fluorescence fingerprint data calculation unit 1, the pass / fail criterion storage unit 2, the pass / fail determination unit 3, the pass / fail information storage unit 4, the output unit 5, and the non-conformance cause analysis unit 6 may each be a computing device with a memory as needed, or may be composed of one computing device with a memory. In this case, the program for causing the computing device to execute a predetermined calculation may be combined into one, or may be divided into multiple parts. Here, the program includes those for causing a computer to execute the procedure of manufacturing inspection, which measures an inspection target that is a product by fluorescence fingerprint measurement in the manufacturing process of the product and outputs a manufacturing inspection result.

[0015] The fluorescence fingerprint data calculation unit 1 receives fluorescence fingerprint data from the spectrofluorometer 11. Then, it performs a predetermined calculation and transmits the calculation result to the pass / fail determination unit 3 and the non-conformance cause analysis unit 6.

[0016] The pass / fail criterion storage unit 2 receives the input of design information and manufacturing information from the outside and transmits the pass / fail criteria to the pass / fail determination unit 3. The pass / fail determination unit 3 determines pass / fail using the pass / fail criteria for the calculation result of the fluorescence fingerprint data calculation unit 1 and transmits the pass / fail information to the pass / fail information storage unit 4 and the non-conformance cause analysis unit 6. Note that the design information and manufacturing information obtained by the pass / fail criterion storage unit 2 from the outside do not necessarily need to obtain both as long as the pass / fail criteria can be obtained, and either one alone may be sufficient.

[0017] The pass / fail information storage unit 4 receives the input of the individual number (e.g., manufacturing number) of the inspection target from the outside and transmits the pass / fail information corresponding to the individual number to the output unit 5. The output unit 5 outputs certification data including the individual number stored in the pass / fail information storage unit 4 and the pass / fail determination result corresponding to the individual number. The individual number is not particularly limited as long as it can identify the inspection target. For example, it may be a number code, symbol, barcode, two-dimensional code, etc.

[0018] The failure cause analysis unit 6 determines the pre-calculation excitation and fluorescence wavelengths that form the basis of the failure cause based on the calculation results received from the fluorescence fingerprint data calculation unit 1 and the pass / fail information received from the pass / fail judgment unit 3, and transmits this information to the output unit 5.

[0019] The output unit 5 outputs pass / fail information corresponding to the individual number and the pre-calculation excitation and fluorescence wavelengths that form the basis for the reason for failure to the external recording medium 12. In this case, the output unit 5 may also transmit and display this data to a display device (described later).

[0020] In this figure, the spectrofluorometer 11 is installed outside the manufacturing inspection system 100, but the manufacturing inspection system 100 may include the spectrofluorometer 11.

[0021] Figure 2 is a flowchart illustrating the manufacturing inspection method in this embodiment.

[0022] In this diagram, first, fluorescence fingerprint data of the object to be inspected is acquired from the spectrofluorometer 11 (step S11). Next, the fluorescence fingerprint data calculation unit 1 performs calculation processing on the fluorescence fingerprint data using a predetermined calculation method (step S12). Then, the fluorescence fingerprint data calculation unit 1 transmits the calculation result to the pass / fail determination unit 3 (step S13). The pass / fail determination unit 3 also reads the pass criteria from the pass criteria storage unit 2 (step S14).

[0023] Next, the pass / fail determination unit 3 determines whether the inspected item passes or fails (step S15).

[0024] If the inspection target passes, the pass / fail determination unit 3 transmits information indicating that it has passed to the pass / fail information storage unit 4 (step S16). The pass / fail information storage unit 4 reads the individual number of the inspection target from an external source and stores it in association with the pass / fail information (step S17). The pass / fail information may also be stored on an external recording medium 12.

[0025] Output unit 5 outputs the individual number and pass / fail information corresponding to the individual number (step S18).

[0026] On the other hand, if the inspection target is found to be unsatisfactory in step S15, the pass / fail determination unit 3 transmits information indicating that it is unsatisfactory to the pass / fail information storage unit 4 (step S21). This information is also transmitted to the failure cause analysis unit 6. The failure cause analysis unit 6 reads the calculation result and the pre-calculation fluorescence fingerprint data from the fluorescence fingerprint data calculation unit 1 (step S22). The failure cause analysis unit 6 then estimates the excitation and fluorescence wavelengths that form the basis of the failure (step S23).

[0027] The output unit 5 outputs the excitation and fluorescence wavelengths that form the basis for the failure cause estimated by the failure cause analysis unit 6 (step S24). The output unit 5 may also transmit the excitation and fluorescence wavelength data to an external recording medium 12 for storage.

[0028] Figure 3 is a configuration diagram showing the hardware of the manufacturing inspection system in this embodiment.

[0029] In this figure, the manufacturing inspection system 300 (computer system) is implemented using a computer and includes a processor 31 (Central Processing Unit (CPU), etc.), memory 32 (Random Access Memory (RAM), etc.), storage device 33 (Read Only Memory (ROM), etc.), input device 34, output device 35, and interface 36 (communication device, etc.). Externally installed input devices 321 (keyboard, touch panel, etc.) and display devices 322 (display, etc.) are connected to the interface 36 of the manufacturing inspection system 300. In addition, an externally installed spectrofluorometer 11 and external recording medium 12 are connected to the interface 36.

[0030] The processor 31 is a unit that performs various calculations. The processor 31 executes various processes by running programs and the like that loaded from the storage device 33 into the memory 32.

[0031] Here, the program is, for example, an application program that can be executed on an OS (Operating System) program. In this embodiment, the program is composed of multiple modules for each function, but it may also be implemented with multiple independent programs for each function.

[0032] Furthermore, the program may be installed in memory 32 from an external storage medium 12 via interface 36, for example. The communication path between interface 36 and an externally installed spectrofluorometer 11, etc., can be implemented via a network such as a LAN (Local Area Network) or the Internet, and may be wired or wireless. The external storage medium 12 may be a portable storage medium such as an SSD (Solid State Drive) using flash memory, an HDD (Hard Disk Drive), or a CD-ROM, or it may utilize cloud services.

[0033] The external recording medium 12 is configured to store design information, manufacturing information, individual identification numbers, etc., and to output them upon request from the processor 31, etc. The external recording medium 12 also receives and stores pass / fail information, the reasons for failure, etc., obtained from calculations performed by the processor 31.

[0034] Here, we will explain the fluorescence fingerprint data that is used for pass / fail determination.

[0035] Fluorescent fingerprint data is acquired from the spectrofluorometer 11 shown in Figure 1. When excitation light is shone onto the resin material to be inspected, the electrons constituting the molecules of the resin material are excited. Subsequently, when the excited electrons return to the ground state, fluorescence may be emitted.

[0036] For example, resin materials often contain additives such as antioxidants and flame retardants. Molecules of antioxidants and flame retardants may be aromatic compounds represented by benzene rings, or they may have π-conjugated electrons with alternating multiple and single bonds. In this case, when irradiated with excitation light, they emit fluorescence. Different excitation wavelengths result in different emission wavelengths. The fluorescence intensity also differs. Resin materials have the characteristic that the distribution of fluorescence wavelengths relative to the excitation wavelength and the fluorescence intensity differ depending on the type and content of the additives. This characteristic can be used to identify the resin material to be inspected. Then, using predetermined acceptance / rejection criteria, it can be determined whether or not the resin material is applicable to the product. In this specification, data that three-dimensionally represents the fluorescence wavelength and fluorescence intensity relative to the excitation wavelength is called "fluorescence fingerprint data." Note that "fluorescence fingerprint data" is not limited to any data that represents the fluorescence wavelength and fluorescence intensity relative to the excitation wavelength. Fluorescence fingerprint data can also be referred to as fluorescence data, fluorescence spectroscopy data, fluorescence intensity data, etc.

[0037] The fluorescence obtained in this way can be detected without being affected by the black pigment, even in recycled materials that have been blackened in appearance due to the addition of black pigments.

[0038] Below, we will explain the inspection targets (1) and (2) using polypropylene resin (PP) as an example of a resin material.

[0039] Figure 4A is a graph showing the fluorescence fingerprint data of the subject (1) being examined. The horizontal axis represents the fluorescence wavelength, and the vertical axis represents the excitation wavelength. The fluorescence intensity is represented by contour lines.

[0040] In this figure, the fluorescence intensity is high in the region where the fluorescence wavelength is 250-350 nm and the excitation wavelength is 250-300 nm. This indicates the fluorescence of additives contained in the virgin material. Therefore, the material being tested (1) is identified as virgin material or a mixed material with a very high proportion of virgin material.

[0041] The graph in this figure is also called the excitation-fluorescence matrix (EEM). The EEM is a three-dimensional plot of the excitation wavelength, the resulting fluorescence wavelength, and the intensity of that fluorescence.

[0042] Figure 4B is a graph showing the fluorescence fingerprint data of the subject (2) being examined.

[0043] Unlike Figure 4A, no fluorescence indicating additives is obtained in this figure. Therefore, the test subject (2) is identified as recycled material, or a mixed material with a very high proportion of recycled material.

[0044] One possible reason why fluorescence indicating additives is not obtained when recycled materials are irradiated with excitation light is that the antioxidants and flame retardants, which are additives contained in the used virgin material that serves as the raw material for recycled materials, have become inactive due to aging or heat treatment.

[0045] Furthermore, in order to enable identification of each recycled material using fluorescent fingerprint data, different types and proportions of additives may be added to each recycled material during its manufacturing process.

[0046] Figure 5A is a table showing the principal component scores for test subjects (1) and (2). Here, the principal component scores are calculated by performing preprocessing such as standardization, smoothing, and differentiation on the fluorescence fingerprint data, and then performing a predetermined analysis to determine the values ​​of the principal components. The principal component scores shown in this figure are the fluorescence intensity values ​​at predetermined coordinates that represent the characteristics of virgin material and recycled material, respectively, in the graphs of Figures 4A and 4B.

[0047] Figure 5B is a graph showing the distribution of test subjects (1) and (2) with respect to two principal components. The horizontal axis represents the first principal component, and the vertical axis represents the second principal component. In the figure, the area above the dashed boundary line represents the virgin material region, and the area below represents the recycled material region.

[0048] The results shown in this figure indicate that the material being inspected (1) is virgin material, and the material being inspected (2) is recycled material.

[0049] In this way, by analyzing the main components, it is possible to determine whether the resin material is virgin or recycled.

[0050] Figure 5C is a graph showing the relationship between the fluorescence fingerprint data after pretreatment and the proportion of recycled material contained in the resin material. The horizontal axis represents the principal component analysis values, which are the fluorescence fingerprint data after pretreatment, and the vertical axis represents the recycled material content, which is the composition ratio.

[0051] The regression equation shown in this figure can be expressed by the following linear function.

[0052] Y = b0 + Σ(b i ×x i ) In the equation, Y is the objective function, b i x is the regression coefficient. i is the explanatory variable, and b0 is a constant.

[0053] In this figure, for the sake of simplification and representation as a two-dimensional graph, the value of i is fixed and the principal component analysis values ​​are treated as one type. In reality, i can be an integer greater than or equal to 2, and can be an n-th degree function such as a quadratic or cubic function. Furthermore, it can be an exponential function, a logarithmic function, or a (1 / n)th degree function such as a square root or cube root.

[0054] This figure shows that, by using a regression equation, it can be determined that the recycled material content (e.g., by mass) is 20% for subject (1) and 70% for subject (2).

[0055] In this way, the recycled material content can be estimated by using principal component analysis values, etc.

[0056] Figure 6 shows an example of the screen of the display device in this embodiment.

[0057] This figure shows that the following are displayed on a single screen: a button to load fluorescent fingerprint data, a graph display of the resulting fluorescent fingerprint data, a setting for pass / fail criteria, a display of the pass / fail criteria, a button to output the pass / fail result, a display of the pass / fail result, and a display of candidate wavelengths that caused failure. Here, the loading of fluorescent fingerprint data can be done manually or automatically. The setting of the pass / fail criteria can also be done automatically, but the operator may be allowed to set or adjust the pass / fail range. The output of the pass / fail result can be done in batch processing or automatically.

[0058] Here, the candidate wavelengths that cause failure can be rephrased as the excitation and fluorescence wavelengths that form the basis for the failure.

[0059] Furthermore, the items displayed on a single screen are not limited to those shown in this diagram; some of these items may be displayed.

[0060] By displaying raw data such as fluorescent fingerprint data, pass / fail criteria, pass / fail results, and reasons for failure in this manner, it is possible to support operators in making decisions regarding the pass / fail status of products. [Examples]

[0061] In describing Example 2, only the differences from Example 1 will be explained, and similar configurations will not be described.

[0062] Figure 7 is a diagram showing the configuration of the manufacturing inspection system in this embodiment.

[0063] The manufacturing inspection system 700 shown in this figure does not have the failure cause analysis unit 6 shown in Figure 1. The other configurations are the same as in Figure 1.

[0064] Figure 8 is a flowchart showing the manufacturing inspection method in this embodiment.

[0065] Unlike Figure 2, in this figure, the process proceeds to steps S16-S18 without branching in step S15. [Examples]

[0066] In describing Example 3, only the differences from Example 1 will be explained, and similar configurations will not be described.

[0067] Figure 9 is a diagram showing the configuration of the manufacturing inspection system in this embodiment.

[0068] In the manufacturing inspection system 900 shown in this figure, the pass / fail information storage unit 4 is configured not to receive external input of the individual identification number of the inspection target shown in Figure 1. The other configurations are the same as in Figure 1.

[0069] Figure 10 is a flowchart showing the manufacturing inspection method in this embodiment.

[0070] In this figure, unlike in Figure 2, the process proceeds to step S108 without performing step S17 as in Figure 2 after step S16. In step S108, pass / fail information is output from the output unit 5. [Explanation of Symbols]

[0071] 1: Fluorescent fingerprint data calculation unit, 2: Acceptance criteria storage unit, 3: Pass / fail judgment unit, 4: Pass / fail information storage unit, 5: Output unit, 6: Failure cause analysis unit, 11: Spectrofluorometer, 12: External recording medium, 31: Processor, 32: Memory, 33: Storage device, 34: Input device, 35: Output device, 36: Interface, 100, 300, 900: Manufacturing inspection system, 321: Input device, 322: Display device.

Claims

1. A manufacturing inspection system that measures the product, which is the object to be inspected, by fluorescent fingerprint measurement in the product manufacturing process and outputs manufacturing inspection results, A spectrofluorometer for measuring the fluorescent fingerprint data of the object to be inspected, A fluorescence fingerprint data calculation unit analyzes the measured fluorescence fingerprint data using a predetermined calculation method, A pass criteria storage unit that stores pass criteria for the specifications of the product, which are determined from one or more of the design specification range defined in the design information of the product and the manufacturing specification range defined in the manufacturing information of the product, A manufacturing inspection system characterized by having a pass / fail determination unit that determines whether to pass or fail by comparing the results analyzed by the fluorescent fingerprint data calculation unit with the acceptance criteria.

2. The manufacturing inspection system according to claim 1, further comprising a pass / fail information storage unit that stores the pass / fail judgment result of the pass / fail judgment unit and the individual number of the inspection target obtained from an external source in association with each other.

3. The manufacturing inspection system according to claim 2, further comprising an output unit that outputs certification data including the individual number stored in the pass / fail information storage unit and the pass / fail judgment result corresponding to the individual number.

4. The manufacturing inspection system according to claim 3, wherein if the pass / fail determination unit determines that the product is unsatisfactory, the output unit displays the excitation and fluorescence wavelengths that form the basis for the cause of failure before analysis using the calculation method.

5. The manufacturing inspection system according to claim 1, wherein the manufacturing inspection result includes the component to be inspected and the proportion of the component.

6. The subject of the inspection is a resin material, The manufacturing inspection system according to claim 5, wherein the aforementioned components include recycled material and virgin material.

7. A manufacturing inspection method that measures the product, which is the object to be inspected, by fluorescent fingerprint measurement in the product manufacturing process and outputs a manufacturing inspection result, The fluorescence fingerprint data calculation unit analyzes the fluorescence fingerprint data of the object being inspected, measured by the spectrofluorometer, using a predetermined calculation method. The acceptance criteria storage unit stores acceptance criteria for the specifications of the product, which are formulated from one or more of the design specification ranges defined in the product's design information and the manufacturing specification ranges defined in the manufacturing information. A manufacturing inspection method characterized in that a pass / fail determination unit determines pass or fail by comparing the results analyzed by the fluorescent fingerprint data calculation unit with the pass criteria.

8. The manufacturing inspection method according to claim 7, wherein the pass / fail information storage unit stores the pass / fail judgment result of the pass / fail judgment unit and the individual number of the inspection target obtained from an external source in association with each other.

9. The manufacturing inspection method according to claim 8, wherein the output unit outputs certification data including the individual number stored in the pass / fail information storage unit and the pass / fail judgment result corresponding to the individual number.

10. The manufacturing inspection method according to claim 9, wherein if the pass / fail determination unit determines that the product is unsatisfactory, the output unit displays the excitation and fluorescence wavelengths that form the basis for the cause of failure before analysis using the calculation method.

11. The manufacturing inspection method according to claim 7, wherein the manufacturing inspection result includes the component to be inspected and the proportion of the component.

12. The subject of the inspection is a resin material, The manufacturing inspection method according to claim 11, wherein the aforementioned components include recycled material and virgin material.

13. A manufacturing inspection apparatus that measures the product, which is the object to be inspected, by fluorescent fingerprint measurement in the product manufacturing process and outputs a manufacturing inspection result, A fluorescence fingerprint data calculation unit analyzes the fluorescence fingerprint data of the subject to be inspected, measured by a spectrofluorometer, using a predetermined calculation method. A pass criteria storage unit that stores pass criteria for the specifications of the product, which are determined from one or more of the design specification range defined in the design information of the product and the manufacturing specification range defined in the manufacturing information of the product, A manufacturing inspection apparatus characterized by having a pass / fail determination unit that determines whether to pass or fail by comparing the results analyzed by the fluorescent fingerprint data calculation unit with the acceptance criteria.

14. The manufacturing inspection apparatus according to claim 13, further comprising a pass / fail information storage unit that stores the pass / fail judgment result of the pass / fail judgment unit and the individual number of the inspection target obtained from an external source in association with each other.

15. The manufacturing inspection apparatus according to claim 14, further comprising an output unit that outputs certification data including the individual number stored in the pass / fail information storage unit and the pass / fail judgment result corresponding to the individual number.

16. If the pass / fail determination unit determines that the product is unsatisfactory, the output unit displays the excitation and fluorescence wavelengths that form the basis for the cause of failure before analysis using the calculation method, as described in claim 15.

17. A program for causing a computer to execute the following manufacturing inspection procedure, which involves measuring the product, which is the object to be inspected, by fluorescence fingerprint measurement during the product manufacturing process and outputting the manufacturing inspection results, The above procedure is, The fluorescence fingerprint data calculation unit analyzes the fluorescence fingerprint data of the object being inspected, measured by the spectrofluorometer, using a predetermined calculation method. The acceptance criteria storage unit stores acceptance criteria for the specifications of the product, which are formulated from one or more of the design specification ranges defined in the product's design information and the manufacturing specification ranges defined in the manufacturing information. A program comprising a pass / fail determination unit that determines whether a result obtained by the fluorescent fingerprint data calculation unit is a pass or a fail by comparing it with the pass criteria.

18. The program according to claim 17, further comprising the pass / fail information storage unit storing the pass / fail judgment result of the pass / fail judgment unit in association with the individual number of the inspected object obtained from an external source.

19. The above procedure is, The program according to claim 18, further comprising outputting certification data including the individual number stored in the pass / fail information storage unit and the pass / fail judgment result corresponding to the individual number.

20. The above procedure is, The program according to claim 19, further comprising the output unit displaying the excitation and fluorescence wavelengths that form the basis for the failure before analysis using the calculation method, if the pass / fail determination unit determines that the program is unsuccessful.

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