Information processing device, information processing method, and program

Abstract

This information processing device comprises: an acquisition unit that acquires first spectrum information pertaining to a base material, second spectrum information pertaining to a resin layer, and a process condition; and a prediction unit that predicts, on the basis of the first spectrum information, the second spectrum information, and the process condition, information pertaining to material characteristics of the resin layer that will be achieved after a process is performed on a laminate in which the base material and the resin layer are laminated.

Description

Information Processing Apparatus, Information Processing Method, and Program

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program.

[0002] An insulating film that covers the surface of a printed circuit board and protects the circuit pattern, and a curable resin composition are widely used as materials for forming circuits on the board. When mounting components, it plays a role in preventing solder from adhering to unnecessary parts, and when forming circuits, it plays a role in preventing plating from adhering to unnecessary parts.

[0003] Such curable resin compositions require various material properties to maintain long-term reliability. For example, there are insulation reliability, pattern shape, plating resistance, flame retardancy, etc. In the case of a photosensitive resin composition for the pattern shape, after exposing a substrate with the photosensitive resin composition formed on the entire surface through a negative film or positive film with a circuit pattern, or by maskless exposure, the parts soluble in the developer are developed with the developer and cured by light or heat to obtain a fine pattern shape. In the case of a thermosetting resin composition, a pattern is formed on a substrate with the thermosetting resin composition formed on the entire surface using a CO ,

[0006] , ,

[0005] laser or the like, and a fine pattern can be formed by performing desmear treatment with a chemical solution or the like. Since such material properties such as the pattern shape affect various properties of the circuit board, a technique for predicting in advance the composition design of the curable resin composition and the material properties based on the process so as to obtain the target shape is required.

[0004] Japanese Patent Application Laid-Open No. 06-112293

[0005] In this regard, although the technique described in Patent Document 1 has devised a method for predicting the pattern shape after development, it does not consider a photosensitive resin composition containing a scatterer such as a solder resist or a thermosetting resin composition. Therefore, a new method is required for predicting the shape of a curable resin composition containing a scatterer (for example, a solder resist).

[0006] The present invention has been made in view of the above-mentioned problems, and aims to provide an information processing device, an information processing method, and a program that can predict material properties such as pattern shape and sensitivity to exposure when processes such as exposure development and drilling are performed on a curable resin composition containing a scattering material.

[0007] Furthermore, with such information processing equipment, it becomes possible to propose process conditions that are suitable for the desired pattern shape and material properties.

[0008] An information processing apparatus according to one aspect of the present invention includes an acquisition unit that acquires first spectral information of a substrate, second spectral information of a resin layer, process conditions, and, if necessary, third spectral information of a protective layer, and a prediction unit that predicts information regarding the material properties of the resin layer when a process is performed on a laminate formed by laminating the substrate and the resin layer, based on the first spectral information, the second spectral information, the process conditions, and, if necessary, the third spectral information of the protective layer.

[0009] The present invention aims to provide an information processing device, an information processing method, and a program that can predict the material properties of a resin layer when each process is executed.

[0010] This is a schematic diagram showing the system configuration of this embodiment. This is a schematic diagram showing the hardware and functional configuration of the information processing device of this embodiment. This is a schematic cross-sectional view of the laminate of this embodiment. This is a diagram showing examples of spectra in each component of the laminate. This is a cross-sectional view showing an example of information regarding the shape of the resin layer after development. This is a conceptual diagram showing an example of information regarding the sensitivity of the resin layer to exposure. This is a schematic diagram showing an example of a two-dimensional or three-dimensional image of the resin layer after development. This is a flowchart showing an example of the processing of this embodiment. This is a flowchart showing another example of the processing of this embodiment.

[0011] Hereinafter, embodiments of the present invention (hereinafter referred to as "this embodiment") will be described in detail with reference to the drawings, but the present invention is not limited thereto, and various modifications are possible without departing from its essence.

[0012] 1. Information Processing Device Figure 1A shows a schematic diagram illustrating the configuration of System 1, which is one embodiment of the present invention. As shown in Figure 1A, in one example of System 1, the server 100 (hereinafter also referred to as "information processing device 100") which is an information processing device and the user terminal 200 may be connected to each other via a network N such as the Internet.

[0013] The information processing device 100 is an information processing device implemented by a program, and may transmit processing results to the user terminal 200 in response to processing requests received from the user terminal 200 via the network N.

[0014] For example, the information processing device 100 may acquire first spectral information of the substrate, second spectral information of the resin layer, and various process conditions from the user terminal 200, and based on this information, transmit to the user terminal 200 prediction results regarding material properties such as the pattern shape of the resin layer when each process is performed on the laminate formed by stacking the substrate and the resin layer.

[0015] Furthermore, the information processing device 100 may acquire information from the user terminal 200 regarding the pattern shape of the resin layer after each desired process, and, through inverse analysis, transmit prediction results to the user terminal 200, including information regarding the substrate, resin layer, and each process condition necessary to achieve those patterns.

[0016] The user terminal 200 is an information processing device used by the user who performs the processing, and may be, for example, a computer, smartphone, tablet terminal, personal computer, etc.

[0017] Figure 1A shows a client / server system including an information processing device 100 and a user terminal 200. The following description will focus on a configuration in which the server functions as the information processing device 100. However, the system of this embodiment is not limited to this configuration, and the user terminal 200 may instead be equipped with the processing functions of the information processing device described later.

[0018] The hardware and functional configurations of the information processing device 100 will be described below with reference to Figure 1B, and then each control will be explained in detail in relation to the functional configuration of the information processing device 100.

[0019] As shown in Figure 1B, the information processing device 100 includes, for example, a processor 110, a communication interface 120, an input / output interface 130, a memory 140, storage 150, and one or more communication buses 160 for interconnecting these components.

[0020] The processor 110 executes processes, functions, or methods implemented by code or instructions contained in a program stored in the storage 150. The processor 110 may include, but is not limited to, one or more central processing units (CPUs), MPUs, GPUs, etc., and may implement each of the processes, functions, or methods disclosed in each embodiment by logic circuits (hardware) or dedicated circuits formed on an integrated circuit or the like.

[0021] As shown in Figure 1B, the processor 110 in this embodiment may be configured to function as an acquisition unit 111, a prediction unit 112, an output unit 113, and a proposal unit 114.

[0022] The communication interface 120 transmits and receives various types of data with other devices via the network N. This communication may be performed via wired or wireless connection, and any communication protocol may be used as long as communication between the devices is possible. For example, the communication interface 120 may be implemented as hardware such as a network adapter, various types of communication software, or a combination thereof.

[0023] The input / output interface 130 includes an input device for inputting various operations to the information processing device 100, and an output device for outputting processing results processed by the information processing device 100. For example, the input / output interface 130 includes information input devices such as a keyboard, mouse, and touch panel, and information output devices such as a display. The information processing device 100 may accept predetermined inputs or perform predetermined outputs by connecting an external input / output interface 130.

[0024] Memory 140 temporarily stores the program loaded from storage 150 and provides a workspace for the processor 110. Memory 140 also temporarily stores various data generated while the processor 110 is executing the program. Memory 140 may be a high-speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid-state memory, or a combination of these.

[0025] The storage 150 stores programs, various functional units, and various data. The storage 150 may be, for example, one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices, or a combination thereof. Another example of the storage 150 is one or more storage devices installed remotely from the processor 110.

[0026] The communication bus 160 is not particularly limited as long as it is a known dedicated communication channel for exchanging data, control information, etc., between hardware configurations.

[0027] Next, we will describe in detail each of the functional units of the information processing device of this embodiment.

[0028] The acquisition unit 111 acquires first spectral information of the substrate, second spectral information of the resin layer, and process conditions. When a protective layer is present on the resin layer of the laminate, the acquisition unit 111 may further acquire third spectral information of the protective layer. The acquisition unit 111 may also further acquire information regarding the pattern shape of the target resin layer.

[0029] The acquisition unit 111 may acquire various information from the user terminal 200 via the network N, or it may acquire various information from inputs to the input / output interface 130. It may also generate and acquire various process conditions in order to perform prediction processing by the proposal unit 114, which will be described later. The generation of these values ​​may be random, or the search space may be narrowed down efficiently using statistical methods such as Bayesian optimization.

[0030] The acquisition unit 111 may also record each acquired piece of information in the storage 150.

[0031] Figure 2A shows a cross-sectional view of the laminate in this embodiment. As shown in Figure 2A, the laminate 10 has a resin layer 12 on a base material 11, and may optionally have a protective layer 13 (light-transmitting in the case of photosensitive) on the resin layer 12.

[0032] Here, the substrate is not particularly limited, but examples include resin plates, glass plates, or metal plates. The first spectral information of such a substrate is not particularly limited, but examples include the reflectance spectrum shown in Figure 2B. As shown in Figure 2B, the reflectance spectrum may differ depending on the type of substrate. The first spectral information may also include absorbance spectra, total light transmittance spectra, or linear transmittance spectra.

[0033] The resin layer is not particularly limited as long as it contains a resin, but for example, in the case of a photosensitive resin composition, it may contain a photosensitive resin, a photopolymerization initiator, and other additives. In the case of a thermosetting resin composition, it may contain a thermosetting resin, a curing agent, and other additives. In particular, it is preferable that the resin layer contains a scattering material. The second spectral information of such a resin layer is not particularly limited, but for example, an absorbance spectrum as shown in Figure 2B can be cited. The second spectral information can also include a reflectance spectrum, a total light transmittance spectrum, a linear transmittance spectrum, an NMR spectrum, an IR spectrum, etc. As shown in Figure 2B, the absorbance spectrum, etc., may differ depending on the type of resin layer.

[0034] The resin layer may be a negative-type photosensitive resin composition in which the portion hardened by exposure remains during development, or a positive-type photosensitive resin composition in which the portion decomposed by exposure is removed during development. It may also be a thermosetting resin composition.

[0035] The protective layer is not particularly limited, but examples include polyesters such as polyethylene terephthalate and polyethylene naphthalate, polycarbonates, and polyacrylates. The third spectral information of such a protective layer is not particularly limited, but examples include the absorbance spectrum shown in Figure 2B. The third spectral information may also include the reflectance spectrum, the total light transmittance spectrum, or the direct transmittance spectrum. As shown in Figure 2B, the absorbance spectrum, etc., may differ depending on the type of protective layer.

[0036] Each spectrum may plot the reflectance, etc., for each wavelength in a predetermined wavelength range, such as 200 to 800 nm, or it may be the reflectance, etc., for a specific wavelength. Preferably, each spectrum is multidimensional information containing two or more values, and may be, for example, reflectance, etc., for two or more specific wavelengths. Furthermore, each spectrum may include information about thickness. For example, absorbance may be measured according to thickness, or it may be normalized per unit thickness (μm).

[0037] Furthermore, these spectra may be obtained by applying various data processing techniques to reduce noise in the spectral data, clarify trends, and extract characteristic peaks. Such techniques are not particularly limited, but examples include the Savitzky-Golay method, moving average method, and principal component analysis.

[0038] When the resin layer is made of a photosensitive resin composition, process conditions include, for example, exposure conditions, development conditions, and post-development curing conditions. Exposure conditions may include the type of exposure light source, illuminance spectrum, irradiation time, positional relationship with the mask, defocus information, and other information that affects exposure. The illuminance spectrum of the exposure light source affects the reaction efficiency of the resin layer, while the irradiation time and irradiation angle can affect the accuracy and uniformity of the exposure pattern. Furthermore, exposure conditions may include information regarding the illuminance spectrum of the exposure light source as shown in Figure 2B.

[0039] Among the material properties, the patterning characteristics of a resin layer made of a photosensitive resin composition, such as the pattern shape and exposure sensitivity, are strongly influenced by the photoreaction of the resin layer due to exposure. The information processing device of this embodiment predicts the patterning characteristics of the resin layer based not only on the second spectral information of the resin layer but also on the first spectral information of the substrate. Therefore, it becomes possible to consider the effects of reflection by the substrate, etc., and to predict the patterning characteristics of the resin layer with high accuracy. Furthermore, by predicting the patterning characteristics of the resin layer based on the exposure conditions, especially the illuminance spectrum of the exposure light source, it becomes possible to consider the interaction between the exposure conditions and the first spectral information of the substrate and the second spectral information of the resin layer, thus enabling even more accurate prediction of the patterning characteristics of the resin layer.

[0040] Development conditions may include, in addition to the developer composition, the temperature and concentration of the developer, the development time, the rinsing time, and, if the development method is a spray method, the pressure of the spray used to spray the developer onto the object, as well as other information that affects development. The developer composition and temperature affect the development speed, and spray pressure, etc., can affect the development speed in terms of the efficiency of developer exchange near the object, and may also affect the mechanical removal performance. Post-development curing conditions include the exposure conditions mentioned above and the thermosetting conditions described later.

[0041] When the resin layer consists of a thermosetting resin composition, process conditions include, for example, laser wavelength, laser power, desmear conditions, and thermosetting conditions. Desmear conditions include, for example, CO ２ These are process conditions for removing residual components (smear) that could not be completely removed from via holes after forming them by irradiating them with a laser or the like. Examples include the composition of the chemical solution used in wet desmear treatment (for example, a chemical solution consisting of permanganates such as sodium permanganate or potassium permanganate and a caustic composition) and the processing conditions for plasma treatment used in dry desmear treatment. Examples of thermosetting conditions include heating temperature and heating time.

[0042] The prediction unit 112 predicts information regarding the material properties of the resin layer when each process treatment is performed on the laminate based on the first spectral information, the second spectral information, the third spectral information of the protective layer if there is a protective layer as needed, and each process condition. More specifically, the prediction unit 112 may input the first spectral information, the second spectral information, and the process conditions into a model and output information regarding the material properties of the resin layer.

[0043] Furthermore, the laminate may or may not have a protective layer, and the exposure of the resin layer may be performed through a protective layer such as polyethylene terephthalate or may be performed without a protective layer. When the laminate has a protective layer, the prediction unit 112 may further predict information regarding the material properties of the resin layer in consideration of the third spectral information in addition to the first spectral information, the second spectral information, and the process conditions.

[0044] Also, the prediction unit 112 may record each predicted information in the storage 150.

[0045] The model used by the prediction unit 112 is not particularly limited. For example, a regression model that takes the first spectral information, the second spectral information, the process conditions, and, if necessary, the third spectral information as inputs and outputs information regarding the material properties of the resin layer can be used. The regression model can be created by machine learning in advance using learning data in which the first spectral information, the second spectral information, the third spectral information, the process conditions, and the information regarding the material properties of the resin layer are associated with each other.

[0046] The regression analysis method is not particularly limited. For example, linear analysis methods such as partial least squares method (PLS), Ridge regression, LASSO (Least Absolute Shrinkage and Selection Operator), Elastic Net, linear support vector regression (Linear SVR), Gaussian process regression (GPR), etc.; non-linear analysis methods such as non-linear support vector regression (Non-Linear SVR), random forest, gradient boosting (XGBoost, Light-GBM), application of different kernel functions in Gaussian process regression (GPR), etc. can be mentioned.

[0047] Also, at this time, for the spectrum, a data processing method can be applied to reduce the noise of the spectral data, clarify the trend, extract characteristic peaks, and use them for learning.

[0048] The information on the material properties of the resin layer predicted by the prediction unit 112 is not particularly limited, and examples include information on the pattern shape or curing reaction rate of the resin layer, and when the resin layer is made of a photosensitive resin composition, information on the exposure sensitivity of the resin layer, etc.

[0049] The curing reaction rate can be calculated using a conventionally known method. For example, nuclear magnetic resonance analysis (NMR), Fourier transform infrared spectroscopy (FT-IR), differential scanning calorimetry analysis (DSC), etc. can be mentioned.

[0050] When the resin layer is made of a photosensitive resin composition, the pattern shape of the resin layer includes the pattern shape of the resin layer after exposure, development, and post-development curing. When the resin layer is made of a thermosetting resin composition, the pattern shape of the resin layer includes the pattern shape of the resin layer after drilling processing such as laser processing and desmear treatment, etc.

[0051] The information regarding the pattern shape of the resin layer is not particularly limited as long as it shows the shape of the resin composed of the parts remaining and removed by the process. The information regarding the pattern shape of the resin layer may be information that allows for the three-dimensional rendering of the pattern shape of the resin layer, or it may be information that allows for the two-dimensional rendering of the parts remaining and removed by the process in any cross-section obtained by cutting the resin layer in the thickness direction.

[0052] Information regarding the pattern shape of such a resin layer may include, for example, in-plane dimensions corresponding to any position in the thickness direction of the resin layer with respect to the portion removed by the process. Figure 2C shows an example in which the portion removed by the exposure and development process is shown in terms of in-plane dimensions at arbitrary thickness positions (Top, 2 / 5, Middle, 4 / 5, Bottom). By showing information about the shape of the resin layer in terms of partial dimensions in this way, for example, detailed three-dimensional data to completely reproduce the shape is not required, thus reducing the amount of data and potentially improving processing efficiency. Furthermore, by focusing on the in-plane dimensions at specific thickness positions, it becomes possible to efficiently grasp the removal characteristics and shape change trends of the process.

[0053] Furthermore, to create the model used by the prediction unit 112, measured dimensional data, as shown in Figure 2C, can be used as training data for information regarding the pattern shape of the resin layer.

[0054] Information regarding the exposure sensitivity of the resin layer includes, for example, gloss sensitivity and residual sensitivity. Gloss sensitivity and residual sensitivity will be explained below using the diagrams. Figure 2D shows a step tablet and a top view of the resin layer after the step tablet is placed on the resin layer, the entire surface is exposed to a predetermined exposure level, and then developed and cured. A step tablet is a test pattern used to form a pattern with different exposure levels (steps). For example, by placing a step tablet on the resin layer, exposing the entire surface to a predetermined exposure level, and then performing a predetermined development process, results for each exposure level (step) can be obtained. Note that for gloss sensitivity and residual sensitivity, a higher number of steps indicates higher sensitivity to exposure.

[0055] The lower part of Figure 2D shows the number of steps in the step tablet on the horizontal axis and the film thickness after development corresponding to each step number when development is performed under predetermined development conditions after full exposure via the step tablet on the vertical axis. As shown in the lower part of Figure 2D, it is possible to identify the minimum exposure amount (maximum step number) at which the film thickness does not substantially decrease due to the development process (hereinafter also referred to as "gloss sensitivity") and the maximum exposure amount (minimum step number) at which the film is substantially completely removed by the development process (hereinafter also referred to as "residual sensitivity").

[0056] Depending on the number of steps, if the film thickness does not decrease due to development, specifically, it means that if the film thickness before development is set to 100%, then 95% or more of the coating thickness remains after development. Furthermore, if the film is substantially removed by development, specifically, it means that if the coating thickness before development is set to 100%, then 5% or less of the coating thickness remains after development. The method for measuring the film thickness in this embodiment is not particularly limited, but for example, it may be measured as the difference between the measured value obtained as the total film thickness and the measured value obtained as the substrate thickness, in accordance with JIS K 5600-1-7:2014.

[0057] Furthermore, in creating the model used by the prediction unit 112, measured gloss sensitivity and residual sensitivity, as shown in Figure 2D, can be used as learning data for information regarding the exposure sensitivity of the resin layer.

[0058] The output unit 113 outputs a two-dimensional or three-dimensional image of the developed resin layer based on the information regarding the pattern shape of the resin layer predicted by the prediction unit 112. The two-dimensional image may be a cross-sectional image in the thickness direction of the resin layer or an image in the in-plane direction. An example of a two-dimensional image is shown on top of Figure 2E, and an example of a three-dimensional image is shown below Figure 2E. If the information regarding the pattern shape of the resin layer predicted by the prediction unit 112 is an in-plane dimension at a specific thickness position, the output unit 113 may apply algorithms such as linear interpolation or spline interpolation to generate a continuous two-dimensional or three-dimensional contour.

[0059] The proposal unit 114 outputs information on process conditions corresponding to the pattern shape information predicted by the prediction unit 112 when the information on the resin layer pattern shape predicted by the prediction unit 112 satisfies the information on the target resin layer pattern shape acquired by the acquisition unit 111. This makes it possible to propose information on process conditions necessary to achieve the target pattern shape. As a result, process conditions can be optimized efficiently, and unnecessary trial and error can be reduced.

[0060] For example, the acquisition unit 111 may arbitrarily generate multiple process conditions, and the prediction unit 112, along with the first spectral information and the second spectral information, predicts information regarding the pattern shape of the resin layer corresponding to them based on the prediction model. The proposal unit 114 may then identify process conditions, etc., that reduce the difference between the predicted resin layer pattern shape and the target resin layer pattern shape to a certain value or less, and propose such process conditions, etc.

[0061] Figure 3A shows an example of a flowchart of the process in this embodiment.

[0062] First, in step S11, the acquisition unit 111 acquires first spectral information of the substrate, second spectral information of the resin layer, and process conditions, and may also acquire third spectral information of the protective layer if necessary.

[0063] In step S12, the prediction unit 112 predicts the material properties of the resin layer when the process is executed, based on the various information acquired in step S11. The material properties may include, for example, information regarding the pattern shape of the resin layer and / or information regarding the exposure sensitivity of the resin layer.

[0064] Then, in step S13, the output unit 113 may output a two-dimensional image or a three-dimensional image of the resin layer after development, based on the information regarding the pattern shape of the resin layer predicted in step S12.

[0065] Figure 3B shows an example of a flowchart of the process in this embodiment.

[0066] First, in step S21, the acquisition unit 111 acquires information regarding the pattern shape of the resin layer desired by the user, first spectral information of the substrate, second spectral information of the resin layer, process conditions, and, if necessary, third spectral information of the protective layer. The acquired information may be input by the user, and the process conditions may be acquired from the conditions generated in step S22.

[0067] In step S22, process conditions are generated by a predetermined algorithm, and the acquisition unit 111 acquires the generated process conditions.

[0068] In step S23, the prediction unit 112 predicts information regarding the pattern shape of the resin layer when the operation is performed, based on the various information acquired by the acquisition unit 111.

[0069] In steps S24 and S25, if the difference between the information regarding the resin layer pattern shape predicted by the prediction unit 112 in step S23 and the information regarding the resin layer pattern shape desired by the user obtained in step S21 is less than or equal to a certain value, the suggestion unit 114 suggests information regarding the process conditions used for that prediction.

[0070] On the other hand, if the difference between the resin layer pattern shape predicted by the prediction unit 112 and the resin layer pattern shape desired by the user obtained in step S21 is not below a certain value, the process may return to step S22, and the acquisition unit 111 may regenerate information regarding the process conditions used for prediction, and steps S23 and S24 may be repeated.

[0071] 2. Information Processing Method The information processing method of this embodiment includes the steps of: an information processing device acquiring first spectral information of a substrate, second spectral information of a resin layer, and process conditions; and predicting the material properties when a process is performed on a laminate formed by laminating the substrate and the resin layer, based on the first spectral information, the second spectral information, and the process conditions.

[0072] The specific details of the method in this embodiment are described in the control processing section above, so a detailed explanation is omitted here.

[0073] 3. Method for Manufacturing Resin Patterns The method for manufacturing resin patterns in this embodiment includes an exposure step of exposing a resin layer made of a photosensitive resin composition laminated on a substrate in a predetermined pattern shape, a developing step of developing the resin layer, and a post-development curing step of curing the resin layer. The exposure step is a step of exposing the resin layer under exposure conditions selected based on information regarding the pattern shape of the resin layer predicted by the prediction unit. Specifically, the exposure step is, for example, a step of exposing the resin layer laminated on the substrate based on exposure conditions proposed by the proposal unit 114 of the information processing device in this embodiment.

[0074] Furthermore, a method for manufacturing a resin pattern according to another embodiment includes a thermosetting step of heating and curing a resin layer made of a thermosetting resin composition laminated on a substrate, and a processing step of drilling holes in the resin layer, wherein the processing step is a processing step of drilling holes under process conditions selected based on information regarding the pattern shape of the resin layer predicted by the prediction unit. Specifically, the thermosetting step is, for example, a step of thermosetting in a hot air circulating drying oven at a predetermined temperature, or thermosetting with a hot plate press, and the processing step is, for example, a drill or CO ２ This process involves irradiating a via hole with a laser or the like to form a via hole, and then removing any remaining components (smear) in the via hole using a chemical solution consisting of a permanganate such as sodium permanganate or potassium permanganate and a caustic composition. More specifically, the processing step is a process in which a resin layer laminated on a substrate is drilled with a laser or the like based on the process conditions proposed by the proposal unit 114 of the information processing device of this embodiment.

[0075] 3. Program In the program of this embodiment, the information processing device is made to perform the steps of: acquiring first spectral information of the substrate, second spectral information of the resin layer, and process conditions; and predicting the material properties of the resin layer when a process is performed on a laminate formed by laminating the substrate and the resin layer, based on the first spectral information, the second spectral information, and the process conditions.

[0076] The program may be recorded on a readable recording medium. The specific details of the processing performed by the program in this embodiment are described in the control processing section above, so a detailed explanation is omitted here.

[0077] 1...System, 10...Laminate, 11...Substrate, 12...Resin layer, 13...Protective layer, 100...Information processing device, 110...Processor, 111...Acquisition unit, 112...Prediction unit, 113...Output unit, 114...Proposal unit, 120...Communication interface, 130...Input / output interface, 140...Memory, 150...Storage, 160...Communication bus, 200...User terminal, N...Network

Claims

1. An information processing device comprising: an acquisition unit that acquires first spectral information of a substrate, second spectral information of a resin layer, and process conditions; and a prediction unit that predicts information regarding the material properties of the resin layer when a process is performed on a laminate formed by laminating the substrate and the resin layer, based on the first spectral information, the second spectral information, and the process conditions.

2. The information processing apparatus according to claim 1, wherein the laminate has a light-transmitting protective layer on a resin layer, the acquisition unit further acquires third spectral information of the protective layer, and the prediction unit predicts information regarding the material properties based on the first spectral information, the second spectral information, the third spectral information, and the process conditions.

3. The information processing apparatus according to claim 1, wherein the information relating to the material properties of the resin layer includes information relating to the pattern shape of the resin layer.

4. The information processing apparatus according to claim 3, wherein the acquisition unit acquires, as the process conditions, at least one selected from exposure conditions, development conditions, and post-development curing conditions, or at least one selected from thermosetting conditions, drilling conditions, and desmear conditions.

5. The information processing apparatus according to claim 3, wherein the information relating to the pattern shape of the resin layer includes in-plane dimensions corresponding to any position in the thickness direction of the resin layer with respect to the portion removed by the process.

6. The information processing apparatus according to claim 3, further comprising an output unit that outputs a two-dimensional or three-dimensional image of the resin layer after processing, based on information regarding the pattern shape of the resin layer predicted by the prediction unit.

7. The information processing apparatus according to claim 1, wherein the resin layer is a resin layer made of a photosensitive resin composition, and the information relating to the material properties of the resin layer includes information relating to the exposure sensitivity of the resin layer.

8. The information processing apparatus according to claim 7, wherein the information relating to the exposure sensitivity of the resin layer includes information relating to the minimum exposure amount or curing rate at which the film thickness does not decrease by development, and / or information relating to the maximum exposure amount or curing rate at which the film is substantially removed by development, when the resin layer is exposed with stepwise exposure amounts or cured to a predetermined degree by said exposure and then developed under predetermined development conditions.

9. The information processing apparatus according to claim 3, wherein the acquisition unit further acquires information relating to the pattern shape of a target resin layer, and when the difference between the information relating to the pattern shape of the resin layer predicted by the prediction unit and the information relating to the pattern shape of the target resin layer is less than or equal to a certain value, the output unit further outputs information relating to process conditions corresponding to the information relating to the pattern shape of the resin layer predicted by the prediction unit.

10. A method for manufacturing a resin pattern, comprising: an exposure step of exposing a resin layer made of a photosensitive resin composition laminated on a substrate in a predetermined pattern shape; a developing step of developing the resin layer after exposure; and a post-development curing step of curing the resin layer after development, wherein the exposure step is a step of exposing the resin layer under process conditions selected based on information regarding the pattern shape of the resin layer predicted by the prediction unit of the information processing device described in claim 3.

11. A method for manufacturing a resin pattern, comprising: a thermosetting step of heating and curing a resin layer made of a thermosetting resin composition laminated on a substrate; and a processing step of drilling holes in the resin layer after thermosetting, wherein the processing step is a step of drilling holes in the resin layer under process conditions selected based on information regarding the pattern shape of the resin layer predicted by the prediction unit of the information processing device described in claim 3.

12. An information processing method comprising: an information processing device that performs the steps of: acquiring first spectral information of a substrate, second spectral information of a resin layer, and process conditions; and predicting information regarding the material properties of the resin layer after processing, when a process is performed on a laminate formed by laminating the substrate and the resin layer, based on the first spectral information, the second spectral information, and the process conditions.

13. A program that causes an information processing device to perform the steps of: acquiring first spectral information of a substrate, second spectral information of a resin layer, and process conditions; and predicting information regarding the material properties of the resin layer after processing, when a process is performed on a laminate formed by laminating the substrate and the resin layer, based on the first spectral information, the second spectral information, and the process conditions.

Images