LASER IRRADIATION APPARATUS, INFORMATION PROCESSING METHOD, PROGRAM, AND METHOD FOR GENERATING LEARNING MODEL

Abstract

To provide a laser irradiation device and the like that on the basis of an operation parameter of a laser annealing device, estimate quality information on a product manufactured by the laser annealing device.SOLUTION: A laser irradiation device comprises: a laser beam source for emitting a laser beam; and a control unit for performing control on irradiating a substrate with the laser beam. The control unit acquires an operation parameter including a detection value from a detection unit provided at the laser irradiation device; derives expected quality information by inputting the operation parameter to a learning model that outputs the expected quality information on a product including the substrate irradiated with the laser beam when the operation parameter is input; and outputs the derived expected quality information in association with the acquired operation parameter.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a laser irradiation device, an information processing method, a program, and a method for generating a learning model. [Background technology]

[0002] A laser annealing device for forming a polycrystalline silicon thin film is known (for example, Patent Document 1). The laser annealing device described in Patent Document 1 includes a waveform shaping device that shapes the waveform of a laser light pulse, and the laser light shaped into a line by the waveform shaping device is irradiated onto an amorphous silicon film to form a polycrystalline silicon thin film. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2012-15545 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the laser annealing apparatus of Patent Document 1 does not take into consideration the estimation of quality information (predicted quality information) of a product manufactured by the laser annealing apparatus based on the operation parameters of the laser annealing apparatus.

[0005] The present invention has been made in consideration of the above circumstances, and aims to provide a laser irradiation device or the like that estimates quality information (predicted quality information) of a product manufactured by a laser annealing device based on the operating parameters of the laser annealing device. [Means for solving the problem]

[0006] The laser irradiation device of this embodiment is a laser irradiation device equipped with a laser light source that emits laser light and a control unit that controls the irradiation of a substrate with the laser light, and the control unit acquires operating parameters including detection values ​​from a detection unit provided in the laser irradiation device, derives predicted quality information by inputting the acquired operating parameters into a learning model that outputs predicted quality information of a product including a substrate irradiated with laser light when the operating parameters are input, and outputs the derived predicted quality information in association with the acquired operating parameters.

[0007] The information processing method of the present embodiment causes a computer to execute a process of acquiring operating parameters including detection values ​​from a detection unit provided in a laser irradiation device, deriving predicted quality information by inputting the acquired operating parameters into a learning model that outputs predicted quality information of a product including a substrate irradiated with laser light when the operating parameters are input, and outputting the derived predicted quality information in association with the acquired operating parameters.

[0008] The program of this embodiment causes a computer to acquire operating parameters including detection values ​​from a detection unit provided in a laser irradiation apparatus, derive predicted quality information by inputting the acquired operating parameters into a learning model that outputs predicted quality information of a product including a substrate irradiated with laser light when the operating parameters are input, and execute a process of outputting the derived predicted quality information in association with the acquired operating parameters.

[0009] The method for generating a learning model in this embodiment acquires operating parameters including detection values ​​from a detection unit provided in the laser irradiation device, acquires quality information of a product including a substrate processed by the laser irradiation device controlled using the operating parameters, and uses training data including question data consisting of the acquired operating parameters and answer data consisting of the acquired quality information to generate a learning model that outputs quality information of a product including a substrate processed by the laser irradiation device when the operating parameters are input. Effect of the Invention

[0010] According to the present invention, it is possible to provide a laser irradiation device or the like that estimates quality information (predicted quality information) of a product manufactured by a laser annealing device based on the operation parameters of the laser annealing device. [Brief description of the drawings]

[0011] [Figure 1] 1 is a diagram showing an example of a system configuration including a laser annealing device according to a first embodiment. [Diagram 2] FIG. 1 is a diagram showing an example of the configuration of a laser annealing apparatus. [Diagram 3] FIG. 2 is a diagram illustrating an example of the configuration of a control device included in the laser annealing apparatus. [Figure 4] FIG. 1 is an explanatory diagram illustrating an example of a learning model. [Diagram 5] 13 is a flowchart showing an example of a processing procedure of a control unit (when learning a learning model). [Figure 6] 13 is a flowchart showing an example of a processing procedure of the control unit (when a learning model is in operation). [Figure 7] FIG. 13 is a diagram illustrating an example of a management screen of the laser annealing apparatus. [Figure 8] 10 is a flowchart showing an example of a processing procedure (deriving an operating parameter) of a control unit according to the second embodiment. [Figure 9] 10A to 10C are cross-sectional views showing steps of a method for manufacturing a semiconductor device according to another embodiment (a method for manufacturing a semiconductor device). [Figure 10] 10A to 10C are cross-sectional views showing steps of a method for manufacturing a semiconductor device according to another embodiment (a method for manufacturing a semiconductor device). [Figure 11] 10A to 10C are cross-sectional views showing steps of a method for manufacturing a semiconductor device according to another embodiment (a method for manufacturing a semiconductor device). [Figure 12] 10A to 10C are cross-sectional views showing steps of a method for manufacturing a semiconductor device according to another embodiment (a method for manufacturing a semiconductor device). [Figure 13]10A to 10C are cross-sectional views showing steps of a method for manufacturing a semiconductor device according to another embodiment (a method for manufacturing a semiconductor device).

[0012] (Embodiment 1) Hereinafter, an embodiment of the present invention will be described. Fig. 1 is a diagram showing an example of a system configuration including a laser annealing apparatus according to embodiment 1. The laser annealing apparatus 1 (laser irradiation apparatus) is, for example, an excimer laser annealing (ELA) apparatus that forms a low temperature polysilicon (LTPS) film.

[0013] The laser annealing apparatus 1 is installed in a manufacturing factory that manufactures semiconductor substrates (substrates 8) such as glass substrates on which a polycrystalline silicon film is formed, and the manufactured substrates 8 are shipped to a final product factory that manufactures final products incorporating the substrates 8. A product server SS that stores and manages quality information of the final products is installed in the final product factory.

[0014] The control device 9 included in the laser annealing apparatus 1 acquires quality information of the final product from the product server SS via an external network GN such as the Internet. In this way, the laser annealing apparatus 1 including the control device 9 and the multiple product servers SS communicably connected via the external network GN constitute a quality information acquisition system that acquires quality information of the final product. The product server SS and the laser annealing apparatus 1 are not limited to being located at different bases, and may be installed at the same base (final product factory). In this case, the product server SS and the laser annealing apparatus 1 are connected by a LAN (intra-factory network) of the final product factory.

[0015] The quality information includes the yield rate, defect occurrence frequency, defect position information, evaluation information, and the like of the substrate 8 incorporated into the final product. The control device 9 uses the acquired quality information of the final product to perform various processes such as generating a learning model 921 described below, or estimating quality information (predicted quality information) of the final product at the production stage of the substrate 8 using the learning model 921. When the management standards of the quality information of the final product are different for each of multiple final product factories, the control device 9 may generate and operate a learning model 921 for each of these final product factories (shipping destinations of the substrate 8). Alternatively, the control device 9 may use information obtained by normalizing, standardizing, or averaging quality information acquired from multiple final product factories to generate a learning model 921 that can be generally applied to each of these final product factories.

[0016] Fig. 2 is a diagram showing a configuration example of a laser annealing apparatus. Fig. 3 is a diagram showing a configuration example of a control device 9 included in the laser annealing apparatus. The laser annealing apparatus 1 irradiates a silicon film formed on a substrate 8 with laser light. This makes it possible to convert an amorphous silicon film (amorphous silicon film: a-Si film) into a polycrystalline silicon film (polysilicon film: p-Si film). The substrate 8 is a semiconductor substrate.

[0017] As illustrated in the present embodiment, in an XYZ three-dimensional Cartesian coordinate system, the Z direction is the vertical direction, which is a direction perpendicular to the substrate 8. The XY plane is a plane parallel to the surface of the substrate 8 on which the silicon film is formed. For example, the X direction is the longitudinal direction of the rectangular substrate 8, and the Y direction is the lateral direction of the substrate 8. When a Θ-axis stage 71 that can rotate from 0° to 90° about the Z axis is used, the X direction can be the lateral direction of the substrate 8, and the Y direction can be the longitudinal direction of the substrate 8.

[0018] The laser annealing apparatus 1 includes an annealing optical system 11, a laser irradiation chamber 7, and a control device 9. The laser irradiation chamber 7 houses a base 72 and a stage 71 arranged on the base 72. In the laser annealing apparatus 1, a silicon film 201 is irradiated with laser light while the stage 71 transports the substrate 8 in the +X direction. Furthermore, the apparatus includes a biplanar phototube 62, an OED sensor 63, an unevenness monitor 64, and a profiler camera 66 as detection units that detect information related to the emitted laser light.

[0019] The annealing optical system 11 is an optical system for generating laser light for crystallizing the amorphous silicon film formed on the substrate 8 and converting it into a polysilicon film, and irradiating the amorphous silicon film with the laser light. The annealing optical system 11 includes a laser light source 2, an attenuator 3, a polarization ratio control unit 4, a beam shaping optical system 5, an epi-illumination mirror 61, and a projection lens 65, and emits a line-shaped laser light.

[0020] The laser light source 2 is a laser generating device that generates a pulsed laser light as a laser light to be irradiated onto the amorphous silicon film (object to be processed). The generated laser light is a laser light for crystallizing the non-crystalline film on the substrate 8 to form a crystallized film, and is, for example, a gas laser light such as an excimer laser light having a central wavelength of 308 nm. Alternatively, the gas laser light is not limited to an excimer laser light, and may be another gas laser such as a Co2 laser.

[0021] In the laser light source 2, a gas such as xenon is sealed in a chamber, and two resonator mirrors are arranged to face each other with the gas in between. One resonator mirror is a total reflection mirror that reflects all light, and the other resonator mirror is a partial reflection mirror that transmits some light. Gas light excited by the gas is repeatedly reflected between the resonator mirrors, and the amplified light is emitted from the resonator mirror as laser light. The laser light source 2 repeatedly emits pulsed laser light at a frequency of, for example, 500 Hz to 600 Hz. The laser light source 2 emits the laser light toward the attenuator 3.

[0022] The attenuator 3 attenuates the incident laser light and adjusts it to a predetermined energy density. These attenuators have a transmittance that indicates the ratio of the emitted laser light to the incident laser light as a characteristic, and the transmittance is configured to be variable based on a signal from the control device 9. The attenuator 3 is provided in the middle of the optical path from the laser light source 2 to the beam shaping optical system 5. The attenuator 3 attenuates the laser light emitted by the laser light source 2 according to the transmittance.

[0023] The energy density (E) emitted from the attenuator 3 is a value (E=E0×T) obtained by multiplying the energy density (E0) of the laser light emitted from the laser light source 2 by the transmittance (T) of the attenuator 3. Although details will be described later, the control device 9 specifies (derives) and changes the transmittance of the attenuator 3 so that the energy density emitted from the attenuator 3 becomes an optimal energy density.

[0024] The polarization ratio control unit 4 is disposed on the output side of the attenuator 3. The polarization ratio control unit 4 is composed of, for example, a half-wave plate (λ / 2 plate) and a polarizing beam splitter, and changes the polarization ratio between the P polarization and the S polarization of the incident laser light. That is, the polarization ratio of the laser light output from the attenuator 3 is changed by the polarization ratio control unit 4. The polarization ratio control unit 4 is configured to change (variably) the polarization ratio based on a control signal output from the control device 9.

[0025] When the transmittance of the attenuator 3 is changed, the polarization ratio of the laser light emitted from the attenuator 3 is changed according to the transmittance. In response to this, the control device 9 changes the polarization ratio of the polarization ratio control unit 4 according to the changed transmittance, thereby controlling the polarization ratio of the laser light emitted from the polarization ratio control unit 4 to be constant.

[0026] When changing the polarization ratio of the polarization ratio control unit 4, the control device 9 may refer to information (polarization ratio table) stored in the storage unit 92 of the control device 9 in table format, for example, to specify (derive) the polarization ratio according to the transmittance. In the polarization ratio table, the polarization ratios corresponding to each transmittance are defined.

[0027] The laser light emitted from the polarization ratio control unit 4 is incident on the beam shaping optical system 5, which shapes the incident laser light to generate laser light having a beam shape suitable for irradiating a silicon film. The beam shaping optical system 5 generates a line beam that is linear along the Y direction.

[0028] The beam shaping optical system 6 splits one beam into multiple beams (multiple line beams aligned in the Z direction) using, for example, a homogenizer made up of a lens array. After splitting into multiple beams, the multiple beams can be combined using a condenser lens to form a line beam. The beam shaping optical system 6 emits the generated (shaped) linear laser light to the epi-illumination mirror 61.

[0029] The epi-mirror 61 is a rectangular reflection mirror extending in the Y direction, and reflects the laser light, which is a plurality of line beams generated by the beam shaping optical system 6. The epi-mirror 61 is, for example, a dichroic mirror, and is a partial reflection mirror that transmits a portion of the light. The epi-mirror 61 reflects the line-shaped laser light to generate reflected light, and transmits a portion of the line-shaped laser light to generate transmitted light. The epi-mirror 61 irradiates the reflected laser light onto the silicon film of the substrate 8, and emits the transmitted laser light to a pulse measuring device, such as a biplanar phototube.

[0030] The projection lens 65 is disposed above the substrate 8. The projection lens 65 has a plurality of lenses for projecting the laser light onto the substrate 8, i.e., onto the silicon film. The projection lens 65 focuses the laser light onto the substrate 8. On the substrate 8, the laser light forms a linear irradiation area along the Y direction. That is, on the substrate 8, the laser light is a line beam with the Y direction as the longitudinal direction. In addition, the silicon film is irradiated with the laser light while the substrate 8 is being transported in the +X direction. This allows the laser light to be irradiated onto a belt-shaped area whose width is the length of the irradiation area in the Y direction.

[0031] The line beam-like laser light irradiated to the epi-illumination mirror 61 has a beam shape with a widened short axis width, that is, the short axis width is somewhat widened and the shape is distorted after being emitted from the condenser lens. The laser light reflected by the epi-illumination mirror 61 passes through the projection lens 65 and is shaped into a line beam-like laser light with a short axis width of about 1 / 5.

[0032] The biplanar phototube 62 is provided at an end of the annealing optical system 11 adjacent to the beam shaping optical system 6, and detects the pulse waveform of the laser light emitted from the laser light source 2 based on the transmitted light that has passed through the epi-illumination mirror 61. The biplanar phototube 62 outputs (transmits) the detected pulse waveform to the control device 9.

[0033] The OED sensor 63 includes an optical sensor, and detects reflected light (light reflected by the substrate 8) of light emitted from a light source (another light source) separate from the laser light source 2, to obtain information about the crystal surface on the substrate 8. The OED sensor 63 outputs (transmits as a signal) the brightness (detection value) of the detected reflected light to the control device 9.

[0034] Mura monitor 64 includes a line camera, which captures an image of a region of interest on substrate 8 irradiated with laser light, detects the average luminance of the region of interest contained in the captured image, and acquires information about scattered light of the surface shape of substrate 8. Mura monitor 64 outputs (transmits as a signal) the detected average luminance (detection value) of substrate 8 (region of interest) to control device 9.

[0035] The profiler camera 66 is a sensor (line beam sensor) that detects information about the shape of the laser light shaped into a line beam by the projection lens 65, and is, for example, a beam profiler. The profiler camera 66 is provided, for example, on the side of the stage 71, and is aligned so that the upper surface of the profiler camera 66 and the substrate 8 placed on the stage 71 are at the same height. The laser light shaped into a line beam by the annealing optical system 11 is irradiated onto the upper surface of the profiler camera 66. The profiler camera 66 includes an imaging unit such as a CMOS camera, and obtains information (data) about the shape of the laser light, such as an image (captured image), by capturing an image of the laser light shaped into a line beam by the imaging unit. The profiler camera 66 may detect, as information about the shape of the laser light shaped into a line beam, information about the axial width of the short axis shape and the long axis shape of the rectangular line beam, distortion or depression of the axis, inclination when the line beam is viewed stereoscopically, and angle or curvature between adjacent surfaces, for example. The profiler camera 66 may further detect information regarding the shape of the raw beam before it is shaped into a line beam. In addition to the profiler camera 66 according to this embodiment, a line beam sensor for acquiring information regarding the shape of the laser beam may be provided, for example, near the biplanar phototube 62, with the Y-axis direction different from that of the biplanar phototube 62.

[0036] The control device 9 is an information processing device such as a personal computer or a server device that performs overall or integrated control or management of the laser annealing apparatus 1. The control device 9 includes a control unit 91, a storage unit 92, a communication unit 93, and an input / output I / F 94, and is communicatively connected to a control device (another control device) that controls the laser light source 2 or each optical system in the annealing optical system 11 via the communication unit 93 or the input / output I / F 94. The control device 9 is communicatively connected to various measuring devices such as a pulse measuring instrument and a photodetector included in the laser annealing apparatus 1, and performs various controls on the laser light source 2 or the annealing optical system 11 based on measurement data output from these various measuring devices.

[0037] The control unit 91 has one or more central processing units (CPUs), micro-processing units (MPUs), graphics processing units (GPUs), or other calculation processing devices equipped with timing functions, and performs various information processing and control processing for each optical system included in the laser light source 2 or the annealing optical system 11 by reading and executing a program P (program product) stored in the memory unit 92.

[0038] The storage unit 92 includes a volatile storage area such as a static random access memory (SRAM), a dynamic random access memory (DRAM), or a flash memory, and a non-volatile storage area such as an EEPROM or a hard disk. The storage unit 92 stores in advance a program P (program product) and data to be referenced during processing. The program P stored in the storage unit 92 may be a program P (program product) read from a recording medium 920 that is readable by the control unit 91. The program P may also be a program P (program product) downloaded from an external computer (not shown) connected to a communication network (not shown) and stored in the storage unit 92. The storage unit 92 stores an actual file of a learning model 921, which will be described later. The actual file of the learning model 921 may be configured as a module included in the program P (program product).

[0039] The communication unit 93 is, for example, a communication module or communication interface conforming to the Ethernet (registered trademark) standard, and an Ethernet cable is connected to the communication unit 93. The communication unit 93 is not limited to being wired, such as an Ethernet cable, and may be, for example, a communication interface compatible with wireless communication, such as a short-range wireless communication module, such as Wi-Fi (registered trademark) or Bluetooth (registered trademark), or a wide-range wireless communication module, such as 4G or 5G. The control device 9 may communicate, via the communication unit 93, with, for example, a product server SS connected to an external network GN.

[0040] The input / output I / F 94 is a communication interface that complies with a communication standard such as RS232C or USB. An input device such as a keyboard or a display device 941 such as a liquid crystal display is connected to the input / output I / F 94. The control device 9 may acquire various detection values ​​from detection units such as the biplanar phototube 62, the OED sensor 63, the mura monitor 64, or the profiler camera 66 via the input / output I / F 94.

[0041] 4 is an explanatory diagram showing an example of the learning model 921. The control unit 91 of the control device 9 trains a neural network using training data, and generates the learning model 921 that outputs quality information (predicted quality information) of a product including the substrate 8 irradiated with laser light when the operation parameters of the laser annealing device 1 are input. The predicted quality information is quality information predicted (estimated) by the learning model 921.

[0042] The operation parameters include detection values ​​(parameters) from a detection unit such as the OED sensor 63 provided in the laser annealing apparatus 1. The detection values ​​are detected at a predetermined cycle, and the operation parameters may include a standard deviation or an average value of a plurality of detection values ​​detected at the predetermined cycle. The product including the substrate 8 irradiated with the laser light is, for example, a final product such as a liquid crystal display or a mobile terminal such as a smartphone. The quality information of the final product is related to defects of the substrate 8 detected when the substrate 8 is incorporated into the final product, and includes, for example, a yield rate, a frequency of occurrence of defects, or a location of occurrence of defects. Furthermore, the quality information may include qualitative information such as evaluation information given by a quality manager of a final product factory.

[0043] The operation parameters may include, in addition to the detection values ​​from the detection units such as the OED sensor 63, parameters (state parameters) related to the state of the laser annealing apparatus 1 and parameters (control parameters) related to the control of the laser annealing apparatus 1. The state parameters include, for example, parameters related to the state of the laser light source 2 and parameters related to the state of the laser irradiation chamber 7 (process chamber) in which the substrate 8 is placed. The control parameters include, for example, parameters related to the control of the laser light source 2, parameters related to the control of the optical system (annealing optical system 11) that shapes the laser light emitted by the laser light source 2, and parameters related to the control of the laser irradiation chamber 7 (process chamber) in which the substrate 8 is placed.

[0044] The various parameters included in the operation parameters are not limited to the above, and for example, all data included in a management screen (FIG. 7) of the laser annealing apparatus 1 described later can be the data included in the operation parameters. The control unit 91 of the control device 9 acquires the operation parameters by acquiring detection values ​​from various sensors such as a detection unit such as the OED sensor 63, a temperature sensor, a vibration sensor, a pressure sensor, and a camera provided at various locations of the laser annealing apparatus 1, and by referring to operation log data stored in the memory unit 92.

[0045] The training data is composed of problem data consisting of operation parameters including detection values ​​from detection units such as the OED sensor 63, state parameters, and control parameters, and answer data consisting of product quality information including yield rates and the like, and these problem data and answer data are associated with each other and stored in the storage unit 92 of the control device 9. The original data that is the problem data of the training data can be generated, for example, by aggregating operation performance data of multiple laser annealing apparatuses 1.

[0046] As described above, the original data that becomes the answer data for the training data can be acquired, for example, via an external network GN, from a product server SS that stores and manages quality information and the like of a final product incorporating a substrate 8 processed by the laser annealing apparatus 1. Alternatively, the control device 9 of the laser annealing apparatus 1 may acquire the quality information by referring to a storage medium in which the quality information of the final product is stored.

[0047] The neural network (learning model 921) trained using the training data is expected to be used as a program module that is part of artificial intelligence software. The learning model 921 is used in the control device 9, and is executed in the control device 9 having such a computing capability to configure a neural network system.

[0048] The learning model 921 is composed of a DNN (Deep Neural Network) and has an input layer that accepts input of operating parameters including detection values, etc., an intermediate layer that extracts features of the operating parameters, and an output layer that outputs quality information (predicted quality information).

[0049] The input layer has a plurality of neurons that accept input of operation parameters including detection values, etc., and passes the input values ​​to the intermediate layer. The intermediate layer is defined using an activation function such as a ReLu function or a sigmoid function, has a plurality of neurons that extract features of each input value, and passes the extracted features to the output layer. Parameters such as weighting coefficients and bias values ​​of the activation function are optimized using the backpropagation method. The output layer is composed of, for example, a fully connected layer, and outputs quality information (predicted quality information) including yield rate, etc., based on the features output from the intermediate layer.

[0050] In this embodiment, the learning model 921 is a DNN, but is not limited to this, and may be a learning model 921 constructed with other learning algorithms, such as a neural network other than a DNN, a transformer, a recurrent neural network (RNN), a long-short term model (LSTM), a CNN, a support vector machine (SVM), a Bayesian network, linear regression, a regression tree, multiple regression, a random forest, an ensemble, etc.

[0051] Although the control device 9 included in the laser annealing apparatus 1 generates the learning model 921, the present invention is not limited to this, and the learning model 921 may be learned and generated by an external server device, such as a cloud server, other than the control device 9. Although the learning model 921 is used by the control device 9, the present invention is not limited to this, and the control device 9 may communicate with a cloud server, for example, connected to the Internet, via the communication unit 93, and obtain predicted quality information (yield rate, etc.) output by the learning model 921 implemented in the cloud server.

[0052] 5 is a flowchart showing an example of a processing procedure of the control unit 91 (during learning of the learning model 921). The control unit 91 of the control device 9 included in the laser annealing apparatus 1 receives an operation by an operator using, for example, a keyboard connected to an input / output, and performs the following processing based on the received operation.

[0053] The control unit 91 of the control device 9 acquires the operation parameters (S11). The control unit 91 of the control device 9 acquires detection values ​​from various sensors such as the OED sensor 63 and temperature sensors, vibration sensors, pressure sensors, and cameras provided at various locations of the laser annealing device 1, and refers to operation log data stored in the memory unit 92, and the like, to acquire the operation parameters including these data.

[0054] The control unit 91 of the control device 9 acquires quality information of the final product (S12). The control unit 91 of the control device 9 acquires the quality information from a product server SS that stores and manages quality information and the like of the final product incorporating the substrate 8 processed by the laser annealing device 1. Alternatively, the control device 9 of the laser annealing device 1 may acquire the quality information by referring to a storage medium in which the quality information of the final product is stored.

[0055] The control unit 91 of the control device 9 generates training data using the acquired operation parameters and quality information of the final product (S13). The control unit 91 of the control device 9 generates training data in which the operation parameters are question data and the quality information is answer data. When generating the training data, the control unit 91 of the control device 9 may perform standard deviation processing, average processing, standardization processing, dimension reduction processing, or the like using detection values ​​at multiple points in time.

[0056] The control unit 91 of the control device 9 uses the generated training data to generate a learning model 921 (S14). The control unit 91 of the control device 9 generates the learning model 921 by, for example, training a neural network using the generated training data.

[0057] When there are multiple final product factories to which the substrate 8 is shipped, the control unit 91 of the control device 9 may generate different learning models 921 corresponding to each of these final product factories. Alternatively, the control unit 91 of the control device 9 may generate different learning models 921 according to the category or type of final product into which the substrate 8 is to be incorporated. Alternatively, the control unit 91 of the control device 9 may generate different learning models 921 according to a combination of the final product factory and the category of the final product, etc.

[0058] When the management standards of the quality information acquired from the product servers SS of the respective final product factories are different, or when the quality information includes qualitative evaluation information, etc., the control unit 91 of the control device 9 may normalize, standardize, average, etc. the quality information acquired and aggregated from each of these final product factories. The control unit 91 of the control device 9 may generate a learning model 921 that can be generally applied to each of these individual final product factories by using the quality information that has been normalized, etc.

[0059] 6 is a flowchart showing an example of a processing procedure of the control unit 91 (when the learning model 921 is in operation). The control unit 91 of the control device 9 included in the laser annealing apparatus 1 receives an operation by an operator using, for example, a keyboard connected to an input / output, and performs the following processing based on the received operation.

[0060] The control unit 91 of the control device 9 acquires the operation parameters (S101). The control unit 91 of the control device 9 acquires detection values ​​from various sensors such as the OED sensor 63 and temperature sensors, vibration sensors, pressure sensors, and cameras provided at various locations of the laser annealing device 1, and refers to operation log data stored in the storage unit 92, and thereby acquires (generates) the operation parameters including these data.

[0061] The control unit 91 of the control device 9 inputs the acquired operation parameters to the learning model 921, and acquires predicted quality information of the final product (S102). The control unit 91 of the control device 9 inputs the acquired operation parameters to the learning model 921. The learning model 921 outputs (estimates) predicted quality information of the final product, such as yield, according to the input operation parameters. The control unit 91 of the control device 9 can derive the predicted quality information (yield, etc.) by acquiring the predicted quality information output by the learning model 921.

[0062] The control unit 91 of the control device 9 outputs the predicted quality information of the final product acquired from the learning model 921 (S103). The control unit 91 of the control device 9 associates the predicted quality information of the final product acquired from the learning model 921 with the operation parameters, and outputs the information to, for example, the display device 941, thereby notifying the manager of the laser annealing apparatus 1 of the predicted quality information of the final product, such as the yield rate estimated from the operation parameters at the current time.

[0063] The control unit 91 of the control device 9 judges whether the yield rate included in the predicted quality information is less than a predetermined threshold value (S104). The threshold value for the yield rate included in the predicted quality information is stored, for example, in the storage unit 92 of the control device 9. The control unit 91 of the control device 9 refers to the threshold value stored in the storage unit 92 and judges whether the yield rate included in the predicted quality information is less than the threshold value.

[0064] If the yield rate is not less than the threshold (S104: NO), i.e., if the yield rate included in the predicted quality information is equal to or greater than the threshold, the control unit 91 of the control device 9 performs a loop process to execute the process of S101 again. If the yield rate is not less than the threshold, i.e., if it is equal to or greater than the threshold, the control unit 91 of the control device 9 determines that the current operating parameters are appropriate (suitable), and performs a loop process to execute the process of S101 again.

[0065] If the yield rate is less than the threshold (S104: YES), the control unit 91 of the control device 9 outputs a notification signal indicating that the yield rate is less than the threshold (S105). If the yield rate is less than the threshold, the control unit 91 of the control device 9 determines that the current operating parameters are inappropriate (not suitable), and outputs a notification signal indicating that the yield rate is less than the threshold to, for example, the display device 941 or a mobile terminal of the manager of the laser annealing device 1.

[0066] After executing the process of S105, the control unit 91 of the control device 9 may perform a loop process to execute the process of S101 again, thereby continuing to monitor the suitability of the operating parameters from the perspective of quality information of the final product.

[0067] 7 is a diagram for explaining an example of a management screen of the laser annealing apparatus 1. The control unit 91 of the control device 9 generates a management screen (screen data) shown as an example in this embodiment by using the acquired operating parameters and the derived (estimated) predicted quality information, and outputs it to, for example, the display device 941 or the like.

[0068] The management screen of the laser annealing apparatus 1 includes display areas for displaying, in list form, data relating to the laser, data relating to the optical system, data relating to the process chamber, and data relating to substrate observation, as well as an area for displaying estimated predicted quality information.

[0069] The display area for laser-related data includes display sections for the laser output system, control system, laser gas system, maintenance system, and utility system. The laser output system display section displays the laser pulse energy, standard deviation (σ) of the laser pulse energy, and pulse waveform. The control system display section displays the electrode voltage, oscillation frequency, and resonator temperature. The laser gas system display section displays the gas ratio and pressure. The maintenance system display section displays the replacement status and condition of consumables. The utility system display section displays the chiller cooling temperature, flow rate, and power supply voltage.

[0070] The display area for data related to the optical system includes display sections for the line beam minor axis shape, line beam major axis shape, and raw beam shape, as well as display items for transmittance and polarization ratio. The display section for the line beam minor axis shape displays the minor axis width, shoulder width, standard deviation (σ) within the minor axis width, and tilt. The display section for the line beam major axis shape displays the major axis width and standard deviation (σ) within the major axis width. The display sections for the raw beam shape display the shape, position, emission angle, and intensity. The display item for transmittance displays the transmittance of the attenuator 3. The display item for polarization ratio displays the polarization ratio of the polarization ratio control unit 4.

[0071] The display area for data relating to the process chamber includes display items for process speed, irradiation atmosphere, stage surface flatness, and process chamber vibration. The process speed display section displays the stage speed and speed stability (ripple). The irradiation atmosphere display section displays the oxygen concentration, distribution, and nitrogen (N2) flow rate. The stage surface flatness display section displays the displacement sensor value. Process chamber vibration displays floor vibration and vibration within the stage. The display area for data relating to substrate observation includes display items for the mura monitor 64 detection value and the OED sensor 63 detection value.

[0072] The area displaying the estimated expected quality information includes a graph display area in which the variation in the yield rate over time is displayed, and a list display area in which the estimated expected quality information is displayed in list form. The horizontal axis of the graph displaying the variation in the yield rate over time indicates the elapsed time, and the vertical axis indicates the yield rate. A threshold value is set for the yield rate in advance. The list display area showing the expected quality information includes display items for the yield rate, the frequency of defects, and the position information of the defects on the board 8.

[0073] In this way, by displaying on the screen the operating parameters acquired in response to the operation of the laser annealing apparatus 1 in association with the yield rate (predicted quality information of the final product into which the substrate 8 is incorporated) derived (estimated) based on the operating parameters, visibility for managers of the laser annealing apparatus 1 can be improved.

[0074] According to this embodiment, by using the learning model 921, the expected quality information (expected quality information of the final product including the substrate 8) derived (estimated) based on the operation parameters including the detection value acquired from the detection unit is acquired and output. As a result, from the viewpoint of the quality information of the product including the substrate 8 irradiated with the laser light, the appropriateness of the detection value (operation parameter) can be judged (state diagnosis) and notified to the manager of the laser annealing apparatus 1 (laser irradiation apparatus). That is, by estimating the quality information (expected quality information) of the product (final product) including the substrate 8 manufactured by the laser annealing apparatus 1 (laser irradiation apparatus) based on the operation parameters including the detection value, the operation parameters are associated with the expected quality information of the product, the operation parameters are optimized according to the association, and the laser light can be efficiently controlled.

[0075] According to this embodiment, if the product yield (yield rate) included in the predicted quality information derived using the learning model 921 is below a predetermined threshold, an alarm signal indicating this is output, thereby prompting the manager of the laser annealing apparatus 1, etc. to make a decision regarding whether to continue operating the laser annealing apparatus 1, etc.

[0076] According to this embodiment, the detection unit includes various detection units such as the OED sensor 63, the unevenness monitor 64, the biplanar phototube 62, and the profiler camera 66, and therefore a plurality of types of detection values ​​by these detection units can be used as input data to the learning model 921, thereby improving the estimation accuracy by the learning model 921. The operating parameters input to the learning model 921 include a standard deviation calculated based on a plurality of detection values ​​detected at a predetermined period, and therefore the estimation accuracy by the learning model 921 can be improved.

[0077] According to this embodiment, the operating parameters input to the learning model 921 include parameters related to the state of the laser light source 2 and parameters related to the state of the laser irradiation chamber 7 (process chamber) in which the substrate 8 is placed, thereby improving the estimation accuracy by the learning model 921.

[0078] According to this embodiment, the operating parameters input to the learning model 921 include parameters related to the control of the laser light source 2, parameters related to the control of the optical system, and parameters related to the control of the laser irradiation chamber 7 (process chamber), thereby improving the estimation accuracy by the learning model 921.

[0079] (Embodiment 2)

[0080] 8 is a flowchart showing an example of a processing procedure (deriving operation parameters) of the control unit 91 according to embodiment 2. The control unit 91 of the control device 9 included in the laser annealing apparatus 1 receives an operation by an operator using, for example, a keyboard connected to an input / output, and performs the following processing based on the received operation.

[0081] The control unit 91 of the control device 9 acquires operation parameters (S201). The control unit 91 of the control device 9 inputs the acquired operation parameters to the learning model 921, and acquires predicted quality information of the final product (S202). The control unit 91 of the control device 9 outputs the predicted quality information of the final product acquired from the learning model 921 (S203). The control unit 91 of the control device 9 determines whether the yield rate included in the predicted quality information is less than a predetermined threshold value (S204). The control unit 91 of the control device 9 outputs a notification signal indicating that the yield rate is less than the threshold value (S205). The control unit 91 of the control device 9 performs the processes from S201 to S205, similar to the processes from S101 to S105 of the first embodiment.

[0082] After executing the process of S205, the control unit 91 of the control device 9 generates a plurality of candidate operating parameters when changing the operating parameters (S206). The control unit 91 of the control device 9 generates a plurality of operating parameters (candidate parameters) in which the values ​​included in the operating parameters at the current time are gradually changed within a predetermined range. When generating the plurality of candidate parameters, the control unit 91 of the control device 9 may gradually change, for example, the control parameters of the laser light source 2 such as the electrode voltage or the oscillation frequency, the control parameters of the annealing optical system 11 such as the transmittance or the polarization ratio, or the control parameters related to the laser irradiation chamber 7 such as the process speed, based on the current operating parameters, and combine these gradually changed various parameters.

[0083] The control unit 91 of the control device 9 inputs a plurality of candidate parameters to the learning model 921 and acquires a plurality of pieces of predicted quality information (S207). The control unit 91 of the control device 9 repeatedly inputs each of the generated plurality of candidate parameters to the learning model 921, thereby acquiring a plurality of pieces of predicted quality information corresponding to each of these candidate parameters.

[0084] The control unit 91 of the control device 9 sets the highest predicted quality information among the multiple pieces of predicted quality information obtained as the target quality information (S208). The control unit 91 of the control device 9 sets the predicted quality information with the highest yield rate, for example, among each of the predicted quality information estimated based on these candidate parameters, as the target quality information. It goes without saying that the set target quality information (target yield rate) is higher than the predicted quality information (yield rate) output (estimated) by the learning model 921 based on the current operating parameters.

[0085] The control unit 91 of the control device 9 identifies the operation parameters corresponding to the set target quality information (S209). The control unit 91 of the control device 9 derives the operation parameters corresponding to the target quality information by identifying the operation parameters that are input data when the learning model 921 outputs (estimates) the target quality information.

[0086] The control unit 91 of the control device 9 resumes operation using the identified operating parameters (S210). When the laser annealing apparatus 1 replaces the substrate 8 or replaces the cassette storing the multiple substrates 8, the control unit 91 of the control device 9 changes the irradiation conditions by changing the operating parameters at the current time to the operating parameters identified in S209, and resumes irradiation of the substrate 8 with the laser light.

[0087] According to this embodiment, the control unit 91 of the control device 9 sets target quality information of higher quality than the predicted quality information estimated by the learning model 921 based on the current driving parameters. The control unit 91 of the control device 9 generates, for the current driving parameters, a plurality of driving parameters in which the values ​​included in the driving parameters are gradually changed within a predetermined range, as candidate driving parameters (candidate parameters). The control unit 91 of the control device 9 inputs each of the generated candidate parameters to the learning model 921, thereby obtaining predicted quality information corresponding to each of these candidate parameters.

[0088] The control unit 91 of the control device 9 sets the predicted quality information with the highest yield rate, for example, from each of the predicted quality information estimated based on these candidate parameters as target quality information, and specifies the operation parameters that are input data when the learning model 921 outputs (estimates) the target quality information. The control unit 91 of the control device 9 controls the irradiation of the laser light to the substrate 8 based on the operation parameters corresponding to the target quality information, thereby improving the yield rate of the final product incorporating the substrate 8 manufactured by the laser annealing device 1 and enhancing the quality information of the final product.

[0089] (Other embodiments) 9, 10, 11, 12 and 13 are process cross-sectional views showing a semiconductor device manufacturing method according to another embodiment (semiconductor device manufacturing method). As another embodiment, a semiconductor device manufacturing method using the laser annealing apparatus 1 according to the above embodiment will be described. In the semiconductor device manufacturing method described below, in the step of crystallizing an amorphous semiconductor film, an annealing process is performed using the laser annealing apparatus 1 according to embodiments 1 and 2.

[0090] The semiconductor device is a semiconductor device including a TFT (Thin Film Transistor), and in this case, the amorphous silicon film 84 can be crystallized by irradiating it with laser light to form a polysilicon film 85. The polysilicon film 85 is used as a semiconductor layer having a source region, a channel region, and a drain region of the TFT.

[0091] The laser annealing apparatus 1 according to the embodiment described above is suitable for manufacturing a TFT array substrate. A method for manufacturing a semiconductor device having a TFT will now be described.

[0092] First, as shown in FIG. 9, a gate electrode 82 is formed on a glass substrate 81 (substrate 8). For the gate electrode 82, for example, a metal thin film containing aluminum or the like can be used. Next, as shown in FIG. 10, a gate insulating film 83 is formed on the gate electrode 82. The gate insulating film 83 is formed so as to cover the gate electrode 82. Thereafter, as shown in FIG. 11, an amorphous silicon film 84 is formed on the gate insulating film 83. The amorphous silicon film 84 is disposed so as to overlap the gate electrode 82 with the gate insulating film 83 interposed therebetween.

[0093] The gate insulating film 83 is a silicon nitride film (SiNx), a silicon oxide film (SiO2 film), or a laminated film thereof. Specifically, the gate insulating film 83 and the amorphous silicon film 84 are continuously formed by a CVD (Chemical Vapor Deposition) method. The glass substrate 81 with the amorphous silicon film 84 becomes a semiconductor film in the laser annealing apparatus 1 (laser irradiation apparatus).

[0094] 12, the amorphous silicon film 84 is irradiated with laser light L3 using the laser annealing apparatus 1 described above to crystallize the amorphous silicon film 84, thereby forming a polysilicon film 85. As a result, a polysilicon film 85 in which silicon is crystallized is formed on the gate insulating film 83.

[0095] 13, an interlayer insulating film 86, a source electrode 87a, and a drain electrode 87b are formed on the polysilicon film 85. The interlayer insulating film 86, the source electrode 87a, and the drain electrode 87b can be formed by using a general photolithography method or a film formation method. The manufacturing process thereafter differs depending on the device to be finally manufactured, so a description thereof will be omitted.

[0096] By using the above-described semiconductor device manufacturing method, a semiconductor device having a TFT including a polycrystalline semiconductor film can be manufactured. Such a semiconductor device is suitable for controlling a high-definition display such as an organic EL (Electro Luminescence) display. By suppressing unevenness in the polysilicon film 85 as described above, a display device with excellent display characteristics can be manufactured with high productivity.

[0097] In carrying out this series of processing steps, the control device 9 of the laser annealing apparatus 1 derives predicted quality information of the final product including the substrate 8 based on the acquired operating parameters, and outputs the predicted quality information to the display device 941. This makes it possible to associate the operating parameters with the predicted quality information of the product, and to monitor the appropriateness of the operating parameters from the viewpoint of the quality information of the final product, thereby supporting the optimization of the operating parameters and efficiently controlling the laser annealing apparatus 1.

[0098] The present disclosure is not limited to the above-mentioned embodiment, and can be appropriately modified within the scope of the present disclosure. For example, in is not limited to the example of forming the polysilicon film 85 by irradiating the amorphous silicon film 84 with a laser beam, but a microcrystalline silicon film may be formed by irradiating the amorphous silicon film 84 with a laser beam. Also, a crystallized film may be formed by irradiating an amorphous film other than a silicon film with a laser beam.

[0099] The embodiments disclosed herein are illustrative in all respects and should not be considered as limiting. The technical features described in each embodiment can be combined with each other, and the scope of the present invention is intended to include all modifications within the scope of the claims and the scope equivalent to the claims. [Explanation of symbols]

[0100] GN External Network SS Product Server 1. Laser annealing device (laser irradiation device) 11 Annealing optical system 2 Laser light source 3 Attenuator 4 Polarization ratio control unit 5 Beam shaping optics 61 Reflection mirror 62 Biplanar phototube 63 OED sensor 64 Unevenness Monitor 65 Projection Lens 66 Profiler camera (line beam sensor) 7 Laser irradiation chamber Stage 71 72 Base 8 Substrate 9. Control Device 91 Control Unit 92 Memory section 920 Recording media P Program (Program Product) 921 Learning Model 93 Communications Department 94 Input / Output Interface 941 Display device 81 Glass Substrate 82 Gate electrode 83 Gate insulating film 84 Amorphous silicon film 85 Polysilicon Film 86 Interlayer insulating film 87a Source electrode 87b Drain electrode

Claims

1. A laser irradiation device including a laser light source that emits laser light and a control unit that controls irradiation of a substrate with the laser light, The control unit is Acquire operating parameters including a detection value from a detection unit provided in the laser irradiation device; deriving predicted quality information by inputting the acquired operation parameters into a learning model that outputs predicted quality information of a product including a substrate irradiated with laser light when the operation parameters are input; outputting the derived predicted quality information in association with the acquired operating parameters; the predicted quality information derived using the learning model includes information regarding a yield of the product; When the yield of the product is less than a predetermined threshold, the control unit outputs a notification signal indicating that the yield is less than the threshold; outputting a management screen including the predicted quality information; The management screen includes a change over time in the yield rate estimated by the learning model. Laser irradiation device.

2. The detection unit includes at least one of an OED sensor, a mura monitor, a biplanar phototube, and a profiler camera; The OED sensor detects information about a crystal surface on the substrate; The mura monitor detects information regarding scattered light of a surface shape of the substrate, The biplanar phototube detects a pulse waveform of the laser light emitted from the laser light source, The profiler camera detects information regarding the shape of the laser light shaped into a line beam.

2. The laser irradiation device according to claim 1.

3. The detection unit obtains a plurality of detection values ​​at a predetermined period, The operating parameter includes a standard deviation calculated based on a plurality of detected values.

3. The laser irradiation device according to claim 1 or 2.

4. The operating parameters include at least one of a parameter related to a state of the laser light source and a parameter related to a state of a laser irradiation chamber in which the substrate is placed. The laser irradiation device according to any one of claims 1 to 3.

5. The operation parameters include control parameters for controlling the laser irradiation device, The control parameters include at least one of a parameter related to control of the laser light source, a parameter related to control of an optical system that shapes the laser light emitted by the laser light source, and a parameter related to control of a laser irradiation chamber in which the substrate is placed. The laser irradiation device according to any one of claims 1 to 4.

6. The control unit is Set target quality information that is higher quality than the derived predicted quality information, Deriving a control parameter corresponding to the set target quality information; Controlling the irradiation of the substrate with the laser light based on the derived control parameters; When deriving a control parameter corresponding to the target quality information, By gradually changing the parameters based on the current operating parameters, a plurality of candidate operating parameters are generated; Inputting each of the generated candidate operating parameters into the learning model to obtain a plurality of pieces of predicted quality information; Among the acquired plurality of pieces of predicted quality information, predicted quality information higher than the predicted quality information output by the learning model based on the current driving parameters is set as the target quality information.

6. The laser irradiation device according to claim 5.

7. On the computer, Acquire operating parameters including detection values ​​from a detection unit provided in the laser irradiation device; deriving predicted quality information by inputting the acquired operation parameters into a learning model that outputs predicted quality information of a product including a substrate irradiated with laser light when the operation parameters are input; outputting the derived predicted quality information in association with the acquired operating parameters; the predicted quality information derived using the learning model includes information regarding a yield of the product; If the yield of the product is less than a predetermined threshold, outputting a notification signal indicating that the yield is less than the threshold; outputting a management screen including the predicted quality information; The management screen includes a change over time in the yield rate estimated by the learning model. An information processing method for executing a process.

8. On the computer, Acquire operating parameters including detection values ​​from a detection unit provided in the laser irradiation device; deriving predicted quality information by inputting the acquired operation parameters into a learning model that outputs predicted quality information of a product including a substrate irradiated with laser light when the operation parameters are input; outputting the derived predicted quality information in association with the acquired operating parameters; the predicted quality information derived using the learning model includes information regarding a yield of the product; If the yield of the product is less than a predetermined threshold, outputting a notification signal indicating that the yield is less than the threshold; outputting a management screen including the predicted quality information; The management screen includes a change over time in the yield rate estimated by the learning model. A program that executes a process.

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