Data collection device, data collection method, and data collection system

Abstract

The present invention constructs a database that stores and manages measurement data obtained by a plurality of measurement devices for the same material and feature quantity data obtained by analyzing the measurement data in association with information that identifies the material.　According to the present invention, a data collection device that collects measurement data acquired by a measurement device has a database that stores material data that includes feature information about a material to be measured and identification information that identifies the material, a measurement recipe distributor that distributes a measurement recipe that includes the identification information and information about an acquisition procedure for measurement data to a control device that controls the measurement device, a data lake that stores measurement data acquired by the measurement device in accordance with the measurement recipe and supplemental information that includes the identification information and device parameters from the time the data was acquired, and a data correspondence relationship creator that registers the measurement data and the supplemental information stored at the data lake at the database in association with the material data stored at the database on the basis of the identification information as included in the supplemental information.

Description

Data collection device, data collection method, and data collection system

[0001] The present invention relates to a data collection device, a data collection method, and a data collection system that collect measurement data output by a measurement device.

[0002] In the field of materials development, in order to achieve desired performance, materials are prototyped using multiple compositions and multiple processing conditions, and the processing results and the resulting material performance are evaluated by acquiring and analyzing a large amount of measurement data using multiple measuring devices, in an attempt to find the optimal conditions.

[0003] In the past, searching for such optimal conditions relied heavily on the experience and intuition of engineers and experienced workers, but in recent years, as materials have become more sophisticated and complex, the types and range of parameters that need to be searched for have expanded, resulting in significant costs in terms of time and effort required to acquire and analyze measurement data.

[0004] To address this issue, materials informatics, which uses information science to analyze large amounts of data and search for optimal conditions to develop new materials, is attracting attention.In such data-driven development sites, the efficient acquisition of large amounts of data is directly linked to development results, so there is a need to improve the efficiency of data acquisition, management, and other processes.

[0005] A conventional invention of this type is described in Patent Document 1 (JP 2023-23329 A), which describes providing a database including data (material data) indicating at least one of composition data, process data, and property data for individual materials, and structure data for individual samples obtained by an analytical device.

[0006] Japanese Patent Application Laid-Open No. 2023-23329

[0007] In the field of materials development, processed materials are not only evaluated for their performance as final products, but also for their physical properties, microstructure, etc. By evaluating the correlation between processing conditions and the characteristics of the material itself, such as the physical properties and microstructure obtained as a result of processing, it is possible to find methods for controlling material microstructure through processing and utilize this information in future developments.

[0008] However, the data output from measurement devices is often non-quantitative data such as images or spectrum data, making it difficult to use this data for quantitative evaluation as is. For this reason, in many cases, in order to evaluate the characteristics of the measurement data, it is necessary to separately quantify the characteristics of the measurement data and structure the data.

[0009] Furthermore, it is rare to evaluate only the measurement results obtained from one measuring device; rather, materials are evaluated using multiple different measuring devices in each manufacturing process, and the multiple measurement results are combined for evaluation.

[0010] Therefore, by constructing a database that stores and manages measurement data obtained by multiple measuring devices for the same material and the feature data obtained by analyzing that data, linked to information that identifies the material, more efficient material development can be expected.

[0011] An object of the present invention is to provide a data collection device that can build such a database.

[0012] In order to solve the above problems, the present invention is a data collection device that collects measurement data acquired by a measuring device, and is configured to include: a database that stores material data including characteristic information of the material to be measured and identification information that identifies the material; a measurement recipe distributor that distributes a measurement recipe including information on the measurement data acquisition procedure and identification information to a control device that controls the measuring device; a data lake that stores measurement data acquired by the measuring device according to the measurement recipe and additional information including device parameters and identification information at the time the data was acquired; and a data correspondence creator that associates the measurement data and additional information stored in the data lake with material data stored in the database based on the identification information included in the additional information and registers them in the database.

[0013] According to the present invention, measurements are performed using a measurement device using a measurement recipe containing material identification information registered in a database, so that the measurement results can be reliably associated with the material data registered in the database, and the feature values ​​obtained by analyzing the measurement results can also be associated with the material data.

[0014] Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments.

[0015] 1 is a configuration diagram of a data collection system in Example 1. FIG. 1 is a diagram showing a scanning electron microscope and its control PC. FIG. 2 is a diagram showing a sample stage of the scanning electron microscope and a plurality of samples arranged on the sample stage. FIG. 3 is a flowchart showing the procedure before starting measurement in Example 1. FIG. 4 is an example of a material information setting screen. FIG. 5 is an example of a screen for specifying a data processing method in a feature extractor. FIG. 6 is an example of a measurement recipe selection screen. FIG. 7 is an example of a measurement recipe selection screen. FIG. 8 is an example of a preset measurement recipe registration screen. FIG. 9 is a flowchart of a data acquisition procedure using a scanning electron microscope using a measurement recipe. FIG. 10 is a flowchart showing the processing procedure in a server after measurement data has been acquired. FIG. 11 is an example of a screen for displaying extracted feature data. FIG. 12 is an example of a screen for displaying extracted feature data. FIG. 13 is a diagram showing the configuration of a server in Example 2. FIG. 14 is a flowchart showing the procedure before starting measurement in Example 2. FIG. 15 is an example of a screen display showing that identification information is being confirmed. FIG. 16 is an example of a screen display notifying a user to start measurement. FIG. 17 is an example of a screen display for confirming whether or not to continue measurement.

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0017] FIG. 1 is a configuration diagram of a data collection system in this embodiment, which comprises a server 100 equipped with an arithmetic unit 110 and a storage unit 120, a plurality of control terminals 140 connected via a network 130 and measuring devices 150 that are controlled by the control terminals 140, and a data processing device 160 connected to the server 100 via the network 130.

[0018] The server 100 functions as a data collection device in this embodiment, and includes a web server 111 that inputs and outputs data and performs settings for each part of the server 100 in response to access from the control terminal 140, data processing device 160, etc., a feature extractor 112 that analyzes measurement results to obtain features, a measurement recipe distributor 113 that distributes measurement recipes to the control terminal 140 of each measuring device 150, a calculation device 110 that has a data correspondence creator 114 that associates data in a data lake (described later) with data on a database, a database 121 that stores various data, and a storage device 120 that has a data lake 122 that stores measurement results.

[0019] The server 100 may be a virtual server on the cloud or an on-premise server. Each of the components in the computing device 110 described above can be implemented by storing a program having the corresponding function in the storage device 120 and having the processor (CPU) of the computing device 110 call up and execute the program. However, each component may also be implemented by a dedicated device, processor, hardware, etc. In the following description, among the processes performed by the server 100, those that are not specifically designated as being performed by a specific entity are assumed to be performed by the CPU of the computing device 110.

[0020] A user can access the web server 111 via the control terminal 140 or the data processing device 160 and register data in the database 121 on the server 100. In addition, data or files in the database 121 can be sent to the control terminal 140 or the data processing device 160 in response to a query from the user. An example of the data processing device 160 is a personal computer, a tablet terminal, or a smartphone.

[0021] The control terminal 140 controls the measurement operation, such as issuing instructions to the measuring device 150 to perform measurements based on a measurement recipe, which will be described later, and also transmits and receives data to and from the server 100 via the network 130. The control terminal 140 may be directly connected to the network 130 to connect to the server 100, or may be connected to the server 100 via a network connection terminal connected via a LAN or the like (not shown).

[0022] The measuring device 150 is a device that qualitatively and quantitatively measures the physical quantity, composition, properties, structure, state, etc. of a sample that is the object to be measured, and examples thereof include an electron microscope, an atomic force microscope, a spectrometer, an X-ray analyzer, and a mass analyzer.

[0023] 2 shows a scanning electron microscope 200 and its control PC 220 as an example of the measuring device 150 and control terminal 140. The scanning electron microscope 200 focuses an electron beam emitted from an electron source 201 by an optical system 202 that receives a control command from an optical system control unit 207, and irradiates the electron beam onto a sample 203 on a sample stage 204. Secondary electrons emitted from the sample 203 are detected by a detector 205 and converted into an image signal by an image forming unit 206.

[0024] The control PC 220 comprises a communication IF 221, a CPU 222, a memory 223, a bus 224, an input device 225, an output device 226, and a storage device 227, and the user can send operation commands to the optical system control unit 207, the image forming unit 206, and the stage driving unit 208 via the communication IF 221.

[0025] The communication IF 221 receives an image signal from the scanning electron microscope 200, and the CPU 22 converts the received image signal into an image, which can be displayed on the output device 226 or stored as an image file in the storage device 227. The communication IF 221 can also transmit and receive information to and from other server devices and the like via a communication line (not shown, such as the network 130 in FIG. 1 ).

[0026] As shown in Fig. 3, a plurality of samples 203 (four samples in Fig. 3) can be placed on the sample stage 204. The sample stage 204 can be moved on two axes, the X and Y directions, on a plane by a stage drive unit 208. This makes it possible to acquire data at multiple locations on multiple samples without the user having to manually move the position of the sample 203 on the sample stage 204.

[0027] Next, the process from registering information required for measurement to starting measurement in the data collection system of this embodiment will be described with reference to the flowchart of FIG.

[0028] Step S401: The user uses the user interface (input device, touch panel, etc.) of the control terminal 140 or the data processing device 160 to register material data in the database 121 from the web server 111, the material data including identification information such as an arbitrary name or identification number for identifying (specifying) the material to be measured, and characteristic data of the material relating to the material composition, manufacturing process, etc.

[0029] Here, the term "composition" includes, for example, the types and composition ratios of elements that make up the material. It may also include information about the types and contents of constituent elements, such as impurities or trace elements that are intentionally added. Furthermore, the term "manufacturing process" includes, for example, information about various manufacturing conditions (temperature, atmosphere, processing time, etc.) and processing history (heat treatment history, etc.) in the material processing step. Additionally, any information that you would like to view in comparison with the measurement results, such as data showing the performance of the material or literature information, may be registered.

[0030] Regarding the identification information of the material, a unique name or identification number may be assigned to each individual piece, or if the same individual piece is divided and measured using different measuring devices, the same name or identification number may be assigned to all of them.

[0031] Figure 5 shows an example of a material information setting screen 500. The user can register information about the object to be measured through this screen. For example, in the case of Figure 5, when the user places the cursor 501 on "Processing Temperature" under "Item," a property 502 for inputting or correcting the numerical value is displayed, and the user can input 300 (503) as the numerical value.

[0032] Step S402: Similarly, the user inputs the type information of the measuring device to be used, etc. Measuring devices that may be used may be registered in advance on the Web server side, and one of these may be selected.

[0033] Step S403: Similarly, the user specifies the data processing method in the feature extractor 112. Here, a feature refers to numerical data that reflects the characteristics of the measurement target of interest contained in unstructured measurement data, such as image or spectrum data. Examples include the position, intensity, and width of a specific peak in spectrum data, or the number, density, area, diameter, and perimeter of a specific structure contained in image data.

[0034] The user can select a data processing method provided in advance by the server via the web server based on the type of measuring device to be used. The algorithms and parameters for calculating the features may be provided as preset methods in the feature extractor 112, or the user can set them via a specification screen displayed on the display device of the control terminal 140 or the data processing device 160.

[0035] FIG. 6 shows an example of a screen 600 for specifying a data processing method in the feature extractor 112. The data processing method can be specified using a section 601 for selecting the type of measurement data to be processed by the feature extractor 112, a section 602 for specifying signal preprocessing such as noise removal and contrast adjustment for the measurement data provided by the feature extractor, a section 603 for specifying processing for extracting a point of interest from an image, a section 604 for specifying an algorithm for calculation processing to quantify the feature amounts of the point of interest, and a section 605 for setting a learning model for deep learning and parameters to be given to the algorithm.

[0036] Step S404: Determine the measurement recipe to be used for the measurement. Here, the measurement recipe refers to a file that pairs device control parameters required for measurement, such as device-specific setting parameters for the measurement device, the number of data acquisition points, and acquisition positions, with sample information including identification information for the object to be measured, written in a format specific to each measurement device. When the user executes the measurement recipe corresponding to the measurement device 150 on the control program on the control terminal 140 of the measurement device 150, the measurement device 150 can perform the measurement process according to the procedure described in the measurement recipe and acquire measurement data for the sample.

[0037] A plurality of representative measurement recipes are preset in the database 121 on the server 100, and the user selects a measurement recipe based on the material data and measurement device type information registered (input) in steps S401 and S402. At this time, the material identification information registered by the user in step S401 is added to the selected measurement recipe as information on the measurement target.

[0038] 7A and 7B show examples of measurement recipe selection screens displayed on the display device of the control terminal 140 or the data processing device 160. In Fig. 7A, all measurement recipes preset in the database 121 are selectable from a pull-down menu 701, so the user selects a measurement recipe based on the material data and measuring device type information registered (input) in steps S401 and S402. On the other hand, in Fig. 7B, measurement recipe candidates are narrowed down and displayed (712) based on the registered (input) material data and measuring device type information 711, allowing the user to select an appropriate recipe.

[0039] Furthermore, as for the measurement recipe, in addition to selecting and specifying a preset measurement recipe as described above, it is also possible to register a separately created measurement recipe or a measurement recipe that has been used with another measurement device, etc., in the database 121 via a web server and add it as a new preset measurement recipe. Figure 8 shows an example of a registration screen 800 for a preset measurement recipe that is displayed on the display device, etc., of the control terminal 140 or the data processing device 160, and has a section 801 for specifying the type of measurement device, a section 802 for specifying the type of material to be measured, a section 803 for specifying the file name of the measurement recipe, a button 804 for uploading the specified measurement recipe file to the database 121, and a cancel button 805 for canceling the upload process, etc.

[0040] Step S405: The measurement recipe determined above is transmitted from the server 100 to the control terminal 140 of the measurement apparatus 150.

[0041] Next, as an example of the operation of the measuring apparatus 150 based on the measurement recipe, the operation of the scanning electron microscope 200 shown in Fig. 2 will be described using the flowchart shown in Fig. 9. It is assumed that the measurement objects are four samples 203 mounted on the sample stage 204 shown in Fig. 3, and that all of these are to be measured sequentially.

[0042] When the CPU 222 of the control PC 220 executes the received measurement recipe, it sends a command to the scanning electron microscope 200, and the electron source 201 starts irradiating the electron beam (step S901).

[0043] Next, in accordance with the designation of the measurement recipe, the stage driving unit 207 moves the sample stage 204 so that the position where the sample 203 to be measured first among the four samples 203 is placed coincides with the irradiation position of the electron beam (step S902). Note that the order of steps S901 and S902 may be reversed.

[0044] Next, the optical system control unit 207 sets a desired imaging magnification for the sample 203 to be measured (step S903), and performs focus adjustment and contrast adjustment of the optical system (steps S904 and S905, respectively). Secondary electrons emitted from the sample 203 are detected by the detector 205, and converted into image signals by the image forming unit 206 to obtain image data (step S906).

[0045] At this time, incidental information, which is various apparatus parameters such as the sample coordinates and measurement conditions at the time of acquiring the measurement data, is output together with the image data, and identification information of the measurement target sample 203 described in the measurement recipe is added to this incidental information to form an incidental information file, which is then saved together with the acquired image data in the storage device 227 in the control PC 220 (step S907). As a result, it is possible to refer to which of the materials registered in the database 121 the output measurement results (image data) belong to using the identification information in the incidental information file.

[0046] The above operation is repeated by changing the position of the sample stage 204 until the desired number of data acquisition points specified in the measurement recipe is reached (step S908). That is, the sample stage 204 is moved to the electron beam irradiation position and measurements are repeated until measurements of all four samples 203 in Fig. 3 are completed ("NO" in step S908), and when measurements of all samples are completed ("YES" in step S908), this flow ends.

[0047] Next, the process flow for registering the measurement data stored in the control terminal 140 in the server 100 will be described with reference to the flowchart shown in FIG.

[0048] Step S1001: The server 100 receives the measurement data and its accompanying information file from the control terminal 140.

[0049] Step S1002: The server 100 stores the received measurement data and accompanying information file in the data lake 122.

[0050] Step S1003: The data correspondence creator 114 refers to the identification information included in the additional information file stored in the data lake 122, and associates the measurement data with material data having the same identification information among the material data recorded in the database 121. This allows the material data recorded in the database 121 to be associated with the corresponding measurement data and additional information (such as the measurement conditions when the measurement data was obtained).

[0051] Step S1004: The measurement data and its associated information linked to the material data are registered as material measurement data in database 121. This allows the user to refer to the material data in database 121 via web server 111, thereby enabling them to view and obtain the names and compositions of materials and the corresponding measurement data.

[0052] Step S1005: The feature extractor performs calculations using the measurement data as input values ​​based on the data processing method specified in step S403 of FIG. 4, and outputs, as feature values, results such as quantification of the composition and structural characteristics of the material contained in the measurement data.

[0053] Step S1006: As in step S1003, the data correspondence creator 114 stores the extracted feature quantities in association with the material data in the database 121. This allows the user to view and obtain not only the measurement data but also the feature quantities extracted from the measurement data. Furthermore, even when measurements are performed separately on the same sample using multiple measuring devices 150, the respective measurement results and feature quantities are associated with the material data, making it easy for the user to comprehensively evaluate and consider them.

[0054] The above-mentioned flow may be performed each time the control terminal 140 acquires measurement data, or after the measurement process has been completed for all measurement devices 150 scheduled for measurement and each corresponding control terminal 140 has acquired measurement data, etc., each control terminal 140 may sequentially perform the process of registering the measurement data, etc. to the server 100.

[0055] 11A shows an example 1100 of a display screen for feature data, etc. in this embodiment. When a user accesses the Web server 111 from the data processing device 160 or the control terminal 140 and sends a request for result output, the Web server 111 extracts the relevant result data, etc. from the database 121 in accordance with the search conditions included in the request and returns it to the data processing device 160 or the control terminal 140, and the returned results can be displayed on the display device, etc. The result display 1101 is an example in which five pieces of data are displayed in the order in which the feature values ​​were extracted, in accordance with the number of items to display specified in the display number specification section 1102.

[0056] Here, "ID," "additive," "addition amount," and "processing temperature" correspond to material data in the database 121, while "measurement device" and "measurement conditions" are extracted from supplementary information from the measurement device and associated with each other by "ID." Furthermore, "feature amount" is extracted from measurement data and associated with each other by "ID." "Result file name" is the name of the file in which data related to the feature amount is recorded. It is also possible to display not only the feature amount but also the measurement data itself.

[0057] Through this screen, the user can view the feature quantities and the measuring device used when acquiring the data, as well as the measurement conditions. The user can then extract and view the desired material feature quantity data and measurement conditions, or output and download the data as a data file in the desired format (txt file, csv file, json file, etc.).

[0058] Also, data to be displayed can be extracted using the extracted item selection section 1103. Fig. 11B shows an example screen 1110 in which only five pieces of data with an identification number (ID) of "001" are extracted and displayed, and five pieces that match the ID "001" selected by the extracted item selection section 1113 are displayed in the result display 1111 as specified by the display number specification section 1112.

[0059] Here, since the results are for the same material, the "ID," "additive," "amount added," and "processing temperature" are all the same, but the "measurement device" and "measurement conditions" are different.

[0060] As described above, according to this embodiment, measurements are performed using a measurement device using a measurement recipe that contains identification information for materials registered in a database, so that the measurement results can be reliably associated with the material data registered in the database, and the feature quantities obtained by analyzing the measurement results can also be associated with the material data.

[0061] This enables data analysis and organization to be processed mechanically without manual intervention, reducing the labor costs associated with data processing and preventing manual data tampering. Furthermore, even when measurements are performed using different measurement recipes with multiple measurement devices, the identification information registered in the same database is referenced, so measurement results for the same material can be associated and saved in the database based on the identification information, allowing users to associate and obtain measurement results and their feature quantities for the same material from multiple measurement devices.

[0062] In Example 1, measurement recipes preset on the server (including those that the user has previously uploaded to the server as preset measurement recipes) are distributed to the control terminal 140 by the measurement recipe distributor 113, but in this example, measurement data and feature quantities are obtained using a measurement recipe created and obtained on the control terminal 140 of the measuring device 150 by the user who is about to perform the measurement.

[0063] The configuration of a server 1200 in Example 2 is shown in Fig. 12. The server 1200 in this example differs from the server 100 in Example 1 in that it has a calculation device 1210 equipped with a measurement recipe analyzer 1211 instead of the measurement recipe distributor 113 in Example 1 (Fig. 1), but the configuration of the entire system otherwise conforms to Fig. 1 (Example 1).

[0064] Figure 13 shows a flowchart from the registration of information used in measurement to the start of measurement in this embodiment. Steps S1301 to S1303 are the same as steps S401 to S403 in the flowchart of Example 1 shown in Figure 4, so a description thereof will be omitted. Note that, when it is necessary to distinguish the identification information included in the material data input in step S1301 from the identification information attached to the measurement target sample described later, the former will be referred to as first identification information and the latter as second identification information.

[0065] Step S1304: The user performing the measurement prepares a measurement recipe to be used in the measurement on the control terminal 140. The user may create a new measurement recipe on the control terminal 140 using, for example, a measurement recipe template, or may create the measurement recipe using a measurement recipe creation app installed on the control terminal 140. Furthermore, if a measurement recipe previously used in the measuring device 150 is stored in the control terminal 140, it may be edited, or a measurement recipe created on another terminal may be obtained via a communication line, memory device, or the like.

[0066] Step S1305: The user obtains the sample identification information (second identification information) by visually checking the sample identification information (second identification information) written on a label or tag attached to a container or the like containing the sample to be measured, and adds the identification information (second identification information) to the measurement recipe prepared in step S1304. Then, the measurement recipe to which the identification information (second identification information) has been added is transmitted from the control terminal 140 to the server 1200. The server 1200 receives the measurement recipe that the user intends to use for measurement via the web server 111.

[0067] In steps S1304 and S1305, the user prepares the measurement recipe and performs the transmission process to the server 1200 using the control terminal 140, but similar processes may be performed using the data processing device 160. In this case, the response from the server 1200, as will be described later in steps S1307 and S1308, is notified to the data processing device 160.

[0068] Step S1306: The measurement recipe analyzer 1211 of the server 1200 reads the sample identification information (second identification information) described in the received measurement recipe, compares it with the identification information (first identification information) of the material data registered in the database 121, and checks whether it matches any of them. The server 1200 also notifies the control terminal 140 via the web server 111 that it is currently checking the contents of the measurement recipe, which also serves as a receipt confirmation that the measurement recipe was received in step S1305. Figure 14 shows an example of a screen displayed on the control terminal 140 notifying that the contents of the measurement recipe are currently being checked.

[0069] Step S1307: In step S1306, if all of the identification information (second identification information) included in the read measurement recipe corresponds to any of the identification information (first identification information) of material data already registered in the database 121 ("YES" in step S1306), the measurement recipe analyzer 1211 determines that it is possible to collect measurement data and notifies the control terminal 140 via the Web server 111 of a message urging the start of measurement, and the control terminal 140 displays a screen urging the start of measurement as shown in Fig. 15A. A user who sees this screen executes the measurement recipe on the control terminal 140, and the measuring device 150 starts measurement.

[0070] The subsequent processing is the same as in Example 1 (Figures 9 and 10, etc.), so detailed explanation will be omitted, but the data correspondence processing in the data correspondence relationship creator 114 is carried out based on the first identification information and the second identification information.

[0071] Step S1308: In step S1306, if the identification information (second identification information) included in the read measurement recipe contains identification information that is not registered in the database 121, or if the measurement recipe does not contain any identification information (NO in step S1306), the measurement recipe analyzer 1211 determines that it is impossible to collect measurement data and notifies the control terminal 140 via the Web server 106 of a message urging the user to check the measurement recipe or a message confirming whether or not the measurement should be continued, and the control terminal 140 displays a screen such as that shown in Fig. 15B. In Fig. 15B, reference numeral 1511 denotes a message prompting the user to check whether or not the identification number (second identification information) described in the measurement recipe is correct, because an identification number (second identification information) not registered in the database 121 was found; 1512 denotes the unregistered identification number; and 1513 denotes a message confirming whether or not the measurement should be continued.

[0072] In addition, if an identification number that is not registered in database 121 is found in a measurement recipe, the following actions are expected: (1) stop the measurement process for all samples; (2) perform the measurement process only for samples for which the same identification number is found in database 121, extract features, and register the results in database 121; or (3) perform the measurement process for all samples and display the measurement data on control terminal 140, or send the measurement data to data lake 122 of server 1200 (no subsequent data analysis is performed), and these actions may be specified by the user.

[0073] As described above, according to this embodiment, a configuration is adopted in which, before starting measurement, it is confirmed that the identification number (second identification information) of the material written in the measurement recipe matches the identification number (first identification information) of the material data written in database 121, and then measurement is started.Therefore, even when using a measurement recipe prepared by the user who is about to perform the measurement, as in Example 1, the measurement data output by measuring device 150 can be reliably associated with the material data registered in database 121 using the above-mentioned identification number included in the accompanying information that is also output, and further, the feature quantities obtained by analyzing the measurement data can also be reliably associated with the material data and recorded in database 121.

[0074] The present invention is not limited to the above-described embodiments, but includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0075] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software, with a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0076] DESCRIPTION OF SYMBOLS 100...server, 110...arithmetic unit, 111...web server, 112...feature extractor, 113...measurement recipe distributor, 114...data correspondence relationship creator, 120...storage device, 121...database, 122...data lake, 130...network, 140...control terminal, 150...measuring device, 160...data processing device, 200...scanning electron microscope, 201...electron source, 202...optical system, 203...sample, 204...sample stage, 205...detector, 206...image forming unit, 207...optical system control unit, 208...stage driving unit, 220...control PC, 221...communication interface, 222...CPU, 223...memory, 224...bus, 225...input device, 226...output device, 227...storage device, 1211...measurement recipe analyzer

Claims

1. A data collection device that collects measurement data acquired by a measuring device, comprising: a database that stores material data including characteristic information of the material to be measured and identification information that identifies the material; a measurement recipe distributor that distributes a measurement recipe including information on a measurement data acquisition procedure and the identification information to a control device that controls the measuring device; a data lake that stores the measurement data acquired by the measuring device according to the measurement recipe and additional information including device parameters at the time the measurement data was acquired and the identification information; and a data correspondence creator that associates the measurement data and the additional information stored in the data lake with the material data stored in the database based on the identification information included in the additional information, and registers them in the database.

2. A data collection device as described in claim 1, further comprising a feature extractor that calculates feature quantities that numerically represent the composition and structural characteristics of the measured material from the measurement data stored in the database, and the data correspondence creator that associates the calculated feature quantities with the material data stored in the database based on the identification information and registers them in the database.

3. A data collection device according to claim 2, further comprising a web server for outputting the feature quantities registered in the database in accordance with specified conditions.

4. A data collection device as described in claim 3, characterized in that the measurement recipe distributed to the control device is selected from a plurality of types of preset measurement recipes pre-stored in the database, and has the identification information added thereto.

5. A data collection device according to claim 4, wherein the preset measurement recipes are selected based on the type of the measurement device to be used.

6. A data collection device according to claim 4, wherein the preset measurement recipe can be additionally registered in the database.

7. A data collection device that collects measurement data acquired by a measuring device, comprising: a database that stores material data including characteristic information of a material to be measured and first identification information that identifies the material to be measured; a measurement recipe analyzer that receives a measurement recipe including information on a procedure for acquiring the measurement data and second identification information that identifies a material to be used for the measurement from a control device that controls the measuring device, and determines whether or not the measurement process in the measuring device can be continued by comparing the second identification information with the first identification information; a data lake that stores the measurement data acquired by the measuring device according to the measurement recipe, and additional information including device parameters at the time the measurement data was acquired and the second identification information; and a data correspondence creator that associates the measurement data and the additional information stored in the data lake with the material data stored in the database based on the first identification information and the second identification information, and registers them in the database.

8. A data collection device as described in claim 7, further comprising a feature extractor that calculates feature quantities that numerically represent the composition and structural characteristics of the measured material from the measurement data stored in the database, and the data correspondence creator registers the calculated feature quantities in the database in correspondence with the material data stored in the database based on the first identification information and the second identification information.

9. A data collection device according to claim 8, further comprising a web server for outputting the feature quantities registered in the database in accordance with specified conditions.

10. A data collection method for collecting measurement data acquired by a measuring device, comprising the steps of: storing material data including characteristic information of the material to be measured and identification information for identifying the material; distributing a measurement recipe including information regarding a procedure for acquiring the measurement data and the identification information to a control device that controls the measuring device; storing the measurement data acquired by the measuring device according to the measurement recipe and additional information including device parameters at the time the measurement data was acquired and the identification information; and registering the measurement data and the additional information in correspondence with the stored material data based on the identification information included in the additional information.

11. A data collection method for collecting measurement data acquired by a measuring device, comprising the steps of: storing material data including characteristic information of a material to be measured and first identification information that identifies the material to be measured; receiving a measurement recipe from a control device that controls the measuring device, the measurement recipe including information on a procedure for acquiring the measurement data and second identification information that identifies a material to be used for the measurement, and determining whether or not to continue the measurement process in the measuring device by comparing the second identification information with the first identification information; storing the measurement data acquired by the measuring device according to the measurement recipe and incidental information including device parameters at the time the measurement data was acquired and the second identification information; and registering the measurement data and the incidental information in correspondence with the stored material data based on the first identification information and the second identification information.

12. A data collection system having a measuring device, a control device that controls the measuring device, and a server connected to the control device via a network, wherein the server has: a database that stores material data including characteristic information of a material to be measured and identification information that identifies the material; a measurement recipe distributor that distributes to the control device a measurement recipe including information on a measurement data acquisition procedure and the identification information; a data lake that stores the measurement data acquired by the measuring device according to the measurement recipe and additional information including device parameters at the time the measurement data was acquired and the identification information; and a data correspondence creator that associates the measurement data and the additional information stored in the data lake with the material data stored in the database based on the identification information included in the additional information, and registers them in the database.

13. A data collection system having a measuring device, a control device that controls the measuring device, and a server connected to the control device via a network, wherein the server has: a database that stores material data including characteristic information of a material to be measured and first identification information that identifies the material to be measured; a measurement recipe analyzer that receives from the control device a measurement recipe including information on a measurement data acquisition procedure and second identification information that identifies a material to be used for measurement, and determines whether or not measurement processing in the measuring device can be continued by comparing the second identification information with the first identification information; a data lake that stores the measurement data acquired by the measuring device according to the measurement recipe, and incidental information including device parameters at the time the measurement data was acquired and the second identification information; and a data correspondence creator that associates the measurement data and the incidental information stored in the data lake with the material data stored in the database based on the first identification information and the second identification information, and registers them in the database.

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