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

Abstract

To construct a database for storing and managing measurement data obtained by a plurality of measurement devices about the same material and feature data obtained by analyzing the measurement data in association with identification information for the material.SOLUTION: A server, which is a data collection device for collecting the measurement data acquired by a measurement device, comprises: a database which stores material data including characteristic information of a material to be measured and identification information for identifying the material; a measurement recipe distributor which distributes a measurement recipe to a control device controlling the measurement device, the measurement recipe including information on a procedure for acquiring measurement data and identification information; a data lake which stores the measurement data acquired by the measurement device according to the measurement recipe and ancillary information including device parameters at the time of data acquisition and the identification information; and a data correlation creator which registers the measurement data and ancillary information stored in the data lake in the database in association with the material data stored in the database on the basis of the identification information included in the ancillary information.SELECTED DRAWING: Figure 1

Description

Technical Field

[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.

Background Art

[0002] In the field of material development, in order to achieve desired performance, materials are prototyped with combinations of multiple compositions and multiple processing conditions, and a large number of measurement data are acquired and analyzed by using multiple measurement devices to evaluate the processing results and the material properties obtained thereby, and attempts are made to search for optimal conditions.

[0003] Conventionally, such search for optimal conditions has largely relied on the experience and intuition of engineers and experts. However, in recent years, with the improvement and complexity of materials, the types and ranges of parameters to be searched have been expanding. For this reason, the time and labor required for acquiring and analyzing measurement data have become a large cost.

[0004] In response to this problem, materials informatics that leads to the development of new materials by analyzing a large number of data based on information science to search for optimal conditions has attracted attention. In such a data-driven development site, since efficiently acquiring a large number of data is directly linked to the development results, it is required to improve the efficiency required for processes such as data acquisition and management.

[0005] Conventionally, as an invention of this kind, there was one described in Patent Document 1 (Japanese Patent Application Laid-Open No. 2023-23329). Patent Document 1 describes providing a database including at least one of composition data, process data, and characteristic data (material data) in individual materials and structure data in individual samples acquired by an analysis device.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

SUMMARY OF THE INVENTION

PROBLEMS TO BE SOLVED BY THE INVENTION

[0007] In the field of material development, processed materials are evaluated not only for their performance as final products but also for their physical properties, microstructure, etc. using various measuring devices. By evaluating the correlation between processing conditions and the characteristics exhibited by the material itself, such as physical properties and microstructure obtained as a result of processing, a method for controlling the material structure by processing can be found and utilized in subsequent development.

[0008] However, data output from measuring devices is often non-numerical data such as images and spectral data, and it is difficult to directly use this data for quantitative evaluation. Therefore, in many cases, in order to evaluate the characteristics of measurement data, it is often necessary to separately perform the operation of quantifying the features of the measurement data and structuring the data.

[0009] In addition, it is rare to evaluate only the measurement results obtained from a single measuring device. Instead, materials are evaluated using multiple different measuring devices in each process of manufacturing, and multiple measurement results are comprehensively evaluated.

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

[0011] An object of the present invention is to provide a data collection device capable of constructing such a database.

MEANS FOR SOLVING THE PROBLEM

[0012] To solve the above problems, the present invention provides a data collection device that collects measurement data acquired by a measurement device, comprising: a database that stores material data including characteristic information of a material to be measured and identification information for identifying the material; a measurement recipe distributor that distributes a measurement recipe including information regarding the acquisition procedure of the measurement data and the identification information to a control device that controls the measurement device; a data lake that stores the measurement data acquired by the measurement device according to the measurement recipe, device parameters at the time of data acquisition, and incidental information including the identification information; and a data correspondence relationship 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 identification information included in the incidental information and registers the associated data in the database.

Advantages of the Invention

[0013] According to the present invention, since measurement is performed using a measurement recipe in which material identification information registered in the database is described, the measurement results can be surely 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.

[0014] Problems, configurations, and effects other than those described above will be clarified by the following description of the embodiments.

Brief Description of the Drawings

[0015]

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Embodiments for Carrying Out the Invention

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

Examples

[0017] FIG. 1 is a configuration diagram of a data collection system in this embodiment, which includes a server 100 having an arithmetic unit 110 and a storage device 120, a plurality of control terminals 140 connected by a network 130, a measurement device 150 which is a control target of the control terminal 140, and a data processing device 160 connected to the server 100 by the network 130.

[0018] Server 100 functions as a data collection device in this embodiment, and includes a Web server 111 that performs data input / output, setting, etc. for each part within Server 100 in response to access from a control terminal 140, a data processing device 160, etc.; a feature extractor 112 for analyzing measurement results to obtain features; a measurement recipe distributor 113 for distributing measurement recipes to the control terminals 140 of the respective measurement devices 150; and a data correspondence relationship creator 114 for creating a correspondence between data in a data lake described later and data on a database. It also has an arithmetic unit 110 and a storage device 120 that includes a database 121 for storing various data and a data lake 122 for storing measurement results.

[0019] Server 100 may be a virtual server on the cloud or an on-premises server. Also, each component within the arithmetic unit 110 described above can be realized by storing programs having those functions in the storage device 120 and having the processor (CPU) of the arithmetic unit 110 call and execute them. However, each of them may also be realized by a dedicated device, processor, hardware, etc. Also, among the processes performed by Server 100 in the following description, for processes where the main body is not particularly specified, it is assumed that the CPU of the arithmetic unit 110 performs them.

[0020] The 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 Server 100. Also, in response to a query from the user, data and files on the database 121 can be transmitted to the control terminal 140 or the data processing device 160. 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 of the measurement device 150, such as issuing an instruction to execute a measurement based on a measurement recipe described later. It also performs data transmission and reception with 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 by a LAN or the like (not shown).

[0022] The measurement device 150 is a device that qualitatively and quantitatively measures the physical quantity, composition, properties, structure, state, etc. of a sample, which is the measurement object. Examples include an electron microscope, an atomic force microscope, a spectroscopic device, an X-ray analysis device, a mass spectrometer, and the like.

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

[0024] The control PC 220 is composed of 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. 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 the image signal from the scanning electron microscope 200, and the CPU 22 can image the received image signal and display it on the output device 226 or save it as an image file in the storage device 227. Also, the communication IF 221 can perform information transmission and reception with other server devices and the like via a communication line (such as the network 130 in FIG. 1) not shown.

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

[0027] Next, in the data collection system of this embodiment, the processing from the registration of information necessary for measurement to the start of measurement will be described using the flowchart of Fig. 4.

[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 including identification information such as an arbitrary name or identification number for identifying (specifying) the material to be measured from the Web server 111 and characteristic data of the material regarding the composition and manufacturing process of the material in the database 121.

[0029] Here, the composition includes, for example, the types and composition ratios of the elements constituting the material. It may also include information regarding the types and contents of the constituent elements of trace elements due to impurities or intentional additives. Further, the manufacturing process includes, for example, information regarding various manufacturing conditions (temperature, atmosphere, processing time, etc.) and processing history (heat treatment history, etc.) in the material processing step. In addition, if there is information such as data indicating the performance of the material or literature information that you want to view in comparison with the measurement results, it may be registered.

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

[0031] FIG. 5 shows an example of the material information setting screen 500. Through this screen, the user can register information regarding the object to be measured. For example, in the case of FIG. 5, when the user aligns the cursor 501 with "Processing Temperature" in "Item", the property 502 for inputting or modifying the value is displayed, and the value 300 (503) can be input as a 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 in advance are registered on the Web server side, and the user may select one of them.

[0033] Step S403: Similarly, the user designates the data processing method in the feature extractor 112. Here, the feature quantity refers to numerical data that reflects the characteristics of the measurement object of interest included in unstructured measurement data such as images and spectral data. For example, the position, intensity, width of a specific peak in spectral data, or the number, density, area, diameter, perimeter, etc. of a specific structure included in image data can be mentioned.

[0034] The user can select, via the Web server, a data processing method provided by the server in advance from the types of measuring devices to be used. Algorithms and parameters for calculating feature quantities may be provided by the methods preset in the feature extractor 112, or may also be set by the user through a designation screen displayed on the display device of the control terminal 140 or the data processing device 160.

[0035] FIG. 6 is an example of a screen 600 for designating the data processing method in the feature extractor 112. Using a part 601 for selecting the type of measurement data processed by the feature extractor 112, a part 602 for designating signal preprocessing such as noise removal and contrast adjustment for the measurement data provided by the feature extractor, a part 603 for designating the process of extracting the location of interest from the image, a part 604 for designating the algorithm for the arithmetic process of quantifying the feature quantity of the location of interest, a part 605 where parameters for the learning model and algorithm for deep learning can be set, etc., the data processing method can be designated.

[0036] Step S404: Determine the measurement recipe to be used for measurement. Here, the measurement recipe refers to a file described in a format unique to each measuring device, which pairs sample information including device-specific setting parameters, the number of data acquisition points, acquisition positions, and other device control parameters necessary for measurement in the measuring device, with identification information of the measurement object. When the user executes the measurement recipe corresponding to the measuring device 150 on the control program on the control terminal 140 of the measuring device 150, the measuring device 150 can execute the measurement process according to the procedures described in the measurement recipe and acquire the measurement data of the sample.

[0037] In the database 121 on the server 100, multiple types of typical measurement recipes are preset in advance. The user selects a measurement recipe based on the material data registered (input) in steps S401 and S402 and the type information of the measuring device. At this time, the identification information of the material registered by the user in step S401 is added to the selected measurement recipe as information about the measurement object.

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

[0039] In addition to selecting and specifying a preset measurement recipe as described above, a separately created recipe or a recipe with a proven track record of use in other measuring devices can be registered in the database 121 via the Web server and added as a new preset measurement recipe. FIG. 8 shows an example of a registration screen 800 for a preset measurement recipe displayed on the display device of the control terminal 140 or the data processing device 160, which includes a section 801 for specifying the type of measuring 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 and the like.

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

[0041] Next, as an example of the operation of the measuring device 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 objects to be measured are four samples 203 mounted on the sample stage 204 shown in FIG. 3, and all of these will be measured sequentially.

[0042] When the CPU 222 of the control PC 220 executes the received measurement recipe, a command is sent to the scanning electron microscope 200, and electron beam irradiation is started from the electron source 201 (step S901).

[0043] Next, in accordance with the specification of the measurement recipe, the sample stage 204 is moved by the stage drive unit 207 so that the position where the sample 203 to be measured first among the four samples 203 is installed 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 the imaging magnification to a desired value 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). Then, the secondary electrons emitted from the sample 203 are detected by the detector 205, converted into an image signal by the image forming unit 206, and image data is acquired (step S906).

[0045] At this time, although the additional information, which is various device parameters such as the sample coordinates and measurement conditions at the time of measurement data acquisition, is output simultaneously with the image data, the identification information of the measurement target sample 203 described in the measurement recipe is added to this additional information to form an additional information file, which is saved together with the acquired image data in the storage device 227 in the control PC 220 (step S907). Thereby, it can be referred to using the identification information of the additional information file whether the output measurement result (image data) is any of the materials registered on the database 121.

[0046] The above operations are 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, until all the measurements of the four samples 203 in FIG. 3 are completed (''NO'' in step S908), the sample stage 204 is moved to the electron beam irradiation position and the measurement is repeated. When the measurement of all the samples is completed (''YES'' in step S908), this flow ends.

[0047] Subsequently, a processing flow for registering the measurement data stored in the control terminal 140 to the server 100 will be described using the flowchart shown in FIG. 10.

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

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

[0050] Step S1003: The data correspondence creator 114 refers to the identification information included in the attached information file stored in the data lake 122, and associates the measurement data with the material data having the same identification information among the material data recorded in the database 121. Thereby, it is possible to associate the material data recorded in the database 121 with the corresponding measurement data and attached information (such as measurement conditions at the time of obtaining the measurement data).

[0051] Step S1004: Register the measurement data and its attached information associated with the material data in the database 121 as material measurement data. Thereby, the user can view and obtain the name and composition of the material and the corresponding measurement data by referring to the material data on the database 121 via the Web server 111.

[0052] Step S1005: The feature extractor performs arithmetic processing using the measurement data as an input value based on the data processing method specified in step S403 of FIG. 4, and outputs, as features, for example, the results of quantifying the composition and structural characteristics of the material included in the measurement data.

[0053] Step S1006: Similar to step S1003, the data correspondence creator 114 associates and stores the extracted features with the material data on the database 121. Thereby, the user can view and obtain not only the measurement data but also the features extracted from the measurement data. Also, even when the same sample is measured separately by a plurality of measurement devices 150, since each measurement result and feature are associated with the material data, the user can easily evaluate and consider them comprehensively.

[0054] Note that the above flow may be executed each time the control terminal 140 acquires measurement data, or after the measurement processing in all the measurement devices 150 scheduled for measurement is completed and each corresponding control terminal 140 acquires the measurement data and the like, each control terminal 140 may sequentially perform the process of registering the measurement data and the like in the server 100.

[0055] Figure 11A shows Example 1100 of a display screen for feature data and the like in this embodiment. When a user accesses Web server 111 from data processing device 160 or control terminal 140 and sends a request for result output, Web server 111 extracts corresponding result data and the like from database 121 according to the search conditions included in the request and returns it to data processing device 160 or control terminal 140, and those display devices and the like can display the returned results. Result display 1101 is an example where five pieces of data are displayed in the order in which the features were extracted according to the number of display items specified by display item specification unit 1102.

[0056] Here, "ID", "additive", "addition amount", and "processing temperature" correspond to material data on database 121, "measuring device" and "measurement conditions" are extracted from the attached information from the measuring device, and are associated by "ID". Also, "feature amount" is extracted from the measurement data and associated by "ID". "Result file name" is the name of the file in which data related to that feature amount is recorded. Not only the feature amount, but also the measurement data itself may be displayed.

[0057] Through this screen, the user can list the feature amounts, the measuring device used by the measuring device at the time of data acquisition, and its measurement conditions, extract and view the desired material feature amount data and measurement conditions, and output and download them in a desired format (txt file, csv file, json file, etc.) as a data file.

[0058] Also, the extraction item selection unit 1103 can extract the data to be displayed. Figure 11B shows Example 1110 of a screen in which only five pieces of data with an identification number (ID) of "001" are extracted and displayed. The extraction item selection unit 1113 extracts those that match "001", and five pieces are displayed in result display 1111 according to the specification of display item specification unit 1112.

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

[0060] As described above, according to this embodiment, since measurement is performed using a measurement recipe in which identification information of the material registered in the database is described by a measurement device, the measurement result can surely be associated with the material data registered in the database, and the feature amount obtained by analyzing the measurement result can also be associated with the material data.

[0061] As a result, mechanical processing that does not involve manual intervention in data analysis and organization becomes possible, which can reduce the human cost related to data processing and prevent data falsification by humans. Also, even when measurement is performed using different measurement recipes with a plurality of measurement devices, since the identification information registered on the same database is referred to, the measurement results of the same material can be associated based on the identification information and stored in the database, and the user can obtain the measurement results and their feature amounts obtained by a plurality of measurement devices for the same material in an associated manner.

Example

[0062] In Example 1, a configuration was adopted in which a measurement recipe preset on the server (including those additionally uploaded by the user to the server in advance as a preset measurement recipe) is distributed to the control terminal 140 by the measurement recipe distributor 113. However, in this example, the user who is about to perform measurement obtains measurement data and feature amounts using the measurement recipe created and obtained on the control terminal 140 of the measurement device 150.

[0063] The configuration of the server 1200 in Example 2 is shown in FIG. 12. The server 1200 of this example is different from the server 100 of Example 1 in that it has an arithmetic device 1210 equipped with a measurement recipe analyzer 1211 instead of the measurement recipe distributor 113 of Example 1 (FIG. 1), and the overall configuration of the other systems conforms to FIG. 1 (Example 1).

[0064] FIG. 13 shows a flowchart from the registration of information used in the measurement in this embodiment to the start of measurement. Since steps S1301 to S1303 are the same as steps S401 to S403 in the flowchart of Example 1 shown in FIG. 4, the 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 is referred to as the first identification information and the latter as the 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 measurement recipe may be newly created by the user on the control terminal 140 using, for example, a template of the measurement recipe, or may be created using a measurement recipe creation application installed on the control terminal 140. Further, if a measurement recipe used in the measurement device 150 in the past is stored in the control terminal 140, it may be edited, or a measurement recipe created on another terminal or the like may be obtained via a communication line, a memory device, or the like.

[0066] Step S1305: The user obtains the identification information (second identification information) of the sample by visually recognizing the identification information (second identification information) of the sample described on a label, a tag, or the like attached to a container or the like containing the measurement target sample, 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) is 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] Note that in steps S1304 and S1305, the user uses the control terminal 140 to prepare the measurement recipe and perform the transmission process to the server 1200, but the same process may be performed using the data processing device 160. Also, in this case, a response from the server 1200 as described in steps S1307 and S1308 to be described later will be notified to the data processing device 160.

[0068] Step S1306: The measurement recipe analyzer 1211 of the server 1200 reads the identification information (second identification information) of the sample 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 they match. Also, the server 1200 notifies the control terminal 140 through the Web server 111 that it is in the process of checking the content of the measurement recipe, also serving as a reception confirmation notice that the measurement recipe was received in step S1305. FIG. 14 shows an example of a screen for notifying the control terminal 140 that the content of the measurement recipe is being checked.

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

[0070] Since the subsequent processing is the same as that in the first embodiment (FIGS. 9 and 10, etc.), a detailed description is omitted, but the processing of associating data in the data correspondence creator 114 will be carried out based on the first identification information and the second identification information.

[0071] Step S1308: In step S1306, if there is identification information (second identification information) included in the read measurement recipe that is not registered in the database 121, or if there is no identification information included in the measurement recipe ("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 prompting confirmation of the measurement recipe or a message confirming whether or not the measurement can be continued, and the control terminal 140 displays a screen as shown in Fig. 15B. In Fig. 15B, 1511 is a message prompting confirmation of the correctness of the identification number (second identification information) written in the measurement recipe because there is an identification number (second identification information) that is not registered in the database 121, 1512 is the unregistered identification number, and 1513 is a message confirming whether or not the measurement can be continued.

[0072] In addition, when an identification number that is not registered in database 121 is found in a measurement recipe, the following actions are possible: (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, and also 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 (without subsequent data analysis). These actions may be specified by the user.

[0073] As described above, according to this embodiment, since a configuration is adopted in which measurement is started after confirming that the identification number (second identification information) of the material described in the measurement recipe before the start of measurement matches the identification number (first identification information) of the material data described in the database 121, even when the user who is about to perform measurement uses the measurement recipe prepared by the user, as in the first embodiment, the measurement data output by the measurement device 150 can be surely associated with the material data registered in the database 121 using the above identification number included in the attached information output together, and also, the feature amount obtained by analyzing the measurement data can be surely associated with the material data and recorded in the database 121.

[0074] Note that the present invention is not limited to the above-described embodiments, and includes various modifications. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Also, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Also, for a part of the configuration of each embodiment, addition, deletion, or replacement with other configurations is possible.

[0075] In addition, each of the above configurations, functions, processing units, processing means, etc. may be realized by hardware, for example, by designing a part or all of them with an integrated circuit. Also, each of the above configurations, functions, etc. may be realized by software by a processor interpreting and executing a program for realizing each function. Information such as a program, table, file, etc. for realizing each function can be placed in a memory, a recording device such as a hard disk or an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

Description of Reference Numerals

[0076] 100… Server, 110… Arithmetic unit, 111… Web server, 112… Feature extractor, 113… Measurement recipe distributor, 114… Data correspondence relation 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… Specimen, 204… Specimen stage, 205… Detector, 206… Image formation unit, 207… Optical system control unit, 208… Stage drive 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 measurement device, comprising: a database that stores material data including characteristic information of a material to be measured and identification information for identifying the material; a measurement recipe distributor that distributes a measurement recipe including information regarding an acquisition procedure of the measurement data and the identification information to a control device that controls the measurement device; a data lake that stores the measurement data acquired by the measurement device according to the measurement recipe, device parameters at the time of acquisition of the measurement data, and incidental information including the identification information; a data correspondence relationship creator that registers the measurement data and the incidental information stored in the data lake in the database in association with the material data stored in the database based on the identification information included in the incidental information; A data collection device, characterized by comprising the above.

2. The data collection device according to claim 1, comprising: a feature quantity extractor that calculates a feature quantity obtained by quantifying characteristics of the composition and structure of the measured material from the measurement data stored in the database; The data correspondence relationship creator registers the calculated feature quantity in the database in association with the material data stored in the database based on the identification information. A data collection device characterized by this.

3. The data collection device according to claim 2, comprising: a Web server that outputs the feature quantity registered in the database according to specified conditions. A data collection device characterized by this.

4. The data collection device according to claim 3, wherein: 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 includes the identification information added thereto. A data collection device characterized by this.

5. The data collection device according to claim 4, wherein: the selection candidates of the preset measurement recipes are determined according to the type of the measurement device to be used. A data collection device characterized by this.

6. The data collection device according to claim 4, wherein: the preset measurement recipes can be additionally registered in the database. A data collection device characterized by this.

7. A data collection device that collects measurement data acquired by a measurement device, comprising: a database that stores material data including characteristic information of a material to be measured and first identification information for identifying the material to be measured; Receiving, from a control device that controls the measurement device, a measurement recipe including information regarding a procedure for acquiring the measurement data and second identification information for specifying a material used in the measurement, and determining whether to continue the measurement process in the measurement device by comparing the second identification information with the first identification information, a measurement recipe analyzer; A data lake that stores the measurement data acquired by the measurement device according to the measurement recipe, device parameters at the time of acquisition of the measurement data, and incidental information including the second identification information; A data correspondence relationship creator that registers the measurement data and the incidental information stored in the data lake in the database in association with the material data stored in the database based on the first identification information and the second identification information; A data collection device, characterized by comprising the above.

8. The data collection device according to claim 7, having a feature quantity extractor that calculates a feature quantity obtained by quantifying characteristics of the composition and structure of the measured material from the measurement data stored in the database; The data collection device, wherein the data correspondence relationship creator registers the calculated feature quantity in the database in association with the material data stored in the database based on the first identification information and the second identification information.

9. The data collection device according to claim 8, characterized by having a Web server that outputs the feature quantity registered in the database according to specified conditions.

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

11. A data collection method for collecting measurement data acquired by a measurement device, comprising: A step of storing material data including characteristic information of a material to be measured and first identification information for identifying the material to be measured; A step of receiving a measurement recipe including information regarding a procedure for acquiring the measurement data and second identification information for identifying a material to be used in the measurement from a control device that controls the measurement device, and determining whether measurement processing in the measurement device can be continued by comparing the second identification information with the first identification information; A step of storing the measurement data acquired by the measurement device according to the measurement recipe, device parameters at the time of acquisition of the measurement data, and additional information including the second identification information; A step of registering the measurement data and the additional information in association with the stored material data based on the first identification information and the second identification information; A data collection method characterized by comprising the above.

12. A data collection system including a measurement device, a control device that controls the measurement 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 for identifying the material; a measurement recipe distributor that distributes a measurement recipe including information regarding a procedure for acquiring measurement data and the identification information to the control device; a data lake that stores the measurement data acquired by the measurement device according to the measurement recipe, device parameters at the time of acquisition of the measurement data, and additional information including the identification information; a data correspondence relationship creator that registers the measurement data and the additional information stored in the data lake in the database in association with the material data stored in the database based on the identification information included in the additional information; A data collection system characterized by comprising the above.

13. A data collection system including a measurement device, a control device that controls the measurement 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 for identifying the material to be measured; Receive a measurement recipe including information on the procedure for acquiring measurement data and second identification information identifying the material to be used in the measurement from the control device, and determine whether the measurement process in the measurement device can be continued by comparing the second identification information with the first identification information. A measurement recipe analyzer; A data lake that stores the measurement data acquired by the measurement device according to the measurement recipe, the device parameters at the time of acquisition of the measurement data, and the incidental information including the second identification information; A data correspondence relationship 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; A data collection system, characterized by comprising:

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