Data management system, data management methods, and recording media that record the procedures.

Abstract

This invention provides a data management system, a data management method, and a recording medium recording a program. The data management system includes: an environmental data acquisition unit that acquires environmental data from environmental sensors that measure the manufacturing environment of products made from raw materials; a sensor selection unit that selects a specific sensor from measuring sensors that measure the manufacturing object to be manufactured, based on the correlation between the sensor and the environmental sensor; and a parameter setting unit that sets the measurement parameters in the specific sensor based on the environmental data.

Description

Technical Field

[0001] This invention relates to a data management system, a data management method, and a recording medium that records the data management program. Background Technology

[0002] Patent document 1 describes "the status of the surrounding environment of the field device 10, or the operating status of other devices that cannot be obtained by the sensors 11 of the field device 10 itself, etc."

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent Application Publication No. 2017-091258 Summary of the Invention

[0006] In a first aspect of the present invention, a data management system is provided. The data management system may include an environmental data acquisition unit that acquires environmental data from environmental sensors that measure the manufacturing environment of a product made from raw materials. The data management system may include a sensor selection unit that selects a specific sensor from measuring sensors that measure the manufactured object based on the correlation with the environmental sensors. The data management system may include a parameter setting unit that sets measurement parameters in the specific sensor based on the environmental data.

[0007] The sensor selection unit can determine the correlation of the measuring sensor based on the distance to the environmental sensor.

[0008] The sensor selection unit can determine the correlation of the measuring sensors based on the category of physical quantities measured by the environmental sensors.

[0009] The sensor selection unit can determine the correlation degree of the measurement sensor based on the correlation between the temporal changes of environmental data measured by the environmental sensor and the temporal changes of measurement data measured by the measurement sensor.

[0010] The sensor selection unit can determine the correlation of the sensor to be measured based on the actual operation of the selected sensor.

[0011] The data management system may also include a list output unit that outputs a list of candidate sensors, which are measurement sensors with a correlation higher than a predetermined threshold. The sensor selection unit selects a specific sensor from the candidate sensors based on user input.

[0012] When environmental data falls outside a predetermined range, the parameter setting unit can change the measurement parameters.

[0013] When the environmental data is within a predetermined range, the parameter setting unit can initialize the measurement parameters.

[0014] The parameter setting unit can set the cycle time used to measure the manufactured object as the measurement parameter.

[0015] The parameter setting unit can set the sensitivity of the manufactured object as the measurement parameter.

[0016] The Environmental Data Acquisition Department can acquire at least one of the following as environmental data: vibration, temperature, humidity, illuminance, odor, gas concentration, pressure, air pressure, stress, magnetic field, sound, and images in the manufacturing environment.

[0017] The data management system may also include: a measurement data acquisition unit, which acquires measurement data obtained from the measurement sensor for measuring the manufactured object; and a data recording unit, which records the measurement data.

[0018] The data recording unit can also record timing information indicating when the measurement parameters have been changed.

[0019] In a second aspect of the present invention, a data management method is provided. The data management method may include acquiring environmental data from environmental sensors that measure the manufacturing environment of a product made from raw materials. The data management method may include selecting a specific sensor from measuring sensors that measure the manufactured object based on the correlation with the environmental sensors. The data management method may include setting measurement parameters in the specific sensor based on the environmental data.

[0020] In a third aspect of the present invention, a recording medium recording a data management program is provided. The data management program can be executed by a computer. The data management program can function as an environmental data acquisition unit, which acquires environmental data obtained from environmental sensors by measuring the manufacturing environment of the product being manufactured from raw materials. The data management program can also function as a sensor selection unit, which selects a specific sensor from measuring sensors that measure the object being manufactured, based on the correlation with the environmental sensors. Finally, the data management program can function as a parameter setting unit, which sets the measurement parameters in the specific sensor based on the environmental data.

[0021] Furthermore, the above summary of the invention does not list all the essential features of the invention. Additionally, sub-combinations of these feature groups can also constitute an invention. Attached Figure Description

[0022] Figure 1 Together with factory 10, this illustrates an example of a block diagram of the data management system 100 of this embodiment.

[0023] Figure 2 This describes a configuration example of the measuring sensor 20 and the environmental sensor 30 installed in factory 10.

[0024] Figure 3 This is an example of the process by which the data management system 100 of this embodiment sets measurement parameters based on environmental data.

[0025] Figure 4 Here is an example of a block diagram of a data management system 100 that represents a variation of this embodiment.

[0026] Figure 5 This is an example of a list of candidate sensors output by the data management system 100, representing a variation of this embodiment.

[0027] Figure 6 Examples of computer 2200 that illustrate how multiple aspects of the present invention can be implemented in whole or in part.

[0028] Label Explanation

[0029] Factory 10

[0030] 20 Measurement Sensors

[0031] 30 Environmental Sensors

[0032] 100 Data Management System

[0033] 110 Measurement Data Acquisition Department

[0034] 120 Data Recording Department

[0035] 130 Environmental Data Acquisition Department

[0036] 140 Sensor Selection Section

[0037] 150 parameter setting section

[0038] 410 List Output Section

[0039] 420 interface section

[0040] 2200 computers

[0041] 2201 DVD-ROM

[0042] 2210 Main Controller

[0043] 2212 CPU

[0044] 2214 RAM

[0045] 2216 Graphics Controller

[0046] 2218 Display Device

[0047] 2220 Input / Output Controller

[0048] 2222 communication interface

[0049] 2224 hard drive

[0050] 2226 DVD-ROM drive

[0051] 2230ROM

[0052] 2240 Input / Output Chip

[0053] 2242 keyboard Detailed Implementation

[0054] The present invention will now be described through embodiments thereof, but these embodiments do not limit the invention as defined in the claims. Furthermore, not all combinations of features described in the embodiments are necessarily required for the solution of the invention.

[0055] Figure 1 An example block diagram of the data management system 100 of this embodiment is shown together with factory 10. In this diagram, as an example, the data management system 100 manages data obtained from multiple sensors installed at factory 10. However, it is not limited to this. The data management system 100 may also manage measurement data from one or more sensors installed at any location different from factory 10.

[0056] Factory 10, besides chemical plants, can also be: a plant that manages and controls well sources such as gas fields or oil fields or their surrounding areas; a plant that manages and controls power generation such as hydropower, thermal power, and nuclear power; a plant that manages and controls environmental power generation such as solar or wind power; and a plant that manages and controls water supply and drainage or dams, etc. In factory 10, the process of manufacturing products from raw materials proceeds from upstream to downstream. In such a factory 10, one or more measuring sensors 20 and one or more environmental sensors 30 can be installed.

[0057] The measuring sensor 20 measures physical quantities of the manufactured object that is being manufactured in the factory 10. The measuring sensor 20 may be, for example, a sensor installed in an OT (Operational Technology) area (e.g., a process control (measurement) sensor), or an industrial sensor connected to or integrated with one or more field devices installed in the factory. As an example, the measuring sensor 20 can acquire measurement data by measuring physical quantities such as flow rate, pressure, and temperature in raw materials (raw materials and finished products), semi-finished products, and finished products that are being manufactured.

[0058] Environmental sensor 30 measures the manufacturing environment in which the product is made from raw materials. Environmental sensor 30 may be, for example, an IoT (Internet of Things) sensor subsequently installed in factory 10. As an example, environmental sensor 30 can acquire environmental data by measuring physical quantities in the manufacturing environment such as vibration, temperature, humidity, illuminance, odor, gas concentration, pressure, air pressure, stress, magnetic field, sound, and images.

[0059] The data management system 100 of this embodiment acquires environmental data from the environmental sensor 30. Then, based on the acquired environmental data, the data management system 100 sets measurement parameters for a specific sensor selected from the measurement sensor 20.

[0060] The data management system 100 can be a PC (personal computer), tablet computer, smartphone, workstation, server computer, or general-purpose computer, or a computer system connecting multiple computers. This computer system is also a computer in a broad sense. Alternatively, the data management system 100 can be implemented through one or more virtual computer environments that can run within the computer. Alternatively, the data management system 100 can be a dedicated computer designed for managing data, or it can be dedicated hardware implemented with dedicated circuitry. Furthermore, if the data management system 100 can connect to the Internet, it can also be implemented through cloud computing.

[0061] The data management system 100 includes a measurement data acquisition unit 110, a data recording unit 120, an environmental data acquisition unit 130, a sensor selection unit 140, and a parameter setting unit 150. Furthermore, these blocks are functionally separate and do not necessarily conform to the actual device structure. That is, although represented as one block in this diagram, it does not necessarily consist of a single device. Similarly, although represented as different blocks in this diagram, they do not necessarily consist of different devices.

[0062] The measurement data acquisition unit 110 acquires measurement data of the manufactured object from the measurement sensors 20. As an example, the measurement data acquisition unit 110 can acquire the measurement data of the manufactured object from each of the plurality of measurement sensors 20 sequentially via a communication unit, such as a communication network. Furthermore, in the above description, as an example, the case where the measurement data acquisition unit 110 acquires measurement data from each of the plurality of measurement sensors 20 via a communication network is shown, but it is not limited to this. The measurement data acquisition unit 110 may also acquire measurement data from each of the plurality of measurement sensors 20 via other units different from the communication network, such as user input or various storage devices.

[0063] This communication network can be a network connecting multiple computers. For example, the communication network can be a global network that interconnects multiple computer networks; as an example, the communication network can be the Internet using Internet Protocol (IP). Alternatively, the communication network can also be implemented via a dedicated line. That is, the measurement data acquisition unit 110 can also directly or indirectly exchange measurement data with mobile phones, smartphones, fourth-generation (4G) terminals, and fifth-generation (5G) terminals.

[0064] The measurement data acquisition unit 110 can acquire measurement data such as flow rate, pressure, temperature, and combinations thereof from each of the plurality of measurement sensors 20, including raw materials, semi-finished products, and finished products that are the objects of manufacturing. Additionally, the measurement data acquisition unit 110 can also acquire values ​​generated mathematically based on these data as measurement data. The measurement data acquisition unit 110 provides the measurement data acquired from each of the plurality of measurement sensors 20 to the data recording unit 120 and the sensor selection unit 140.

[0065] The data recording unit 120 records the measurement data. As an example, the data recording unit 120 can record the measurement data provided by the measurement data acquisition unit 110 from multiple measurement sensors 20 in a time sequence for each measurement sensor 20.

[0066] The environmental data acquisition unit 130 acquires environmental data from the environmental sensors 30, obtained by measuring the manufacturing environment of the product made from raw materials. As an example, similar to the measurement data acquisition unit 110, the environmental data acquisition unit 130 acquires environmental data from each of the plurality of environmental sensors 30 sequentially via a communication network. Furthermore, in the above description, as an example, the environmental data acquisition unit 130 acquires environmental data from each of the plurality of environmental sensors 30 via a communication network, but this is not a limitation. Similar to the measurement data acquisition unit 110, the environmental data acquisition unit 130 may also acquire environmental data from each of the plurality of environmental sensors 30 via other units different from the communication network, such as user input or various storage devices.

[0067] The environmental data acquisition unit 130 can acquire at least one of the following as environmental data: vibration, temperature, humidity, illuminance, odor, gas concentration, pressure, air pressure, stress, magnetic field, sound, and images in the manufacturing environment. Additionally, the environmental data acquisition unit 130 can also acquire values ​​generated using mathematical formulas based on these data as environmental data. The environmental data acquisition unit 130 provides environmental data acquired from each of the plurality of environmental sensors 30 to the sensor selection unit 140.

[0068] The sensor selection unit 140 acquires measurement data provided by the measurement data acquisition unit 110. Additionally, the sensor selection unit 140 acquires environmental data provided by the environmental data acquisition unit 130. Then, the sensor selection unit 140 selects a specific sensor from the measurement sensors 20 that measure the object to be manufactured, based on the correlation with the environmental sensor 30. At this time, the sensor selection unit 140 may, for example, determine the correlation of the measurement sensor 20 based on its distance from the environmental sensor 30. Furthermore, for example, the sensor selection unit 140 may determine the correlation of the measurement sensor 20 based on the category of physical quantities measured by the environmental sensor. Additionally, the sensor selection unit 140 may, for example, determine the correlation of the measurement sensor 20 based on the correlation between the temporal changes of the environmental data measured by the environmental sensor 30 and the temporal changes of the measurement data measured by the measurement sensor 20. This will be described later. The sensor selection unit 140 provides information related to the selected specific sensor to the parameter setting unit 150.

[0069] The parameter setting unit 150 obtains information related to a specific sensor from the sensor selection unit 140. Then, based on environmental data, the parameter setting unit 150 sets the measurement parameters for that specific sensor. For example, the parameter setting unit 150 can set the measurement period of the manufactured object to the measurement parameters of the manufacturing environment measured by the specific sensor. Additionally, the parameter setting unit 150 can set the sensitivity of the manufactured object to the measurement parameters of the manufacturing environment measured by the specific sensor. This will be described later. Correspondingly, the measurement sensor 20 measures the manufactured object according to the parameters set by the parameter setting unit 150.

[0070] Additionally, the parameter setting unit 150 can also provide setting information related to the set measurement parameters to the data recording unit 120. This setting information may include, for example, information indicating at what time the measurement parameters were changed (e.g., a flag). Correspondingly, in addition to recording measurement data, the data recording unit 120 can also record information indicating the time at which the measurement parameters were changed.

[0071] Figure 2This diagram illustrates an example configuration of the measuring sensor 20 and the environmental sensor 30 installed in factory 10. As an example, the diagram shows the manufacturing of products X and Y from raw materials M and N via flow path AC in factory 10. As shown in the diagram, it is assumed that measuring sensor 20a1 (also referred to as "measuring sensor 20a") is installed in flow path A. Furthermore, it is assumed that multiple measuring sensors 20b1, 20b2, 20b3, 20b4, and 20b5 (collectively referred to as "measuring sensors 20b") are installed from upstream to downstream in flow path B. Additionally, it is assumed that multiple measuring sensors 20c1, 20c2, 20c3, 20c4, and 20c5 (collectively referred to as "measuring sensors 20c") are installed from upstream to downstream in flow path C. Furthermore, measuring sensors 20a, 20b, and 20c are collectively referred to as "measuring sensor 20". Furthermore, in order to measure various manufacturing environments at various locations within the factory 10, it is assumed that multiple environmental sensors 30i, 30j, 30k, and 30l (collectively referred to as "environmental sensors 30") are installed in the factory 10. The data management system 100 of this embodiment acquires environmental data, for example, from the environmental sensors 30 installed in such a factory 10. Then, based on the acquired environmental data, the data management system 100 sets measurement parameters for a specific sensor selected from the measurement sensors 20. The process will be described in detail below.

[0072] Figure 3 This is an example of the process by which the data management system 100 of this embodiment sets measurement parameters based on environmental data.

[0073] In step 310, the data management system 100 acquires measurement data. For example, the measurement data acquisition unit 110 acquires measurement data of the manufactured object from each of the plurality of measurement sensors 20 in a timely manner via a communication network. At this time, the measurement data acquisition unit 110 can acquire measurement data of the manufactured object from each of the plurality of measurement sensors 20, such as the flow rate, pressure, temperature, and combinations thereof of raw materials M and N, semi-finished products, and products X and Y flowing through flow paths A, B, and C. The measurement data acquisition unit 110 provides the measurement data acquired from each of the plurality of measurement sensors 20 to the data recording unit 120 and the sensor selection unit 140.

[0074] In step 320, the data management system 100 records the measurement data. As an example, the data recording unit 120 records the measurement data acquired by the measurement data acquisition unit 110 from each of the plurality of measurement sensors 20 in step 310 in a time sequence for each measurement sensor 20.

[0075] In step 330, the data management system 100 acquires environmental data. For example, the environmental data acquisition unit 130 acquires environmental data from each of a plurality of environmental sensors 30 in a time-sequential manner, based on measurements of the manufacturing environment from which the product is manufactured from raw materials, via a communication network. At this time, the environmental data acquisition unit 130 can acquire, for example, at least one of the following environmental data: vibration, temperature, humidity, illuminance, odor, gas concentration, pressure, air pressure, stress, magnetic field, sound, and image from the manufacturing environment. For example, the environmental data acquisition unit 130 acquires environmental data from environmental sensor 30i, based on measurements of vibration in the manufacturing environment. Additionally, the environmental data acquisition unit 130 acquires environmental data from environmental sensor 30j, based on measurements of gas concentration in the manufacturing environment. Furthermore, the environmental data acquisition unit 130 acquires environmental data from environmental sensor 30k, based on measurements of sound in the manufacturing environment. Additionally, the environmental data acquisition unit 130 acquires environmental data from environmental sensor 30l, based on measurements of temperature in the manufacturing environment. The environmental data acquisition unit 130 provides the environmental data acquired from each of the plurality of environmental sensors 30 to the sensor selection unit 140. Furthermore, this figure illustrates, as an example, the acquisition of environmental data by the data management system 100 after acquiring measurement data, but it is not limited to this. The data management system 100 can acquire measurement data after acquiring environmental data. That is, step 330 can also be performed before steps 310 and 320.

[0076] In step 340, the data management system 100 determines whether the setting change conditions are met. For example, the sensor selection unit 140 compares the environmental data provided by the environmental data acquisition unit 130 in step 330 with a reference corresponding to each of the plurality of environmental sensors 30. Then, the environmental data acquisition unit 130 compares the data with the respective references, and if there is environmental data showing a change in state, it determines that the setting change conditions are met.

[0077] For example, the sensor selection unit 140 compares the vibration data obtained from the environmental sensor 30i with a predetermined reference corresponding to the environmental sensor 30i. Furthermore, if the sensor selection unit 140 detects that the vibration data has changed from a predetermined range to outside the range, it can determine that the setting change condition for the measurement parameter is met (e.g., setting the measurement parameter to a first value different from the initial value). That is, if the sensor selection unit 140 detects vibration outside the permissible range in the manufacturing environment based on environmental data, it can determine that the setting change condition for the measurement parameter is met. Additionally, if the sensor selection unit 140 subsequently detects that the vibration data remains within the predetermined range for a certain period, it can determine that the initialization condition for the measurement parameter is met (e.g., restoring the measurement parameter from the first value to the initial value). That is, if the sensor selection unit 140 does not detect vibration outside the permissible range in the manufacturing environment based on environmental data for a certain period, it can determine that the initialization condition for the measurement parameter is met. Furthermore, for example, if the sensor selection unit 140 detects that the vibration data has been in a stable range that is the same as or different from the predetermined range for a certain period of time in a stable state, it can determine that the setting change condition of the measurement parameter is met (for example, the condition of setting the measurement parameter to a second value that is different from the initial value).

[0078] Similarly, the sensor selection unit 140 compares the gas concentration data obtained from the environmental sensor 30j with a predetermined reference corresponding to the environmental sensor 30j. Furthermore, if the sensor selection unit 140 detects that the concentration of a specific gas component in the gas concentration data obtained from the environmental sensor 30j has changed from a predetermined range to outside the range, it can determine that the setting change condition for the measurement parameters has been met. That is, if the sensor selection unit 140 detects a gas leak in the manufacturing environment based on environmental data, it can determine that the setting change condition for the measurement parameters has been met. Additionally, if the sensor selection unit 140 subsequently detects that the concentration of a specific gas component remains within the aforementioned predetermined range for a certain period, it can also determine that the initialization condition for the measurement parameters has been met. That is, if the sensor selection unit 140 does not detect a gas leak in the manufacturing environment for a certain period based on environmental data, it can determine that the initialization condition for the measurement parameters has been met. Furthermore, for example, if the sensor selection unit 140 detects that the gas concentration data has remained within a stable range that is the same as or different from the predetermined range for a certain period of time in a stable state, it can also be determined that the conditions for changing the setting of the measurement parameters are met.

[0079] Similarly, the sensor selection unit 140 compares the sound data obtained from the environmental sensor 30k with a predetermined reference corresponding to the environmental sensor 30k. Furthermore, if the sensor selection unit 140 detects that the sound data obtained from the environmental sensor 30k has changed from a predetermined range to outside that range, it can determine that the setting change condition for the measurement parameters has been met. That is, if the sensor selection unit 140 detects an abnormal sound (e.g., an explosion or popping sound) in the manufacturing environment based on environmental data, it can determine that the setting change condition for the measurement parameters has been met. Additionally, if the sensor selection unit 140 detects that the sound data has remained within the aforementioned predetermined range for a certain period, it can determine that the initialization condition for the measurement parameters has been met. That is, if the sensor selection unit 140 does not detect any abnormal sound in the manufacturing environment for a certain period based on environmental data, it can determine that the initialization condition for the measurement parameters has been met. Furthermore, for example, if the sensor selection unit 140 detects that the sound data has remained within a stable range that is the same as or different from the aforementioned predetermined range for a certain period in a stable state, it can also determine that the setting change condition for the measurement parameters has been met.

[0080] Similarly, the sensor selection unit 140 compares the temperature data obtained from the environmental sensor 30l with a predetermined reference corresponding to the environmental sensor 30l. Furthermore, if the sensor selection unit 140 detects that the temperature data obtained from the environmental sensor 30l has changed from a predetermined range to outside the range, it can determine that the setting change condition for the measurement parameters has been met. That is, if the sensor selection unit 140 detects a temperature outside the permissible range in the manufacturing environment based on environmental data (for example, detecting a surface temperature or ambient temperature in a specific device that exceeds a predetermined threshold), it can determine that the setting change condition for the measurement parameters has been met. Additionally, if the sensor selection unit 140 subsequently detects that the temperature data remains within the aforementioned predetermined range for a certain period, it can also determine that the initialization condition for the measurement parameters has been met. That is, if the sensor selection unit 140 does not detect a temperature outside the permissible range in the manufacturing environment based on environmental data for a certain period, it can determine that the initialization condition for the measurement parameters has been met. Furthermore, for example, if the sensor selection unit 140 detects that the temperature data has remained within a stable range that is the same as or different from the predetermined range for a certain period of time in a stable state, it can also be determined that the setting change conditions of the measurement parameters are met.

[0081] If, in step 340, it is determined that the conditions for changing the setting of the measurement parameter are not met ("No"), the data management system 100 returns the process to step 310 to continue the flow. On the other hand, if, in step 340, it is determined that the conditions for changing the setting of the measurement parameter are met ("Yes"), the data management system 100 proceeds the process to step 350.

[0082] In step 350, the data management system 100 determines the correlation degree. As an example, the sensor selection unit 140 determines the correlation degree between the environmental sensor 30, which measures the environmental data used in step 340 when the conditions for changing the setting of the measurement parameters are determined to be met, and the multiple measurement sensors 20.

[0083] For example, if vibration outside the permissible range in the manufacturing environment is detected in step 340, the sensor selection unit 140 determines the correlation between the environmental sensor 30i, which measured the vibration data used when the vibration was detected, and the plurality of measurement sensors 20. In this case, as an example, the sensor selection unit 140 can determine the correlation of the measurement sensors 20 based on the distance from the environmental sensor 30i. That is, the sensor selection unit 140 can determine a scored correlation (e.g., 1 to 0) for each of the plurality of measurement sensors 20 based on the distance from the location where the environmental sensor 30i is located to the location where each of the plurality of measurement sensors 20 is located. In this case, the sensor selection unit 140 can determine the correlation for each of the plurality of measurement sensors 20 such that it increases as the distance approaches (e.g., close to 1) and decreases as the distance recedes (e.g., close to 0).

[0084] Furthermore, in the above description, as an example, the correlation degree was determined based on the distance between the location where the target environmental sensor 30i is installed and the location where the measurement sensor 20 is installed. However, this is not a limitation. Instead of the above description, or in addition to the above description, the sensor selection unit 140 may also determine the correlation degree based on the distance between the location where the target environmental sensor 30i is installed and the flow path. That is, the sensor selection unit 140 may also determine the correlation degree for each of the plurality of measurement sensors 20, so that the measurement sensor 20 installed on the flow path (e.g., flow path A) that is closer to the target environmental sensor 30i has a higher correlation degree, and the measurement sensor 20 installed on the flow path that is farther away from the target environmental sensor 30i has a lower correlation degree.

[0085] Additionally, for example, if a temperature outside the permissible range in the manufacturing environment is detected in step 340, the sensor selection unit 140 determines the correlation between the environmental sensor 301, which measured the temperature data used when the temperature was detected, and the plurality of measuring sensors 20. As an example, when the environmental sensor 301 measures the surface temperature in the piping of flow path C, the sensor selection unit 140 may determine the correlation in such a way that the correlation of the measuring sensor 20c installed on flow path C is higher than that of the measuring sensors 20a and 20b installed on other flow paths A and B. In this case, the sensor selection unit 140 may also determine the scored correlation for each of the plurality of measuring sensors 20c installed on flow path C based on the distance from the location where the environmental sensor 301 is installed to the location where each of the plurality of measuring sensors 20c is installed.

[0086] Alternatively, or in addition, as an example, the sensor selection unit 140 can determine the correlation of the measuring sensors 20 based on the category of physical quantities measured by the environmental sensor 30. For example, if a gas leak is detected in the manufacturing environment in step 340, the correlation can be determined for each of the multiple measuring sensors 20, such that the measuring sensor 20 with higher participation in detecting the component of the gas leak has a higher correlation, and the measuring sensor 20 with lower participation has a lower correlation. That is, if the specific gas component of the gas leak is detected to be caused by raw material M, the sensor selection unit 140 can determine the correlation in such a way that the correlation of the measuring sensor 20a provided on flow path A, and the correlation of the measuring sensors 20b3, 20b4, and 20b5 provided on flow path B that are located downstream of the confluence point with flow path A, are higher than the correlation of the measuring sensor 20c provided on flow path C, and the correlation of the measuring sensors 20b1 and 20b2 provided on flow path B that are located upstream of the confluence point with flow path A. In other words, the sensor selection unit 140 can determine the correlation degree for each of the multiple measuring sensors 20 based on the correlation between the type of physical quantity measured by the environmental sensor 30 and the measurement object (e.g., raw materials, semi-finished products, and finished products) measured by the measuring sensor 20.

[0087] Furthermore, if abnormal sounds are detected in the manufacturing environment in step 340, the sensor selection unit 140 may determine the correlation degree in such a way that the correlation degree of the pressure measuring sensor 20 among the plurality of measuring sensors 20 is higher than that of the flow rate and temperature measuring sensors 20 among the plurality of measuring sensors 20. In other words, the sensor selection unit 140 may also determine the correlation degree for each of the plurality of measuring sensors 20 based on the correlation between the type of physical quantity measured by the environmental sensor 30 and the type of physical quantity measured by the measuring sensors 20.

[0088] Alternatively, or as an example, the sensor selection unit 140 can determine the correlation degree of the measurement sensor 20 based on the correlation between the temporal changes of the environmental data measured by the environmental sensor 30 and the temporal changes of the measurement data measured by the measurement sensor 20. For example, if an abnormal sound is detected in the manufacturing environment in step 340, the correlation degree can be determined such that the correlation degree of the measurement sensor 20 whose temporal change characteristics of the measurement data changed with respect to the timing of the abnormal sound is higher than that of the measurement sensor 20 whose temporal characteristics did not change. That is, assuming that an abnormal sound is detected based on environmental data from the environmental sensor 30k, the temporal change characteristics of the measurement data of the measurement sensor 20a provided on flow path A and the measurement sensor 20b provided on flow path B did not change before and after the occurrence of the abnormal sound, while the temporal change characteristics of the measurement data of the measurement sensor 20c provided on flow path C changed before and after the occurrence of the abnormal sound. In this case, the sensor selection unit 140 can determine the correlation degree in such a way that the correlation degree of the sensor 20c is higher than that of the sensors 20a and 20b.

[0089] In this way, the sensor selection unit 140 determines the correlation degree for each of the multiple measuring sensors 20 using one or more indicators. Alternatively, when determining the correlation degree using multiple indicators, the sensor selection unit 140 can also determine each correlation degree for each of the multiple indicators. Alternatively, the sensor selection unit 140 can also determine a correlation degree by performing calculations (e.g., multiplication) on each correlation degree determined by the multiple indicators. In this case, when determining a correlation degree by performing calculations on each correlation degree, the sensor selection unit 140 can also use different weights for each indicator.

[0090] In step 360, the data management system 100 selects a specific sensor. For example, the sensor selection unit 140 selects a specific sensor from the measurement sensors 20 that measure the object being manufactured, based on the correlation with the environmental sensor 30. For instance, the sensor selection unit 140 may select one or more measurement sensors 20 whose correlation, determined in step 350, exceeds a predetermined threshold (e.g., measurement sensors 20 with a correlation of 0.8 or higher) as specific sensors. Alternatively, or otherwise, the sensor selection unit 140 may select one or more measurement sensors 20 whose correlation, determined in step 350, is relatively high (e.g., measurement sensors 20 with a correlation ranking second highest). The sensor selection unit 140 provides information related to the selected specific sensor to the parameter setting unit 150.

[0091] In step 370, the data management system 100 sets the measurement parameters. For example, the parameter setting unit 150 acquires information related to the specific sensor selected in step 360. Then, based on environmental data, the parameter setting unit 150 sets the measurement parameters for the specific sensor. At this time, the parameter setting unit 150 can, for example, set the measurement period of the manufactured object to the measurement parameters of the specific sensor's measurement environment. Additionally, the parameter setting unit 150 can, for example, set the sensitivity of the manufactured object to the measurement parameters of the specific sensor's measurement environment.

[0092] That is, when vibrations outside the permissible range in the manufacturing environment are detected based on environmental data from environmental sensor 30i, and measurement sensors 20b4 and 20b3, which are relatively close to environmental sensor 30i, are selected as specific sensors, the parameter setting unit 150 can set measurement parameters for these specific sensors, making the measurement period of the manufactured object shorter than the value before the setting change (initial value). Similarly, when vibrations outside the permissible range in the manufacturing environment are detected based on environmental data from environmental sensor 30i, and measurement sensors 20b4 and 20b3, which are relatively close to environmental sensor 30i, are selected as specific sensors, the parameter setting unit 150 can set measurement parameters for these specific sensors, making the sensitivity of the manufactured object higher than the value before the setting change (initial value). At this time, the parameter setting unit 150 can set measurement parameters corresponding to the correlation degree for specific sensors. As an example, when the correlation of sensor 20b4 is higher than that of sensor 20b3, the parameter setting unit 150 can set the measurement parameters for these specific sensors in such a way that the rate of change of the measurement parameters of sensor 20b4 before and after the setting change is greater than the rate of change of the measurement parameters of sensor 20b3 before and after the setting change. In this way, the parameter setting unit 150 can change the measurement parameters of specific sensors even when the environmental data is outside a predetermined range.

[0093] Furthermore, if, based on environmental data from environmental sensor 30i, no vibration outside the permissible range in the manufacturing environment is detected for a certain period, the parameter setting unit 150 can change the measurement parameters of these specific sensors to the values ​​before the setting change (initial values). In this way, the parameter setting unit 150 can initialize the measurement parameters when the environmental data is within a predetermined range. Additionally, the above description illustrates, as an example, the parameter setting unit 150 initializes the measurement parameters by restoring the measurement parameters in specific sensors to the values ​​before the setting change. However, it is not limited to this. The parameter setting unit 150 can also initialize the measurement parameters by restoring the measurement parameters in specific sensors to the values ​​at the start of operation of factory 10. Furthermore, in a stable state, if, based on environmental data from environmental sensor 30i, the vibration in the manufacturing environment remains within a stable range for a certain period, the parameter setting unit 150 can set the measurement parameters for these specific sensors such that the measurement period of the manufactured object becomes a second value longer than the value before the setting change (initial value). Similarly, in a stable state, based on environmental data from the environmental sensor 30i, if the vibration in the manufacturing environment has remained within a stable range for a certain period of time, the parameter setting unit 150 can set measurement parameters for these specific sensors, so that the sensitivity of measuring the manufactured object becomes a second value that is lower than the value before the setting change (initial value).

[0094] Then, the parameter setting unit 150 provides setting information related to the measurement parameters set in this way to the data recording unit 120. Furthermore, as described above, this setting information may include information indicating at what time the measurement parameters were changed. Correspondingly, in addition to recording the measurement data, the data recording unit 120 may also record information indicating the time at which the measurement parameters were changed.

[0095] Conventionally, techniques exist for obtaining information perceived by operators from sensor measurements. In these prior art techniques, this information is additionally acquired to determine the operational status of the equipment. In contrast, the data management system 100 of this embodiment acquires environmental data from the environmental sensor 30. Then, based on the correlation with the environmental sensor 30, the data management system 100 selects a specific sensor from the measurement sensors 20 and sets the measurement parameters of that specific sensor based on the environmental data. Thus, the data management system 100 of this embodiment can appropriately change the measurement parameters of the measurement sensors 20, which were previously fixed or manually set based on the operator's experience or intuition, based on the environmental data acquired from the environmental sensor 30. Furthermore, the data management system 100 of this embodiment acquires at least one of the following environmental data from the manufacturing environment: vibration, temperature, humidity, illuminance, odor, gas concentration, pressure, air pressure, stress, magnetic field, sound, and images. Therefore, the data management system 100 of this embodiment can set measurement parameters considering not only the states perceived by the operator's five senses but also states that cannot be perceived by human senses alone. Furthermore, the data management system 100 of this embodiment determines the correlation degree, for example, based on the distance from the environmental sensor 30, the type of physical quantity measured by the environmental sensor 30, and the correlation between the temporal changes of the environmental data and the temporal changes of the measurement data. Therefore, according to the data management system 100 of this embodiment, when changing the measurement parameters, a specific sensor as the target can be automatically selected from multiple measurement sensors 20 according to objective indicators. Additionally, the data management system of this embodiment changes the measurement parameters when the environmental data is outside a predetermined range. In this case, the data management system 100 of this embodiment sets, for example, the measurement period or sensitivity of the manufactured object as the measurement parameters. Therefore, according to the data management system 100 of this embodiment, when the environmental data is outside a predetermined range, i.e., when some anomalies are detected in the manufacturing environment, the measurement period or sensitivity of the measurement sensor 20 for measuring the manufactured object is changed, thus enabling the measurement sensor 20 to perform the measurement of the manufactured object under measurement conditions suitable for the manufacturing environment. Furthermore, the data management system 100 of this embodiment initializes the measurement parameters when the environmental data is within a predetermined range. Therefore, according to the data management system 100 of this embodiment, when the manufacturing environment returns to a stable state, the measurement sensor 20 can perform measurement of the manufactured object using the initially set setting change conditions. The data management system 100 of this embodiment also includes a measurement data acquisition unit 110 and a data recording unit 120. Therefore, the data management system 100 of this embodiment can realize both the function of a data recorder and the function of setting measurement parameters within the same system.Furthermore, in the data management system 100 of this embodiment, the data recording unit 120 records not only the measurement data but also information indicating the timing of changes to the measurement parameters. Therefore, according to the data management system 100 of this embodiment, it is possible to establish a correlation between the measurement data recorded in chronological order and the timing of changes to the measurement parameters, and to identify the setting conditions under which the measurement data at each time point was measured.

[0096] Figure 4 This is an example of a block diagram illustrating a modified version of the data management system 100 of this embodiment. Figure 4 In the middle, for those with Figure 1 Components with the same function and structure are labeled with the same reference numerals, and descriptions are omitted except for the following differences. The data management system 100 of this variant also includes a list output unit 410 and an interface unit 420.

[0097] In the above description, as an example, the sensor selection unit 140 automatically selects a specific sensor based on the correlation degree determined for each of the plurality of measurement sensors 20. However, in the data management system 100 of this modified example, after determining the correlation degree for each of the plurality of measurement sensors 20, the sensor selection unit 140 provides information related to one or more candidate sensors with a correlation degree higher than a predetermined threshold to the list output unit 410.

[0098] The list output unit 410 outputs a list of measurement sensors 20, i.e., candidate sensors, whose correlation is higher than a predetermined threshold. As an example, the list output unit 410 may be a display unit, displaying the list of candidate sensors provided by the sensor selection unit 140. However, it is not limited to this. The list output unit 410 may be a communication unit, for example, or it may send the list of candidate sensors provided by the sensor selection unit 140 to other systems.

[0099] Interface unit 420 accepts user input. For example, interface unit 420 obtains input from a user who has viewed a list of candidate sensors via a GUI (Graphical User Interface). For instance, interface unit 420 obtains information via the GUI regarding which measurement sensor 20 the user selects as a specific sensor from the list of candidate sensors.

[0100] Then, in the data management system 100 of this modified example, the sensor selection unit 140 selects a specific sensor from the candidate sensors based on user input. As an example, the sensor selection unit 140 selects one or more measurement sensors 20 selected by the user from the candidate sensors as the specific sensor.

[0101] Furthermore, in the data management system 100 of this modified example, the sensor selection unit 140 can also determine the correlation of the measurement sensor 20 based on the actual operation of the selected sensor. In the data management system 100 of this modified example, the sensor selection unit 140 can know which measurement sensor 20 the user actually selected as the specific sensor from the candidate sensors through user input via the interface unit 420. That is, the sensor selection unit 140 can know the actual operation of the selected sensor. Therefore, the sensor selection unit 140 can determine the correlation based on the actual operation in such a way that, for example, for the environmental sensor 30 as the target, the correlation of the measurement sensor 20 that was previously selected as the specific sensor and has actual operation is higher than that of the measurement sensor 20 that was selected as the specific sensor but has no actual operation.

[0102] Figure 5 This figure shows an example of a list of candidate sensors output by the data management system 100, a variation of this embodiment. In this figure, an example is shown where measurement sensors 20, up to the fifth highest correlation level, are listed as candidate sensors for environmental sensor 30i. As shown in the figure, the list output unit 410 can, for example, correlate the correlation level with the identification information of the measurement sensor 20 and output a list of candidate sensors arranged in descending order of correlation level. Then, the interface unit 420 can, for example, obtain information via a GUI related to which measurement sensor 20 (in this figure, measurement sensors 20b4 and 20a1) the user selected from the list of candidate sensors as a specific sensor.

[0103] The data management system 100 of this modified example outputs a list of candidate sensors. Then, the data management system 100 selects a specific sensor from the candidate sensors based on user input. Thus, according to the data management system 100 of this modified example, in the selection of a specific sensor, it can provide the user with a highly relevant candidate list and reflect the user's intention in the actual sensor selection. Furthermore, the data management system 100 of this modified example determines the relevance based on the actual operation of the selected sensor. Therefore, according to the data management system 100 of this modified example, it also considers past actual operations and can determine the relevance for each of the multiple measurement sensors 20.

[0104] Various embodiments of the present invention can be described with reference to flowcharts and block diagrams, wherein a block may represent (1) a stage of the process of performing an operation, or (2) a portion of a device having the function of performing an operation. Specific stages and portions may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable medium, and / or a processor provided with computer-readable instructions stored on a computer-readable medium. Dedicated circuitry may include digital and / or analog hardware circuitry and may include integrated circuits (ICs) and / or discrete circuitry. Programmable circuitry may include reconfigurable hardware circuitry containing logic AND, logic OR, logic XOR, logic NAND, logic NOR and other logic operations, memory elements such as flip-flops, registers, field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), etc.

[0105] Computer-readable media can include any tangible device capable of storing instructions executable by a suitable device, resulting in a computer-readable medium having instructions stored therein comprising executable instructions for creating units to perform operations specified in a flowchart or block diagram. Examples of computer-readable media include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of computer-readable media include floppy disks (registered trademark), magnetic disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), Blu-ray disc (registered trademark), memory stick, integrated circuit card, etc.

[0106] Computer-readable instructions may include assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, and any combination of source code or object code written in one or more programming languages, including object-oriented programming languages ​​such as Smalltalk (registered trademark), JAVA (registered trademark), and C++, and existing procedural programming languages ​​such as the "C" programming language or similar programming languages.

[0107] Computer-readable instructions can be provided via a local area network (LAN), a wide area network (WAN) such as the Internet, to the processor or programmable circuitry of a general-purpose computer, a special-purpose computer, or other programmable data processing device, for the purpose of creating units that perform the operations specified in a flowchart or block diagram. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0108] Figure 6 This describes an example of a computer 2200 that can implement all or part of the various embodiments of the present invention. A program installed on the computer 2200 enables the computer 2200 to function as an operation associated with or one or more parts of a device according to embodiments of the present invention, or enables the computer 2200 to perform that operation or those one or more parts, and / or enables the computer 2200 to perform a process or a stage of that process according to embodiments of the present invention. Such a program can be executed by the CPU 2212 to cause the computer 2200 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described in this specification.

[0109] The computer 2200 of this embodiment includes a CPU 2212, RAM 2214, a graphics controller 2216, and a display device 2218, which are interconnected via a host controller 2210. The computer 2200 also includes input / output units, such as a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an IC card driver, which are connected to the host controller 2210 via an input / output controller 2220. The computer also includes conventional input / output units, such as a ROM 2230 and a keyboard 2242, which are connected to the input / output controller 2220 via an input / output chip 2240.

[0110] CPU 2212 operates according to the program stored in ROM 2230 and RAM 2214, thereby controlling each unit. Graphics controller 2216 obtains image data generated by CPU 2212 from frame buffers or other storage provided in RAM 2214 or from within itself, and displays the image data on display device 2218.

[0111] Communication interface 2222 communicates with other electronic devices via a network. Hard disk drive 2224 stores programs and data used by CPU 2212 within computer 2200. DVD-ROM drive 2226 reads programs or data from DVD-ROM 2201 and provides programs or data to hard disk drive 2224 via RAM 2214. IC card drive reads programs and data from IC card and / or writes programs and data to IC card.

[0112] ROM 2230 stores boot programs and / or programs dependent on the hardware of computer 2200 that are executed by computer 2200 upon activation. Input / output chip 2240 can also connect various input / output units to input / output controller 2220 via parallel ports, serial ports, keyboard ports, mouse ports, etc.

[0113] The program is provided by a computer-readable medium such as a DVD-ROM 2201 or an IC card. The program is read from the computer-readable medium, installed in a hard disk drive 2224, RAM 2214, or ROM 2230, which is also an example of a computer-readable medium, and executed by a CPU 2212. The information processing written in these programs is read by the computer 2200, which provides cooperation between the program and the aforementioned various types of hardware resources. An apparatus or method can be constructed by implementing the manipulation or processing of information according to the use of the computer 2200.

[0114] For example, when communication is performed between computer 2200 and an external device, CPU 2212 can execute a communication program loaded in RAM 2214 and, based on the processing written in the communication program, instruct communication interface 2222 to perform communication processing. Under the control of CPU 2212, communication interface 2222 reads transmission data stored in a transmission buffer processing area provided in a recording medium such as RAM 2214, hard disk drive 2224, DVD-ROM 2201, or IC card, and sends the read transmission data to the network, or writes received data received from the network to a receive buffer processing area provided on the recording medium, etc.

[0115] In addition, CPU 2212 can also read all or necessary portions of files or databases stored in external recording media such as hard disk drive 2224, DVD-ROM drive 2226 (DVD-ROM 2201), IC card, etc., into RAM 2214, and perform various types of processing on the data in RAM 2214. Then, CPU 2212 writes the processed data back to the external recording media.

[0116] Various types of information, such as various types of programs, data, tables, and databases, can be stored in the recording medium and processed. The CPU 2212 can perform various types of processing on data read from the RAM 2214 and write the results back to the RAM 2214. This processing includes various types of operations specified by program instruction sequences as described throughout this disclosure, such as information processing, conditional judgment, conditional branching, unconditional branching, and information retrieval / replacement. Furthermore, the CPU 2212 can also retrieve information from files, databases, etc., within the recording medium. For example, when multiple entries with attribute values ​​of a first attribute respectively associated with the attribute value of a second attribute are stored in the recording medium, the CPU 2212 can retrieve from these multiple entries an entry that matches the condition and specifies the attribute value of the first attribute, and read the attribute value of the second attribute stored in that entry, thereby obtaining the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0117] The programs or software modules described above can be stored on or near computer-readable media on computer 2200. Alternatively, recording media such as hard disks or RAM provided in a server system connected to a dedicated communication network or the Internet can also be used as computer-readable media, thereby providing programs to computer 2200 via the network.

[0118] The present invention has been described above using embodiments, but the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications or improvements can be made to the above embodiments. As can be understood from the claims, methods obtained by such modifications or improvements can also be included within the technical scope of the present invention.

[0119] It should be noted that the execution order of actions, processes, steps, and stages in the apparatus, system, program, and method shown in the claims, specification, and drawings can be implemented in any order, unless specifically stated as "before," "first," etc., and unless the output of a previous process is used for a subsequent process. Even if terms such as "firstly," "next," etc., are used for convenience in describing the flow of actions in the claims, specification, and drawings, it does not mean that they must be implemented in that order.

Claims

1. A data management system comprising: an environment data acquisition section that acquires environment data from an environment sensor that is an IoT (Internet of Things) sensor, the environment data being data obtained by measuring a manufacturing environment in which a product is manufactured from a raw material; a sensor selection section that selects, from among measurement sensors that measure a process of a manufacturing target that is an object of the manufacturing, a sensor whose degree of association with the environment sensor exceeds a predetermined threshold value or whose degree of association with the environment sensor is relatively high, as a specific sensor; a parameter setting section that sets, based on the environment data, a measurement parameter in the specific sensor, the sensor selection section determining the degree of association of the measurement sensor based on a correlation between a time-series change in the environment data measured by the environment sensor and a time-series change in measurement data measured by the measurement sensor.

2. The data management system according to claim 1, wherein the sensor selection section determines the degree of association of the measurement sensor based on a distance from the environment sensor.

3. The data management system according to claim 1 or 2, wherein the sensor selection section determines the degree of association of the measurement sensor based on a category of a physical quantity measured by the environment sensor.

4. The data management system according to claim 1 or 2, wherein the sensor selection section determines the degree of association of the measurement sensor based on an actual operation in which the specific sensor is selected.

5. The data management system according to claim 1 or 2, wherein the data management system further comprises a list output section that outputs a list of candidate sensors that are the measurement sensors whose degrees of association are higher than a predetermined threshold value, the sensor selection section selects the specific sensor from among the candidate sensors according to a user input.

6. The data management system according to claim 1 or 2, wherein the parameter setting section changes the measurement parameter when the environment data is outside a predetermined range.

7. The data management system according to claim 6, wherein the parameter setting section initializes the measurement parameter when the environment data is within a predetermined range.

8. The data management system according to claim 1 or 2, wherein the parameter setting section sets, as the measurement parameter, a period for measuring the manufacturing target.

9. The data management system according to claim 1 or 2, wherein the parameter setting section sets, as the measurement parameter, a sensitivity for measuring the manufacturing target.

10. The data management system according to claim 1 or 2, wherein the environment data acquisition section acquires, as the environment data, at least any one of a vibration, a temperature, a humidity, an illuminance, an odor, a gas concentration, a pressure, an air pressure, a stress, a magnetic field, a sound, and an image in the manufacturing environment.

11. The data management system according to claim 1 or 2, wherein the data management system further comprises: ​ The measurement data acquisition section acquires measurement data obtained by measuring the manufacturing object from the measurement sensor; and The data recording section records the measurement data.

12. The data management system according to claim 11, wherein The data recording section further records information indicating timing at which the measurement parameter is changed.

13. A data management method comprising the steps of: acquiring environmental data from an environmental sensor that is an IoT (Internet of Things) sensor, the environmental data being data obtained by measuring a manufacturing environment in which a product is manufactured from a raw material; selecting, as a specific sensor, a sensor whose correlation degree with the environmental sensor exceeds a predetermined threshold or whose correlation degree with the environmental sensor is relatively high, from among measurement sensors that measure a manufacturing object that is an object of the manufacturing, based on a correlation between a time-series change in the environmental data measured by the environmental sensor and a time-series change in measurement data measured by the measurement sensor; and setting a measurement parameter in the specific sensor based on the environmental data, In the selection of the specific sensor, the correlation degree of the measurement sensor is determined based on a correlation between a time-series change in the environmental data measured by the environmental sensor and a time-series change in measurement data measured by the measurement sensor.

14. A recording medium that records a data management program that is executed by a computer and causes the computer to function as: an environmental data acquisition section that acquires environmental data from an environmental sensor that is an IoT (Internet of Things) sensor, the environmental data being data obtained by measuring a manufacturing environment in which a product is manufactured from a raw material; a sensor selection section that selects, as a specific sensor, a sensor whose correlation degree with the environmental sensor exceeds a predetermined threshold or whose correlation degree with the environmental sensor is relatively high, from among measurement sensors that measure a manufacturing object that is an object of the manufacturing, based on a correlation between a time-series change in the environmental data measured by the environmental sensor and a time-series change in measurement data measured by the measurement sensor; and a parameter setting section that sets a measurement parameter in the specific sensor based on the environmental data, the sensor selection section determines the correlation degree of the measurement sensor based on a correlation between a time-series change in the environmental data measured by the environmental sensor and a time-series change in measurement data measured by the measurement sensor. ​

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