JP7633884B2 - Data management system and method thereof - Google Patents

Description

The present invention relates to a data management system and method for managing test data.

When inspecting various manufactured products on each production line at a factory manufacturing site, the inspection results for each process are collected as inspection data, and the collected inspection data is analyzed. When analyzing data, for example, there is a technique for determining whether multiple columns that have similar attributes or store similar data are synonymous columns (columns that store the same information for the same management target) (see Patent Document 1). There is also a technique that makes it possible to absorb differences in the format of data generated by production equipment (see Patent Document 2).

JP 2011-232879 A JP 2020-57089 A

When collecting inspection result data from each process, if the inspection specifications change over time, the meaning of the inspection result data will change, even for the same process. Also, data with the same meaning may be stored in different inspection items (data items). For example, if the processing of multiple inspection devices is distributed, the inspection results of inspection devices with different inspection specifications may end up with data with the same meaning, depending on the processing method of each inspection device. For this reason, simply recording the change in the process in the inspection results makes it impossible to distinguish whether the inspection results are for the same inspection specifications or different inspection specifications, and unrelated data may be mixed in with the inspection result data for each process, resulting in a lack of necessary data for the inspection results for each process.

The object of the present invention is to manage change description data by distinguishing between synonymous data and non-synonymous data.

In order to solve the above problem, the present invention comprises a data storage unit that stores time-series inspection data obtained by an inspection device inspecting an inspection target, a change description storage unit that stores, in association with the inspection data, data in a synonymous or heterosynonymous relationship indicating that at least one of the inspection specifications, inspection items, or inspection targets of the inspection device has been changed, and that includes the time of the change and the content of the change, a data extraction unit that uses the data storage unit and the change description storage unit as search targets to extract data from the search target, and a data extraction instruction unit that outputs an extraction request including the extraction target item and time to the data extraction unit. When the data extraction unit receives the extraction request, it searches for the search target based on the received extraction request, extracts from the data storage unit the inspection data that belongs to the time specified in the extraction request and corresponds to the extraction target item specified in the extraction request, extracts from the change description storage unit the change description data including the change content at the change time corresponding to the time specified in the extraction request, determines whether the synonymous or heterosynonymous data exists in the extracted change description data, and normalizes and outputs the extracted inspection data based on the determination result.

According to the present invention, it is possible to distinguish between synonymous data and non-synonymous data and manage change description data.

1 is a configuration diagram illustrating an example of a configuration of a data management system according to a first embodiment of the present invention; FIG. 2 is a configuration diagram showing a display example of the display device according to the first embodiment of the present invention. FIG. 2 is a diagram showing an example of the configuration of change description data according to the first embodiment of the present invention; FIG. 11 is a diagram showing another example of the configuration of change description data according to the first embodiment of the present invention. 11 is a flowchart illustrating an example of pre-processing of a data extraction unit according to the first embodiment of the present invention. 11 is a flowchart showing an example of a change description data extraction process of the data extraction unit according to the first embodiment of the present invention. 11 is a flowchart illustrating an example of a data normalization process of the data extraction unit according to the first embodiment of the present invention.

The following describes an embodiment of the present invention with reference to the drawings.

Figure 1 is a configuration diagram showing an example of the configuration of a data management system according to a first embodiment of the present invention. In Figure 1, the data management system 1 is composed of a computer (not shown) equipped with, for example, a processor, a main memory device, an auxiliary memory device, an input device, an output device, and a communication device, and is placed in a factory having a production line for manufacturing various products.

The processor is configured, for example, using a CPU (Central Processing Unit) or an MPU (Micro Processing Unit).

The main memory device is a device that stores computer programs and data, and is, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), or a non-volatile semiconductor memory.

The auxiliary storage device may be, for example, a hard disk drive, a solid state drive (SSD), an optical storage medium (e.g., a compact disc (CD) and a digital versatile disc (DVD)), a storage system, an integrated circuit card (IC card), a secure digital (SD) memory card, or a read/write device for recording media, as well as the storage area of a cloud server. Computer programs and data stored in the auxiliary storage device are loaded into the main storage device as needed.

Examples of input devices include keyboards, mice, touch panels, card readers, and audio input devices. Output devices (display devices) are user interfaces that provide the user with various information such as the progress and results of processing. Examples of output devices include screen display devices (i.e., liquid crystal monitors, LCDs (Liquid Crystal Displays), or graphics cards), audio output devices (i.e., speakers, etc.), or printing devices, etc.

The communication device is a wired or wireless communication interface that realizes communication with other devices via a communication means such as a LAN or the Internet. The communication device is, for example, a NIC (Network Interface Card), a wireless communication module, a USB (Universal Serial Bus) module, or a serial communication module.

The data management system 1 includes, as software resources, a change input unit 10, a change description registration unit 12, a change description storage unit 14, a data generation unit 16, a data registration unit 18, a data storage unit 20, a data extraction unit 22, a data extraction instruction unit 24, and an extracted data storage unit 26.

The change input unit 10 inputs information according to the operation of the change inputter as information from an operation terminal operated by the change inputter, such as a keyboard or mouse. For example, the change input unit 10 inputs information indicating the time (change time) when at least one of the inspection specifications, inspection items, and inspection devices in each process of the production line was changed and the change content (change content). The change description registration unit 12 registers the input information input from the change input unit 10, which includes the change time and the change description, in the change description storage unit 14. At this time, if information related to the change description belonging to the input information already exists in the change description storage unit 14, the change description registration unit 12 updates the already existing information with the input information and registers it. The change description data belonging to the input information stored in the change description storage unit 14 is data of synonymous or heterosynonymous relationship, and is stored in the storage area sequentially as time-series data.

Here, synonymous data means, for example, that the performance or function of multiple inspection devices is the same. Unlikely data means, for example, that the inspection specifications for one of multiple inspection devices are different from the inspection specifications for the other inspection device. In addition, if the change times (change times) are t1, t2, t3, ..., t(n-1), tn, for example, the change description data for each change time t1 to tn is stored sequentially in the memory area of the change description storage unit 14. At this time, the data extraction unit 22, which will be described later, manages the change description data stored in the change description storage unit 14 by setting the time period between change time t1 and change time t2 as phase 1, the time period between change time t2 and change time t3 as phase 2, ..., and the time period between change time t(n-1) and change time tn as phase (n-1).

The data generation unit 16 imports data from inspection devices at the production site, such as product inspection data, generates data in which information such as the inspection time and work target is added to the imported inspection data, and transfers the generated data to the data registration unit 18. When the data registration unit 18 receives inspection data transferred from the data generation unit 164, it registers the received inspection data in the data storage unit 20. At this time, if the received inspection data is in CSV (Comma Separated Value) format, the data registration unit 18 converts the CSV format inspection data into, for example, JSON (javascript (registered trademark) object notation) format inspection data, and registers the converted inspection data in the data storage unit 20.

When storing data such as test data in the data storage unit 20, each data is stored in the storage area in sequence as time-series data. Here, if the time stamps indicating the time of the test or the time of data collection are t1, t2, t3, ..., t(n-1), tn, the data at each time stamp t1 to tn is stored in the storage area of the data storage unit 20 in sequence for each time stamp. In this case, the data extraction unit 22, which will be described later, manages the data stored in the data storage unit 20 by setting the time period between time stamp t1 and time stamp t2 as phase 1, the time period between time stamp t2 and time stamp t3 as phase 2, ..., and the time period between time stamp t(n-1) and time stamp tn as phase (n-1). In this embodiment, for the sake of convenience, the time stamps t1 to tn of the data stored in the data storage unit 20 and the change times t1 to tn of the change description data stored in the change description storage unit 14 are set to the same time.

When an extraction request including items to be extracted (data items) and time (change time) is input from the data extraction instruction unit 24 operated by the data extraction supporter, the data extraction unit 22 searches the change description storage unit 14 and the data storage unit 20 as search targets based on the extraction request, extracts change description data from the change description storage unit 14 and test data from the data storage unit 20 as data for the time specified in the extraction request, normalizes the test data extracted from the data storage unit 20 by the contents of the change description data specified by the test data with the time specified in the extraction request (change time) as the reference time, and stores the normalized data in the extracted data storage unit 26 as extracted data.

In the software resources of the data management system 1, the processor reads and executes the computer programs stored in the main memory device, thereby realizing the various functions of the change input unit 10, the change description registration unit 12, the change description storage unit 14, the data generation unit 16, the data registration unit 18, the data storage unit 20, the data extraction unit 22, the data extraction instruction unit 24, and the extracted data storage unit 26.

2 is a block diagram showing a display example of the display device according to the first embodiment of the present invention. In FIG. 2, the display screen 100 of the display device is a screen for a change input person to operate an operation terminal to input information into the data management system 1, and is composed of a change time column 101, a change form column 102, an equivalent device ID column 103, an added device ID column 104, and a line configuration diagram display area 105. When the change input person performs an operation to change the time when the data such as the inspection specifications is changed to, for example, "January 12, 2021, 8:12:43", the change time column 101 displays the information "2021-01-12T08:12:43+0900". When the change input person performs an operation to add an equivalent device as an inspection device, for example, the change form column 102 displays the information "Equivalent device added". When the change input person performs an operation to specify an inspection device (equivalent device) that is connected in parallel to the added inspection device (additional device) and has the same performance as the added device, the equivalent device ID column 103 displays information such as "E12" as a device identifier that uniquely identifies the equivalent device. When the change input person performs an operation to specify the added inspection device (additional device), the additional device ID column 104 displays information such as "E13" as a device identifier that uniquely identifies the added device. The line configuration display area 105 displays device identifiers ("E01", "E11", "E12", "E21", "E31") that uniquely identify each inspection device (device) belonging to the line configuration of the production line E, and information on the connection lines that indicate the connection relationship between each device. In this case, the additional device with device identifier E13 is added to the production line E in a state of being connected in parallel to the equivalent device with device identifier E12. As a result, on production line E, after the change time, the inspection result data for the equivalent device (E12) and the inspection result data for the additional device (E13) are both managed as the same data.

The display screen 200 of the display device is a screen for the change input person to operate the operation terminal to input information into the data management system 1, and is composed of a change time column 201, a change form column 202, an old item ID column 203, a new item ID column 204, a conversion rule column 205, and a line configuration diagram display area 206. When the change input person performs an operation to change the time when data such as the inspection specifications for the inspection device (E21) was changed to, for example, "January 12, 2021, 8:12:43", the change time column 201 displays the information "2021-01-12T08:12:43+0900". When the change input person performs an operation to change the inspection specifications of the inspection device (E21) in the production line E, for example, the change form column 202 displays the information "inspection specification change". When the change input person performs an operation to identify an item before the change in the inspection specifications of the inspection device (E21) on production line E, information such as "E21-a" is displayed in the old item ID column 203 as the inspection item identifier that identifies the old item in the inspection specifications. When the change input person performs an operation to identify an item after the change in the inspection specifications of the inspection device (E21) on production line E, information such as "E21-a'" is displayed in the new item ID column 204 as the inspection item identifier that identifies the new item in the inspection specifications.

When the change input user performs an operation to convert the inspection specifications of the old conversion rule to the specifications of the new conversion rule, the conversion rule column 205 displays information such as "E21-a' = E21-a * 0.01" as the conversion rule for converting the inspection specifications of the old conversion rule to the specifications of the new conversion rule. This means that the scale for data belonging to data item E21-a after the change time "January 12, 2021, 8:12:43" becomes 1/100, and in order to align the scale of the data of each phase for calculation, the data before the change time is multiplied by 0.01 for comparison.

In the line configuration display area 206, similar to the line configuration display area 105, equipment identifiers ("E01", "E11", "E12", "E21", "E31") that uniquely identify each piece of equipment that makes up production line E and information indicating the connection relationships between each piece of equipment are displayed.

Figure 3 is a configuration diagram showing an example of the configuration of change description data according to the first embodiment of the present invention. In Figure 3, the change description storage unit 14 stores change description data 300 including, for example, change descriptions of synonymous relationships. The change description data 300 is data written in the JSON data format, and is an example description of data of synonymous relationships. In the change description data 300, for example, when equipment E13 (equipment having a synonymous relationship with equipment E12) having the same performance as equipment E12, which is an inspection device, is added to production line E at the time of "January 12, 2021, 8:12:43", data of "2021-01-12T08:12:43+0900" is recorded as the value ("rdf:value") of the change time (change time) specified by "cd:from", data of "E12" is recorded as the value ("line:name") of the equivalent equipment, which is a value specified by "cd:object", and data of "E13" is recorded as the value ("cd:addedSame") of the added equipment.

At this time, it is possible to determine that the change description data 300 is composed of synonymous data from the data identifying the added device ("cd:addedSame") and its value ("E13"), and the data identifying the equivalent device ("line:name") and its value ("E13"). In other words, it is possible to determine that device E12 and device E13 are devices that have a synonymous relationship with each other. Note that after this data is stored, if a change occurs that cancels the stored data, an operation is executed to add the time when the data to be canceled became invalid, using "cd:expiredAt" as a key, in the same format as "cd:from".

Figure 4 is a configuration diagram showing another example of the configuration of change description data related to Example 1 of the present invention. In Figure 4, the change description storage unit 14 stores, for example, change description data 400 including change descriptions of synonymous relationships. The change description data 400 is data written in the JSON data format and is an example of a description of synonymous data. In this change description data 400, for example, when the inspection specifications of an inspection device are changed and the inspection item is changed from the old item to the new item at 8:12:43 on January 12, 2021, the data of "2021-01-12T08:12:43+0900" is recorded as the value "rdf:value" of the change time (change time) specified by "cd:from". Additionally, in the change description data 400, the data "E21-a" is recorded as the value "cd:fromItem" (item name) of the old item identified by "cd:object", the data "E21-a'" is recorded as the value of the new item "cd:toItem", and the data "E21-a' = E21-a * 0.01" is recorded as the value of the conversion rule "cd:convEq".

At this time, it can be determined that the change description data 400 is composed of data with a synonymous relationship from the data identifying the old item ("cd:fromItem") and its item name data ("E21-a"), the data identifying the new item ("cd:toItem") and its item name data ("E21-a'"), and the data identifying the conversion rule ("cd:convEq"). In other words, since the old item (test item) and the new item (search item) have different test specifications and are synonymous with each other, it can be determined that a conversion rule has been specified.

The changed conversion rule means that after the time of the change, the data of the old items is multiplied by the constant "0.01", so that the scale when calculating the data becomes 1/100. Note that if a change occurs that cancels the stored data after this data is stored, an operation is executed to append the time when the data to be canceled became invalid, using "cd:expiredAt" as the key, in the same format as "cd:from".

Figure 5 is a flow chart showing an example of pre-processing of the data extraction unit according to the first embodiment of the present invention. In Figure 5, the data extraction unit 22 searches the change description data 300, 400 stored in the change description storage unit 14 as the search target, and extracts the time when some change occurred (change time) from the change description data stored in the change description storage unit 14, for example, the change description data 300, 400 (S11). At this time, for example, if change times (change times) t1, t2, t3, ..., tn exist in the change description data 300, 400 stored in the change description storage unit 14, these change times t1 to tn are extracted.

Next, the data extraction unit 22 extracts one or more change times (modification times) that are included in the period during which each change description is valid from each change description data stored in the change description storage unit 14, and divides each change description by the extracted change times (one or more change times) (S21). For example, if the valid period of a certain change description A is from change time a to change time b, and the change time that falls within the valid period of change time a to change time b is t3 (change time a < change time t3 < change time b), then change description A is divided into change description A1 that falls within change time a to change time t3, and change description A2 that falls within change time t3 to change time b. Here, the valid period means that change time a to change time b is within the valid period of change description A when the change time of the change content that has a change time after change time a of change description A and is closest to change description A among the change contents that overwrite the change contents included in change description A (for example, a change description that adds device E13 with the same meaning to device E12, and then a change description that states that device E12 and device E13 no longer have the same meaning appears).

Figure 6 is a flow chart showing an example of the change description data extraction process of the data extraction unit according to the first embodiment of the present invention. In Figure 6, when an extraction request is input from a data extraction instructing person via the data extraction instruction unit 24 with the instruction "Extract data item i_q at time t_q", the data extraction unit 22 searches for change description data in the change description storage unit 14 based on the time t_q, identifies the phase (time period) that includes the change time t_q from among the change description data, and sets the identified phase as phase p_q (S21). Note that hereinafter, t means time, i means item, p means phase, q means a number such as time or phase, and conv means convert.

Next, the data extraction unit 22 collects data (synonymous relationship description data) indicating descriptions of synonymous relationships included in the identified phase p_q from the change description data storage unit 14, extracts data items synonymous with the data item i_q instructed by the data extraction instructor from the collected synonymous relationship description data, and updates data item i_q with the extracted data item (S22). For example, from the change description data 300 in Figure 3, if the data item i_q instructed by the data extraction instructor is "line:name": "E12", "cd:addedSame": "E13" is extracted as a data item synonymous with this data item.

Next, the data extraction unit 22 initializes the initial value of the variable c with the value of q used in phase p_q (S23).

Next, the data extraction unit 22 collects data (opinion relationship description data) showing the change description of the synonymous relationship targeting the data item i_c from among the change description data stored in the change description storage unit 14, and creates a conversion rule set conv_c-1_c for the data of phase p_c-1 based on the collected synonymous relationship description data (S24). For example, as a change description of the synonymous relationship targeting the data item i_c, one in which the data item i_c is included in "cd:toItem" in FIG. 4 (E21-a) is collected, and based on the collected data, a conversion rule set conv_c-1_c for the data of phase p_c-1 (data of the change description having the change time included in phase p_c-1) is created. Specifically, a change description having a time in phase p_c-1 as the change time, for example, the information "E21-a'=E21-a*0.01" of the conversion rule "cd:convEq" in FIG. 4 is created as the conversion rule set conv_c-1_c. In this case, this means that data item E21-a' after the change time (8:12:43 on January 12, 2021) will have the same value as 1/100 of the value of data item E21-a before that. Therefore, by dividing the value of the data item before the change time by 1/100, the value of the data item before the change time can be compared on the same basis as the value of the data item belonging to phase p_c of the change time.

Next, the data extraction unit 22 extracts, from each change description data stored in the change description storage unit 14, change description data that belongs to phase p_c-1, which is one phase before phase p_c, and has a synonymous relationship (S25). For example, from the change description data 300 shown in FIG. 3, the data extraction unit 22 extracts information on "@type:cd:addEquipment" ("E13") as change description data that specifies an additional device. In step S25, the data extraction unit 22 also extracts, from each change description data stored in the change description storage unit 14, a data item that is synonymous with the data item that appears in "line:name" among the synonymous relationships in phase p_c, and sets the extracted data item as data item i_c-1. For example, in the change description data 300 shown in FIG. 3, the data item "cd:addedSame": "E13", which is a data item synonymous with the data item E12 that appears in "line:name", and indicates that a device E13 equivalent to E12 has been added, is set as data item i_c-1.

Then, the data extraction unit 22 sets the variable c to c-1 (S26), and determines whether the variable c is greater than 0 (S27). If the variable c is greater than 0, the process returns to step S24, and repeats the processes of steps S24 to S27 to collect data prior to the change time t_q until the variable c becomes 0. If the variable c is less than 0, the process proceeds to step S28, and the variable c is set to q again.

Next, the data extraction unit 22 collects change description data that indicates a change description of a different meaning relationship belonging to phase p_c+1 and targets data item i_c from among the change description data stored in the change description storage unit 14, and creates a conversion rule set conv_c+1_c for data belonging to phase p_c+1 based on the collected change description data (S29). For example, as change description data of a different meaning relationship belonging to phase p_c+1 and targeting data item i_c, from the change description data 400 in FIG. 4, data that includes information (E12) on data item i_c in "cd:from:Item" is collected. At this time, the conversion rule set conv_c+1_c for data belonging to phase p_c+1 is, for example, information ("E21-a'=E21-a*0.01") specified by "cd:convEq" in FIG. 4 among the change description data that has a time in phase p_c+1 as the change time. This means that the data of data item E21-a' after the change time (change time): 8:12:43 on January 12, 2021 will be 1/100th the value of the data of data item E21-a before that. Therefore, by applying the inverse function conversion rules to data items after the above change time and multiplying the data value of the data item after the above change time by 100, the data value of the data item after the above change time can be compared using the same criteria as the data value of the data item belonging to phase p_c of the above change time.

Next, in step S30, the data extraction unit 22 extracts, from each change description data stored in the change description storage unit 14, change description data that has a synonymous relationship and belongs to the phase p_c+1 that follows phase p_c. For example, from the change description data 300 shown in FIG. 3, information on "@type:cd:addEquipment" ("E13") is extracted as change description data that specifies an additional device. Next, in step S30, the data extraction unit 22 deletes the data item that appears in "cd:addedSame" of the change description data for phase p_c+1 from the data item i_c to be extracted in phase p_c. For example, "E13", which is information on the data item specified by "cd:addedSame", is deleted. This is because the data item identified by "cd:addedSame" in the change description data for phase p_c+1 is no longer a synonymous change description from phase p_c+1 onwards.

After that, in step S30, the data extraction unit 22 creates an initial value i_c+1 for the data item i_c to be extracted, with the data item specified by "cd:addedSame" deleted, extracts data items synonymous with the initial value i_c+1 from each change description data stored in the change description storage unit 14, and updates the initial value i_c+1 with the extracted data item. At this time, the data item group with synonymous relationships in phase p_c+1 is determined to be the data item group with synonymous relationships in phase p_c+1, with the data item i_c to be extracted in phase p_c deleted from the data item group with synonymous relationships. Furthermore, if the information (E12) of the data item that appears in "line:name" in FIG. 3 in the change description data for phase p_c+1 is included in the initial value i_c+1, the information (E13) of the data item identified by "cd:addedSame" that corresponds to "line:name" is extracted as a data item that is synonymous with the initial value i_c+1, and the extracted information is added to the initial value i_c+1.

Next, the data extraction unit 22 sets the variable c to c+1 (S31), and then determines whether the variable c is smaller than n (n: an integer indicating the number of change times) (S32). If the variable c is smaller than n, the process returns to step S29, and repeats the processing of steps S29 to S32 to collect data after the change time tq until the variable c becomes larger than n. If the variable c is larger than n, the process ends as all processing has been completed.

Figure 7 is a flowchart showing an example of data normalization processing of the data extraction unit according to the first embodiment of the present invention. In Figure 7, the data extraction unit 22 sets a variable k corresponding to phase p to 1 (S41), and extracts data items that have a timestamp in phase p_k and are included in the extraction target item i_k from the data storage unit 20 (S42). For example, if the data storage unit 20 stores "timestamp:2021-01-10T08:12:12+0900" as timestamp information and "E12-a:10" and "E13-z:20" as data item information, these pieces of information are extracted from the data storage unit 20.

Next, the data extraction unit 22 converts the meaning of the data item extracted from the data storage unit 20 using the conversion rule conv_pk_pk+1 (S43). For example, if the same conversion rule as the conversion rule set conv_c-1_c created in step S24 of FIG. 6 is used as the conversion rule conv_pk_pk+1, the meaning of the data item is converted using the conversion rule "E21-a' = E21-a * 0.01". At this time, if the data item extracted from the data storage unit 20 contains information on "E21", the value is multiplied by "0.01".

Next, the data extraction unit 22 treats the data belonging to phase p_k among the data collected from the data storage unit 20 as data of phase p_k+1 thereafter (S44). That is, the data of phase p_k is converted to data of phase p_k+1 using the conversion rules for phase p_k+1, and therefore, after conversion, it is processed as data of phase p_k+1.

The data extraction unit 22 then sets the value of variable k to k+1 (S45), and then determines whether variable k is smaller than phase number q (S46). If variable k is smaller than phase number q, the process returns to step S42 and repeats the processing of steps S42 to S46 until variable k is larger than phase number q. If variable k is larger than phase number q, variable k is set to n-1 and variable k is initialized to the last phase number (n-1) (S47).

Next, the data extraction unit 22 extracts data items that have a timestamp in phase p_k and are included in the extraction target item i_k from the data storage unit (S48). For example, if the data storage unit 20 stores "timestamp:2021-01-10T08:12:12+0900" as the timestamp information and "E12-a:10" and "E13-z:20" as the data item information, these pieces of information are extracted from the data storage unit 20.

Next, the data extraction unit 22 converts the meaning of the data item extracted from the data storage unit 20 using the conversion rule conv_pk_pk-1 (S49). For example, when using an inverse function conversion rule as the conversion rule conv_pk_pk-1, which is the same conversion rule as the conversion rule set conv_c-1_c created in step S29 of FIG. 6, the conversion rule "E21-a' = E21-a * 0.01" is used to convert the meaning of the data item. At this time, if the data item extracted from the data storage unit 20 contains information on "E21", the inverse function conversion rule is used to multiply the value by "100".

Next, the data extraction unit 22 treats the data collected from the data storage unit 20 as data belonging to phase p_k as data of phase p_k-1 thereafter (S50). That is, the data of phase p_k is converted to data of phase p_k-1 using the conversion rules for phase p_k-1, and therefore, after conversion, it is processed as data of phase p_k-1.

The data extraction unit 22 then sets the value of variable k to k-1 (S51), and then determines whether variable k is greater than phase number q (S52). If variable k is greater than phase number q, the process returns to step S48 and repeats the processes of steps S48 to S52 until variable k becomes smaller than phase number q. If variable k is smaller than phase number q, the process proceeds to step S53.

In step S53, the data extraction unit 22 stores all data, including the data converted in step S43 and the data converted in step S49, as data of phase p_q in the extracted data storage unit 20, notifies the data extraction supporter via the data extraction instruction unit 24 that data storage has been completed, and then ends the processing of this routine. At this time, the data of phase p_q means the data of phases p_1 to p_n-1 normalized at the time of change time t_q.

In this embodiment, when the data extraction unit 22 receives an extraction request, it extracts from the data storage unit 20 the test data that belongs to the time specified in the extraction request and corresponds to the extraction target item specified in the extraction request, extracts from the change description storage unit 14 the change description data at the change time that belongs to the time specified in the extraction request, determines whether or not there is synonymous or differently-synonymous data in the extracted change description data, and normalizes and outputs the extracted test data based on the determination result. In other words, when a change occurs in the data, the content of the change and the time of the change are recorded in the change description data as synonymous or differently-synonymous data, so that even if the content of the change is synonymous or differently-synonymous, the test data of the extraction target item specified in the extraction request can be extracted by normalizing it to the content of the test data at the reference time based on the time specified in the extraction request, and as a result, test data based on any point (time) instructed in the extraction request can be extracted.

When extracting the test data, the data extraction unit 22 can extract the test data that belongs to a time period before the reference time indicating the time specified in the extraction request and corresponds to the extraction target item specified in the extraction request from the data storage unit 20 as the test data that belongs to a time period before the reference time. Furthermore, when determining the change description data, the data extraction unit 22 can determine whether or not there is data with a synonymous or different synonymous relationship in the change description data that belongs to a time period before the reference time, and can normalize the test data that belongs to a time period before the reference time according to the change content corresponding to the test data at the reference time based on the determination result. In other words, even if there is a change in the data in the time period before the reference time, if the content of the change and the change time are recorded in the change description data as data with a synonymous or different synonymous relationship, even if the content of the change in the data in the time period before the reference time is synonymous or different synonymous, the test data of the extraction target item specified in the extraction request and in the time period before the reference time can be extracted by normalizing it according to the change content corresponding to the test data at the time based on the time specified in the extraction request.

When extracting the test data, the data extraction unit 22 can extract the test data that belongs to a time period after the reference time indicating the time specified in the extraction request and corresponds to the extraction target item specified in the extraction request from the data storage unit 20 as the test data that belongs to a time period after the reference time. Furthermore, when determining the change description data, the data extraction unit 22 can determine whether or not there is data with a synonymous or different synonymous relationship in the change description data that belongs to a time period after the reference time, and can normalize the test data that belongs to a time period after the reference time according to the change content corresponding to the test data at the reference time based on the determination result. In other words, even if there is a change in the data in the time period after the reference time, if the content of the change and the change time are recorded in the change description data as data with a synonymous or different synonymous relationship, even if the content of the change in the data in the time period after the reference time is synonymous or different synonymous, the test data of the extraction target item specified in the extraction request and in the time period after the reference time can be extracted by normalizing it according to the change content corresponding to the test data at the time based on the time specified in the extraction request.

In addition, when the data extraction unit 22 determines that synonymous data exists in the change description data belonging to a time period earlier than the reference time, it converts the test data belonging to a time period earlier than the reference time based on the synonymous data in the change description data, and normalizes the test data belonging to a time period earlier than the reference time converted with the synonymous data to match the change content corresponding to the test data at the reference time; when the data extraction unit 22 determines that synonymous data exists in the change description data belonging to a time period earlier than the reference time, it creates synonymous conversion rules based on the data, converts the test data belonging to a time period earlier than the reference time based on the created synonymous conversion rules, and normalizes the test data belonging to a time period earlier than the reference time converted with the synonymous conversion rules to match the change content corresponding to the test data at the reference time.

For example, if data belonging to change description data 300 exists as synonymous data in the change description data belonging to a time period before the reference time, the test data specified by these data can be normalized to match the change content corresponding to the test data at the reference time, so that the synonymous test data belonging to a time period before the reference time can be treated on the same scale as the test data at the reference time. Also, if data belonging to change description data 400 exists as synonymous data in the change description data belonging to a time period before the reference time, the test data specified by these data can be converted using the conversion rules generated by change description data 400, and the converted test data can be normalized to match the change content corresponding to the test data at the reference time, so that the synonymous test data belonging to a time period before the reference time can be treated on the same scale as the test data at the reference time.

In addition, when the data extraction unit 22 determines that synonymous data exists in the change description data belonging to a time period after the reference time, it converts the test data belonging to a time period after the reference time based on the synonymous data in the change description data, and normalizes the test data belonging to a time period after the reference time converted with the synonymous data to match the change content corresponding to the test data at the reference time; when the data extraction unit 22 determines that synonymous data exists in the change description data belonging to a time period after the reference time, it creates synonymous conversion rules based on the data, converts the test data belonging to a time period after the reference time based on the created synonymous conversion rules, and normalizes the test data belonging to a time period after the reference time converted with the synonymous conversion rules to match the change content corresponding to the test data at the reference time.

For example, if data belonging to change description data 300 exists as synonymous data in change description data belonging to a time period after the reference time, the test data specified by these data can be normalized to the change content corresponding to the test data at the reference time, so that the synonymous test data belonging to a time period after the reference time can be treated on the same scale as the test data at the reference time. Also, if data belonging to change description data 400 exists as synonymous data in change description data belonging to a time period after the reference time, the test data specified by these data can be converted using the conversion rules generated by change description data 400, and the converted test data can be normalized to the change content corresponding to the test data at the reference time, so that the synonymous test data belonging to a time period after the reference time can be treated on the same scale as the test data at the reference time.

In addition, the change description registration unit 12 can register change description data that is different from the change description data stored in the change description storage unit 14, for example new change description data, based on the operation of the change input person. This makes it possible to efficiently track changes in the field, even if there are new changes to the inspection specifications, etc., on the production line at the field. By simply adding the content of the new change to the change description data, it is possible to distinguish between synonymous data and synonymous data and manage the change description data without rewriting the information and procedures required for normalizing the inspection data.

According to this embodiment, it is possible to distinguish between synonymous data and non-synonymous data and manage the change description data, and as a result, it is possible to extract test data based on any point (time) specified in the extraction request.

The present invention is not limited to the above-described embodiment, but includes various modified examples and equivalent configurations within the spirit of the appended claims. For example, the change description storage unit 14 and the data storage unit 20 can be integrated as a database or memory unit. The above-described embodiment has been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to having all of the configurations described.

Furthermore, each of the configurations, functions, etc. described above may be realized in part or in whole in hardware, for example by designing them as integrated circuits, or in software, by a processor interpreting and executing a program that realizes each function.

Information such as programs, tables, and files that realize each function can be stored in a storage device such as a memory, a hard disk, or an SSD (Solid State Drive), or in a recording medium such as an IC (Integrated Circuit) card, an SD card, or a DVD (Digital Versatile Disc).

REFERENCE SIGNS LIST 1 data management system, 10 change input section, 12 change description registration section, 14 change description storage section, 16 data generation section, 18 data registration section, 20 data storage section, 22 data extraction section, 24 data extraction instruction section, 26 extracted data storage section

Claims (12)

a data storage unit for storing time-series inspection data obtained by the inspection device inspecting the inspection object;
a change description storage unit for storing change description data, which is data of a synonymous or heterosynonymous relationship indicating that at least one of the inspection specifications, the inspection items, or the inspection target of the inspection device has been changed, the change description data including the time of the change and the content of the change, in association with the inspection data;
a data extraction unit that searches the data storage unit and the change description storage unit to extract data from the search target;
a data extraction instruction unit that outputs an extraction request including an extraction target item and a time to the data extraction unit,
The data extraction unit includes:
a data management system characterized in that, when the extraction request is received, the search target is searched based on the received extraction request, the inspection data belonging to the time specified in the extraction request and corresponding to the extraction target item specified in the extraction request is extracted from the data storage unit, the change description data including the change content at the change time corresponding to the time specified in the extraction request is extracted from the change description storage unit, whether or not data of the synonymous relationship or the heterosynonymous relationship is present in the extracted change description data, and the extracted inspection data is normalized and output based on the result of the determination. 2. The data management system according to claim 1,
The data extraction unit includes:
A data management system characterized in that the test data which belongs to a time period before a reference time indicating the time specified in the extraction request and corresponds to the extraction target item specified in the extraction request is extracted from the data storage unit as test data belonging to a time period before the reference time, the data management system determines whether or not the synonymous or heterologous data exists in the extracted change description data which belongs to a time period before the reference time, and based on the determination result, normalizes the test data which belongs to a time period before the reference time to the change content corresponding to the test data at the reference time. 2. The data management system according to claim 1,
The data extraction unit includes:
A data management system characterized in that the test data which belongs to a time period later than a reference time indicating the time specified in the extraction request and corresponds to the extraction target item specified in the extraction request is extracted from the data storage unit as test data belonging to a time period later than the reference time, the data management system determines whether or not the synonymous or heterologous data exists in the extracted change description data which belongs to a time period later than the reference time, and normalizes the test data which belongs to a time period later than the reference time based on the result of the determination to match the change content corresponding to the test data at the reference time. 3. The data management system according to claim 2,
The data extraction unit includes:
a data management system comprising: when it is determined that synonymous data exists in the change description data belonging to a time period earlier than the reference time, the system converts inspection data belonging to a time period earlier than the reference time based on the synonymous data in the change description data, and normalizes the inspection data belonging to a time period earlier than the reference time that has been converted using the synonymous data to match the change content corresponding to the inspection data at the reference time; and when it is determined that opposite synonymous data exists in the change description data belonging to a time period earlier than the reference time, the system creates opposite synonymous data conversion rules based on the opposite synonymous data, converts inspection data belonging to a time period earlier than the reference time based on the created opposite synonymous conversion rules, and normalizes the inspection data belonging to a time period earlier than the reference time that has been converted using the opposite synonymous conversion rules to match the change content corresponding to the inspection data at the reference time. 4. The data management system according to claim 3,
The data extraction unit includes:
a data management system comprising: when it is determined that synonymous data exists in the change description data belonging to a time period later than the reference time, the system converts inspection data belonging to a time period later than the reference time based on the synonymous data in the change description data, and normalizes the inspection data belonging to a time period later than the reference time that has been converted using the synonymous data to match the change content corresponding to the inspection data at the reference time; and when it is determined that opposite synonymous data exists in the change description data belonging to a time period later than the reference time, the system creates opposite synonymous data conversion rules based on the opposite synonymous data, converts inspection data belonging to a time period later than the reference time based on the created opposite synonymous conversion rules, and normalizes the inspection data belonging to a time period later than the reference time that has been converted using the opposite synonymous conversion rules to match the change content corresponding to the inspection data at the reference time. 2. The data management system according to claim 1,
2. A data management system further comprising a change description registration section for registering change description data different from the change description data stored in the change description storage section. A method for managing data in a database using a computer, comprising:
a data storage step in which the computer stores in the database time-series inspection data obtained by the inspection device inspecting the inspection object;
a change description storage step in which the computer stores in the database, in association with the inspection data, change description data which is synonymous or heterosynonymous data indicating that at least one of the inspection specifications, the inspection items, or the inspection targets of the inspection device has been changed, the change description data including the time of the change and the content of the change;
a data extraction step in which the computer searches the database and extracts data from the search target;
a data extraction instruction step of outputting an extraction request including an extraction target item and a time,
The computer includes:
In the data extraction step,
A data management method characterized in that, when the extraction request is received, the search target is searched based on the received extraction request, the inspection data belonging to the time specified in the extraction request and corresponding to the extraction target item specified in the extraction request is extracted from the database, the change description data including the change content at the change time corresponding to the time specified in the extraction request is extracted from the database, whether or not the synonymous or heterosynonymous data is present in the extracted change description data, and the extracted inspection data is normalized and output based on the result of the determination. 8. The data management method according to claim 7,
The computer includes:
In the data extraction step,
A data management method characterized by extracting from the database the test data that belongs to a time period earlier than a reference time indicating the time specified in the extraction request and that corresponds to the extraction target item specified in the extraction request as test data belonging to a time period earlier than the reference time, determining whether or not the synonymous or heterologous data exists in the extracted change description data that belongs to a time period earlier than the reference time, and normalizing the test data that belongs to a time period earlier than the reference time based on the determination result to match the change content corresponding to the test data at the reference time. 8. The data management method according to claim 7,
The computer includes:
In the data extraction step,
A data management method characterized by: extracting from the database the test data that belongs to a time period after a reference time indicating the time specified in the extraction request and that corresponds to the extraction target item specified in the extraction request as test data belonging to a time period after the reference time; determining whether or not the synonymous or heterologous data exists in the extracted change description data that belongs to a time period after the reference time; and normalizing the test data that belongs to a time period after the reference time based on the result of the determination to match the change content corresponding to the test data at the reference time. 9. The data management method according to claim 8,
The computer includes:
In the data extraction step,
a data management method comprising: when it is determined that synonymous data exists in the change description data belonging to a time period earlier than the reference time, converting inspection data belonging to a time period earlier than the reference time based on the synonymous data in the change description data, and normalizing the inspection data belonging to a time period earlier than the reference time that has been converted using the synonymous data to match the change content corresponding to the inspection data at the reference time; when it is determined that opposite synonymous data exists in the change description data belonging to a time period earlier than the reference time, creating an opposite synonymous data conversion rule based on the opposite synonymous data, converting the inspection data belonging to a time period earlier than the reference time based on the created opposite synonymous conversion rule, and normalizing the inspection data belonging to a time period earlier than the reference time that has been converted using the opposite synonymous conversion rule to match the change content corresponding to the inspection data at the reference time. 10. The data management method according to claim 9,
The computer includes:
In the data extraction step,
a data management method comprising: when it is determined that synonymous data exists in the change description data belonging to a time period later than the reference time, converting inspection data belonging to a time period later than the reference time based on the synonymous data in the change description data, and normalizing the inspection data belonging to a time period later than the reference time that has been converted using the synonymous data to match the change content corresponding to the inspection data at the reference time; when it is determined that opposite synonymous data exists in the change description data belonging to a time period later than the reference time, creating an opposite synonymous data conversion rule based on the opposite synonymous data, converting inspection data belonging to a time period later than the reference time based on the created opposite synonymous conversion rule, and normalizing the inspection data belonging to a time period later than the reference time that has been converted using the opposite synonymous conversion rule to match the change content corresponding to the inspection data at the reference time. 8. The data management method according to claim 7,
The data management method further comprises a change description registration step in which the computer registers in the database change description data different from the change description data stored in the database.

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