Information processing device, information processing method, and program

Abstract

To make it possible to reduce trouble of extracting information on problems to be solved at a production site.SOLUTION: An information processing device comprises: a sensor information acquisition unit that acquires sensor information including a signal acquisition entity, which is an entity that acquires a signal, a value of the signal acquired from the signal acquisition entity, a timestamp for representing a time when the signal is acquired, and a signal name of the signal; a process information acquisition unit that acquires process information for indicating a configuration of a work process including a process where the signal acquisition entity is operating; a linking unit that links pieces of the sensor information with one another based on the process information; and a display control unit for displaying the pieces of sensor information linked by the linking unit according to a display rule based on the process information.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] At production sites such as factories, improvement of QCD (quality, cost, delivery time) is a constant challenge, and problem extraction based on data obtained by IoT (Internet of Things) has become common. For example, there is a known quality control system that is installed on a specific type of machine and identifies information about defective products at the time of production based on data obtained by sensors (Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-27323 Summary of the Invention [Problem to be solved by the invention]

[0004] In conventional quality control systems, the relationships between various types of data obtained from sensors were expressed based on a predefined schema. However, the type of product, production method, and data collection method vary from production site to production site. For example, workpiece identification, equipment status, and measurement values ​​vary from factory to factory. Therefore, in order to visualize issues at production sites, it was necessary to build a schema for each production site. For example, in the past, data obtained through IoT, like in business intelligence (BI) tools, was displayed on a screen with individual display settings. With this method, it was necessary to create individual editing programs to edit the obtained data so that it could be displayed as the desired information. There is a need to reduce the effort required to identify issues at production sites.

[0005] The present invention has been made in view of the above points, and provides an information processing device, an information processing method, and a program that can reduce the effort required for problem extraction at a production site. [Means for solving the problem]

[0006] The present invention has been made to solve the above-mentioned problems, and one aspect of the present invention is a system including a signal acquisition entity that acquires a signal, a sensor information acquisition unit that acquires sensor information including a value of the signal acquired from the signal acquisition entity, a timestamp indicating when the signal was acquired, and a signal name of the signal, and a configuration of a work process including a process by the signal acquisition entity. , using at least the key signal to which the signal name is associated a process information acquisition unit that acquires process information indicated by the process information acquisition unit; a classification unit that groups the sensor information into work process units based on the work process and the time stamp indicated by the process information using the key signal; and The information processing device includes a linking unit that links the sensor information together, and a display control unit that displays the sensor information linked by the linking unit according to a display rule based on the process information.

[0008] In one aspect of the present invention, in the information processing device, the work process is a work process for a workpiece that includes a process performed by equipment that is the subject of signal acquisition.

[0009] In one aspect of the present invention, in the information processing device, the classification unit groups the sensor information by workpiece or by facility based on the process information.

[0010] In one aspect of the present invention, in the information processing device, the work process is a work process performed by a worker.

[0011] In one aspect of the present invention, in the information processing device, the classifying unit groups the sensor information by worker based on the process information.

[0012] In one aspect of the present invention, the information processing device further includes a process information generating unit that generates the process information.

[0013] In one aspect of the present invention, the information processing device further includes a sensor information editing unit that edits at least the signal acquisition entity and the signal name among the attributes of the sensor information.

[0014] In addition, one aspect of the present invention is a signal acquisition process including a signal acquisition entity that acquires a signal, a sensor information acquisition step that acquires sensor information including a value of the signal acquired from the signal acquisition entity, a timestamp indicating when the signal was acquired, and a signal name of the signal, and a process by the signal acquisition entity. , using at least the key signal to which the signal name is associated a process information acquisition step of acquiring process information indicating the process information; a classification step of grouping the sensor information into work process units based on the work process and the time stamp indicated by the process information using the key signal; and The information processing method includes a linking step of linking the sensor information to each other, and a display control step of displaying the sensor information linked in the linking step according to a display rule based on the process information.

[0015] In addition, one aspect of the present invention is a method for controlling a computer to perform a process including a signal acquisition entity that acquires a signal, a sensor information acquisition step that acquires sensor information including a value of the signal acquired from the signal acquisition entity, a timestamp indicating when the signal was acquired, and a signal name of the signal, and a process by the signal acquisition entity. , using at least the key signal to which the signal name is associated a process information acquisition step of acquiring process information indicating the process information; a classification step of grouping the sensor information into work process units based on the work process and the time stamp indicated by the process information using the key signal; and The program executes a linking step of linking the sensor information together, and a display control step of displaying the sensor information linked in the linking step according to a display rule based on the process information. [Effects of the Invention]

[0016] According to the present invention, the effort required for problem extraction at the production site can be reduced. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a diagram showing an example of the configuration of a production management system according to a first embodiment of the present invention. [Figure 2]FIG. 1 is a diagram showing an example of an outline of the flow of information processing according to a first embodiment of the present invention. [Figure 3] 1 is a diagram illustrating an example of a functional configuration of an information processing device according to a first embodiment of the present invention. [Figure 4] FIG. 2 is a diagram showing an example of the flow of information processing according to the first embodiment of the present invention. [Figure 5] FIG. 2 is a diagram illustrating an example of a time-series queue according to the first embodiment of the present invention. [Figure 6] FIG. 3 is a diagram illustrating an example of a model signal generation process according to the first embodiment of the present invention. [Figure 7] FIG. 2 is a diagram illustrating an example of a model signal queue according to the first embodiment of the present invention. [Figure 8] FIG. 1 is a diagram illustrating an example of a factory model according to a first embodiment of the present invention. [Figure 9] FIG. 3 is a diagram illustrating an example of a display process according to the first embodiment of the present invention. [Figure 10] 3A and 3B are diagrams showing examples of search conditions and display rule information according to the first embodiment of the present invention. [Figure 11] FIG. 2 is a diagram showing an example of a display screen according to the first embodiment of the present invention. [Figure 12] FIG. 2 is a diagram showing an example of a display screen according to the first embodiment of the present invention. [Figure 13] FIG. 4 is a diagram showing an example of the flow of data extraction processing in the display processing according to the first embodiment of the present invention. [Figure 14] FIG. 2 is a diagram showing an example of an outline of information processing when video data is added as a sensor signal according to the first embodiment of the present invention. [Figure 15] FIG. 2 is a diagram showing an example of an outline of the relationship between a factory model and a display screen according to the first embodiment of the present invention. [Figure 16] FIG. 10 is a diagram illustrating an example of a factory model according to a modified example of the first embodiment of the present invention. [Figure 17] FIG. 10 is a diagram showing an example of a display screen according to a modified example of the first embodiment of the present invention. [Figure 18]FIG. 2 is a diagram showing an example of a table in which data provided in advance as a package and data set by a user according to the first embodiment of the present invention are organized. [Figure 19] FIG. 2 is a diagram showing an example of a list of components of each factory model according to the first embodiment of the present invention. [Figure 20] FIG. 2 is a diagram showing an example of a setting screen according to the first embodiment of the present invention. [Figure 21] FIG. 2 is a diagram showing an example of a setting screen according to the first embodiment of the present invention. [Figure 22] FIG. 10 is a diagram illustrating an example of the configuration of an operation estimation system according to a second embodiment of the present invention. [Figure 23] FIG. 10 is a diagram showing an example of a signal dictionary according to a second embodiment of the present invention. [Figure 24] FIG. 10 is a diagram showing an example of an analysis screen according to the second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018] (First embodiment) Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. [Outline of Production Management System 1] The configuration and processing of a production management system 1 according to this embodiment will be outlined with reference to FIGS. 1 is a diagram showing an example of the configuration of a production management system 1 according to this embodiment. The production management system 1 is a system for displaying the efficiency of equipment and workers, and the quality of products at a production site such as a factory. The production management system 1 comprises an information processing device 2, a connection device 3, a terminal device 4, and a display device 5.

[0019] The information processing device 2 acquires sensor information from various sensing devices installed at the production site via the connection device 3 or the terminal device 4. The information processing device 2 links the sensor information together based on the process information. The information processing device 2 displays the linked sensor information on the display device 5 according to display rules based on the process information.

[0020] The information processing device 2 is, for example, a single server. In the information processing device 2, a single server runs multiple operating systems (OS). In other words, the information processing device 2 is a virtual server. Note that the information processing device 2 may be configured by multiple servers.

[0021] The connection device 3 and the terminal device 4 each acquire sensor signals output from various sensing entities installed in the production site. A sensor signal is a signal output from a sensing entity. The connection device 3 and the terminal device 4 each output the acquired sensor signals to the information processing device 2. The connection device 3 and the terminal device 4 are each connected to the various sensing entities by wire or wirelessly, and each acquires sensor signals from the various sensing entities.

[0022] The various sensing entities include, for example, sensors, buttons, buzzers, mobile terminal devices carried by workers, cameras, etc. The sensing entities are an example of signal acquiring entities that acquire signals. The various types of equipment include, for example, various machine tools, processing machines, assembly machines, inspection machines, machine tools using computerized numerical control (CNC), programmable logic controllers (PLC), robots, etc. The various types of equipment also include inspection machines used to inspect parts when they are received and to inspect products that are processed, assembled, and shipped. The sensor signals acquired by the various types of equipment include, for example, job IDs, lots, production orders, serial numbers, etc.

[0023] The mobile terminal device carried by the worker is, for example, a tablet terminal or a smartphone. The sensor signals acquired by the mobile terminal device are various types of information input by the worker. The worker inputs information such as sampling inspection, reasons for shutdown, inspection result input, equipment inspection results, and maintenance records into the mobile terminal device. The mobile terminal device into which the worker inputs various types of information is an example of a signal acquisition entity that acquires signals. The camera captures images of the production site and records them as video. The sensor signals acquired by the camera include video data and still image data.

[0024] The connection device 3 is, for example, a connection device specialized for acquiring a sensor signal. The terminal device 4 is, for example, a computer such as a server or a personal computer (PC). Although only one connection device 3 and one terminal device 4 are shown in Figure 1, the production management system 1 has multiple connection devices 3 and multiple terminal devices 4 depending on the number of sensing entities of each connection device 3 and terminal device 4.

[0025] The sensor signals output from the connection device 3 or the terminal device 4 are input to the information processing device 2 via a connector provided on the information processing device 2. The information processing device 2 acquires the input sensor signals as sensor information C1. In other words, the information processing device 2 acquires sensor signals output from various sensing subjects as sensor information C1.

[0026] The information processing device 2 performs information processing based on the acquired sensor information C1 and displays the results on the display device 5. The display device 5 displays the results of the information processing by the information processing device 2 on a standard screen. Alternatively, the display device 5 displays the results using an analysis tool based on business intelligence (BI) or AI (artificial intelligence). The display device 5 is, for example, a display.

[0027] An overview of the flow of information processing by the information processing device 2 will now be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of an overview of the flow of information processing according to this embodiment. The information processing by the information processing device 2 includes a sensor signal mapping function, a model signal generation function, a dictionary function, and an information display function. The sensor signal mapping function, the model signal generation function, the dictionary function, and the information display function are respectively indicated as function F1, function F2, function F3, and function F4 in Fig. 2.

[0028] The information processing device 2 associates the signal names of the sensor signals included in the sensor information C1 with key signals (also called reserved signals) (sensor signal mapping function). Here, the information processing device 2 updates the signal names included in the sensor signals acquired from the sensors with the associated key signals. The key signals are registered in a signal dictionary or a production resource dictionary according to a predetermined factory model. The signal dictionary and the production resource dictionary are stored as databases in the information processing device 2, and the information processing device 2 refers to them during the information processing process (dictionary function).

[0029] A factory model is a model that shows the configuration of work processes for work, including processes using sensing equipment. Factory models are based on a signal dictionary and a production resource dictionary (dictionary function). Factory models include traceability models and Overall Equipment Effectiveness (OEE) models.

[0030] The information processing device 2 generates data that includes a set of a sensing subject of a sensor signal, a value of the sensor signal acquired from the sensing subject, a timestamp indicating when the sensor signal was acquired, and a signal name of the sensor signal. The data is also referred to as a raw signal. When the information processing device 2 generates a raw signal, the information processing device 2 adds the raw signal to a queue (referred to as a time-series queue A2) in which the raw signals are arranged in time series. The time-series queue A2 is stored in the information processing device 2 as a database.

[0031] The information processing device 2 generates a model signal by linking the raw signals stored in the time-series queue A2 together based on a predetermined factory model (model signal generation function).

[0032] The information processing device 2 adds the generated model signal to a queue in which model signals are arranged (referred to as a model signal queue A3). The model signal queue A3 is stored in the information processing device 2 as a database.

[0033] The information processing device 2 selects a display target from among the model signals included in the model signal queue A3 stored in the database based on a signal dictionary and a production resource dictionary (dictionary function). The information processing device 2 displays the selected model signal on the display device 5 based on a screen display dictionary (information display function, dictionary function). The screen display dictionary indicates display rules based on the factory model. The model signal is associated with a display screen based on the screen display dictionary.

[0034] [Functional configuration of information processing device 2] 3 is a diagram showing an example of the functional configuration of the information processing device 2 according to this embodiment. The information processing device 2 includes a sensor information acquisition unit 20, a process information acquisition unit 21, an external information acquisition unit 22, a sensor signal mapping unit 23, a linking unit 24, a classification unit 25, a process information generation unit 26, a sensor information editing unit 27, a display control unit 28, and a storage unit 210.

[0035] Each functional unit of the information processing device 2 is realized by a CPU (Central Processing Unit) reading a program from a ROM (Read Only Memory) and executing the process. As described above, in this embodiment, the information processing device 2 is a virtual server, and therefore each functional unit of the information processing device 2 is realized in a distributed manner by one or more virtual servers.

[0036] The sensor information acquisition unit 20 acquires sensor information C1. The sensor information C1 includes a sensing subject of a signal, a value of the signal acquired from the sensing subject, a timestamp indicating when the signal was acquired, and a signal name of the signal.

[0037] The process information acquisition unit 21 acquires process information A1. The process information A1 is information indicating the configuration of a work process for a workpiece, including a process performed by equipment that is the sensing subject. The process information A1 includes signal dictionary information A11 and production resource dictionary information A12. As described above, the factory model is based on the signal dictionary information A11 and production resource dictionary information A12. In this embodiment, a factory model M1, which is a traceability model, is used as the factory model.

[0038] The external information acquisition unit 22 acquires external information A5. The external information A5 indicates planned values, design values, calendars, production quantities, etc. at the production site. The external information A5 is used, for example, to evaluate the value of a sensor signal. For example, the value of the sensor signal is compared with the design value included in the external information A5, and the acceptability of the value of the sensor signal is evaluated.

[0039] Here, the data format of the external information A5 is the same as the data format of the raw signal. In other words, the external information A5 is data that pairs at least the entity that acquires (generates) the external information, the name of the external information, and the value of the external information (planned value, design value, calendar, production number at the production site, etc.). This allows the external information acquisition unit 22 to easily refer to the data when referencing the external information A5 without having to change the data reference method depending on the type of data. Note that in the external information A5, the value of the entity that acquires (generates) the external information may be null.

[0040] The sensor signal mapping unit 23 associates the signal names of the sensor signals included in the sensor information C1 with key signals. The key signals are indicated by the signal dictionary information A11 or the production resource dictionary information A12.

[0041] The sensor information acquisition unit 20 and the sensor signal mapping unit 23 described above are configured to include the connector shown in FIG. The association between the signal names of the sensor signals and the key signals may be performed by the connection device 3 or the terminal device 4. In this case, the sensor signal mapping unit 23 may be omitted from the configuration of the information processing device 2.

[0042] The linking unit 24 links the aggregated data, index value calculation results, and sensor information C1 together based on the process information A1. The linking unit 24 generates a model signal as a result of linking the aggregated data, index value calculation results, and sensor information C1 together. In the process of linking the aggregated data, index value calculation results, and sensor information C1 together, the linking unit 24 uses the results of grouping the aggregated data, index value calculation results, and sensor information C1 by the classification unit 25.

[0043] The classification unit 25 groups the sensor information C1 into work process units based on the process information A1 and the timestamp. The classification unit 25 also groups the sensor information C1 into work units or equipment units based on the process information A1. The process information generating unit 26 generates the process information A1. The sensor information editing unit 27 edits at least the sensing subject and the signal name from among the attributes of the sensor information C1.

[0044] The display control unit 28 displays the sensor information C1 linked by the linking unit 24 according to a display rule based on the process information A1. The operation receiving unit 29 receives various operations from the user of the information processing device 2.

[0045] The storage unit 210 stores various types of information, including process information A1, time-series cues A2, model signal cues A3, display rule information A4, and external information A5. The display rule information A4 indicates a display rule based on the process information A1. The display rule information A4 includes the above-mentioned screen display dictionary. The storage unit 210 is configured using a storage device such as a magnetic hard disk drive or a semiconductor storage device.

[0046] [Information processing flow of information processing device 2] FIG. 4 is a diagram showing an example of the flow of information processing according to this embodiment. Step S10: The sensor information acquisition unit 20 acquires the sensor information C1. The sensor information acquisition unit 20 acquires the sensor information C1 every time the sensor information C1 is output from the sensing subject via the connection device 3 or the terminal device 4. The sensor information acquisition unit 20 supplies the acquired sensor information C1 to the sensor signal mapping unit 23.

[0047] The sensor information acquisition unit 20 acquires the sensor information C1 through a connector provided in the information processing device 2. One or more connectors are provided according to the number of sensing subjects, and the connectors and sensing subjects are associated in advance. This association is performed in advance by the user of the production management system 1.

[0048] Step S20: The process information acquisition unit 21 acquires the process information A1. The process information acquisition unit 21 acquires the process information A1 by reading the process information A1 from the storage unit 210. The process information acquisition unit 21 supplies the signal dictionary information A11 included in the acquired process information A1 to the sensor signal mapping unit 23.

[0049] Step S30: The sensor signal mapping unit 23 associates the signal names of the sensor signals included in the sensor information C1 with key signals. The sensor signal mapping unit 23 updates the signal names using the key signals included in the signal dictionary information A11 or the production resource dictionary information A12 supplied from the process information acquisition unit 21.

[0050] The sensor signal mapping unit 23 updates the signal name acquired by the connector from among the key signals included in the signal dictionary information A11 or the production resource dictionary information A12, using a key signal that is pre-specified according to the sensing entity associated with the connector that acquired the sensor information C1.

[0051] Step S40: The sensor signal mapping unit 23 generates a raw signal by pairing the sensing subject of the sensor signal, the value of the sensor signal acquired from the sensing subject, a timestamp indicating when the sensor signal was acquired, and the signal name of the sensor signal.

[0052] The sensor signal mapping unit 23 adds the generated raw signals to the time-series queue A2. The information processing device 2 adds the generated raw signals to the time-series queue A2 in chronological order based on the timestamps included in the raw signals.

[0053] An example of the time-series queue A2 is shown in Fig. 5. In the raw signals stored in the time-series queue A2 shown in Fig. 5, a set of "facility" that is the sensing subject, a timestamp, a signal name, and a sensor signal value is formed.

[0054] In the time-series queue A2 shown in FIG. 5, two types of sensing-subject "equipment" are stored: "Cutting Machine" and "Assembly Machine 1." In the time-series queue A2 shown in FIG. 5, the time indicated by the timestamp is indicated by letters such as "T1" for simplicity. "T1," "T2," and so on indicate the order of time. In the time-series queue A2 shown in FIG. 5, the signal names stored are "Input," "S / N," "Processing Condition 1," "Discharge," "Processing Condition 2," "Exit," "Subpart S / N," and "Measurement Value 1." Note that "S / N" is an abbreviation for serial number. In FIG. 5, among the signal names of the sensor signals, the signal names associated with key signals are underlined. In the time-series queue A2 shown in FIG. 5, values ​​corresponding to the signal names are stored as the sensor signal values.

[0055] Returning to Figure 4, we will continue to explain the flow of information processing. Step S50: The linking unit 24 generates a model signal. The linking unit 24 generates a model signal by linking the raw signals together based on the factory model M1. As described above, the model signal is generated by linking the raw signals together. In this sense, the model signal is a signal that represents the relationship between the raw signals.

[0056] The data format of the model signal is the same as the data format of the raw signal. In other words, the model signal is data that combines at least the sensing subject of the sensor signal, the signal name of the sensor signal, and the value of the sensor signal. The model signal is stored in the model signal queue A3 as data in the above-mentioned format. This allows the information processing device 2 to easily refer to the model signal without having to change the data reference method depending on the type of model signal.

[0057] In the model signal, the data of the sensing subject is generated based on the factory model during the process of generating the model signal. As described above, in the model signal, the sensing subject and the value of the sensor signal are paired. Therefore, in the factory model, like an actual sensing subject, the sensing subject included in the model signal corresponds to virtual equipment that acquires the value of the sensor signal.

[0058] In a model signal, the value of the sensor signal may be the actual value of the sensor signal acquired from the sensing subject, or may be a value generated in the process of generating the model signal. Also, in a model signal, a value calculated as an index using a threshold or the like based on a factory model may be stored as the value of the sensor signal. In the sense that the value is calculated based on the factory model, the sensing subject included in the model signal corresponds to virtual equipment.

[0059] Here, the model signal generation process in which the linking unit 24 generates a model signal will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the model signal generation process according to this embodiment. Fig. 6 describes the model signal generation process in the case where the factory model is a factory model M1 that is a traceability model.

[0060] Step S110: The linking unit 24 generates a "cycle" signal. The linking unit 24 reads the model signal queue A3 stored in the memory unit 210. The linking unit 24 causes the classification unit 25 to execute a process of grouping the raw signals into work process units. The method of grouping the raw signals into work process units is shown in the factory model M1. Here, in the traceability model, the work process in question is called a "cycle."

[0061] Based on the factory model M1, the classification unit 25 classifies, in the model signal queue A3, raw signals whose sensing subject is the same "equipment," one or more raw signals ranging from a raw signal whose signal name is "input" ("input" signal) to a raw signal whose signal name is "discharge" ("discharge" signal), into raw signals belonging to one "cycle." The "input" signal and the "discharge" signal correspond to the start and end of the "cycle," respectively.

[0062] In the model signal queue A3, the raw signals are arranged in chronological order, and therefore the sensor signals from the "input" signal to the "discharge" signal are also arranged in timestamp order. Therefore, the classification unit 25 groups the sensor information C1 into work process units based on the factory model M1 and the timestamps. This allows the information processing device 2 to group data regardless of the type of data, enabling flexible construction and addition of data models.

[0063] In addition, for raw signals in which the sensing subject is a certain "equipment," the classification unit 25 classifies adjacent raw signals into one "cycle" for the remaining raw signals, excluding raw signals with the signal name "discharge" from raw signals with the signal name "input."

[0064] In the example of the time-series queue A2 shown in Figure 5 above, the raw signals are classified into a total of three "cycles." First, for the raw signals whose "equipment" is "cutting machine," the four raw signals from the raw signal whose signal name is "input" to the raw signal whose signal name is "discharge" (raw signals whose timestamps are "T1" to "T4") are classified into the first "cycle." The name of the first "cycle" is set to "[cutting machine = C1]."

[0065] Next, for the raw signals where "equipment" is "cutting machine," the remaining raw signals that were not classified into the first "cycle" are the raw signal with the signal name "S / N" and the raw signal for "processing condition 2" (raw signals with timestamps from "T5" to "T6"), which are classified into the second "cycle." The name of the second "cycle" is set to "[Cutting machine = C2]".

[0066] Finally, for the raw signals whose "equipment" is "Assembly Machine 1," the five raw signals from the raw signal whose signal name is "Input" to the raw signal whose signal name is "Discharge" (raw signals whose timestamps are "T16" to "T21") are classified into the third "cycle." The name of this third "cycle" is set to "[Assembly Machine = C1]".

[0067] The linking unit 24 generates one "cycle" signal each time the classification unit 25 classifies a raw signal into one "cycle." The "cycle" signal is one of the model signals. In the "cycle" signal, the "equipment" that is the sensing subject of the raw signal classified into that "cycle" is stored as sensing subject data. In the "cycle" signal, "cycle" is stored as the signal name. In the "cycle" signal, the name of the "cycle" is stored as the signal value. The linking unit 24 adds the generated model signal to the model signal queue A3.

[0068] An example of the model signal queue A3 is shown in Fig. 7. The model signals included in row R1 shown in Fig. 7 are three model signals ("cycle" signals) generated in response to the raw signals included in the time series queue A2 shown in Fig. 5 being classified into three "cycles."

[0069] The linking unit 24 also generates a new model signal by linking the generated "cycle" signal with each of one or more raw signals classified into one "cycle" when generating the "cycle" signal. The linking unit 24 stores the value of the sensor signal in the "cycle" signal as sensing-subject data in the newly generated model signal. The linking unit 24 also stores the signal name and sensor signal value of the sensor signal in the raw signal linked to the "cycle" signal when generating the newly generated "cycle" signal as the signal name and sensor signal value of the sensor signal in the newly generated model signal. The linking unit 24 adds the generated model signal to the model signal queue A3.

[0070] As described above, when the linking unit 24 generates a model signal, it generates a new model signal by linking the model signal to each of one or more raw signals that were classified into work processes when generating the model signal.

[0071] The model signals included in row R2 shown in Figure 7 are examples of newly generated model signals linked to each of the three "cycle" signals included in row R1. The model signals included in rows R21, R22, and R23 are linked to the "cycle" signals of "[Cutting machine = C1]," "[Cutting machine = C2]," and "[Assembly machine = C1]," respectively, included in row R1.

[0072] In the model signals included in row R2 shown in Figure 7, the three model signals included in row R1 are linked to one or more raw signals that were classified into work processes when those model signals were generated. In the model signals included in row R2, the sensor signal values ​​("[Cutting machine = C1]," "[Cutting machine = C2]," "[Assembly machine = C1]") of the "Cycle" signal, which is the model signal included in row R1 that was linked to the raw signal when the model signal included in row R2 was generated, are stored as sensing-based data. In the model signals included in row R2, the signal names and sensor signal values ​​are respectively stored as the sensor signal names and sensor signal values ​​("On," "TRUE," etc.) of the sensor signals of the raw signals that were linked to the model signals when the model signal included in row R2 was generated.

[0073] Step S120: The classification unit 25 generates a work number. The classification unit 25 refers to the model signal queue A3 and extracts "S / N" from the signal names included in the "cycle" signals grouped into a certain "cycle." When the classification unit 25 extracts the signal name "S / N," the linking unit 24 generates a work number linked to the signal name "S / N." Note that if the signal name "S / N" extracted by the classification unit 25 has already been extracted, the linking unit 24 does not generate a duplicate work number because a work number linked to the signal name "S / N" has already been generated.

[0074] The linking unit 24 generates a new model signal based on the generated work number. In this model signal, the work number is stored as the sensing subject data. In this model signal, "S / N" is stored as the signal name. In this model signal, the value of "S / N" is stored as the sensor signal value. The model signal included in row R3 shown in Figure 7 is an example of a model signal generated based on the work number. In this model signal, "[Work #1]" is stored as the sensing subject data. The linking unit 24 adds the generated model signal to the model signal queue A3.

[0075] Step S130: The linking unit 24 generates a "passed workpiece" signal and an "OK / NG" signal. The "passed workpiece" signal and the "OK / NG" signal are examples of model signals. The linking unit 24 refers to the model signal queue A3 and extracts "discharge" from the signal names included in the "cycle" signals grouped into a certain "cycle." When the signal name "discharge" is extracted, the linking unit 24 generates a "passing work" signal linked to the signal name "discharge."

[0076] Here, when the value of the sensor signal of the "cycle" signal from which the signal name "discharge" was extracted is a value indicating that the work process has been completed normally (for example, "TRUE", "OK", etc.), the linking unit 24 generates an "OK passed work" signal as the "passed work" signal. On the other hand, when the value of the sensor signal of the "cycle" signal from which the signal name "discharge" was extracted is a value indicating that the work process has not been completed normally (for example, "FALSE", "NG", etc.), the linking unit 24 generates an "NG passed work" signal as the "passed work" signal.

[0077] Furthermore, when the linking unit 24 extracts the signal name "discharge", it links it to the workpiece number and generates an "OK / NG" signal.

[0078] The model signal included in row R4 shown in Figure 7 is an example of an "OK passed work" signal generated by linking it to the signal name "Discharge" extracted from the signal names included in the "Cycle" signal of "[Assembly machine = C1]". In this "OK passed work" signal, "Assembly line" is stored as the sensing subject data, "OK passed work" is stored as the signal name, and "[Work #1]" is stored as the sensor signal value. Here, "Assembly line", which is the data stored as the sensing subject, is a value that is included in advance in the factory model M1.

[0079] The model signal included in row R5 in Figure 7 is an example of an "OK / NG" signal generated in association with a workpiece number. In this "OK passed workpiece" signal, "[Work#1]" is stored as the sensing subject data, "OK / NG" is stored as the signal name, and "OK" is stored as the sensor signal value.

[0080] As described above, the classification unit 25 groups the sensor information C1 into workpieces or equipment units based on the process information A1. This allows the information processing device 2 to link each work process to a workpiece or equipment via the model signal.

[0081] Step S140: The linking unit 24 generates a "passing cycle" signal. The "passing cycle" signal is an example of a model signal. The linking unit 24 generates the "passing cycle" signal by linking the "cycle" from which the signal name "discharge" was extracted in step S130. Note that the linking unit 24 does not generate a "passing cycle" signal for a "cycle" from which the signal name "discharge" was not extracted.

[0082] In the "passing cycle" signal, the workpiece number generated in step S120 is stored as the sensing-based data. In the "passing cycle" signal, the name of the "cycle" (the value of the sensing-based data in the "cycle" signal) is stored as the sensor signal value. Each of the two model signals included in row R5 shown in FIG. 7 is an example of a "pass cycle" signal.

[0083] Step S150: The linking unit 24 determines whether or not there is a child part serial number ("child part S / N") in the "cycle." The linking unit 24 causes the classification unit 25 to extract the child part serial number from the "cycle" signal. The linking unit 24 makes the determination based on the extraction result by the classification unit 25. If the linking unit 24 determines that the child part serial number is in the "cycle" (step S150; YES), it executes the process of step S160. On the other hand, if the linking unit 24 determines that the child part serial number is not in the "cycle" (step S150; NO), it ends the model signal generation process.

[0084] Step S160: The linking unit 24 generates a "child part work" signal. The "child part work" signal is an example of a model signal. The linking unit 24 generates a "child part S / N" signal before generating a "child part work" signal. The linking unit 24 generates the "child part S / N" signal by linking it to the child part serial number extracted by the classification unit 25. The model signal included in row R71 shown in FIG. 7 is an example of a "child part S / N" signal.

[0085] The linking unit 24 generates a child part work number based on the work number stored in the sensing subject data in the generated "child part S / N" signal. The linking unit 24 stores the generated child part work number in the data of the sensor signal value to generate a "child part work" signal. The model signal included in row R72 shown in FIG. 7 is an example of a "child part work" signal. With this, the linking unit 24 ends the model signal generation process.

[0086] Now, with reference to FIG. 8, the factory model will be described. FIG. 8 is a diagram showing an example of a factory model according to this embodiment. In the factory model, it is modeled that work is performed on workpieces in virtual equipment. In the factory model shown in FIG. 8, an "assembly line" is equipped with a "cutting machine" and an "assembly machine" as virtual equipment. In this factory model, it is modeled that work is performed on workpieces indicated by workpiece numbers "[Work#1]" and "[Work#2]" by the "cutting machine" and the "assembly machine" equipment, each in units of work processes called "cycles."

[0087] As described above, the model signal is generated by the linking unit 24 based on the factory model M1. The model signal is generated by grouping the sensor information C1 based on the factory model M1 and linking the sensor information C1 together. As a result, the sensor information C1 is grouped by work process, workpiece, or equipment indicated by the factory model M1.

[0088] Returning to Figure 4, we will continue to explain the flow of information processing. Step S60: The display control unit 28 displays the data included in the model signal based on the display rule information A4.

[0089] Here, a display process for displaying data included in a model signal based on display rule information A4 by the display control unit 28 will be described with reference to Fig. 9. Fig. 9 is a diagram showing an example of the display process according to this embodiment.

[0090] Step S210: The operation receiving unit 29 receives an operation indicating a search condition from the user of the information processing device 2. The search condition is indicated by, for example, any one or more of equipment, work, or work process that meets a specific condition.

[0091] Step S220: The display control unit 28 extracts, from the model signal queue A3, model signals associated with equipment, work, or work processes that satisfy the search conditions indicated by the operation accepted by the operation accepting unit 29, based on the display rule information A4. The display control unit 28 generates a display screen from the data included in the extracted model signals, based on the display rule information A4.

[0092] The display rule information A4 specifies, based on the factory model M1, which types of data included in the model signal should be paired to be displayed. As described above, the model signal is data in a format in which the sensing subject of the sensor signal, the signal name of the sensor signal, and the value of the sensor signal are paired. In the display rule information A4, for example, a pair of sensor signal values ​​in one or more model signals that share common sensing subject data is specified as a display target.

[0093] Furthermore, the display rule information A4 specifies that, depending on the type of data, data linked to the data in question be referenced based on the factory model M1. When data is referenced, the referenced data becomes the data to be displayed. For example, when a signal name is specified as the data to be displayed and the value of a sensor signal linked to the signal name is referenced, the value of the sensor signal becomes the data to be displayed.

[0094] Furthermore, in the display rule information A4, for a set of data designated as a display target, the layout of the data when the data is displayed is designated based on the factory model M1. Furthermore, the display rule information A4 specifies a template of a display screen for displaying data based on the factory model M1. The template includes settings such as the layout and design of the display screen. The information processing device 2 can generate a display screen by simply allocating data using the template.

[0095] Step S230: The display control unit 28 displays the data included in the extracted model signal based on the display rule information A4. Here, the display control unit 28 generates a display screen for displaying the data included in the extracted model signal based on the display rule information A4. The display control unit 28 displays the generated display screen on the display device 5. The display control unit 28 may convert the data included in the extracted model signal into a CSV (Comma Separated Value) format and output it to a file based on the display rule information A4. With this, the display control unit 28 ends the display process. With this, the information processing device 2 ends the information processing.

[0096] Here, the search conditions and display rule information A4 will be described with reference to FIG. In the example shown in Fig. 10, "OK passed work" in the input "assembly line" is specified as the search condition. From among the workpieces, the workpiece indicated by the value of the sensor signal included in the "OK passed workpiece" signal is extracted by workpiece number. A model signal having the workpiece indicated by the extracted workpiece number as sensing subject data is extracted.

[0097] 10, the display rule information A4 specifies the workpiece number as the sensing subject, and the signal names of the sensor signals as "S / N," "OK / NG," "processing conditions," "inspection value," and "sub-part serial number." It also specifies that the value of the sensor signal is to be referenced for each of these signal names. As described above, relevant data from the data contained in the model signal extracted based on the search conditions is extracted or referenced based on the display rule information A4 and displayed on the display screen.

[0098] An example of the display screen is shown in Fig. 11. In the example shown in Fig. 11, the display screen is a two-dimensional tabular data consisting of rows and columns in which various data are stored for each workpiece number. The various data are the values ​​of the sensor signals that are referenced by the signal names that are specified to be displayed in combination with the workpieces by the display rule information A4 as described above.

[0099] Here, a display screen when a template specified by the display rule information A4 is used will be described with reference to Fig. 12. Fig. 12 is a diagram showing an example of a display screen according to this embodiment. Display screen P1 is an example of a display screen generated using a template when the factory model is a traceability model. Display screen P1 displays the quality of products, including components, produced on a target line within a specified period.

[0100] Area P10 shows search conditions, while area P11 shows the serial number, cycle, serial numbers of components (sub-components), values ​​of various sensor signals, values ​​of "OK / NG" signals, cycles of components (sub-components), and processing conditions for the product (work).

[0101] As described above, in the display process, data to be displayed on the display screen is extracted based on the factory model M1. Here, another example of the data extraction process by the display control unit 28 will be described with reference to Fig. 13. Fig. 13 is a diagram showing an example of the flow of the data extraction process in the display process according to this embodiment.

[0102] The data shown in FIG. 13 includes production resources, IoT (Internet of Things) data, and external data. The production resources are data specified in advance by the production resource dictionary information A12. The production resources include data such as line configuration and monitored objects. The IoT data is data acquired from various sensing entities and is an example of the time series queue A2 and the model signal queue A3. The external data is data regarding plans and design values. The external data is read using a CSV file or a file created by spreadsheet software, or acquired from a database external to the production management system 1.

[0103] Furthermore, generating a model signal and storing it in advance as a sensor signal value in IoT data (model signal queue A3) may result in high costs in terms of data resources. In such cases, the return value of the function may be used. When a search condition is entered, a calculation is immediately performed by an external function according to the search condition. As a result, the return value of the external function is displayed as the search result, as the value specified in the search condition.

[0104] An example of a case where costs become high in terms of data resources is when tracking (traceability) by individual identification is not possible. A specific example of a case where tracking is not possible is when the "passing time" of a passing process is predicted and calculated based on "time" based on the standard cycle time and operating status of each process.

[0105] As described above, in the information processing device 2, the model signal queue A3 is generated based on the signal dictionary information A11, and the model signals are linked to each other (signal dictionary function). In addition, in the display rule information A4, the data reference destination is specified based on the result of linking the model signals to each other based on the factory model M1.

[0106] As described above, the display control unit 28 extracts model signals associated with equipment, work, or work processes that satisfy the search conditions from the model signal queue A3 based on the search conditions and the display rule information A4 (data extraction function). The display rule information A4 is based on the process information A1, which includes the signal dictionary information A11. Therefore, when extracting model signals, the display control unit 28 extracts model signals that match the search conditions based on the signal dictionary information A11. The display control unit 28 generates a display screen from the data included in the extracted model signals based on the display rule information A4 (screen display function).

[0107] For example, to display the serial numbers of workpieces that passed through the line on a certain day, "assembly line" and "OK passed workpiece" are entered as search conditions along with information specifying a period. In the signal dictionary information A11, for example, the signal name "OK passed workpiece" is associated with the data reference destination of "information source = IoT." In this case, the "OK passed workpiece" signal is extracted from the model signal stored as IoT data.

[0108] For example, to display the passage time of a specific process from a product serial number, the serial number and the process name are entered as search conditions. In the signal dictionary information A11, for example, "passage time" is associated with a data reference of "information source = function F(x)." In this case, the function F(x) is called to calculate the time.

[0109] With the above-described configuration, when the information processing device 2 extracts data from the model signal queue A3 generated based on the factory model, the signal dictionary information A11 associates certain data with the reference destination of the data, so that the data can be extracted without depending on the structure of the factory model.

[0110] Furthermore, the information processing device 2 can display planned values, design values, pre-specified production resources (such as line configurations), and indicators obtained by immediate calculation using functions simply by specifying the signal name according to the purpose as a search condition, so the user only needs to perform the same operations regardless of the type of data being referenced.

[0111] In the factory model M1, a sensor signal that is not included in the pre-prepared package may be added. Here, referring to FIG. 14, a case where video data is added as a sensor signal will be described. FIG. 14 is a diagram showing an example of an overview of information processing when video data is added as a sensor signal according to this embodiment. The sensing range of various pieces of equipment provided in the production facility is limited. Video data captured by a camera is used to supplement the sensing range of the various pieces of equipment.

[0112] When video data is added as a sensor signal, the production management system 1 includes a video clipping server 6 in addition to the configurations shown in Fig. 1 and Fig. 3. The video clipping server 6 may be provided as a separate entity from the information processing device 2, or may be provided in the information processing device 2 as a virtual server similar to the respective functional units provided in the information processing device 2.

[0113] The video clipping server 6 acquires video data captured by a camera (not shown) installed in a factory, and clips out a predetermined frame from among the frames included in the video data based on a clipping signal.

[0114] The cutout signal is a sensor signal associated with the start and end times of frame cutout. The cutout signal associated with the start time of frame cutout is also called a "From" signal. The cutout signal associated with the end time of frame cutout is also called a "To" signal. Which sensor signal is used as the cutout signal is set in the signal dictionary information A11.

[0115] In the example shown in Figure 14, when a workpiece is carried into the assembly machine, a sensor signal with the signal name "carry-in" ("carry-in" signal) is output, and when a workpiece is carried out from the assembly machine, a sensor signal with the signal name "carry-out" ("carry-out" signal) is output. The "carry-in" signal is used as the "From" signal. The "carry-out" signal is used as the "To" signal.

[0116] The video clipping server 6 outputs an "index" signal during the period from when it receives the "From" signal to when it receives the "To" signal. The "index" signal is a sensor signal, and its value is the index of the video data clipped by the video clipping server 6.

[0117] The "index" signal output by the video extraction server 6 is acquired by the sensor information acquisition unit 20 provided in the information processing device 2, in the same way as other sensor signals, with the sensing subject being the "camera," the signal name being "index," and the value of the sensor signal being an index of the video data.

[0118] The video data index is used to link and play back the linked and extracted video data in association with abnormalities during production, equipment status, etc. For example, when linking video data to the reason for a stoppage and referencing it, equipment abnormalities, etc. can be confirmed by playing back the video data. Also, when linking video data to a cycle and referencing it, the processing status, waiting, etc. can be confirmed by playing back the video data.

[0119] The relationship between the factory model and the display screen will now be summarized with reference to Fig. 15. Fig. 15 is a diagram showing an example of an outline of the relationship between the factory model and the display screen according to this embodiment. The factory model M1 is an example of a traceability factory model described in this embodiment. In a factory model, signals are linked to each other by a hierarchical structure. For example, in the factory model M1, a "factory" signal is placed at the top layer. Directly below the "factory" signal is placed a "line" signal. Directly below the "line" signal are placed one or more "equipment" signals and one or more "work" signals. Directly below the one or more "equipment" signals are placed one or more "cycle" signals.

[0120] As described above, the information processing device 2 generates a model signal based on the factory model. One or more model signals are associated with various signal names included in the factory model M1. The model signal includes various data (sensor information C1) in pairs.

[0121] According to search conditions that specify the data to be displayed, the data is referenced based on the factory model, and the data to be displayed is extracted from the various data included in the model signal. The screen display function displays the extracted data based on the factory model. Display screen D1 shows a display screen displayed based on the traceability factory model.

[0122] At least the sensing subject and the signal name may be edited by the user. Editing includes changing and adding. The editing operation is accepted by the operation accepting unit 29. The sensor information editing unit 27 edits at least the sensing subject and the signal name among the attributes of the sensor information C1 based on the editing operation accepted by the operation accepting unit 29. This allows the user to edit the sensing subject and the signal name when the information processing device 2 wants to acquire a sensor signal from equipment specific to the production site.

[0123] Components of the factory model may be added by the user. For example, a signal name of a line, equipment, or operation that is not included in the signal dictionary or the production resource dictionary may be added by the user. The factory model itself may also be added by the user.

[0124] An operation to add a component of a factory model or an operation to add a factory model is accepted by the operation accepting unit 29. The process information generating unit 26 adds a signal name to the signal dictionary information A11 or the production resource dictionary information A12 based on the operation accepted by the operation accepting unit 29. The process information generating unit 26 associates the added signal name with a signal name that is already included in the signal dictionary or the production resource dictionary.

[0125] Therefore, the process information generation unit 26 generates the signal dictionary information A11 or the production resource dictionary information A12. That is, the process information generation unit 26 generates the process information A1. This allows the user to change the process information A1 (the factory model indicated by the signal dictionary information A11 and the production resource dictionary information A12) in the information processing device 2 when extracting issues specific to a production site as well as issues common to the production site.

[0126] [Factory model features] As described above, the information processing by the information processing device 2 according to this embodiment is processing for visualizing data based on a factory model. Here, the features of the information processing by the information processing device 2 are summarized. The features described below are common features regardless of the type of factory model.

[0127] This information processing allows the data that you want to visualize (the information you want to see) at the production site to be provided simply by inputting the minimum necessary signals (key signals). In this information processing, data to be visualized at the production site is pre-installed in the package (signal dictionary information A11, production resource dictionary information A12). In addition, in this information processing, data that is not pre-installed in the package can be added at any time using add-in software. In this information processing, a set of the minimum necessary signals (key signals) is determined for each factory model, and the user assigns the values ​​of the sensor signals actually acquired from the sensors to the key signals in advance. This allows the factory model to treat the actual sensor signals as key signals even if the signal names differ between the key signals and the sensor signals.

[0128] This information processing can handle sensor signals, production resources (e.g., line configurations), design and planning values ​​(e.g., production plans and calendars), and the results of calculations made by combining these, in a unified manner in the same format (sensing subject of the sensor signal, signal name of the sensor signal, and value of the sensor signal).As a result, this information processing can handle the extraction of data to be displayed on the display screen via a signal dictionary without being aware of the data source, and can create templates by combining it with key signals.

[0129] In this information processing, the results of calculations made by combining sensor signals (for example, production volume forecasts and OEE values) can be calculated not only on-the-fly using functions, but also pre-calculated and saved in the same format as IoT data (raw signals, model signals) for reference. This reduces the calculation cost when referencing data. For example, daily summaries can be pre-calculated once a day. It is also possible to view the daily trends in OEE index values ​​over a span of several months, for example.

[0130] This information processing makes it possible to visualize data at the production site using a set of key signals, virtual equipment (generation of model signals based on a factory model), and template screens.Key signals, virtual equipment, and template screens can each be added at any time using add-in software.By using this set of key signals, virtual equipment, and template screens, this information processing significantly reduces the effort required for visualization compared to conventional methods.

[0131] In this information processing, in the process of generating a model signal, raw signals from one key signal to another key signal in the time-series queue A2 are classified into one group. In other words, sensor signals output during the period from when one sensor signal is output to when another sensor signal is output can be grouped. This makes it possible to incorporate sensor signals other than those corresponding to key signals into the model. In the example of a traceability model, various sensor signals are output in the corresponding cycle of the corresponding process. For example, in the corresponding cycle, sensor signals are output having the equipment status such as hydraulic pressure and quality measurement values ​​such as radius as their respective sensor signal values.

[0132] The above describes the features of information processing by the information processing device 2 that are common to all types of factory models. However, the key signals, model signals, and template screens differ for each factory model. Below, we will explain the features of the traceability model, which is the factory model M1 of this embodiment.

[0133] In the traceability model, even if the signal name of a model signal is not a serial number, by linking the model signals to each other based on the workpiece number, it is possible to identify which workpiece work process the model signal corresponds to. In this embodiment, an example has been described in which a "cycle passage" signal is generated, which is a model signal that uses the workpiece number as the sensing subject and has the cycle as the value of the sensor signal. Since the "cycle passage" signal links the workpiece number and the cycle, it is possible to identify whether the various model signals included in the cycle correspond to the workpiece work process corresponding to the workpiece number.

[0134] In the traceability model, even if a workpiece has passed through the same process multiple times, such as in the case of reprocessing, it can be identified for each pass. Measurement values ​​for the same workpiece are recorded multiple times, but it is possible to identify which pass the measurement value was for. The traceability model makes it possible to identify which equipment the work has passed through in the case of parallel processes. The traceability model can automatically calculate production volume and NG numbers on the line or factory based on the values ​​of the sensor signals output from each piece of equipment.

[0135] In the traceability model, when a sensor signal (e.g., video data) that is not included in the pre-prepared package is added, the added sensor signal is generated between the start of the cycle (e.g., the time when the "in" signal is generated) and the end of the cycle (e.g., the time when the "discharge" signal is generated). This makes it possible to easily include the added sensor signal in the cycle, and makes the added sensor signal a traceable signal.

[0136] [Variation 1] Another example of the factory model is the OEE model, which will be described below as a modified example of this embodiment. 16 is a diagram showing an example of a factory model according to this modified example. Factory model M21 and factory model M22 are each an example of an OEE model. In factory model M21, an "equipment 1" signal is placed on the top layer. Immediately below the "equipment 1" signal are placed an "operating" signal, a "stopped" signal, an "OK" signal, and an "NG" signal. Immediately below each of the "operating" signal and the "stopped" signal, one or more signals indicating the operating status of the equipment (such as an "hydraulic pressure abnormality" signal) are placed.

[0137] In factory model M22, the "OEE" signal is placed on the top layer. The "OEE" signal is placed below the "Equipment 1" signal in a factory model with the same structure as factory model M21, along with the "OK" and "NG" signals. Directly below the "OEE" signal are the "OEE index" signal, the "Loss time" signal, and the "Frequency" signal.

[0138] In the OEE model, model signals that indicate various operating states of equipment (such as equipment shutdown or waiting) are held together with model signals that indicate more detailed operating states and causes (such as reasons for shutdown).

[0139] There are several methods for understanding the operating status and causes in more detail. For example, in the case of a short stop, a stop time less than a set value is automatically classified as a short stop. In addition, the user may preset a specific reason for the stop by checking the status of an alarm, etc. After a model signal is generated, the user may input the reason for the stop. The user may specify a monitoring signal and preset the reason. For example, the "From" signal and "To" signal described above in Figure 14 are used as monitoring signals. The reason (non-operation, rest time, etc.) is entered by referring to a calendar.

[0140] The OEE model automatically generates index values ​​and loss time aggregated by section in advance. For example, defect loss and performance loss are calculated from quantities, etc., and then subtracted from operating hours to aggregate the loss time.

[0141] Here, a display screen when a template specified by the display rule information A4 is used will be described with reference to Fig. 17. Fig. 17 is a diagram showing an example of a display screen according to this modified example. Display screen P2 is an example of a display screen generated using a template when the factory model is an OEE model. Display screen P2 displays various OEEs for a certain processing step on a target line within a specified period.

[0142] Area P20 shows the search conditions. Area P21 shows the results of comparing the calculated OEE with the target OEE. The OEE is calculated as the product of the equipment availability rate, the performance rate, and the non-defective product rate. The target OEE is included in external information A5. Area P22 shows the output. Area P23 shows the calculated performance rate. Area P24 shows the results of an analysis of the reasons for equipment shutdowns.

[0143] [Organizing various data] For each factory model, data provided in advance as a package (PKG) and data set by the user are organized in a table for each of the production resource dictionary information A12, external information A5, raw signals, model signals, and display rule information A4. Fig. 18 is a diagram showing an example of a table organizing data provided in advance as a package and data set by the user according to this embodiment.

[0144] The production resource dictionary is included in the production resource dictionary information A12. Raw signals are sensor signals acquired from various sensing entities. Planned values ​​and design values ​​are included in the external information A5. Model signals are sensor signals generated based on a factory model and are not set by the user. Display screen templates are included in the display rule information A4.

[0145] Next, referring to Figure 19, the components of each factory model will be summarized. Fig. 19 is a diagram showing an example of a list of components of each factory model according to this embodiment, which shows a list of components of each of the traceability model and the OEE model. As described above, the components of the factory model include raw signals to which sensor signals from sensors are assigned, data predefined as production resources, and values ​​of sensor signals (model signals) generated by virtual equipment based on the factory model.

[0146] Here, the setting screen for the user to make settings will be described with reference to FIGS. FIG. 20 is a diagram showing an example of a setting screen P3 according to this embodiment. Production resources are set on the setting screen P3. In area P30, line configurations and equipment configurations are displayed in a hierarchical structure. In area P31, properties are displayed. The hierarchical structure shows how the line configurations, equipment configurations, and properties are linked to each other. Using the setting screen P3, the user can set production resources while checking how each configuration is linked to the other.

[0147] FIG. 21 is a diagram showing an example of a setting screen P4 according to this embodiment. Signal allocation is set on the setting screen P4. A list of raw signals and model signals is displayed in a hierarchical structure in an area P40. The hierarchical structure indicates how the raw signals and model signals are linked to each other. A list of sensor signals acquired from the sensing subject is displayed in an area P41. The user can use the setting screen P4 to perform settings for allocating sensor signals to raw signals. The user can also use the setting screen P4 to check how the raw signals and model signals are linked to each other.

[0148] In the present embodiment, a work process refers to a work process for a workpiece, including a process performed by equipment that acquires signals. The classification unit 25 groups the sensor information C1 by workpiece or by equipment based on process information indicating the configuration of the work process. However, this is not limiting. The work process may also be a work process performed by a worker. In this case, the classification unit 25 groups the sensor information C1 by worker based on process information indicating the configuration of the work process performed by the worker. Work performed by a worker includes, for example, work in which the worker transports parts, work in which the worker processes parts, and work in which the worker assembles parts. When the work process is a work process performed by a worker, the signal acquisition entity, as in the present embodiment, is, for example, a sensor, a button, a buzzer provided on various pieces of equipment, a mobile terminal device carried by the worker, a camera, etc. In particular, when the signal acquisition entity is a mobile terminal device, the worker inputs various pieces of information related to the work process into the mobile terminal device, thereby causing the mobile terminal device to acquire a signal. Furthermore, the work process may include both work processes for workpieces, including processes performed by equipment, and work processes for work performed by workers.

[0149] As described above, the information processing device 2 according to this embodiment includes the sensor information acquisition unit 20, the process information acquisition unit 21, the linking unit 24, and the display control unit . The sensor information acquisition unit 20 acquires sensor information C1 including a signal acquisition entity (in this embodiment, a sensing entity) that acquires a signal, the value of the signal acquired from the signal acquisition entity (in this embodiment, the sensing entity), a timestamp indicating when the signal was acquired, and the signal name of the signal. The process information acquiring unit 21 acquires process information A1 that indicates the configuration of the work process including a process performed by equipment that is a signal acquiring subject (a sensing subject in this embodiment). The linking unit 24 links the sensor information C1 together based on the process information A1. The display control unit 28 displays the sensor information C1 linked by the linking unit 24 according to a display rule based on the process information A1.

[0150] With this configuration, the information processing device 2 according to this embodiment can include a method of extracting issues common to production sites in a general-purpose package (process information A1), thereby significantly reducing the effort required for extracting issues at production sites.

[0151] At production sites such as factories, improving QCD (quality, cost, delivery) is a constant challenge, and issues are being identified based on data obtained through IoT (Internet of Things). However, the types of products, production methods, and data collection methods vary depending on the production site. However, the issues that need to be identified are based on QCD, and are common to all production sites, such as the efficiency of equipment and workers and the resulting quality of the products. The information processing device 2 significantly reduces the effort required to bridge the gap between the fact that the data used for problem extraction varies depending on the production site, and the fact that the problems to be extracted are common to all production sites.The information processing device 2 can include a general-purpose method for extracting problems common to all production sites in a package (process information A1), which results in quick problem extraction for the factory and shortens the improvement cycle.

[0152] The information processing device 2 also enables more flexible construction and addition of data models in terms of data format than conventional devices. Conventionally, data was saved based on a predefined schema, and relationships between data were expressed within the predefined schema. In the information processing device 2, the data format of a model signal expressing relationships between raw signals is the same as the data format of the raw signals, so that a model signal expressing relationships between raw signals can be stored in the same manner as the raw signals. In the process of generating a model signal (e.g., a cycle signal in this embodiment) expressing relationships between raw signals, the information processing device 2 utilizes the fact that raw signals are stored in chronological order in the time-series queue A2. This enables the information processing device 2 to flexibly construct and add data models.

[0153] In the information processing device 2, a general-purpose method for extracting issues common to production sites is included in a package (process information A1). In the information processing device 2, the package (process information A1) can create a flexible data model from IoT data (sensor signals output from various sensing entities). In the information processing device 2, the package (process information A1) can create display settings common to the production site based on display rules (display rule information A4) based on the process information A1, and can realize a display screen based on the display settings.

[0154] Furthermore, with the information processing device 2, the user can obtain key indicators simply by assigning acquired sensor signals to key signals and specifying search conditions, thereby significantly reducing the effort required to extract issues at the production site. Previously, in order to obtain sensor signals from sensors, it was necessary to set up a separate Business Intelligence (BI) tool for each factory line, or process them using separate programs. This was because the sensor signals obtained from the sensors, the equipment status to be known, the workpiece measurements, and the method of identifying individual workpieces all differed from line to line, requiring separate configuration. In particular, the method of identifying individual workpieces often differs from line to line, and it is practically difficult to include identifiers for individual workpieces, such as serial numbers, in all sensor data. This complicated the individual configuration, slowing down the utilization of BI tools. In the information processing device 2, each work process can be linked to a workpiece number via the model signal.

[0155] In the present embodiment, an example has been described in which the information processing device 2 is used to extract problems using IoT at a production site such as a factory, but the present invention is not limited to this. By changing the factory model to a model corresponding to another industry, the configuration of the information processing device 2 can be applied to extract problems in various industries such as agriculture, construction, and medicine.

[0156] (Second embodiment) The second embodiment of the present invention will be described in detail below with reference to the drawings. In this embodiment, we will explain a case where the system determines the work performed by workers based on the operating status of equipment, the position of workers, and objects (work, carts, etc.), and visualizes the lost time and value time of the work. The system according to this embodiment is referred to as an operation assuming system 1a, and the information processing device is referred to as an information processing device 2a.

[0157] Fig. 22 is a diagram showing an example of the configuration of a work estimation system 1a according to this embodiment. The work estimation system 1a is a system for determining the work process and work of a worker based on the operating status of equipment, the location of the worker, and objects (workpieces, carts, etc.), and visualizing the lost time and value time of the work. The work estimation system 1a includes an information processing device 2a, a display device 5, a position information collection device 7a, and an equipment information collection device 8a.

[0158] The location information collecting device 7a acquires location information of the worker output from a sensor worn by the worker. The sensor includes, for example, a GPS (Global Positioning System) module and acquires location information of the device itself. A mobile terminal such as a watch-type mobile terminal or a smartphone may be used instead of the sensor. The location information is three-dimensional location information.

[0159] The equipment information collection device 8a acquires various equipment information from various sensing entities. The various sensing entities are, for example, CNCs, PLCs, etc. The PLCs acquire various sensor signals from sensors installed at predetermined positions in the work site and generate equipment information based on the values ​​of the sensor signals. The equipment information is, for example, information indicating equipment operation, equipment status, and the status of objects.

[0160] The location information collecting device 7a and the equipment information collecting device 8a are each a computer such as a server or a PC. At least one of the location information collecting device 7a and the equipment information collecting device 8a may have its function provided as a virtual server in the information processing device 2a.

[0161] The information processing device 2a acquires the worker's location information from the location information collection device 7a. The information processing device 2a also acquires equipment information from the equipment information collection device 8a. The information processing device 2a determines the worker's work from the acquired location information and equipment information based on a signal dictionary. The information processing device 2a displays the determined work on the display device 5 according to display rules. The information processing device 2a is, for example, a virtual server that runs multiple OSs on one server. Note that the information processing device 2 may be configured with multiple servers.

[0162] Information processing based on a signal dictionary by the information processing device 2a will be described. The information processing device 2a determines the work process linked to the worker's stay area from the acquired location information based on the signal dictionary. The information processing device 2a determines the work linked to the operating status of the equipment, the status of the worker, the status of the object, etc. from the acquired equipment information based on the signal dictionary. The information processing device 2a generates a model signal from the determined work process, determined work, etc. based on the signal dictionary.

[0163] Here, a signal dictionary used for information processing by the information processing device 2a will be described with reference to Fig. 23. Fig. 23 is a diagram showing an example of a signal dictionary according to this embodiment. In this signal dictionary, the stay area of ​​a worker is linked to a work process. In addition, in this signal dictionary, equipment information such as the operating status of the equipment, the status of the worker, and the status of the object is linked to the work in the work process. In the work identification system 1a, work determined using the signal dictionary is considered to be work performed by a worker without directly observing the actual work status of the worker.

[0164] Equipment operation information used to determine work includes, for example, the equipment operation status (operating or stopped), the equipment inventory status (empty or loaded), equipment alarms (alarm code, delay message, etc.), the worker (moving or stationary), and the relationship between the worker and the cart (whether the distance between the worker and the cart is within a specified distance, whether there is movement, etc.).

[0165] For example, when the location indicated by the location information is an area in front of the equipment, the information processing device 2a determines the work associated with the equipment operation status in the signal dictionary. For example, when the location indicated by the location information is an area other than the area in front of the equipment, the information processing device 2a determines the work associated with the area in the signal dictionary.

[0166] The information processing device 2a classifies the time of the work performed by the worker from the determined work (deemed work) into value time and work loss time based on the signal dictionary. The information processing device 2a analyzes the loss time and value time. The information processing device 2a displays the analysis results as an analysis screen on the display device 5.

[0167] Furthermore, the conditions for counting work and the conditions for lost time differ for each user. In the signal dictionary held by the information processing device 2a, the conditions for counting work and the allocation of lost time are held in a matrix-format definition body, and this definition body can be changed for each user. The information processing device 2a generates work information as a model signal by referencing this definition body contained in the signal dictionary. By using a signal dictionary that holds the above definition body, the work counting system 1a ensures versatility even if the conditions (conditions for counting work and conditions for lost time) differ from one production site to another.

[0168] FIG. 24 is a diagram showing an example of an analysis screen P5 according to this embodiment. On the analysis screen P5, lost time and value time are displayed in the form of a graph. Examples of analysis screens are not limited to the analysis screen P5 shown in FIG. 24. On the analysis screen, workers, the operating status of equipment, and work may be displayed immediately. On the analysis screen, the results of an analysis of the personal characteristics of work (such as work experience and craftsmanship status) may be displayed (visualized).

[0169] The task estimation system 1a according to this embodiment can visualize the task status of workers, the operating status of equipment, and the like, and can therefore be used to improve the operating rate and productivity at production sites and work sites.

[0170] In the past, it was sometimes difficult to analyze work status by manually inputting work tasks or identifying tasks using sensors. For example, depending on the work site or work process, it may not be possible to wear a mobile device such as a watch-type mobile device or smartphone. Also, there are cases where inputting work tasks is cumbersome or where it is not possible to add more sensors due to cost.

[0171] Even in the above-mentioned cases, the work estimation system 1a can identify and analyze work based on a pre-set signal dictionary by combining sensor signals from sensors that can acquire equipment operation information with worker location information. The work estimation system 1a generates new model signals that indicate the work status by determining work by combining sensor signals from sensors that can acquire information on work that cannot be acquired directly from the production site with location information. This makes it possible for the work estimation system 1a to visualize and analyze work with a certain degree of accuracy even when only a small number of sensors are installed at the production site.

[0172] Note that a portion of the information processing devices 2 and 2a in the above-described embodiments may be implemented by a computer. In this case, a program for implementing the control function may be recorded on a computer-readable recording medium, and the program may be loaded into a computer system and executed. Note that the term "computer system" as used herein refers to a computer system built into the information processing devices 2 and 2a, including hardware such as an OS and peripheral devices. Furthermore, the term "computer-readable recording medium" refers to portable media such as flexible disks, optical magnetic disks, ROMs, and CD-ROMs, as well as storage devices such as hard disks built into the computer system. Furthermore, the term "computer-readable recording medium" may also include media that dynamically store programs for a short period of time, such as communication lines used when transmitting programs via networks such as the Internet or telephone lines, or media that store programs for a fixed period of time, such as volatile memory within a computer system that serves as a server or client. The program may be designed to implement a portion of the above-described functions, or may be capable of implementing the above-described functions in combination with a program already stored in the computer system. Furthermore, part or all of the information processing devices 2, 2a in the above-described embodiments may be realized as an integrated circuit such as an LSI (Large Scale Integration). Each functional block of the information processing devices 2, 2a may be individually implemented as a processor, or part or all of them may be integrated into a processor. Furthermore, the integrated circuit implementation method is not limited to LSI, and may be implemented using a dedicated circuit or a general-purpose processor. Furthermore, if an integrated circuit implementation technology that can replace LSI emerges due to advances in semiconductor technology, an integrated circuit based on that technology may be used.

[0173] One embodiment of the present invention has been described in detail above with reference to the drawings, but the specific configuration is not limited to that described above, and various design changes and the like are possible within the scope that does not deviate from the gist of the present invention. [Explanation of symbols]

[0174] 2, 2a...information processing device, 20...sensor information acquisition unit, 21...process information acquisition unit, 24...linking unit, 28...display control unit, C1...sensor information, A1...process information

Claims

1. a signal acquisition entity that acquires a signal; and a sensor information acquisition unit that acquires sensor information including a value of the signal acquired from the signal acquisition entity, a timestamp indicating when the signal was acquired, and a signal name of the signal; a process information acquisition unit that acquires process information indicating a configuration of a work process including a process by the signal acquisition subject, using at least a key signal to which the signal name is associated; a classification unit that groups the sensor information into work process units based on the work process and the time stamp indicated by the work information using the key signal; a linking unit that links the sensor information classified into the same group by the grouping of the sensor information by the classification unit; a display control unit that displays the sensor information linked by the linking unit according to a display rule based on the process information; An information processing device comprising:

2. The work process is a work process for a workpiece including a process performed by the equipment that is the subject of signal acquisition. The information processing device according to claim 1 .

3. The classification unit groups the sensor information into workpiece units or equipment units based on the process information. The information processing device according to claim 2 .

4. The work process is the work process performed by the worker. The information processing device according to claim 1 .

5. The classification unit groups the sensor information by worker based on the process information. The information processing device according to claim 4 .

6. a process information generating unit that generates the process information The information processing device according to claim 1 .

7. a sensor information editing unit that edits at least the signal acquisition entity and the signal name among the attributes of the sensor information; The information processing device according to claim 1 .

8. a sensor information acquisition step of acquiring sensor information including a signal acquisition entity that acquires a signal, a value of the signal acquired from the signal acquisition entity, a timestamp indicating when the signal was acquired, and a signal name of the signal; a process information acquisition step of acquiring process information indicating a configuration of a work process including a process by the signal acquisition subject, using at least a key signal to which the signal name is associated; a classification step of grouping the sensor information into work process units based on the work process and the time stamp indicated by the process information using the key signal; a linking step of linking the sensor information classified into the same group by grouping the sensor information in the classification step; a display control step of displaying the sensor information linked in the linking step according to a display rule based on the process information; An information processing method comprising:

9. On the computer, a sensor information acquisition step of acquiring sensor information including a signal acquisition entity that acquires a signal, a value of the signal acquired from the signal acquisition entity, a timestamp indicating when the signal was acquired, and a signal name of the signal; a process information acquisition step of acquiring process information indicating a configuration of a work process including a process by the signal acquisition subject, using at least a key signal to which the signal name is associated; a classification step of grouping the sensor information into work process units based on the work process and the time stamp indicated by the process information using the key signal; a linking step of linking the sensor information classified into the same group by grouping the sensor information in the classification step; a display control step of displaying the sensor information linked in the linking step according to a display rule based on the process information; A program to execute.

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