Information processing method, information processing apparatus, control program, recording medium, article manufacturing method, learning data acquisition method

Abstract

To make it easy for an operator to execute operations such as confirmation and comparison of given partial data from collected time-series data.SOLUTION: There is adopted in an information processor an information processing method characterized by displaying: a first image displaying a plurality of pieces of partial time-series data related to physical quantities concerning the status of a machine; a second image displaying the partial time-series data at a smaller interval than an interval of the partial time-series data on the first image; a first mark indicating predetermined first partial time-series data in the partial time-series data displayed on the first image; and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed on the second image.SELECTED DRAWING: Figure 11

Description

Technical Field

[0001] The present invention relates to an information processing method and an information processing apparatus.

Background Art

[0002] The operating state of a mechanical device can change moment by moment due to changes in the state of its components, etc. If we call the case where the operating state is within the allowable range the normal state and the case outside the allowable range the failure state in light of the purpose of use of the mechanical device, for example, in the case of a production machine, when it enters the failure state, problems such as manufacturing defective products or stopping the production line will occur.

[0003] In production machines, etc., in order to prevent the occurrence of failure states as much as possible, even when the same work is repeatedly carried out, it is common to perform maintenance work regularly or irregularly. To increase preventive safety, it is effective to shorten the implementation interval of maintenance work. However, since the production machine, etc. is stopped during maintenance work, if the frequency of maintenance work is increased excessively, the operating rate of the production machine, etc. will decrease. Therefore, it is desirable to be able to detect when a machine, etc. is still in the normal state but the occurrence of a failure state is approaching. If it is possible to detect that the occurrence of a failure state is approaching (predict the occurrence of a failure), then maintenance work on the machine, etc. can be carried out at that time, so it is possible to suppress the operating rate from decreasing more than necessary.

[0004] As a method for predicting the occurrence of a failure, there is known a method in which a learned model obtained by machine learning the state of a mechanical device is created in advance, and the state of the mechanical device at the time of evaluation is evaluated using the learned model. To improve the prediction accuracy, it is important to construct a learned model suitable for failure prediction. For that purpose, it is important to prepare learning data (teacher data) used when generating a failure prediction model of a mechanical device by machine learning. To determine whether the extracted data is suitable as learning data, detailed data analysis such as waveform confirmation and comparison is required.

[0005] For example, there is a trend graph display system described in Patent Document 1. Patent Document 1 has a first area that displays time series data over time, a second area that displays an enlarged version of the time series data for a specific period selected by the user from the first area, and a third area that displays the time series data corresponding to the specific period in a table format. The time series data is compared by comparing the data in the table displayed in the third area with data at other times in conjunction with a cursor indicating the specific time point selected by the user in the second area. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2013-232061 A Summary of the Invention [Problem to be solved by the invention]

[0007] In general, in order to manage the operating state of machinery and equipment, various parameters (physical quantities) are measured and a huge amount of time-series data is acquired. In order to build a trained model suitable for predicting failures in machinery and equipment, it is necessary to extract appropriate data from the huge amount of acquired time-series data and perform detailed data analysis such as checking and comparing waveforms to determine whether the data is suitable for learning.

[0008] However, for example, in the case of machinery such as industrial robots installed in production lines, the frequency of failures is generally not high, so it is necessary to collect time series data over a long period of time. Furthermore, the collected time series data is data for managing the operating state of the machinery, so there are many measurement parameters, and in order to analyze the waveforms in detail, the sampling rate needs to be high, and the amount of collected data becomes enormous. Thus, when extracting data related to irregular failures from data collected at a high sampling rate over a long period of time and performing tasks such as comparison, the conventional data display method places a heavy burden on the worker, causing problems in work efficiency and accuracy.

[0009] Patent Document 1 describes displaying cursors that are linked to a trend graph for a specific period and a table showing data corresponding to the trend graph. However, when displaying a graph of time-series data collected over a long period of time, the larger the data is enlarged as in the conventional data display method, and it becomes cumbersome to check and compare the detailed behavior of the time-series data.

[0010] Therefore, there has been a demand for an information processing method and an information processing device that allows an operator to easily perform tasks such as checking and comparing arbitrary partial data from collected time-series data. [Means for solving the problem]

[0011] In view of the above problems, the present invention provides: Processing unit is related to the physical quantity related to the state of the machine At least two A first image showing partial time series data; In The partial time series data In the time axis direction interval The partial time series data is sampled at different intervals from that a first mark indicating a first partial time series data in the partial time series data displayed in the first image, and a second mark indicating a second partial time series data corresponding to the first partial time series data in the partial time series data displayed in the second image. And , In the second image, the interval of the partial time series data is made smaller than that in the first image and displayedAn information processing method characterized by the above is adopted.

Advantages of the Invention

[0012] According to the present invention, when an operator checks or compares any partial data from the collected time-series data, these operations can be easily executed.

Brief Description of the Drawings

[0013]

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Mode for Carrying Out the Invention

[0014] With reference to the drawings, an information processing method, an information processing apparatus, etc., which are embodiments of the present invention, will be described. In the drawings referred to in the following description of the embodiments, elements denoted by the same reference numerals have the same functions unless otherwise specified.

[0015] (First Embodiment) FIG. 1 is a schematic diagram for explaining the configuration of functional blocks included in an information processing apparatus according to an embodiment. In FIG. 1, functional elements necessary for explaining the features of the present embodiment are represented by functional blocks, but descriptions of general functional elements not directly related to the problem-solving principle of the present invention are omitted. Further, each functional element shown in FIG. 1 is conceptually functional and does not necessarily have to be physically configured as shown in the figure. For example, the specific form of dispersion or integration of each functional block is not limited to the illustrated example, and all or part of them can be functionally or physically dispersed and integrated in any unit according to the usage situation or the like.

[0016] As shown in FIG. 1, a time-series data display device 100 as an information processing apparatus according to the embodiment is communicably connected to a mechanical device 10 as a mechanical device to be measured.

[0017] The mechanical device 10 is various industrial equipment such as, for example, an industrial robot or a production device installed on a production line. The mechanical device 10 is provided with various sensors 11 for measuring physical quantities related to the state of the mechanical device. For example, when the mechanical device 10 is an articulated robot, sensors for measuring the current value of the motor that drives the joint, joint angle sensors, sensors for measuring speed, vibration, and sound, etc. can be installed. However, this is merely an example, and depending on the type of the mechanical device 10, its working purpose, etc., appropriate types and numbers of sensors can be installed as the sensor 11 at appropriate positions. Various sensors such as force sensors, torque sensors, vibration sensors, sound sensors, imaging sensors, distance sensors, temperature sensors, humidity sensors, flow sensors, pH sensors, pressure sensors, viscosity sensors, gas sensors, etc. can be used for the sensor 11. In addition, in FIG. 1, the sensor 11 is shown as a single unit for the convenience of illustration, but usually a plurality of sensors are installed so as to be communicable with the time-series data display device 100.

[0018] The mechanical device 10 is connected by wire or wirelessly so as to be communicable with the time-series data display device 100 as an information processing device, and the time-series data display device 100 can acquire the data measured by the sensor 11 through communication. Hereinafter, the functional blocks of the time-series data display device 100 will be described in order. The time-series data display device 100 includes a control unit 110, a storage unit 120, a display unit 130, and an input unit 140.

[0019] The control unit 110 includes a plurality of functional blocks, and these functional blocks are configured, for example, by the CPU of the time-series data display device 100 reading out and executing a control program stored in a storage device or a non-temporary recording medium. Alternatively, part or all of the functional blocks may be configured by hardware such as an ASIC provided in the time-series data display device 100.

[0020] The storage unit 120 includes a time-series data storage means 121, an event data storage means 122, an extraction data storage means 123, a combined data storage means 124, a display mark storage means 125, and an image information storage means 126. These means included in the storage unit 120 are appropriately allocated to the storage areas of storage devices such as hard disk drives, RAMs, and ROMs and configured. The storage unit 120 is a data storage unit that stores various necessary data in order to create an image for easily displaying time-series data.

[0021] The display unit 130 and the input unit 140 are user interfaces provided in the time-series data display device 100. For the display unit 130, display devices such as liquid crystal displays and organic EL displays are used, and for the input unit 140, input devices such as keyboards, jog dials, mice, pointing devices, and voice input devices are used.

[0022] The data collection means 111 provided in the control unit 110 acquires time-series data and event data related to the mechanical device from the mechanical device 10 and stores them in the time-series data storage means 121 and the event data storage means 122, respectively. The data collection means 111 can also be called a data acquisition unit.

[0023] The data collection means 111 collects time-series data of physical quantities related to the state of the mechanical device, such as current, speed, pressure, vibration, sound, and temperature of each part, measured by the sensor 11 of the mechanical device 10 and stores it in the time-series data storage means 121. Alternatively, the data collection means 111 may calculate the maximum value, minimum value, average value, integral value, integral conversion value in the frequency domain, differential value, second differential value, etc. for the measurement values obtained from the sensor 11 for each predetermined period and store them in the time-series data storage means.

[0024] In addition, the data collection means 111 collects event data related to events occurring in the machine device 10 and stores it in the event data storage means 122. The machine device 10 sets the occurrence of a predetermined state as an event, and collects, for example, time information when the event occurs as event data and stores it in the event data storage means 122. For example, when it is determined that an event is that the machine device 10, which normally operates continuously and repeatedly (cycle operation), enters a stopped state, the date and time when the stopped state occurred are stored in the event data storage means 122. Events such as failures and maintenance, which are the causes of the occurrence of the stopped state, are generally irregular or occur at long time intervals. However, the information processing apparatus according to the embodiment is suitable for handling events that occur discretely or irregularly in terms of time in this way.

[0025] The data extraction means 112 extracts partial time-series data related to an event from the time-series data stored in the time-series data storage means 121 based on the event data stored in the event data storage means 122, and stores it in the extraction data storage means 123. The data extraction means 112 can also be called a data extraction unit. The data extraction means 112 may, for example, create an image in which the extracted partial time-series data is arranged on a linear scale using time as an index, and store it in the extraction data storage means 123.

[0026] For example, when the extraction condition (predetermined condition) is the stop of the mechanical device 10, the date and time data of the stop of the mechanical device 10 is read from the event data storage means 122 as event data. Then, based on this event data, for example, the measured values of the sensor 11 collected during the operation cycle immediately before the stop of the mechanical device 10 are extracted and stored in the extraction data storage means 123 as partial time series data. Alternatively, the maximum value, minimum value, average value, integral value, integral conversion value in the frequency domain, differential value, second differential value, etc. for each predetermined period of the measured values before one operation of the stop of the mechanical device 10 are extracted from the time series data storage means 121. And they may be stored in the extraction data storage means 123 as partial time series data. The created image can be displayed on the display unit 130 or printed using a printing device (not shown) according to the needs of the operator (worker).

[0027] In addition, although the processing in the case where there is one type of event data stored in the event data storage means 122 has been described, there may also be a case where event data related to a plurality of types of events is stored in the event data storage means 122. In that case, the operator selects a predetermined event from among the plurality of types of events via the input unit 140, and the data extraction means 112 may extract the partial time series data related to the selected predetermined event and store it in the extraction data storage means 123. Alternatively, a predetermined event selected from among the plurality of types of events may be registered in advance, and the partial time series data related to the registered predetermined event may be automatically extracted and stored in the extraction data storage means 123.

[0028] The data combining means 113 creates a graph arranging the partial time series data related to the event based on the partial time series data stored in the extraction data storage means 123. The data combining means 113 creates, for example, a graph in which the partial time series data related to the event is combined or a graph in which they are arranged in proximity along the horizontal axis indicating the number of data, and stores it in the combined data storage means 124. The created image can be displayed on the display unit 130 or printed using a printing device (not shown) according to the needs of the operator (worker).

[0029] The display mark generation means 114 creates an image with a display mark superimposed on the images stored in the extraction data storage means 123 and the combined data storage means 124 in order to facilitate the recognition of any selected partial time-series data. For example, the display mark may be superimposed in a rectangular area so that the entire selected partial time-series data can be recognized. Also, when it is desired to know the position of the selected partial time-series data, it may be superimposed as a point on the selected partial time-series data. The image with the display mark superimposed is stored in the display mark storage means 125. When storing in the display mark storage means 125, information related to the selected partial time-series data may also be stored together. Examples of display marks include a mouse cursor, a mouse pointer, an area displayed by a drag operation of the mouse, and the like.

[0030] The editing means 115 edits the image created by the data extraction means 112 or the data combining means 113 so as to be convenient (for example, it becomes easier to understand the information) when the operator performs an arbitrary operation, and stores it in the image information storage means 126. The editing means 114 can also be called an image editing unit or an editing unit.

[0031] Next, FIG. 2 schematically shows an example of the hardware configuration of the time-series data display device according to the embodiment. As shown in FIG. 2, the time-series data display device can include PC hardware having a CPU 1601 as a main control means, a ROM 1602 as a storage device, and a RAM 1603. Information such as a processing program for realizing an information processing method described later can be stored in the ROM 1602. Also, the RAM 1603 is used as a work area of the CPU 1601 when executing the information processing method. Further, an external storage device 1606 is connected to the PC hardware. The external storage device 1606 is composed of an HDD, an SSD, an external storage device of another system mounted on a network, and the like.

[0032] The processing program of the CPU 1601 for realizing the information processing apparatus or the information processing method according to the embodiment can be stored in a storage unit such as an external storage device 1606 composed of an HDD, an SSD, etc., or a storage unit such as the ROM 1602 (for example, the EEPROM area). In that case, the processing program of the CPU 1601 for realizing the information processing method (for example, the time series data display method) can be supplied to each of the above storage units via the network interface 1607 and can be updated to a new and different program. Alternatively, the processing program of the CPU 1601 for realizing the information processing method can be supplied to each of the above storage units via storage means such as various magnetic disks, optical disks, flash memories, etc. and a drive device therefor, and the content thereof can be updated. Various storage means, storage units, or storage devices in a state where a program capable of executing the processing of the CPU 1601 for realizing the information processing method is stored are computer-readable recording media according to the information processing method or the information processing apparatus of the present invention.

[0033] The sensor 11 shown in FIG. 1 is connected to the CPU 1601. In FIG. 2, for simplicity of illustration, the sensor 11 is shown as being directly connected to the CPU 1601, but it may be connected via, for example, IEEE 488 (so-called GPIB). Further, the sensor 11 may be configured to be communicably connected to the CPU 1601 via the network interface 1607 and the network 1608.

[0034] The network interface 1607 can be configured using communication standards such as wired communication such as IEEE 802.3, and wireless communication such as IEEE 802.11 and 802.15. The CPU 1601 can communicate with the external device 1104 and the external device 1121 via the network interface 1607. For example, if the object of the time series data display is an industrial robot, the external device 1104 and the external device 1121 may be a control device such as a PLC or a sequencer arranged for controlling and managing the industrial robot, a management server, or the like.

[0035] In the example shown in FIG. 2, as a UI device (user interface device), an operation unit 1604 corresponding to the input unit 140 shown in FIG. 1 and a display device 1605 corresponding to the display unit 130 are connected. The operation unit 1604 can be constituted by a terminal such as a handy terminal, or a device such as a keyboard, jog dial, mouse, pointing device, voice input device (or a control terminal having them). The display device 1605 may be any device that can display information related to the processes executed by the data extraction means 112, data combination means 113, etc. on the display screen. For example, a liquid crystal display device can be used.

[0036] Next, with reference to the flowchart of FIG. 3, an information processing method (time-series data display method) executed by the time-series data display device 100 will be described. FIG. 3 shows an example of the processing procedure executed by the time-series data display device. FIG. 4 is an example diagram of various data collected by the time-series data display device 100. FIG. 4(a) is an example diagram of time-series data, and FIG. 4(b) is an example diagram of event data.

[0037] First, in step S101, the time-series data display device 100 collects time-series data and event data from the mechanical device 10 and the sensor 11. FIG. 4(a) shows an example of the time-series data collected by the time-series data display device 100, which is a series of data obtained by periodically sampling and measuring the drive current of an industrial robot provided in the mechanical device 10. The data collection means 111 of the time-series data display device 100 collects such time-series data from the sensor 11 of the mechanical device 10 and stores it in the time-series data storage means 121.

[0038] Here, the time-series data to be collected will be described in more detail. Illustrated in FIG. 5 is the time-series data for one cycle operation when the industrial robot included in the machine device 10 is operating normally, imaged as a current waveform graph. Also shown in FIG. 6 is an image when a plurality of the current waveform graphs shown in FIG. 5 are arranged. Illustrated in FIG. 6(a) is the time-series data collected when the industrial robot is continuously performing a cycle operation, imaged as a current waveform graph. FIG. 6(a) illustrates the case where a waveform SPW with a specific amplitude is included in the graph. Further, illustrated in FIG. 6(b) is a graph showing the time-series data collected over a long period with the time-axis direction compressed more than in FIG. 6(a). In FIG. 6(b), although it can be seen that two waveforms SPW with specific amplitudes are included, since the waveforms of each cycle operation are collapsed in the time-axis direction, it can be understood that it is difficult to perform a detailed confirmation or comparison between the specific waveforms in the image of FIG. 6(b).

[0039] Next, FIG. 4(b) shows an example of the event data collected by the time-series data display device 100. This is data that records the time when an event occurred when the industrial robot included in the machine device 10 stopping is set as an event. In this example, stops due to maintenance work performed regularly or irregularly and stops due to failures occurring irregularly are treated as events. The data collection means 111 receives control information from, for example, a control unit that manages the operation of the machine device 10 and collects event data in parallel with the collection of time-series data, and stores it in the event data storage means 122.

[0040] Returning to FIG. 3, in step S102, the data extraction means 112 extracts partial time-series data related to a predetermined event from the time-series data stored in the time-series data storage means. Here, the predetermined event refers to an event arbitrarily selected by an operator from the event data stored in the event data storage means 122, but it may be configured to be automatically selected by the control unit 110.

[0041] For example, based on the event data shown in FIG. 4(b), partial time series data related to a predetermined event is extracted from the time series data shown in FIG. 4(a). Specifically, the partial time series data related to the operation one cycle before the point in time when the selected predetermined event occurred (the point in time when the industrial robot stopped) is extracted as the partial time series data. Note that this is just an example. For example, time series data separated by a predetermined number of operation cycles from the occurrence of the predetermined event may be extracted, or time series data for a plurality of consecutive operation cycles may be grouped and extracted as the partial time series data. Alternatively, it is also possible to extract the time series data of the operation cycle itself in which the predetermined event occurred as the partial time series data. The extracted partial time series data is stored in the extraction data storage means 123 together with the time information related to the partial time series data.

[0042] Here, first assume a case where the extracted partial time series data is arranged and displayed on a linear scale (i.e., the absolute time axis) with time as the index. FIG. 7 schematically shows the display screen W. In the graph, most of the time series data during continuous operation is not drawn because it was not extracted, and only the waveform of the partial time series data related to the event is drawn. Therefore, it can be said that the redundancy is significantly reduced compared to the graph in FIG. 6(b). However, when time series data has been collected over a long period of time, on the display screen W, the waveform of the partial time series data is compressed and flattened in the time axis direction, making it difficult to check the details of each waveform. Also, when trying to expand the time axis direction to facilitate the observation of the waveform shape, since the partial time series data are spaced non-uniformly apart, when trying to compare and observe a plurality of waveforms, they may go out of the screen.

[0043] Therefore, in the present embodiment, in step S103, the data combining means 113 as a processing unit performs a process of combining the partial time-series data stored in the extraction data storage means 123 and stores it in the combined data storage means 124. That is, an image (combined data) is created in which information (e.g., a graph) related to each of the plurality of extracted partial time-series data is arranged so that the distance between each other is smaller than when arranged on a linear scale with time as an index. The data combining means 113 arranges information (e.g., a graph) related to the partial time-series data so that information (e.g., a graph) related to adjacent partial time-series data is connected to each other or arranged at a predetermined distance (short distance). For example, image processing is performed so that the distance in the horizontal axis direction separating the waveforms of each partial time-series data in FIG. 7 becomes zero or a small predetermined distance, thereby reducing the interval between the waveforms.

[0044] Then, in step S104, using the extraction data stored in the extraction data storage means 123, a graph is displayed as an image on the display unit 130. At this time, as assumed above, the extracted partial time-series data is arranged and displayed on a linear scale with time as an index (i.e., the absolute time axis).

[0045] Next, in step S105, using the combined data stored in the combined data storage means 124, a graph is displayed as an image on the display unit 130. At this time, the horizontal axis direction can be enlarged as necessary so that it is easy to observe and compare waveforms. Also, it is preferable that the index (scale) of the horizontal axis of the graph is not the absolute time but the number of samples of the original measurement data, the number of operation cycles, the number of one waveform, etc. This is because, since the partial time-series data that were separated at non-uniform intervals are arranged side by side, if the index (scale) of the horizontal axis is the absolute time, the values of the index will jump discontinuously at the boundaries between the partial time-series data, making it difficult for the operator to intuitively understand.

[0046] Also, in step S105, instead of displaying the created image using the display unit 130, the image may be transmitted to a display device separate from the time-series data display device 100 for display, or transmitted to a printing device for printing. That is, the created image may be output according to the convenience of the operator.

[0047] FIG. 8 illustrates an image displayed on the display screen W of the display unit 130 in step S105. The waveforms of the partial time-series data related to the event are connected and displayed so as to be adjacent in the horizontal axis direction. That is, the fact that the industrial robot has stopped is treated as event data, and a graph is displayed in which partial time-series data is extracted and combined for each event from the time-series data monitoring the current value of the industrial robot. In this way, since only the partial time-series data at the time of the event occurrence is combined and displayed, the operator can very easily check and compare the graphs related to the event occurrence.

[0048] FIG. 9 illustrates images displayed on the display screen W of the display unit 130 in steps S104 and S105. The upper image is an image in which the extracted partial time-series data created in step S104 is arranged on a linear scale with time as an index. The lower image is an image in which the combined partial time-series data created in step S105 is arranged with the horizontal axis as an index of the sampling number of the partial time-series data. Also, in the upper right of the screen W, information on the content of the event data as the extraction condition (predetermined condition) and what physical quantity the time-series data is displayed in (current value in FIG. 9) is displayed.

[0049] Next, in step S106, the partial time-series data stored in the extraction data storage means 123 and the combined data storage means 124 is displayed on the display screen W of the display unit 130 as shown in FIG. 9. At this time, any partial time-series data in the displayed image can be selected.

[0050] Then, in step S107, the display mark generation means 114 as the processing unit generates a display mark. When arbitrary partial time-series data is selected for an image displayed on the display screen W of the display unit 130, a display mark is generated to facilitate the recognition of the selected arbitrary partial time-series data. Then, the display mark is superimposed on the image displayed on the display screen W of the display unit 130, and information related to the partial time-series data selected by the operator (worker) by the display mark is stored in the display mark storage means 125. The shape of the display mark when the display mark generation means 114 superimposes the display mark on the image may be various shapes as long as the work (operation) of the operator (worker) is easy or the shape is easy for the worker to recognize. For example, a line shape, an arrow shape, a round shape, a rectangular shape, a star shape, a finger shape, a region display shape at the time of range selection, and the like.

[0051] FIG. 10 illustrates an image in which the display mark 200 generated by the display mark generation means 114 is superimposed on an image displayed on the display screen W of the display unit 130 when arbitrary partial time-series data is selected for the image. In FIG. 10, in order for the operator to easily recognize one cycle waveform of the selected partial time-series data, the shape of the display mark 200 superimposed on the image is formed into a rectangle. At that time, the start point and the end point of one cycle of the selected partial time-series data are arranged so as to fit within the rectangle-shaped display mark 200. Further, the display mark 200 is displayed in a transparent state so that the selected one-cycle waveform can be confirmed.

[0052] Next, in step S108, the editing means 115 as the processing unit refers to the data related to the selected arbitrary partial time-series data stored in the display mark storage means 125. Then, in conjunction with the display mark 200 generated by the display mark generation means 114, a display mark 201 for highlighting the corresponding partial time-series data in the other image (upper graph) so that the operator can easily recognize it is displayed. Also, the image is edited to display the information related to the selected partial time-series data and stored in the image information storage means 126.

[0053] Illustrated in FIG. 11 is the image after the editing process by the editing means 115 in step S108. The upper part is the graph created in step S104 (a graph in which partial time-series data is arranged on a linear scale with time as an index), and the lower part is the graph created in step S105 (a graph in which the horizontal axis is arranged with the sampling number of partial time-series data as an index). In step S106, when any partial time-series data is selected from the lower graph, in step S107, the display mark 200 is superimposed on the lower graph so that the operator can easily recognize one cycle of the selected partial time-series data for the selected partial time-series data.

[0054] Then, in step S108, in conjunction with the display mark 200 of the selected partial time-series data, an inverted triangle display mark 201 is displayed above the corresponding data in the upper graph so that the corresponding data to the selected partial time-series data can be easily recognized.

[0055] In addition, the time of the selected partial time series data and the information related to the event data when the partial time series data was extracted in step S102 are displayed. The information content icon 301 indicates that the event in the selected partial time series data is "fault stop" and it occurred or was acquired on "2017 / 5 / 14 / (May 14, 2017)". Also, in the lower graph where the display mark 200 is superimposed in step S107, the information content icon 300 shows the information of the maximum peak value of the waveform within the area of the display mark 200, "Peak maximum value: 50", and it is displayed superimposed on the lower graph. In this embodiment, the maximum peak value of the current value is displayed in the information content icon 300, but the minimum peak value may also be used. Also, the current value at the starting point or the current value at the ending point may be used. The display content of the information content icon 300 may be provided with a graphical user interface so that it can be appropriately set by the operator. For example, by clicking or double-clicking on the content of the information content icon 300, a pull-down menu 400 is displayed. The pull-down menu 400 displays the content to be displayed such as the minimum peak value, and the operator appropriately sets the content to be displayed.

[0056] As described above, according to this embodiment, when the operator checks and compares the year, month, frequency of occurrence of a predetermined event, and the detailed behavior of the extracted partial time series data, etc., it can be executed without selecting a specific period again, so the work becomes easier. Also, since the detailed information within the partial time series data is shown conspicuously, it becomes even easier to check and compare the data details.

[0057] (Second Embodiment) In the above-described embodiment, one partial time series data was selected, but a plurality of partial time series data may be selected. This will be described in detail below. In the following, the parts of the hardware and control system configurations that are different from the above-described embodiment will be illustrated and described. Also, for the parts that are the same as the above-described embodiment, the same configurations and operations as above are assumed to be possible, and the detailed description thereof will be omitted.

[0058] Figure 12 shows the display screen W in the present embodiment. The display control of the display screen W is to be executed by the display mark generation means 114 and the editing means 115. In step S106 of FIG. 3, a plurality of partial time-series data are selected and displayed on the display screen W of the display unit 130. In the lower graph, the partial time-series data of the 6th cycle and the partial time-series data of the 22nd cycle are selected. A display mark 200 is superimposed on the partial time-series data of the 6th cycle, and a display mark 202 is superimposed on the partial time-series data of the 22nd cycle. Similar to the above-described embodiment, the display mark 200 is arranged so that the start point and the end point of the partial time-series data of the 6th cycle are accommodated, and the display mark 202 is arranged so that the start point and the end point of the partial time-series data of the 22nd cycle are accommodated.

[0059] In addition, an inverted triangle display mark 201 for highlighting the partial time-series data in the upper graph corresponding to the partial time-series data of the 6th cycle in the lower graph is displayed. Similarly, an inverted triangle display mark 203 for highlighting the partial time-series data in the upper graph corresponding to the partial time-series data of the 22nd cycle in the lower graph is displayed.

[0060] And, in order to make it easier to recognize the correspondence relationship of these display marks, a linear display mark 204 and a display mark 205 are displayed. The display mark 204 indicates that the display mark 200 and the display mark 201 correspond to each other, and the display mark 205 indicates that the display mark 202 and the display mark 203 correspond to each other.

[0061] The information content icon 301 indicates that the event in the selected partial time-series data is "fault stop" and it was acquired or occurred on "2017 / 5 / 14 (May 14, 2017)". Similarly, the information content icon 303 indicates that the event in the selected partial time-series data is "fault stop" and it was acquired or occurred on "2018 / 3 / 15 (March 15, 2018)". Also, in the information content icon 300, in the waveform of the 6th cycle of the lower graph, information on the maximum peak value of the waveform within the area of the display mark 200, "Peak maximum value: 50", is shown and is displayed superimposed on the lower graph. Similarly, in the information content icon 302, in the waveform of the 22nd cycle of the lower graph, information on the maximum peak value of the waveform within the area of the display mark 202, "Peak maximum value: 46", is shown. Similar to the above-described embodiment, the information of the information content icon 300 and the information content icon 302 may be the peak minimum value, and a graphical user interface may be provided so that it can be appropriately set by the operator.

[0062] Also, an arrow-shaped display mark 206 showing the time-series relationship between the selected waveform of the 6th cycle and the waveform 22 of the 22nd cycle is displayed. On the display mark 206, an information content icon 304 indicating how much time interval there is is displayed. The information content icon 304 indicates that the waveform of the 6th cycle and the waveform of the 22nd cycle are "315 days" apart in time series. In this embodiment, it is represented by the number of days, but it may be indicated by seconds, fractions, hours, weeks, months, years, etc. A graphical user interface may also be provided so that these can be appropriately set by the operator. For example, by clicking or double-clicking on the content of the information content icon 304, a pull-down menu 401 is displayed. Various time-series intervals to be displayed are shown in the pull-down menu 401, and the operator appropriately sets the interval to be displayed.

[0063] In this embodiment, the display marks 206 and the information content icons 304 are displayed between the partial time series data of the upper graph. However, the display marks 206 and the information content icons 304 may be displayed between the partial time series data of the lower graph. Further, in this embodiment, the information content icons 304 are displayed in a superimposed manner on the display marks 206, but they may be displayed at an appropriate position on the display screen W other than the display marks 206.

[0064] As described above, according to this embodiment, it becomes easy to confirm and compare the detailed behaviors of the waveforms of each selected partial time series data. Also, it becomes possible to easily grasp the event occurrence date and time and the periods of each selected partial time series data. Further, when the operator checks and compares the year and month when a predetermined event occurred, the frequency, and the detailed behaviors of the extracted partial time series data, the operation can be executed without selecting a specific period again, thus facilitating the work. Furthermore, when a plurality of partial time series data are selected, it shows how they correspond in the lower graph and the upper graph, and moreover, it becomes easy to confirm and compare the detailed behaviors of the waveforms. Also, it shows how far apart the selected plurality of waveforms are in time series, which can assist in data comparison.

[0065] (Third Embodiment) Next, the case of magnifying, observing, and comparing one waveform of the lower graph will be described in detail. In the following, the parts of the hardware and control system configurations that are different from the above-described embodiments will be illustrated and described. Also, for the parts that are the same as the above-described embodiments, the same configurations and operations are assumed to be possible, and the detailed descriptions thereof will be omitted.

[0066] FIG. 13 shows an example of the display screen W in the present embodiment. It is assumed that the display control of the display screen W is executed by the display mark generation means 114 and the editing means 115. In FIG. 13, in the lower graph, in step S105, when the graph is image-displayed on the display unit 130 using the combined data stored in the combined data storage means 124, it is enlarged and displayed in the horizontal axis direction so that waveforms can be easily observed and compared. Therefore, the entire combined data does not fit on the display screen W of the display unit 130. In the above-described actual embodiment, waveforms up to 24 cycles could be displayed (FIGS. 9 to 12), whereas in the present embodiment, only waveforms up to 12 cycles are displayed (FIG. 13).

[0067] Therefore, in the present embodiment, a scroll bar 402, a knob 403, an arrow 404, and an arrow 405 are displayed so that the lower graph can be scrolled and observed in a predetermined direction. When the knob 403 is moved to the right side of the paper surface or the arrow 405 is clicked, the waveform of the 25th cycle can be displayed. When the knob 403 is moved to the left side of the paper surface or the arrow 404 is clicked, the waveform of the 12th cycle can be displayed. Thereby, waveforms that cannot be displayed in the lower graph can also be displayed by the scroll bar 402, the knob 403, the arrow 404, and the arrow 405, and the work of observing and comparing waveforms can be easily performed.

[0068] Also, in the upper graph, by selecting a waveform different from the currently selected waveform, the lower graph may be automatically scrolled. FIG. 14 shows the display screen W when the lower graph is automatically scrolled from the display state of FIG. 13.

[0069] FIG. 14 shows a display screen W when transitioning from the display state of FIG. 13 when the waveform of the 6th cycle indicated by the display mark 201 is selected in the upper graph. When the waveform of the 6th cycle indicated by the display mark 201 is selected, the knob 403 automatically moves, and the waveform of the 6th cycle is displayed in the lower graph. Accordingly, the display mark 200 is displayed superimposed on the waveform of the 6th cycle in the lower graph. Similar to the above-described embodiment, the information of the information content icon 300 and the information content icon 302 may be the peak minimum value, and a graphical user interface may be provided so that it can be appropriately set by the operator.

[0070] According to the present embodiment as described above, it becomes easy to confirm and compare the detailed behavior of the waveforms of each selected partial time series data. Also, when comparing a plurality of waveforms, etc., since the lower graph automatically moves by using the scroll bar or selecting the upper waveform, it can be executed without selecting a specific period again, and the work becomes easy.

[0071] In the present embodiment, a scroll bar for scrolling the lower graph is displayed, but a scroll bar for scrolling the upper graph may be displayed.

[0072] (Fourth Embodiment) [Example of Connecting the Time Series Data Display Device to a Robot] FIG. 15 shows an example of connecting the time series data display device 100 of each of the above-described embodiments to a 6-axis articulated robot as an example of the mechanical device 10.

[0073] The links 500, 501, 502, 503, 504, 505, 506 provided in the six-axis articulated robot are connected in series by six rotational joints J1, J2, J3, J4, J5, J6. The six-axis articulated robot is provided with sensors for measuring the rotational speed of the motors of each rotational joint, sensors for measuring the rotational angles of the joints, torque sensors, sensors for measuring the current of the motors, pressure sensors for measuring the pressure of the air for driving the actuators, and the like. A robot hand 510, for example, can be attached to and detached from the tip link as an actuator.

[0074] The time-series data display device 100 of the embodiment is communicably connected to the six-axis articulated robot, and the time-series data display device 100 collects time-series data of physical quantities related to the state of the robot and event data related to events occurring in the robot.

[0075] The six-axis articulated robot, for example, repeatedly performs operations such as assembling parts to manufacture an article. The operator can give a command via the input unit 140 to the time-series data display device 100 to create an image and perform display and printing of the image.

[0076] For example, when the six-axis articulated robot grips a predetermined workpiece and performs a process of assembling it to another workpiece to manufacture an article, an image combining graphs of partial time-series data related to a predetermined event (for example, a failure) can be created and displayed on the display unit 130. By performing such display, the operator can easily confirm the past history of the robot related to the predetermined event, and thus can make a judgment as to whether it is possible to further continue the manufacturing operation of the article by the robot or not. That is, if the time-series data display device of the present invention is connected to a manufacturing device such as a robot to display partial time-series data, it is possible to manufacture an article while preventing a stop due to a failure in advance.

[0077] FIG. 16 shows another example of the display screen W according to the embodiment. In this example, adjacent partial time-series data (graphs) are connected and arranged so as to be separated by a predetermined short distance so that an operator can easily visually recognize the boundary of the partial time-series data (the lower graph in the above-described embodiment). Further, a display mark indicating information related to the event content is added as a label to each graph. In this example, as labels representing sub-classifications related to the device stop which is an event, a display mark indicating a stop in a normal state (for example, inspection) and a display mark indicating a stop due to an abnormal state (for example, failure) are set, and are label-displayed in the image in correspondence with each graph. Further, above each label, a check box (icon) for selecting a waveform to be adopted as learning data for creating a failure prediction model from the waveforms is displayed. The labels and the check boxes may be displayed by an operator instructing via the input unit 140, or the control program may be configured to automatically display them.

[0078] Thereby, the operator can create teacher data (learning data) used to construct a learned model for predicting a failure of the robot using the time-series data display device 100. The operator selects a predetermined event from the event data acquired by the time-series data display device 100, causes the time-series data display device 100 to extract partial time-series data from the time-series data of various physical quantities, and can display an image that enables easy comparison of graphs and the like. By using the check box illustrated in FIG. 16, the operator can easily flag data determined to be suitable as teaching materials for machine learning, and can easily construct teacher data (learning data).

[0079] In the example described above, partial time-series data of a single type of physical quantity, such as "current value", was extracted and graphs were arranged and displayed along the horizontal axis. However, the graphs displayed on one screen are not limited to those related to partial time-series data of a single type of physical quantity. If graphs of partial time-series data related to multiple types of physical quantities can be displayed on the same screen, for example, it is convenient for an operator (operator) to easily judge the correlation between different physical quantities in the event, and it is also convenient when extracting learning data for creating a failure prediction model. Also, the display screen W in FIG. 16 may be implemented in the various embodiments described above.

[0080] (Other Embodiments) Note that the present invention is not limited to the embodiments described above, and many modifications are possible within the technical idea of the present invention.

[0081] For example, the implementation of the present invention is not limited to the graph display of physical quantities related to a single type of event. For example, in step S102 of the flowchart in FIG. 3, a plurality of types of predetermined events are set as extraction conditions (predetermined conditions). Then, for each of the plurality of types of predetermined events in step S103, partial time-series data of physical quantities is extracted and a combined graph is created along the horizontal axis, and can be arranged and displayed within one screen in step S104. This is convenient when an operator verifies whether there is a correlation between multiple types of events regarding the physical quantity.

[0082] In the various embodiments described above, in the upper graph on the display screen W, partial time-series data was extracted according to a predetermined condition, and most of the time-series data during continuous operation was not drawn and displayed. However, if it is time-series data during continuous operation in a state where redundancy has been reduced to a certain extent, the original time-series data (raw waveform, raw data) may be displayed as it is. Even in that case, with the associated display marks, operations such as confirming the behavior of the details of the partial time-series data and comparison can be easily performed.

[0083] The present invention can also be realized by a process in which a program that implements one or more functions of an embodiment is supplied to a system or apparatus via a network or a storage medium, and one or more processors in a computer of the system or apparatus read and execute the program. It can also be realized by a circuit (for example, ASIC) that implements one or more functions. A control program capable of executing the information processing method or display method of the embodiment, and a non-transitory recording medium readable by a computer storing the control program are also included in the embodiments of the present invention.

[0084] In addition, in the above-described embodiment, a six-axis articulated robot has been described as an example of the mechanical device 10, but it is not limited thereto. For example, a machine that can automatically perform operations such as expansion / contraction, flexion / extension, vertical movement, horizontal movement, or turning, or a combination of these operations based on information in a storage device provided in a control device can be applied as the mechanical device 10.

Explanation of Reference Numerals

[0085] 10 Mechanical device 11 Sensor 100 Time-series data display device 110 Control unit 111 Data collection means 112 Data extraction means 113 Data combination means 114 Cursor generation means 115 Editing means 120 Storage unit 121 Time-series data storage means 122 Event data storage means 123 Extracted data storage means 124 Combined data storage means 125 Cursor storage means 126 Image information storage means 130 Display unit 140 Input unit 200, 201, 202, 203, 204, 205, 206 Display marks 300, 301, 302, 303, 304 Information content icons 400, 401 Pull-down menu 402 Scroll bar 403 Knob 404, 405 Arrow 500, 501, 502, 503, 504, 505, 506 Link 510 Robot hand J1, J2, J3, J4, J5, J6 Joint W Display screen

Claims

1. The processing unit displays a first image showing at least two partial time series data related to a physical quantity related to the state of the mechanical device, a second image showing the partial time series data at an interval different from the interval in the time axis direction of the partial time series data in the first image, a first mark indicating first partial time series data in the partial time series data displayed in the first image, and a second mark indicating second partial time series data corresponding to the first partial time series data in the partial time series data displayed in the second image, and in the second image, the interval of the partial time series data is displayed smaller than that in the first image characterized information processing method.

2. In the information processing method according to claim 1, the processing unit when the first partial time series data or the second partial time series data is selected by the user, the first mark and the second mark are displayed. characterized information processing method.

3. In the information processing method according to claim 1 or 2, the processing unit displays a third mark indicating the correspondence relationship between the first mark and the second mark. characterized information processing apparatus.

4. The processing unit displays a first image showing at least two partial time series data related to a physical quantity related to the state of the mechanical device, a second image showing the partial time series data at an interval different from the interval in the time axis direction of the partial time series data in the first image, a first mark indicating first partial time series data in the partial time series data displayed in the first image, and a second mark indicating second partial time series data corresponding to the first partial time series data in the partial time series data displayed in the second image, and when first partial time series data that is displayed in the first image but for which corresponding second partial time series data is not displayed in the second image is selected by the user, the second image is updated so that the second partial time series data is displayed. characterized information processing method.

5. In the information processing method according to claim 4, the processing unit displays the second partial time series data by scrolling the second image in a predetermined direction. characterized information processing method.

6. The processing unit displays a first image showing at least two partial time series data related to a physical quantity related to the state of the mechanical device, A second image in which the partial time-series data is displayed at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, A first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image are displayed, When at least two of the first partial time-series data or at least two of the second partial time-series data are selected by a user, a fourth mark indicating a temporal relationship is displayed between the at least two first partial time-series data or between the at least two second partial time-series data. An information processing method characterized by the above.

7. In the information processing method according to claim 6, The processing unit Displays a first icon indicating an amount of time between the at least two first partial time-series data or between the at least two second partial time-series data. An information processing method characterized by the above.

8. In the information processing method according to claim 7, The processing unit When the first icon is selected, displays a first menu for setting a unit of the amount of time in the first icon. An information processing method characterized by the above.

9. The processing unit A first image displaying at least two partial time-series data related to a physical quantity related to the state of a mechanical device, A second image in which the partial time-series data is displayed at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, A first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image are displayed, The second mark is displayed so as to enclose from a first point to a second point of the second partial time-series data selected by the user. An information processing method characterized by the above.

10. In the information processing method according to claim 9, The first point is a start point in the second partial time-series data, and the second point is an end point in the second partial time-series data. An information processing method characterized by the above.

11. The processing unit A first image displaying at least two partial time-series data related to a physical quantity related to the state of a mechanical device, A second image that displays the partial time-series data at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, a first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image are displayed, a second icon indicating the physical quantity of the second partial time-series data indicated by the second mark is displayed, An information processing method characterized by the above.

12. In the information processing method according to claim 11, when the processing unit, when the second icon is selected, a second menu for setting the type of the physical quantity in the second icon is displayed, An information processing method characterized by the above.

13. The processing unit, a first image displaying at least two partial time-series data related to a physical quantity related to the state of the mechanical device, a second image that displays the partial time-series data at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, a first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image are displayed, when the processing unit, the partial time-series data is data extracted from time-series data according to a predetermined condition, the content of the predetermined condition and / or the date and time related to the selected first partial time-series data or second partial time-series data are displayed, An information processing method characterized by the above.

14. In the information processing method according to claim 13, when the processing unit, in the first image, the content of the predetermined condition and / or the date and time are displayed, An information processing method characterized by the above.

15. In the information processing method according to any one of claims 1 to 14, when the processing unit, a scroll bar for scrolling the first image or the second image is displayed, An information processing method characterized by the above.

16. In the information processing method according to any one of claims 1 to 15, when the processing unit, the second mark is displayed in a rectangle, An information processing method characterized by the above.

17. In the information processing method according to any one of claims 1 to 16, when the processing unit, displaying while transmitting the second mark An information processing method characterized by the above.

18. In the information processing method according to any one of Claims 1 to 17, the processing unit displays the first mark in an inverted triangle. An information processing method characterized by the above.

19. In the information processing method according to any one of Claims 1 to 18, the processing unit displays the first partial time series data on a linear scale with time as an index in the first image. An information processing method characterized by the above.

20. The processing unit displays a first image showing at least two partial time series data related to a physical quantity related to the state of the mechanical device, a second image showing the partial time series data at an interval different from the interval in the time axis direction of the partial time series data in the first image, a first mark indicating first partial time series data in the partial time series data displayed in the first image, and a second mark indicating second partial time series data corresponding to the first partial time series data in the partial time series data displayed in the second image, and the processing unit displays, in the second image, a plurality of the second partial time series data extracted from the first partial time series data connected together. An information processing method characterized by the above.

21. In the information processing method according to any one of Claims 1 to 20, the processing unit displays a third icon for the user to set whether it is normal or abnormal in the second partial time series data. An information processing method characterized by the above.

22. In the information processing method according to Claim 21, the third icon is a check box. An information processing method characterized by the above.

23. In the information processing method according to any one of Claims 1 to 22, the partial time series data is sensor data from a sensor provided in the mechanical device. An information processing method characterized by the above.

24. In the information processing method according to any one of Claims 1 to 23, the partial time series data displayed in the second image is displayed in an enlarged manner compared to the partial time series data displayed in the first image. An information processing method characterized by the above.

25. A program for causing a computer to execute the information processing method according to any one of Claims 1 to 24.

26. A computer-readable recording medium having recorded thereon the program according to claim 25. **Claim 27** A first image displaying at least two partial time-series data regarding a physical quantity related to the state of a mechanical device, a second image displaying the partial time-series data at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, a first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image, are displayed, In the second image, the interval of the partial time-series data is displayed to be smaller than that in the first image An information processing apparatus characterized by the above. **Claim 28** A first image displaying at least two partial time-series data regarding a physical quantity related to the state of a mechanical device, a second image displaying the partial time-series data at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, a first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image, are displayed, When first partial time-series data that is displayed in the first image but for which corresponding second partial time-series data is not displayed in the second image is selected by a user, the second image is updated so that the second partial time-series data is displayed. An information processing apparatus characterized by the above. **Claim 29** A first image displaying at least two partial time-series data regarding a physical quantity related to the state of a mechanical device, a second image displaying the partial time-series data at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, a first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image, are displayed, When at least two of the first partial time series data or at least two of the second partial time series data are selected by a user, a fourth mark indicating a temporal relationship is displayed between the at least two first partial time series data or between the at least two second partial time series data. An information processing apparatus characterized by the above.

30. A first image displaying at least two partial time series data regarding a physical quantity related to the state of a mechanical device, A second image displaying the partial time series data at an interval different from the interval in the time axis direction of the partial time series data in the first image, A first mark indicating first partial time series data in the partial time series data displayed in the first image, and a second mark indicating second partial time series data corresponding to the first partial time series data in the partial time series data displayed in the second image are displayed. The second mark is displayed so that a range from a first point to a second point of the second partial time series data selected by the user is surrounded. An information processing apparatus characterized by the above.

31. A first image displaying at least two partial time series data regarding a physical quantity related to the state of a mechanical device, A second image displaying the partial time series data at an interval different from the interval in the time axis direction of the partial time series data in the first image, A first mark indicating first partial time series data in the partial time series data displayed in the first image, and a second mark indicating second partial time series data corresponding to the first partial time series data in the partial time series data displayed in the second image are displayed. A second icon indicating the physical quantity of the second partial time series data indicated by the second mark is displayed. An information processing apparatus characterized by the above.

32. A first image displaying at least two partial time series data regarding a physical quantity related to the state of a mechanical device, A second image displaying the partial time series data at an interval different from the interval in the time axis direction of the partial time series data in the first image, A first mark indicating first partial time series data in the partial time series data displayed in the first image, and a second mark indicating second partial time series data corresponding to the first partial time series data in the partial time series data displayed in the second image are displayed. The partial time-series data is data extracted from time-series data under a predetermined condition, and displays the content of the predetermined condition and / or the date and time related to the selected first partial time-series data or the second partial time-series data. An information processing apparatus characterized by the above.

33. A first image displaying at least two pieces of partial time-series data related to a physical quantity related to the state of a mechanical device, a second image displaying the partial time-series data at an interval different from the interval in the time-axis direction of the partial time-series data in the first image, a first mark indicating first partial time-series data in the partial time-series data displayed in the first image, and a second mark indicating second partial time-series data corresponding to the first partial time-series data in the partial time-series data displayed in the second image are displayed, In the second image, a plurality of the second partial time-series data extracted from the first partial time-series data are concatenated and displayed. An information processing apparatus characterized by the above.

34. Based on the first image and the second image displayed by the information processing apparatus according to any one of Claims 27 to 33, the user causes the mechanical device to execute an operation, and the mechanical device manufactures an article. A method for manufacturing an article, characterized by the above.

35. Learning data for creating a learned model for predicting a failure of the mechanical device is obtained by the information processing apparatus according to any one of Claims 27 to 33. A method for obtaining learning data, characterized by the above.

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