JP7830050B2 - Information processing device, system, production equipment, information processing method, method for manufacturing articles, program, and recording medium - Google Patents

Description

This invention relates to information processing.

In recent years, predictive maintenance has been implemented, where sensors are used to measure the condition of machinery and equipment incorporated into production facilities. Based on the deterioration of these machines, parts are replaced, repaired, or updated. Predictive maintenance reduces unnecessary parts replacement and labor costs. Furthermore, by installing sensors on the machinery and collecting measurement data, malfunctions and abnormalities can be detected early, allowing for detailed diagnosis of the machinery.

Patent Document 1 proposes a device that can connect multiple sensors and acquire sensing data, i.e., measurement data, at sensing intervals assigned to each of the multiple sensors. This Patent Document 1 describes how, when the sensing timings are the same, packet collisions can be prevented by shifting the sensing timing of sensors with longer sensing intervals relative to the sensing timing of sensors with shorter sensing intervals.

Japanese Patent Publication No. 2010-220036

Incidentally, in the diagnosis of mechanical equipment, there are cases where measurement is urgent. However, the technology described in Patent Document 1 focuses primarily on preventing packet collisions, and does not focus on whether measurement is urgent or not. Therefore, for example, when considering the diagnosis of mechanical equipment, the timing of measurement may not necessarily be appropriate.

Therefore, the present invention aims to measure the state of a mechanical device at the appropriate timing.

A first aspect of the present disclosure is an information processing device to which a sensor for measuring the state of a machine is connected, comprising a processing unit capable of measuring the state of the machine using the sensor by executing a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, wherein when two or more event conditions among the plurality of event conditions are fulfilled, the processing unit can execute a priority process in which two or more measurement tasks corresponding to the two or more event conditions are executed in order of decreasing priority , and in the priority process, if the two or more measurement tasks include at least two measurement tasks with the same priority, the processing unit executes the at least two measurement tasks in order of decreasing execution time .
A second aspect of the present disclosure is an information processing device to which a sensor for measuring the state of a machine is connected, comprising a processing unit capable of measuring the state of the machine using the sensor by executing a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, wherein the processing unit is capable of executing priority processing to execute two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority when two or more of the plurality of event conditions are fulfilled, and further comprises an AD conversion unit capable of executing AD conversion processing to convert an analog signal from the sensor into a digital signal, wherein the processing unit generates measurement data by applying signal processing to the digital signal, and the processing unit determines the priority of the two or more measurement tasks by referring to a priority table in which priority is assigned to each processing content of the signal processing.
A third aspect of the present disclosure is an information processing device to which a sensor for measuring the state of a machine is connected, comprising a processing unit capable of measuring the state of the machine using the sensor by executing a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, wherein when two or more event conditions among the plurality of event conditions are fulfilled, the processing unit can execute a priority process that executes two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority, displays a third screen on which the priority of the measurement tasks can be set based on the measurement data measured by the measurement tasks, and the third screen can set a first threshold value for the measurement data for automatically changing the priority of the measurement tasks.
A fourth aspect of the present disclosure is an information processing device to which a sensor for measuring the state of a machine is connected, comprising a processing unit capable of measuring the state of the machine using the sensor by executing a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, wherein when two or more event conditions among the plurality of event conditions are fulfilled, the processing unit can execute priority processing to execute two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority, displays a third screen on which the priority of the measurement tasks can be set based on the measurement data measured by the measurement tasks, and on the third screen, a second threshold value for the measurement data can be set for issuing an alarm.
A fifth aspect of the present disclosure is an information processing device to which a sensor for measuring the state of a machine is connected, comprising a processing unit capable of measuring the state of the machine using the sensor by executing a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, wherein when two or more of the plurality of event conditions are fulfilled, the processing unit can execute a priority process that executes two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority, displays a third screen on which the priority of the measurement tasks can be set based on the measurement data measured by the measurement tasks, and the third screen can set a third threshold for the amount of change in the measurement data for automatically changing the priority of the measurement tasks.
A sixth aspect of the present disclosure is an information processing device to which a sensor for measuring the state of a machine is connected, comprising a processing unit capable of measuring the state of the machine using the sensor by executing a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, wherein when two or more event conditions among the plurality of event conditions are fulfilled, the processing unit can execute a priority process that executes two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority, and displays a third screen on which the priority of the measurement tasks can be set based on the measurement data measured by the measurement tasks, wherein the measurement data is displayed as a graph on the third screen.

A seventh aspect of this disclosure is a system comprising: a gateway device; a sensor for measuring the state of a mechanical device; and a node device connected to the sensor and capable of transmitting measurement data to the gateway device by wireless or wired communication, wherein the node device includes a processing unit capable of measuring the state of the mechanical device using the sensor by executing a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, the processing unit is capable of executing a priority process when two or more event conditions among the plurality of event conditions are fulfilled, executing two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority , and in the priority process, if the two or more measurement tasks include at least two measurement tasks with the same priority, the system is characterized in that the at least two measurement tasks are executed in order of shortest execution time .

An eighth aspect of the present disclosure is an information processing method in which a processing unit executes a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, thereby measuring the state of a mechanical device using a sensor, wherein when two or more event conditions among the plurality of event conditions are fulfilled, the processing unit executes a priority process in which it executes two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority , and in the priority process, if the two or more measurement tasks include at least two measurement tasks with the same priority, the processing unit executes the at least two measurement tasks in order of decreasing execution time .

According to this invention, the state of a machine or device can be measured at the appropriate timing.

A schematic diagram of the production equipment according to the first embodiment. A block diagram of the monitoring node device according to the first embodiment. An explanatory diagram showing an example of a task table in the first embodiment. A flowchart of the information processing method according to the first embodiment. A flowchart illustrating the process for calculating the execution time in the first embodiment. (a) is an explanatory diagram showing an example of the first table in the first embodiment, and (b) is an explanatory diagram showing an example of the second table in the first embodiment. An explanatory diagram showing the priority table used in the information processing method according to the second embodiment. A flowchart showing a method for determining the signal processing time according to the third embodiment. A flowchart showing a method for determining the output time according to the fourth embodiment. An explanatory diagram showing the settings screen for setting the priority according to the fifth embodiment. An explanatory diagram showing the settings screen for setting the priority according to the fifth embodiment. An explanatory diagram showing the settings screen for setting the priority according to the sixth embodiment. An explanatory diagram showing the settings screen for setting the priority according to the sixth embodiment. A flowchart of the information processing method according to the seventh embodiment. An explanatory diagram showing the settings screen for setting the priority according to the seventh embodiment. A flowchart of the information processing method according to the eighth embodiment. An explanatory diagram showing the settings screen for setting the priority according to the eighth embodiment.

The embodiments for carrying out the present invention will be described in detail below with reference to the drawings.

[First Embodiment]
Figure 1 is a schematic diagram of a production facility 1000 according to the first embodiment. The production facility 1000 is equipment used to manufacture goods W and is located in a factory or the like. The production facility 1000 comprises a machine device 101 that is to be monitored, and a monitoring system 100, which is an example of a system, that monitors the machine device. The machine device 101 is, for example, a pump. The production facility 1000, including the machine device 101, manufactures goods W by a predetermined manufacturing method while monitoring the status of the machine device 101 by measuring it with the monitoring system 100. Goods W may be finished products or intermediate products in the process of being manufactured.

The monitoring system 100 is used for predictive maintenance of the mechanical device 101. By monitoring the mechanical device 101 with the monitoring system 100, malfunctions and abnormalities in the mechanical device 101 can be detected early, and the mechanical device 101 can be diagnosed in detail.

The monitoring system 100 includes at least one sensor used for monitoring the mechanical device 101. In this embodiment, the at least one sensor is a plurality, for example, two sensors 102 and 103. The monitoring system 100 also includes a monitoring node device 104, which is an example of a monitoring device and a node device; a monitoring gateway device 106, which is an example of a gateway device; a database 108; and a terminal 109.

Each of the sensors 102 and 103 is a sensor for measuring the state of the mechanical device 101 and is installed on the mechanical device 101. Each of the sensors 102 and 103 is a sensor capable of outputting sensor data that quantifies the state of the mechanical device 101 as a physical quantity, such as a vibration sensor, acceleration sensor, pressure sensor, light sensor, torque sensor, and temperature sensor. For example, the vibration sensor outputs the intensity of vibration as a physical quantity, namely voltage.

The monitoring node device 104 has a terminal section 105 to which sensors can be connected. The terminal section 105 includes multiple channel terminals to which multiple sensors can be connected. In this embodiment, among the multiple channel terminals of the terminal section 105, sensor 102 is connected to channel terminal 1ch, and sensor 103 is connected to another channel terminal 2ch. Sensor 102 and channel terminal 1ch are connected by a cable 121, which includes, for example, power lines, ground lines, and signal lines. Sensor 103 and channel terminal 2ch are connected by a cable 122, which includes, for example, power lines, ground lines, and signal lines.

One or more monitoring node devices 104 are installed in the monitoring system 100 as needed. This embodiment describes a case where the monitoring system 100 has one monitoring node device 104, but it may have multiple monitoring node devices. For example, the monitoring system 100 may have as many monitoring node devices as there are items to be monitored. Each monitoring node device 104 is assigned a unique node number.

The monitoring node device 104 has a communication unit 110, and the monitoring gateway device 106 has a communication unit 111. These communication units 110 and 111 enable the monitoring node device 104 and the monitoring gateway device 106 to communicate with each other. The monitoring node device 104 can transmit measurement data to the monitoring gateway device 106 via wireless or wired communication. The monitoring gateway device 106 can collect information from the monitoring node device 104.

The communication method of communication units 110 and 111 may be wireless communication such as LPWA (Low Power Wide Area) or wireless LAN, or wired communication such as Ethernet® or field network. Furthermore, communication units 110 and 111 may have both wireless and wired communication functions and be configured to selectively execute one of the two communication methods. In the first embodiment, communication units 110 and 111 have both wireless and wired communication functions and are configured to selectively execute one of the two communication methods.

The monitoring gateway device 106 is set to be within communication range of the monitoring node device 104. Measurement data generated by the monitoring node device 104 is collected by the monitoring gateway device 106 via communication units 110 and 111.

The monitoring gateway device 106, the database 108, and the terminal 109 are connected to the network 107. The network 107 may be a dedicated network within the factory or a wide-area network such as the internet. Measurement data collected by the monitoring gateway device 106 is stored in the database 108, which is an example of a data storage device, via the network 107. The terminal 109 is a computer equipped with a display. The terminal 109 may also be equipped with a speaker if necessary.

Furthermore, the monitoring gateway device 106 may be implemented in the database 108 or terminal 109 as a software process for the database 108 or terminal 109. The database 108 may also be a storage device or storage medium. The terminal 109 may be configured to allow the user to check the results stored in the database 108 through user operation. The terminal 109 may also be configured to notify the user, as necessary, via notification means such as alerts or email, if an abnormality occurs in the machine device 101.

Figure 2 is a block diagram of the monitoring node device 104 according to the first embodiment. In the first embodiment, the monitoring node device 104 is an information processing device, i.e., a computer. The monitoring node device 104 includes a terminal unit 105, a trigger generation unit 202, a power supply unit 204, a signal input unit 205 (an example of an AD conversion unit), a signal processing unit 206 (an example of a processing unit), an output unit 207, and a storage unit 210. These are connected by a bus 220. The storage unit 210 is a storage device such as an HDD or SSD.

The power supply unit 204 is connected to a battery 203. The battery 203 may be integrated into the monitoring node device 104 or it may be detachable from the monitoring node device 104. Alternatively, the battery 203 may be located outside the monitoring node device 104. The power supply unit 204 supplies power to each sensor 102 and 103 at a timing determined by the program. Each sensor 102 and 103 becomes capable of sensing when power is supplied and outputs an analog signal, which is the sensing signal obtained through sensing.

The signal input unit 205 is configured to receive analog signals from each sensor 102 and 103 and to perform analog-to-digital conversion (AD conversion) to convert the analog signals into digital signals. The signal input unit 205 may also be built into each sensor 102 and 103. As part of the AD conversion process, the analog signal acquired from the specified channel terminal is sampled at a specified sampling frequency and a specified number of samples to generate a digital signal.

The signal processing unit 206 also serves as a control unit that comprehensively controls the trigger generation unit 202, power supply unit 204, signal input unit 205, output unit 207, and storage unit 210. The signal processing unit 206 is, for example, composed of a CPU, and can perform various processes by executing a control program 230, which is an example of a program stored in the storage unit 210. That is, the signal processing unit 206 can measure the state of the mechanical device 101 using each of the sensors 102 and 103 by executing the measurement tasks described later.

The measurement task includes an AD conversion task that causes the signal input unit 205 to perform A/D conversion, a signal processing task that processes the digital signal generated by the signal input unit 205 to generate measurement data, and an output processing task that causes the output unit 207 to output the measurement data.

Signal processing involves multiple processing steps. The following are specific examples of these processing steps, but the system is not limited to them. Furthermore, the signal processing unit 206 may have all of the functions of the processing steps described below, or it may have only the necessary functions.

Signal processing includes, for example, relay processing, FFT processing, partial overall processing, envelope processing, frequency filtering, differentiation processing, integration processing, wavelet processing, averaging processing, standard deviation processing, maximum value processing, and minimum value processing. Furthermore, signal processing also includes, for example, peak-to-peak processing, peak hold processing, RMS processing, crest factor processing, form factor processing, impulse coefficient processing, margin coefficient processing, and machine learning model inference processing. The signal processing unit 206 executes selected processing from among these multiple processing functions. If two or more processing functions are selected, the signal processing unit 206 executes the two or more selected processing functions in a specified order.

The following describes each processing step. Relay processing is the process of passing the input digital signal directly to the output unit 207. FFT processing is the process of decomposing the input digital signal into frequency components. Partial overall processing is the process of calculating the sum of products of the FFT-processed frequency components by limiting the frequency range. Envelope processing is the process of performing envelope processing on the input digital signal. Frequency filtering is the process of removing unwanted signal components by passing the input digital signal through a low-pass filter, high-pass filter, or band-pass filter at a set frequency. Differential processing is the process of differentiating the input digital signal. Integral processing is the process of integrating the input digital signal. Wavelet processing is the process of decomposing the input digital signal into frequency components and time components. Average processing is the process of calculating the average value of the input digital signal. Standard deviation processing is the process of calculating the standard deviation of the input digital signal. Maximum value processing is the process of calculating the maximum value of the input digital signal. Minimum value processing is the process of finding the minimum value of an input digital signal. Peak-to-peak processing is the process of finding the difference between the maximum and minimum values of an input digital signal. Peak hold processing is the process of obtaining the maximum value from the input digital signal within a predetermined period. RMS value processing is the process of finding the RMS value of an input digital signal. Climb factor processing is the process of finding the crest factor by dividing the maximum value of the input digital signal by the RMS value. Waveform factor processing is the process of finding the waveform factor by dividing the RMS value of the input digital signal by the average value. Impulse coefficient processing is the process of finding the impulse coefficient by dividing the maximum value of the input digital signal by the average of the absolute values of the digital signal. Margin coefficient processing is the process of finding the margin coefficient by dividing the maximum value of the input digital signal by the square of the average of the square roots of the digital signal. Machine learning model inference processing is the process of finding the output based on the input digital signal and a machine learning model. A machine learning model is generated by loading training data into a computer, having the computer analyze the data, and defining rules for classification and identification. The generated machine learning model is pre-installed in the monitoring node device 104.

In summary, the signal processing unit 206 performs the selected signal processing on the digital signal to generate measurement data. Note that if the selected signal processing is relay processing, the digital signal acquired by the signal processing unit 206 is output to the output unit 207 as measurement data, and is therefore identical to the measurement data. Although there is no change in content between the digital signal and the measurement data, relay processing is included in the process of generating measurement data.

The output unit 207 is a device capable of outputting measurement data generated by the signal processing unit 206. That is, the output unit 207 can output measurement data by executing output processing. The output unit 207 includes a communication unit 110 and a general-purpose input/output unit 212. The communication unit 110 includes a communication module 208 for wireless communication and a communication module 209 for wired communication. The communication module 208 can output measurement data wirelessly. In this case, the monitoring gateway device 106 will acquire the measurement data from the monitoring node device 104 as radio waves. The communication module 209 can output measurement data to the network 107. In this case, the monitoring gateway device 106 will acquire the measurement data from the monitoring node device 104 via the network 107.

The output unit 207 is configured to allow signal input and output, but it is sufficient if it is configured to output at least measurement data. Furthermore, depending on the communication method used in the monitoring system 100, either the communication module 208 or the communication module 209 may be omitted in the output unit 207.

Furthermore, the output unit 207 can also output measurement data to the storage unit 210. The output unit 207 can also output measurement data to an external device (e.g., external storage) connected to the general-purpose input/output unit 212. Additionally, as part of the output processing, the output unit 207 outputs node number information for identifying individual monitoring node devices 104, and task number information for the measurement task executed by the signal processing unit 206, along with the measurement data. For example, the output unit 207 outputs this data to the monitoring gateway device 106 via wireless or wired communication, in the order of node number information, task number information, and measurement data.

The trigger generation unit 202 generates a trigger signal to the signal processing unit 206 when an event occurs. That is, the trigger generation unit 202 outputs a trigger signal corresponding to the event that occurred. The trigger signal includes task number information.

Here, "an event occurs" means that the conditions for starting measurement are met. Hereafter, these conditions will be referred to as event conditions. In this embodiment, the conditions for starting measurement, i.e., event conditions, are set in the trigger generation unit 202 by the signal processing unit 206. The event conditions set by the signal processing unit 206 may be one or multiple. If multiple event conditions are set in the trigger generation unit 202 by the signal processing unit 206, the trigger generation unit 202 outputs trigger signals corresponding to the met event conditions to the signal processing unit 206 in the order they were met.

The event conditions that can be set by the signal processing unit 206 include time conditions such as the measurement time interval or the measurement start time. Therefore, the trigger generation unit 202 has a timer 216 as an example of a timing unit. While it is assumed that the timer 216 is located within the trigger generation unit 202, this is not the only possible location. The timer 216 may be located anywhere within the monitoring node device 104. The trigger generation unit 202 can determine whether the time condition has been met by timing with the timer 216. Furthermore, in this embodiment, the event conditions that can be set by the signal processing unit 206 also include conditions other than time conditions. Examples of conditions other than time conditions include external trigger input signals, state changes of the monitoring node device 104, calls from other tasks within the monitoring node device 104, calls from the monitoring gateway device 106, and calls from other monitoring node devices.

If the event condition is a measurement time interval, the event occurs at predetermined time intervals. If the event condition is a measurement time, the event occurs at a predetermined time, and if a day of the week is also specified, the event occurs at the predetermined time on that day of the week. If the event condition is an external trigger input signal, the event occurs when the signal of the general-purpose input/output unit 212 changes. If the event condition is a state change of the monitoring node device 104, the event occurs when the battery level of the monitoring node device 104 changes or when the temperature sensor inside the monitoring node device 104 changes. If the event condition is a call from another task within the monitoring node device 104, the event occurs when it is called by the output conditions of another task other than the measurement task within the same monitoring node device 104. If the event condition is a call from the monitoring gateway device 106, the event occurs when a task execution command is received from the monitoring gateway device 106. If the event condition is a call from another monitoring node device, the event occurs when it is called by the output processing of another monitoring node device.

The processing details of the AD conversion process of the signal input unit 205, the signal processing of the signal processing unit 206, and the output processing of the output unit 207, each associated with a set of multiple event conditions, are recorded as measurement tasks in the task table 240. The task table 240 is stored, for example, in the storage unit 210. The signal processing unit 206 refers to the task table 240 and performs measurements using the sensors specified in the measurement tasks defined in the task table 240. While the storage location of the task table 240 is preferably the storage unit 210 inside the monitoring node device 104, it is not limited to this. For example, the task table 240 may be stored in an external storage device outside the monitoring node device 104. The information in the task table 240 is set by a person, such as an operator or user.

External devices can be connected to the general-purpose input/output unit 212. As an example of an external device, a recording medium 214 containing the control program 230 can be connected to the general-purpose input/output unit 212. The recording medium 214 is a computer-readable, non-temporary recording medium containing the control program 230. The control program 230 recorded on the recording medium 214 can be stored in the storage unit 210 via the general-purpose input/output unit 212. The recording medium 214 may be a recording disk such as a magnetic disk or optical disk (e.g., CD-ROM or DVD-ROM), or a storage device such as flash memory (e.g., SD card).

Figure 3 is an explanatory diagram showing an example of a task table 240 in the first embodiment. The task table 240 includes a plurality of task number information ₃₀₁₁ , ₃₀₁₂ , ₃₀₁₃ , a plurality of event conditions ₃₀₂₁ , ₃₀₂₂ , ₃₀₂₃ , a plurality of priority information ₃₀₃₁ , ₃₀₃₂ , ₃₀₃₃ , and a plurality of measurement tasks ₃₁₀₁ , ₃₁₀₂ , _3103. In the task table 240, task number information ₃₀₁₁ , event condition ₃₀₂₁ , priority information ₃₀₃₁ , and measurement task ₃₁₀₁ are associated with each other. In the task table 240, task number information ₃₀₁₂ , event condition ₃₀₂₂ , priority information ₃₀₃₂ , and measurement task ₃₁₀₂ are associated with each other. In the task table 240, task number information 301 ₃ , event conditions 302 ₃ , priority information 303 ₃ , and measurement tasks 310 ₃ are associated with each other. That is, each of the multiple measurement tasks 310 ₁ to 310 ₃ is assigned its own priority information 303 ₁ to 303 ₃ .

Task number information 3011 to 3013 is information with numbers such as ₁ , 2, and _3. Priority information 3031 to ₃₀₃₃ is information that represents priority with numbers such as ₁ , 2, and 3. In the example in Figure 3, a smaller number indicates a higher priority. Note that these are just examples and are not limiting. For example, a larger number could indicate a higher priority. Here, measurement tasks that are relatively urgent are assigned a higher priority.

Each measurement task ₃₁₀₁ to ₃₁₀₃ includes three tasks. Measurement task ₃₁₀₁ includes task ₃₀₄₁ , task 3051, and task 3061. Measurement task ₃₁₀₂ includes task 3042, task ₃₀₅₂ , and task _3062. Measurement task ₃₁₀₃ includes task ₃₀₄₃ , task ₃₀₅₃ , and task _3063. Each task _{3041 to 3043} is a first task in which the signal input unit 205 performs AD conversion processing. Each task _{3051 to 3053} is a second task in _which the signal processing unit 206 performs signal processing on the digital signal to generate measurement data. Each task ₃₀₆₁ to ₃₀₆₃ is a third task in which the output unit 207 performs output processing to output the measurement data.

The task table 240 consists of several items 301 to 306. Item 301 is where task number information ₃₀₁₁ to ₃₀₁₃ is registered. Item 302 is where event conditions ₃₀₂₁ to ₃₀₂₃ are registered. Item 303 is where priority information ₃₀₃₁ to ₃₀₃₃ is registered. Items 304 to 306 are where measurement tasks ₃₁₀₁ to ₃₁₀₃ are registered. Specifically, item 304 is where tasks ₃₀₄₁ to ₃₀₄₃ for AD conversion processing in the signal input unit 205 are registered. Item 305 is where tasks ₃₀₅₁ to ₃₀₅₃ (processing details) for signal processing in the signal processing unit 206 are registered. Item 306 is the item in which tasks ₃₀₆₁ to ₃₀₆₃ (output format) for output processing in the output unit 207 are registered.

Thus, the task table 240 contains pre-registered measurement tasks corresponding to multiple event conditions, along with task number information and priority information.

Figure 4 is a flowchart showing the procedure for the monitoring node device 104 to monitor the machine device 101, i.e., the information processing method, according to the first embodiment. When the power to the monitoring node device 104 is turned ON, i.e., when the monitoring node device 104 starts up, the monitoring node device 104 begins the control flow for monitoring the machine device 101. In this embodiment, the signal processing unit 206 refers to the task table 240 and executes a measurement task corresponding to the fulfilled event condition.

First, when the monitoring node device 104 is started, the signal processing unit 206 reads the task table 240 that has been pre-registered in the storage unit 210 (S101).

The signal processing unit 206 registers multiple event conditions ₃₀₂₁ to ₃₀₂₃ registered in the task table 240 with task number information ₃₀₁₁ to ₃₀₁₃ and registers them with the trigger generation unit 202 (S102). If any of the multiple event conditions ₃₀₂₁ to ₃₀₂₃ are met, the trigger generation unit 202 outputs a trigger signal corresponding to the met event condition. The trigger signal output by the trigger generation unit 202 includes task number information associated with the met event condition so that the signal processing unit 206 can determine which event condition was met.

The signal processing unit 206 determines whether any of the multiple event conditions ₃₀₂₁ to ₃₀₂₃ read in step S101 have been met, that is, whether a trigger signal has been received from the trigger generation unit 202 (S103). If no event conditions have been met, that is, if no trigger signal has been received from the trigger generation unit 202 (S103: NO), the signal processing unit 206 continues the determination process in step S103. In other words, the signal processing unit 206 enters a state of waiting for a trigger signal.

When the signal processing unit 206 receives a trigger signal from the trigger generation unit 202, i.e., when an event condition is met (S103: YES), it determines whether two or more event conditions are met simultaneously (S104). Hereafter, two or more event conditions will be referred to as N event conditions, where N is an integer greater than or equal to 2.

If none of the N event conditions are met simultaneously (S104: NO), the signal processing unit 206 proceeds to step S107. In this case, only one event condition is met. The signal processing unit 206 reads the measurement task corresponding to this met event condition from the task table 240 (S107). For example, if event condition 302 ₁ is met, the signal processing unit 206 reads the measurement task 310 ₁ corresponding to event condition 302 _1. The measurement task 310 ₁ includes the AD conversion processing task 304 ₁ to be executed by the signal input unit 205, the signal processing task 305 ₁ to be executed by the signal processing unit 206, and the output processing task 306 ₁ to be executed by the output unit 207. The following explanation will use the case where the measurement task read by the signal processing unit 206 in step S107 is measurement task 310 ₁ as an example. Furthermore, the signal processing unit 206 processes measurement tasks other than measurement task 310 1 in the same manner even if the measurement task for which the event condition has been met is a measurement task other than measurement task 310 ₁ .

The signal processing unit 206 instructs the signal input unit 205 to perform task 304 _1. The signal input unit 205 performs AD conversion processing according to task 304 ₁ (S108). As a result, the signal input unit 205 converts the analog signal from the sensor into a digital signal and outputs the digital signal to the signal processing unit 206. The signal processing unit 206 performs signal processing on the digital signal received from the signal input unit 205 according to task 305 ₁ (S109). The signal processing unit 206 outputs the measurement data to the output unit 207 and instructs the output unit 207 to perform task 306 _1. The output unit 207 performs output processing according to task 306 ₁ (S110). As a result, the output unit 207 outputs the measurement data.

The signal processing unit 206 determines whether all measurement tasks have been completed (S111). Since there is only one measurement task, all measurement tasks have been completed (S111: YES), and the signal processing unit 206 returns to the process in step S103.

If N event conditions are met simultaneously in step S104 (S104: YES), the signal processing unit 206 performs priority processing in steps S105 to S113, executing N measurement tasks corresponding to the N event conditions in order of priority.

In this embodiment, packet communication is performed between the trigger generation unit 202 and the signal processing unit 206, where a group of information is communicated as a single unit. That is, a packet is used as the trigger signal. When N event conditions are simultaneously met, the trigger generation unit 202 outputs N task number information corresponding to the N event conditions in a packet. In this case, the packet output by the trigger generation unit 202 may be a single packet or multiple segmented packets. This allows the signal processing unit 206 to obtain the task number information associated with the N simultaneously met event conditions from the trigger generation unit 202.

In step S104, the signal processing unit 206 preferably determines whether N event conditions are met simultaneously, but they may be met approximately simultaneously. For example, multiple event conditions may be met consecutively. In this case, although the multiple event conditions did not occur simultaneously, it may be appropriate to treat multiple event conditions that occurred approximately simultaneously as if they occurred simultaneously. Here, multiple event conditions being met approximately simultaneously means that the time interval between the first and last event conditions among multiple consecutively met event conditions is less than or equal to a predetermined time. The predetermined time is, for example, 0.5 seconds.

In other words, when an event condition is met, the trigger generation unit 202 enters a waiting state from the moment the event condition is met until a predetermined time, for example, 0.5 seconds, has elapsed. If another event condition is met during this waiting state, the trigger generation unit 202 includes task number information corresponding to the previously met event condition and task number information corresponding to the later met event condition in a packet. The trigger generation unit 202 then outputs this packet to the signal processing unit 206. This allows the signal processing unit 206 to determine that N event conditions have been met approximately simultaneously. Thus, by providing a predetermined waiting time, the trigger generation unit 202 can notify the signal processing unit 206 of information regarding N event conditions that were met approximately simultaneously. Note that if simultaneity is paramount, the waiting time can be omitted. Without a waiting time, the trigger generation unit 202 can notify the signal processing unit 206 of information indicating that N event conditions were met simultaneously.

If multiple (N) event conditions are met simultaneously (or nearly simultaneously) in step S104 (S104: YES), the signal processing unit 206 arranges the N measurement tasks in order of priority (S105). That is, the signal processing unit 206 determines the execution order of the N measurement tasks.

Next, the signal processing unit 206 determines whether there are at least two measurement tasks with the same priority among the N measurement tasks (S106). Hereafter, at least two measurement tasks will be referred to as M measurement tasks, where M is an integer between 2 and N.

If there are no M measurement tasks with the same priority as the N measurement tasks (S106: NO), the signal processing unit 206 proceeds to step S107. The signal processing unit 206 then reads the N measurement tasks in the order they are listed and executes each measurement task (S107-S111). If all measurement tasks have been executed (S111: YES), the signal processing unit 206 returns to step S103. Thus, when N event conditions are met simultaneously (or nearly simultaneously), the signal processing unit 206 executes the N measurement tasks corresponding to the N event conditions in order of priority.

In step S106, if the N measurement tasks include M measurement tasks with the same priority (S106: YES), the signal processing unit 206 proceeds to the processing in step S112.

The signal processing unit 206 estimates, i.e., calculates, the execution time for each of the M measurement tasks with the same priority (S112). The signal processing unit 206 calculates the execution time for each measurement task based on the sampling rate, sampling frequency, proportionality constant K, and proportionality constant L, which will be described later. This estimation calculation is performed before executing the M measurement tasks in the later steps S107 to S111. The signal processing unit 206 then arranges the M measurement tasks in order of shortest execution time (S113).

The signal processing unit 206 then reads the N measurement tasks in the order they are listed and executes each measurement task (S107-S111). If all measurement tasks have been executed (S111: YES), the signal processing unit 206 returns to step S103. In summary, if the N measurement tasks include M measurement tasks with the same priority, the signal processing unit 206 executes the M measurement tasks in order of shortest execution time when executing the N measurement tasks.

The information processing method described above will now be explained using a specific example of the task table 240 shown in Figure 3. The timer 216 of the trigger generation unit 202 starts timing from the moment the monitoring node device 104 is powered on or reset.

Event condition 302 ₁ is met once every 60 minutes, i.e., every time 60 minutes have elapsed. The following explanation assumes that only event condition 302 ₁ is met. When event condition 302 ₁ is met (S103: YES), a trigger signal containing task number information 301 ₁ , i.e., the information "1", is transmitted from the trigger generation unit 202 to the signal processing unit 206. The signal processing unit 206 executes the measurement task 310 ₁ corresponding to the task number information 301 _1. The measurement task 310 ₁ includes task 304 ₁ , task 305 ₁ , and task 306 ₁ .

First, the signal processing unit 206 reads measurement task 310 ₁ from the task table 240 (S107) and instructs the signal input unit 205 to perform task 304 _1. The signal input unit 205, in accordance with task 304 ₁ , converts the analog signal from channel terminal ch1 into a digital signal with a sampling frequency of 10 kHz, an input range of 0 to 5 V, 5,000 sampling points, and an amplification factor of 50 times (S108).

Next, the signal processing unit 206 performs signal processing on the digital signal according to task 305 _1. Specifically, the signal processing unit 206 performs frequency filtering and averaging on the digital signal (S109). Here, let's assume that the average value is less than or equal to the threshold "50".

The signal processing unit 206 instructs the output unit 207 to perform task 306 _1. In task 306 ₁ , "wireless" is selected. Therefore, the communication module 208 of the output unit 207 transmits the measurement data to the monitoring gateway device 106 via wireless communication (S110).

Next, we will explain the case where event condition 302 ₁ and event condition 302 ₂ are met simultaneously. Here, priority is determined by the number, with smaller numbers indicating higher priority. Event condition 302 ₂ is met once every 24 hours, that is, every time 24 hours have passed.

When event condition 302 ₁ and event condition 302 ₂ are met simultaneously, a trigger signal containing task number information 301 ₁ , i.e., "1", and task number information 301 ₂ , i.e., "2", is transmitted from the trigger generation unit 202 to the signal processing unit 206.

The signal processing unit 206 determines the priority by referring to the task table 240 because two event conditions ₃₀₂₁ and ₃₀₂₂ are simultaneously met (S104: YES). The priority of event condition ₃₀₂₁ is "2", and the priority of event condition ₃₀₂₂ is "1". Therefore, the priority of event condition ₃₀₂₂ is higher than that of event condition _3021. For this reason, the signal processing unit 206 executes the two measurement tasks ₃₁₀₁ and ₃₁₀₂ in order of priority, i.e., measurement task ₃₁₀₂ followed by measurement task _3101. Measurement task ₃₁₀₂ includes task ₃₀₄₂ , task ₃₀₅₂ , and task ₃₀₆₂ .

First, the signal processing unit 206 reads measurement task 310 ₂ from the task table 240 (S107) and instructs the signal input unit 205 to perform task 304 _2. The signal input unit 205, in accordance with task 304 ₂ , converts the analog signal from channel terminal ch2 into a digital signal with a sampling frequency of 54 kHz, an input range of 0 to 5V, a sampling rate of 10,000 points, and an amplification factor of 50 times (S108).

Next, the signal processing unit 206 performs signal processing on the digital signal according to task 305 _2. Specifically, the signal processing unit 206 performs FFT processing on the digital signal (S109).

The signal processing unit 206 instructs the output unit 207 to perform task 306 _2. In task 306 ₂ , "wired" is selected. Therefore, the communication module 209 of the output unit 207 transmits the measurement data to the monitoring gateway device 106 via wired communication (S110).

After performing measurement task 310 ₂ , the signal processing unit 206 performs measurement task 310 ₁ (S107-S110). Since measurement task 310 ₁ has been described above, its explanation will be omitted. In this way, the measurement tasks are executed in order of priority.

Next, we will explain the case where only event condition 302 ₁ is met first, and then event conditions 302 ₂ and 302 ₃ are met simultaneously. The priority of measurement task 310 ₂ corresponding to event condition 302 ₂ and the priority of measurement task 310 ₃ corresponding to event condition 302 ₃ are the same.

First, the signal processing unit 206 executes the measurement task 310 ₁ corresponding to event condition 302 _1. At this time, it is assumed that an abnormality has occurred in the monitored machine 101, and the average value has exceeded the threshold "50". When the result of the measurement performed by task number "1" exceeds a certain threshold, a more detailed measurement is performed by task number "3". At this time, it is assumed that the event condition 302 ₃ for "call" of task number "3" is met, and at the same time, the event condition 302 ₂ for "24-hour interval" of task number "2" is met.

When event condition 302 ₂ and event condition 302 ₃ are met simultaneously, a trigger signal containing task number information 301 ₂ , i.e., "2", and task number information 301 ₃ , i.e., "3", is transmitted from the trigger generation unit 202 to the signal processing unit 206.

The signal processing unit 206 determines the priority by referring to the task table 240 because two event conditions 302 ₂ and 302 ₃ are simultaneously met (S104: YES). The priority of measurement task 310 ₂ corresponding to event condition 302 ₂ is "1", and the priority of measurement task 310 ₃ corresponding to event condition 302 ₃ is "1". Therefore, the priority of measurement task 310 ₂ and the priority of measurement task 310 ₃ are the same (S106: YES). For this reason, the signal processing unit 206 calculates the execution time required to execute each measurement task 310 ₂ and 310 ₃ (S112).

The following describes a preferred specific example of the process for calculating the execution time in step S112. Figure 5 is a flowchart of the process for calculating the execution time in the first embodiment. Figure 6(a) is an explanatory diagram showing an example of table 251 in the first embodiment, and Figure 6(b) is an explanatory diagram showing an example of table 252 in the first embodiment. Tables 251 and 252 are stored in the storage unit 210 shown in Figure 2. Table 251 is the first table, and table 252 is the second table. The information in each table 251 and 252 is set by a person, such as an operator or user.

Here, the execution time required for the measurement task 310 ₂ includes the sampling time required for the task 304 ₂ , the signal processing time required for the task 305 ₂ , and the output time required for the task 306 _2. The execution time required for the measurement task 310 ₃ includes the sampling time required for the task 304 ₃ , the signal processing time required for the task 305 ₃ , and the output time required for the task 306 _3. The sampling time is the first time, the signal processing time is the second time, and the output time is the third time. In this embodiment, the execution time is calculated by the sum of the sampling time, the signal processing time, and the output time.

Table 251 is a table that associates the processing details of the signal processing unit 206 with the proportionality constant K. The proportionality constant K is the first proportionality constant. Table 252 is a table that associates the output format of the output processing unit 207 with the proportionality constant L. The proportionality constant L is the second proportionality constant.

First, the signal processing unit 206 reads tables 251 and 252 from the storage unit 210 (S201, S202). Based on the sampling frequency and number of samples used when the signal input unit 205 performs AD conversion processing, the signal processing unit 206 determines the sampling time corresponding to each measurement task ₃₁₀₂ and ₃₁₀₃ (S203).

The sampling time is the time required to sample a signal. The signal processing unit 206 calculates the sampling time corresponding to each measurement task ₃₁₀₂ and ₃₁₀₃ by dividing the number of samples by the sampling frequency. The number of samples and sampling frequency corresponding to each measurement task ₃₁₀₂ and ₃₁₀₃ are registered in each task ₃₀₄₂ and _3043. That is, in the example in Figure 3, both tasks ₃₀₄₂ and ₃₀₄₂ have a number of samples of 10,000 and a sampling frequency of 54 kHz. The sampling time corresponding to each measurement task ₃₁₀₂ and ₃₁₀₃ can be estimated as 10,000 / 54 kHz = 0.185 seconds by dividing the number of samples by the sampling frequency.

The signal processing unit 206 determines the signal processing time (S204) based on the number of samples used when the signal input unit 205 performs AD conversion and the proportionality constant K corresponding to the processing content of the signal processing. In this embodiment, the signal processing unit 206 determines the signal processing time by referring to table 251.

The signal processing time is the time required to process the digital signal obtained from the signal input unit 205. It is proportional to the sampling rate, and the proportionality constant is denoted by K. The proportionality constant K varies depending on the signal processing content. Therefore, it is necessary to set the proportionality constant K individually according to the processing content. Furthermore, if there are multiple monitoring node devices, it is necessary to set it individually for each of the monitoring node devices. The correspondence between the processing content and the proportionality constant K is defined in Table 251 shown in Figure 6(a).

In step S204, the signal processing unit 206 calculates the signal processing time corresponding to each measurement task ₃₁₀₂ , ₃₁₀₃ by multiplying the number of samples by the proportionality constant K.

The number of samples corresponding to each measurement task ₃₁₀₂ and ₃₁₀₃ is registered for each task ₃₀₄₂ and _3043. That is, in the example in Figure 3, the number of samples for both tasks ₃₀₄₂ and ₃₀₄₂ is 10,000.

The signal processing in measurement task 310 ₂ is FFT processing. Referring to Table 251, the proportionality constant K associated with FFT processing is 2 × ^10⁻⁴ . The signal processing time corresponding to measurement task 310 ₂ can be estimated as 10,000 × 2 × ^10⁻⁴ = 2 seconds by multiplying the number of samples by the proportionality constant K.

The signal processing in measurement task 310 ₃ is averaging. Referring to Table 251, the proportionality constant K associated with averaging is 2 × ^10⁻⁵ . The signal processing time corresponding to measurement task 310 ₃ can be estimated as 10,000 × 2 × ^10⁻⁵ = 0.2 seconds by multiplying the number of samples by the proportionality constant K.

The signal processing unit 206 determines the output time (S205) based on the number of samples used when the signal input unit 205 performs AD conversion processing, and the proportionality constant L corresponding to the output format of the output unit 207. In this embodiment, the signal processing unit 206 determines the output time by referring to table 252.

The output time is the time required for communication and is proportional to the number of samples, with L being the proportionality constant. The proportionality constant L varies depending on the output format of the measurement data in the output unit 207. That is, the output time differs depending on whether the measurement data is output wirelessly, via a wired connection, or written to external storage. Therefore, the proportionality constant L must be set individually according to the output format. Furthermore, if there are multiple monitoring node devices, it must be set individually for each of the multiple monitoring node devices. The correspondence between the output format and the proportionality constant L is defined in Table 252 shown in Figure 6(b).

In step S205, the signal processing unit 206 calculates the output time corresponding to each measurement task ₃₁₀₂ , ₃₁₀₃ by multiplying the number of samples by the proportionality constant L.

The number of samples corresponding to each measurement task ₃₁₀₂ and ₃₁₀₃ is registered for each task ₃₀₄₂ and _3043. That is, in the example in Figure 3, the number of samples for both tasks ₃₀₄₂ and ₃₀₄₂ is 10,000.

The output format in measurement task 310 ₂ is wired. Referring to Table 252, the proportionality constant L associated with wired is 2 × ^10⁻⁵ . The output time corresponding to measurement task 310 ₂ can be estimated as 10,000 × 2 × ^10⁻⁵ = 0.2 seconds by multiplying the number of samples by the proportionality constant L.

The output format in measurement task 310 ₃ is wireless. Referring to Table 252, the proportionality constant L associated with wireless is 1 × ^10⁻⁴ . The output time corresponding to measurement task 310 ₃ can be estimated as 10,000 × 1 × ^10⁻⁴ = 1 second by multiplying the number of samples by the proportionality constant L.

Based on the above, the execution time for measurement task 310 ₂ is 0.185 + 2 + 0.2 = 2.385 seconds, and the execution time for measurement task 310 ₃ is 0.185 + 0.2 + 1 = 1.385 seconds. Using this calculation, the signal processing unit 206 determines the execution time for each measurement task 310 ₁ and 310 ₂ (S206). In this example, the execution time for measurement task 310 ₃ is shorter than that for measurement task 310 _2. Therefore, measurement task 310 ₃ , which has a shorter execution time, is executed first.

The explanation described the case where the execution time calculation is performed in step S112 after determining YES in step S106, but this is not the only option. For example, the execution time may be calculated at the time when the task table 240 and tables 251 and 252 are stored in the monitoring node device 104.

As described above, according to the first embodiment, even when N event conditions are met simultaneously, the N measurement tasks are executed in order of priority, preventing delays in high-priority measurement tasks. Furthermore, if the N measurement tasks include M measurement tasks with the same priority, the M measurement tasks are executed in order of shortest execution time, thus reducing waiting time when executing each of the M measurement tasks. For example, if there is a measurement task among the M measurement tasks that needs to be executed reliably in a specific cycle, the waiting time when executing that measurement task can be reduced. Therefore, according to the first embodiment, the state of the machine device 101 can be measured at the appropriate timing.

[Second Embodiment]
The information processing method according to the second embodiment will now be described. In the second embodiment, the overall configuration of the production equipment is the same as that of the production equipment 1000 in the first embodiment, and therefore will not be described. In the second embodiment, some parts of the information processing method differ from those of the first embodiment.

In other words, the first embodiment described a case in which the priority of each measurement task is registered in advance in the task table 240. That is, the case described a case in which a person such as an operator or user registers the priority corresponding to each of multiple measurement tasks in the task table 240.
In this embodiment, we will describe a case in which the signal processing unit 206 automatically determines the priority of each measurement task. In the following, we will describe in detail the parts that differ from the first embodiment in the second embodiment, and omit the description of parts that are the same.

Figure 7 is an explanatory diagram showing a priority table 260 used in the information processing method according to the second embodiment. In the task table 240 shown in Figure 3, multiple measurement tasks ₃₁₀₁ to ₃₁₀₃ corresponding to multiple task number information ₃₀₁₁ to ₃₀₁₃ are registered. In the second embodiment, it will be explained that in the task table 240 shown in Figure 3, the priority item 303 itself does not exist, or even if the priority item 303 exists, the priority information is not registered.

If N event conditions are met simultaneously (S104 in Figure 4: YES), the signal processing unit 206 executes the N measurement tasks corresponding to the N event conditions in order of priority. Therefore, in step S105 in Figure 4, the signal processing unit 206 refers to the priority table 260 shown in Figure 7 to assign priorities to the N measurement tasks. That is, in step S105, the signal processing unit 206 refers to the priority table 260 to determine the priority of the N measurement tasks for which the event conditions were met simultaneously. Then, the signal processing unit 206 arranges the N measurement tasks in order of priority. The priority table 260 is pre-stored in the storage unit 210 in Figure 2. The information in the priority table 260 is set by a person, such as an operator or user.

In the priority table 260, a priority is assigned to each signal processing operation that the signal processing unit 206 can perform. That is, in the priority table 260, the signal processing operation content and its priority are associated.

For example, as shown in Figure 7, priority 1 is assigned to tasks that require relatively little time for signal processing and communication, such as maximum value processing, minimum value processing, and average value processing. Priority 3 is assigned to tasks that require relatively more time for signal processing and communication, such as FFT processing. By registering priorities in this way, when N event conditions overlap, measurement tasks that require less processing time will be executed preferentially over measurement tasks that require more processing time. This prevents delays in the execution of subsequent measurement tasks, i.e., prevents long waiting times when executing subsequent measurement tasks.

The format of the priority table 260 is not particularly limited, but it is preferably in CSV format. In this way, even if priorities are not pre-registered in the task table 240, the signal processing unit 206 can determine the execution order of N measurement tasks by referring to the priority table 260. By having the signal processing unit 206 automatically determine the priority of each measurement task in this way, the task of assigning priorities to each measurement task by a human can be eliminated, thereby reducing the workload on human personnel.

[Third Embodiment]
The information processing method according to the third embodiment will now be described. In the third embodiment, the overall configuration of the production equipment is the same as that of the production equipment 1000 in the first embodiment, and therefore will not be described. In the third embodiment, a part of the information processing method differs from that of the first embodiment.

In other words, the first embodiment described a case where the proportionality constant K is pre-registered in table 251. Specifically, it described a case where a person, such as an operator or user, registers the proportionality constant K in table 251. The third embodiment describes a case where the signal processing unit 206 automatically registers the proportionality constant K. Below, the differences between the third embodiment and the first embodiment will be described in detail, while similar parts will be omitted.

In step S112 shown in Figure 4, the signal processing unit 206 calculates the execution time, and in doing so, it determines the signal processing time, which is the second time included in the execution time. Figure 8 is a flowchart showing the method for determining the signal processing time according to the third embodiment.

First, the signal processing unit 206 reads the first table, the proportionality constant K table 251, from the storage unit 210 (S301). The signal processing unit 206 then determines whether the proportionality constant K corresponding to the signal processing content included in each of the M measurement tasks in the task table 240 is registered in table 251 (S302). If it is registered (S302: YES), the signal processing unit 206 refers to table 251 and calculates the signal processing time for each of the M measurement tasks (S303).

If even one proportionality constant K is not registered (S302: NO), the signal processing unit 206 sets the signal processing time for the processing content for which the proportionality constant K is not registered to the default value, terminates the calculation process (S304), and executes steps S113 onwards in Figure 4. Then, when the signal processing unit 206 actually executes the processing content for which the proportionality constant K is not registered in step S109, it starts measuring the actual signal processing time (S305). The signal processing unit 206 executes the signal processing (S306), and once the signal processing is complete, it terminates the measurement of the signal processing time (S307). This ensures that the actual signal processing time corresponding to the processing content is measured.

The signal processing unit 206 calculates the proportionality constant K corresponding to the signal processing content by dividing the measured signal processing time by the number of samples set for the measurement task (S308). Then, the signal processing unit 206 records the calculated proportionality constant K in table 251, associating it with the processing content (S309). In summary, the signal processing unit 206 registers the proportionality constant K in table 251, associating it with the signal processing content, based on the measured signal processing time.

Through the above processing, the proportionality constant K, which was not previously registered in Table 251, will be registered. This reduces the workload on workers and users by eliminating the need for them to manually register the proportionality constant K in Table 251.

[Fourth Embodiment]
The information processing method according to the fourth embodiment will now be described. In the fourth embodiment, the overall configuration of the production equipment is the same as that of the production equipment 1000 in the first embodiment, and therefore will not be described. In the fourth embodiment, a part of the information processing method differs from that of the first embodiment.

In other words, the first embodiment described a case where the proportionality constant L is pre-registered in table 252. Specifically, it described a case where a person, such as an operator or user, registers the proportionality constant L in table 252. The fourth embodiment describes a case where the signal processing unit 206 automatically registers the proportionality constant L. Hereinafter, the differences between the fourth embodiment and the first embodiment will be described in detail, while similar parts will be omitted.

In step S112 shown in Figure 4, the signal processing unit 206 calculates the execution time, and at that time, it determines the output time, which is the third time included in the execution time. Figure 9 is a flowchart showing the method for determining the output time according to the fourth embodiment.

First, the signal processing unit 206 reads the second table, table 252 of proportionality constants L, from the storage unit 210 (S401). The signal processing unit 206 then determines whether the proportionality constants L corresponding to the output format of the output processing included in each of the M measurement tasks in the task table 240 are registered in table 252 (S402). If they are registered (S402: YES), the signal processing unit 206 refers to table 252 and calculates the output time for each of the M measurement tasks (S403).

If even one proportionality constant L is not registered (S402: NO), the signal processing unit 206 sets the output time to the default value for output formats where the proportionality constant L is not registered, terminates the calculation process (S404), and executes steps S113 onwards in Figure 4. Then, when the signal processing unit 206 actually outputs measurement data in step S110 for output formats where the proportionality constant L is not registered, it starts measuring the actual output time (S405). The signal processing unit 206 executes the output processing (S406), and once the output processing is complete, it terminates the measurement of the output time (S407). This ensures that the actual output time corresponding to the output format is measured.

The signal processing unit 206 calculates the proportionality constant L corresponding to the output format by dividing the measured output time by the number of samples set for the measurement task (S408). Then, the signal processing unit 206 records the calculated proportionality constant L in table 252, associating it with the output format (S409). In summary, the signal processing unit 206 registers the proportionality constant L in table 252, associating it with the output format, based on the measured output time.

For example, in the measurement task 310 ₁ of task table 240, task 306 ₁ (output format) is "wireless," and in task 304 ₁ , the sampling rate is 5,000 points. Therefore, by dividing the measured output time by 5,000, the proportionality constant L corresponding to "wireless" can be automatically determined.

Through the above processing, the proportionality constant L, which was not previously registered in Table 252, will be registered. This reduces the workload on workers and users by eliminating the need for them to manually register the proportionality constant L in Table 252.

[Fifth Embodiment]
The information processing method according to the fifth embodiment will now be described. In the fifth embodiment, the overall configuration of the production equipment is the same as that of the production equipment 1000 in the first embodiment, and therefore will not be described. In the fifth embodiment, a part of the information processing method differs from that of the first embodiment.

In the second embodiment described above, priorities were set using a pre-created priority table 260. This embodiment describes a method in which the terminal 109 references the storage unit 210 of the monitoring node device 104, displays each measurement task on the display unit, and allows the user to set the priority corresponding to each measurement task. The terminal 109 has some of the processing unit's functions. This embodiment details the case where each measurement task is displayed on the display unit of the terminal 109. However, it is also possible to connect a terminal such as a laptop computer to the monitoring node device 104 and display each measurement task on the display unit of the connected laptop computer. The terminal 109 functions as an information processing device capable of communicating with the monitoring node device 104. The information processing device may be configured using any of these terminals and the monitoring node device 104.

Figure 10 is an explanatory diagram showing an example of the setting screen 109b displayed on the display unit 109a of the terminal 109 in the fifth embodiment, when setting the priority of the measurement task. The setting screen 109b shown in Figure 10 is an example of the first screen. In this embodiment, the monitoring node device 104 stores the signal processing time, output time, and execution time information, as detailed in the first embodiment, in the storage unit 210, associating it with each measurement task.

When the user instructs the terminal 109 to set the priority of the measurement tasks, the terminal 109 refers to the task table 240 stored in the storage unit 210 of the monitoring node device 104 and the data containing information for each time period. The terminal 109 then extracts the items for each measurement task and displays the information for each time period, corresponding to the extracted measurement task items, as a setting table 250 on the display unit 109a. Item 307 is the signal processing time information, item 308 is the output time information, and item 309 is the execution time information. Item 303 displays the currently set priority information. The terminal 109 may also display the sampling time information for each measurement task on the display unit 109a.

The settings screen 109b shown in Figure 10 displays the signal processing time, output time, and execution time information for measurement task 310 ₂ with task number "2" and measurement task 310 ₃ with task number "3". Furthermore, when the user clicks the cell for item 303 of a predetermined measurement task, the terminal 109 displays a pull-down menu 303a, allowing the user to change the priority information. If the user changes the priority and clicks the register button 320, the terminal 109 saves the changed priority information to the storage unit 210. If the user clicks the back button 321, the terminal 109 does not save the changed priority information to the storage unit 210. If the register button 320 is clicked, the terminal 109 instructs the monitoring node device 104 to save the changed information to the storage unit 210, and the monitoring node device 104 updates the task table 240 in the storage unit 210 with the changed priority information.

Figure 11 is an explanatory diagram showing an example of a setting screen 109c, which is a modified version of the fifth embodiment. In Figure 10, the signal processing time, output time, and execution time information are displayed in separate columns of the setting table 250, but they can also be displayed in a single column using the pull-down menu 307a. In the example shown in Figure 11, the signal processing time information is displayed, but this can be changed to displaying the output time and execution time using the pull-down menu 307a.

As described above, according to this embodiment, the user can set priorities for each measurement task while referring to information such as signal processing time, output time, and execution time, as well as event conditions and signal processing type. This allows the user to set appropriate priorities while referring to the characteristics of each measurement task.

[Sixth Embodiment]
The information processing method according to the sixth embodiment will now be described. In the sixth embodiment, the overall configuration of the production equipment is the same as that of the production equipment 1000 in the first embodiment, and therefore will not be described. In the sixth embodiment, some parts of the information processing method differ from those of the first embodiment.

In the fifth embodiment, the user manually entered the priority in item 303. However, the user may be allowed to set a reference item, and the terminal 109 may be allowed to automatically set the priority based on that item.

Figure 12 is an explanatory diagram showing an example of the setting screen 109d displayed on the display unit 109a of the terminal 109 in the sixth embodiment, when setting the priority of the measurement task. The setting screen 109d shown in Figure 12 is an example of the second screen. From Figure 12, it can be seen that in this embodiment, the terminal 109 displays a reference box 322, a condition box 323, a priority box 324, and an automatic setting button 325 on the display unit 109a. The reference box 322 is an example of the first box, the condition box 323 is an example of the second box, and the priority box 324 is an example of the third box.

The Criteria Box 322 is a box where the user can set the item (criteria) that the terminal 109 should focus on when automatically setting the priority. In the example shown in Figure 12, "Signal Processing Time" is set as the item to focus on in the Criteria Box 322. The Priority Box 324 is a box where the user can set the priority that the terminal 109 will automatically set. In the example shown in Figure 12, "1" is set as the priority in the Priority Box 324. The Condition Box 323 is a box where the user can set the condition that the terminal 109 will automatically set to the priority set in the Priority Box 324, and that the item (criteria) set in the Criteria Box 322 must satisfy. In the example shown in Figure 12, "2 seconds or less" is set as the condition that the criterion must satisfy in the Condition Box 323.

Then, when the user clicks the automatic setting button 325, the priority of measurement tasks with a signal processing time of 2 seconds or less is automatically set to "1". In the example shown in Figure 12, the priority of measurement task 310 ₂ with task number "2" and measurement task 310 ₃ with task number "3" are both automatically set to "1".

Furthermore, as shown in Figure 13, the signal processing information for item 305 may be set in the reference box 322. In the example shown in Figure 13, "FFT processing" is set. In Figure 13, since the item of focus is the processing content, "-" is displayed in the condition box 323. "3" is set in the priority box 324.

Then, when the automatic setting button 325 is clicked, the priority of the measurement task whose signal processing is FFT processing is automatically set to "3". In the example shown in Figure 13, the priority of measurement task ₃₁₀₂ is set to "3".

According to this embodiment, the priority of measurement tasks can be automatically set according to the user's requirements. This makes it possible to easily and appropriately set priorities when the number of measurement tasks is enormous, by automatically assigning priorities.

[Seventh Embodiment]
The information processing method according to the seventh embodiment will now be described. In the seventh embodiment, the overall configuration of the production equipment is the same as that of the production equipment 1000 in the first embodiment, and therefore the description will be omitted. In the seventh embodiment, a part of the information processing method differs from that of the first embodiment.

In the seventh embodiment, we will describe a case where priority is set based on measurement data measured by each measurement task, which is stored in the database 108. Figure 14 is a control flowchart in the seventh embodiment. Figure 15 is an explanatory diagram showing an example of the setting screen 109e displayed on the display unit 109a of the terminal 109 when setting the priority of the measurement task in the seventh embodiment. The setting screen 109e shown in Figure 15 is an example of the third screen.

As shown in Figure 14, first, in step S501, terminal 109 accesses database 108 and refers to the latest values of measurement data obtained by executing each measurement task. Then, in step S502, terminal 109 updates the latest values of measurement data. Then, as shown in Figure 15, terminal 109 displays a measurement data graph 330 plotting the measurement data from each measurement task. The horizontal axis shows the number of measurements, with the measurement data from the 1st, 2nd, etc., from left to right. The vertical axis shows the value of the measurement data. In addition, in the measurement data graph 330, "O" represents the measurement data for measurement task 310 ₁ with task number "1", and "Δ" represents the measurement data for measurement task 310 ₂ with task number "2".

As shown in Figure 15, in this embodiment, the terminal 109 displays the measurement data graph 330 while also displaying the setting table 270 for setting priorities. Item 332 displays the latest measurement data referenced in steps S501 and S502, and the priority currently set for the measurement task, with item 332a being the latest value and item 332b being the priority.

Furthermore, item 333 displays the first threshold for each measurement task, and item 334 displays the second threshold. The values of items 333 and 334 can be changed by the user.

The first threshold is the threshold at which the priority of a measurement task is changed. Terminal 109 changes the priority when the value of the measurement data exceeds the set first threshold. Item 333a displays the set value of the first threshold, and item 333b sets the priority to be changed when the value of the measurement data exceeds the first threshold. For measurement task 310 ₁ , task number "1", the first threshold is set to "5", and the changed priority is set to "1". Similarly, for measurement task 310 ₂ , task number "2", the first threshold is set to "5", and the changed priority is set to "1".

The second threshold is the value at which an abnormality is alerted to the user. An alarm is triggered when the measurement data exceeds the value of the set second threshold. Various methods can be used to trigger the alarm, such as email notification, buzzer, or lamp illumination. In measurement task 310 ₁ , task number "1", the second threshold is set to "8", and similarly, in measurement task 310 ₂ , task number "2", the second threshold is also set to "8".

Then, as shown in Figure 14, from step S503, terminal 109 determines whether the latest measurement data value is equal to or greater than the second threshold. If there is measurement data where the latest measurement data value is equal to or greater than the second threshold (S503: YES), terminal 109 proceeds to step S504, issues an alarm to the user, and terminates the flow. If there is no measurement data where the value is equal to or greater than the second threshold (S503: NO), terminal 109 proceeds to step S505.

In step S505, terminal 109 determines whether the latest measurement data is equal to or greater than the first threshold. If there is measurement data where the latest measurement data is equal to or greater than the first threshold (S505: YES), terminal 109 proceeds to step S506 and changes the priority of the measurement task for measuring the measurement data that is equal to or greater than the first threshold. It then transmits the changed priority to the monitoring node device 104, which updates the task table 240. If there is no measurement data equal to or greater than the first threshold (S505: NO), terminal 109 terminates the flow. These flows are executed at time intervals set in box 335, which shows the periodic update time column in Figure 15. In the example in Figure 15, they are executed at 5-minute intervals.

As described above, this embodiment allows for changing the priority of measurement tasks based on measurement data. In particular, by setting a first and second threshold, measurement tasks that measure data reaching the first threshold can be prioritized and monitored as "high-priority" tasks, aiding in the early detection of anomalies in the monitored target. Furthermore, if measurement data reaching the second threshold exists, an alarm is issued indicating an "anomaly," allowing the user to immediately perform maintenance on the monitored target.

[Eighth Embodiment]
The information processing method according to the eighth embodiment will now be described. In the eighth embodiment, the overall configuration of the production equipment is the same as that of the production equipment 1000 in the first and seventh embodiments, so the description will be omitted. In the eighth embodiment, some parts of the information processing method differ from those of the first and seventh embodiments.

The seventh embodiment described above explained how to change the priority of a measurement task that measures measurement data exceeding a first threshold. The eighth embodiment details how to change the priority of a measurement task that measures measurement data where the value has suddenly changed, even when the measurement data is not exceeding the first threshold. Figure 16 is a control flowchart in the eighth embodiment. Figure 17 is an explanatory diagram showing an example of the setting screen 109f displayed on the display unit 109a of the terminal 109 when setting the priority of the measurement task in the eighth embodiment. The setting screen 109f shown in Figure 17 is an example of the third screen.

As shown in Figure 16, the differences between the eighth embodiment and the seventh embodiment are the presence of a step S507 to determine whether or not there is measurement data where the gradient (amount of change) of the measurement data is greater than or equal to the gradient threshold, and the presence of an item 336 for setting gradient monitoring, as shown in Figure 17. Item 336 displays an item 336a for setting the gradient threshold and an item 336b for the user to set the priority when the gradient threshold is exceeded. The gradient threshold is an example of a third threshold and is the amount of change of the latest measurement data relative to the previous measurement data. In measurement task 310 ₁ , task number "1", the gradient threshold is set to "2", and the priority when the gradient threshold is exceeded is set to "1". Similarly, in measurement task 310 ₂ , task number "2", the gradient threshold is also set to "2", and the priority when the gradient threshold is exceeded is set to "1".

In step S507, terminal 109 determines whether the gradient of the latest measurement data is greater than or equal to the gradient threshold. If the gradient of the latest measurement data is greater than or equal to the gradient threshold (S507: YES), terminal 109 proceeds to step S506 and changes the priority of the measurement task for measuring the measurement data that is greater than or equal to the gradient threshold. It then transmits the changed priority to the monitoring node device 104, which updates the task table 240. If there is no measurement data greater than or equal to the gradient threshold (S507: NO), terminal 109 terminates the flow. These flows are executed at time intervals set in box 335, which shows the periodic update time column in Figure 17. In this embodiment, they are executed at 5-minute intervals.

As described above, this embodiment allows for changing the priority of measurement tasks based on measurement data. In particular, by setting a gradient threshold, measurement tasks that measure data showing sudden changes can be given higher priority and monitored as "high-priority" tasks, which helps in the early detection of anomalies in the monitored data.

The present invention is not limited to the embodiments described above, and many modifications are possible within the technical concept of the present invention. Furthermore, the effects described in the embodiments are merely a list of the most preferred effects arising from the present invention, and the effects of the present invention are not limited to those described in the embodiments.

The above embodiment describes a case where the monitoring device 101 is equipped with multiple sensors 102 and 103, but it is not limited to this. For example, the monitoring device 101 may be equipped with only one sensor. In this case, the monitoring node device 104 may use only one sensor to perform each of the multiple measurement tasks.

Furthermore, while the above-described embodiment described a pump as an example of the monitored mechanical device 101, it is not limited to this. For example, the mechanical device 101 may be a six-axis articulated robot, or it may be a machine that can automatically perform movements such as extension and retraction, bending and straightening, vertical movement, horizontal movement, or rotation, or combinations thereof, based on information stored in a memory device provided in the control device.

(Other examples)
The present invention can also be realized by supplying a program that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (for example, an ASIC) that implements one or more functions.

100... Monitoring system (system), 101... Mechanical device, 102... Sensor, 103... Sensor, 104... Monitoring node device (information processing device, node device), 106... Monitoring gateway device (gateway device), 206... Signal processing unit (processing unit)

Claims (31)

An information processing device to which sensors for measuring the state of a machine are connected,
The system includes a processing unit capable of measuring the state of the mechanical device using the sensor, by executing a measurement task corresponding to a fulfilled event condition among multiple event conditions associated with multiple measurement tasks.
The aforementioned processing unit,
When two or more of the aforementioned multiple event conditions are met, priority processing can be executed to perform two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority .
In the priority processing described above, if the two or more measurement tasks include at least two measurement tasks with the same priority, the at least two measurement tasks are executed in order of shortest execution time.
An information processing device characterized by the following: The processing unit estimates the execution time before performing the at least two measurement tasks.
The information processing apparatus according to feature 1. The system further includes an AD conversion unit capable of performing AD conversion processing to convert the analog signal from the sensor into a digital signal.
The processing unit performs signal processing on the digital signal to generate measurement data.
The information processing apparatus according to claim 1 or 2 . The system further includes an output unit capable of outputting the measurement data generated by the processing unit.
The information processing apparatus according to claim 3 . The processing unit refers to a task table in which the multiple event conditions and the multiple measurement tasks are associated, and executes the measurement task corresponding to the fulfilled event condition.
The information processing apparatus according to any one of claims 1 to 4 . In the task table, each of the multiple measurement tasks is assigned a priority.
The information processing apparatus according to feature 5 . An information processing device to which sensors for measuring the state of a machine are connected,
The system includes a processing unit capable of measuring the state of the mechanical device using the sensor, by executing a measurement task corresponding to a fulfilled event condition among multiple event conditions associated with multiple measurement tasks.
The aforementioned processing unit,
When two or more of the aforementioned multiple event conditions are met, priority processing can be executed to perform two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority.
The system further includes an AD conversion unit capable of performing AD conversion processing to convert the analog signal from the sensor into a digital signal.
The processing unit performs signal processing on the digital signal to generate measurement data.
The processing unit refers to a priority table in which priority is assigned to each processing content of the signal processing, and determines the priority of the two or more measurement tasks.
An information processing device characterized by the following: The measurement task includes a first task in which the AD conversion unit performs the AD conversion process, a second task in which the processing unit applies the signal processing to the digital signal to generate the measurement data, and a third task in which the output unit outputs the measurement data.
The information processing apparatus according to feature 4 . The execution time required for the execution of the measurement task includes the first hour required for the execution of the first task, the second hour required for the execution of the second task, and the third hour required for the execution of the third task.
The information processing apparatus according to feature 8 . The processing unit determines the first time based on the sampling frequency and number of samples used when causing the AD conversion unit to perform the AD conversion process.
The information processing apparatus according to feature 9 . The processing unit determines the second time based on the number of samples used when causing the AD conversion unit to perform the AD conversion process, and a first proportionality constant corresponding to the processing content of the signal processing.
The information processing apparatus according to claim 9 or 10 . The processing unit refers to a first table that associates the processing content with the first proportionality constant to determine the second time.
The information processing apparatus according to feature 11 . The processing unit registers the first proportionality constant in the first table in association with the processing content based on the measured second time.
The information processing apparatus according to feature 12 . The processing unit determines the third time based on the number of samples used when the AD conversion unit performs the AD conversion process, and a second proportionality constant corresponding to the output format in the output unit.
The information processing apparatus according to any one of claims 9 to 13 . The processing unit calculates the third time by referring to a second table which associates the output format with the second proportionality constant.
The information processing apparatus according to feature 14 . The processing unit registers the second proportionality constant in the second table, in association with the output format, based on the measured third time.
The information processing apparatus according to feature 15 . A first screen is displayed that allows setting the priority of the measurement task, including at least one piece of information for the first time, the second time, and the third time.
The information processing apparatus according to feature 9 . A second screen is displayed that allows for the automatic setting of the priority of the measurement task based on at least one of the first, second, and third time periods.
The information processing apparatus according to feature 9 . The second screen includes a first box for setting criteria for automatically setting the priority of the measurement task, a second box for setting conditions that the criteria must satisfy to automatically set the priority of the measurement task, and a third box for setting the priority that will be automatically set when the criteria satisfy the conditions that the criteria must satisfy.
The information processing apparatus according to feature 18 . The first box can further configure the processing content of the measurement task.
The information processing apparatus according to feature 19 . An information processing device to which sensors for measuring the state of a machine are connected,
The system includes a processing unit capable of measuring the state of the mechanical device using the sensor, by executing a measurement task corresponding to a fulfilled event condition among multiple event conditions associated with multiple measurement tasks.
The aforementioned processing unit,
When two or more of the aforementioned multiple event conditions are met, priority processing can be executed to perform two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority.
A third screen is displayed that allows setting the priority of the measurement task based on the measurement data measured by the measurement task.
On the third screen, a first threshold value for the measurement data can be set to automatically change the priority of the measurement task.
An information processing device characterized by the following: An information processing device to which sensors for measuring the state of a machine are connected,
The system includes a processing unit capable of measuring the state of the mechanical device using the sensor, by executing a measurement task corresponding to a fulfilled event condition among multiple event conditions associated with multiple measurement tasks.
The aforementioned processing unit,
When two or more of the aforementioned multiple event conditions are met, priority processing can be executed to perform two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority.
A third screen is displayed that allows setting the priority of the measurement task based on the measurement data measured by the measurement task.
On the third screen, a second threshold value for the measurement data can be set for issuing an alarm.
An information processing device characterized by the following: An information processing device to which sensors for measuring the state of a machine are connected,
The system includes a processing unit capable of measuring the state of the mechanical device using the sensor, by executing a measurement task corresponding to a fulfilled event condition among multiple event conditions associated with multiple measurement tasks.
The aforementioned processing unit,
When two or more of the aforementioned multiple event conditions are met, priority processing can be executed to perform two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority.
A third screen is displayed that allows setting the priority of the measurement task based on the measurement data measured by the measurement task.
On the third screen, a third threshold can be set for the amount of change in the measurement data in order to automatically change the priority of the measurement task.
An information processing device characterized by the following: An information processing device to which sensors for measuring the state of a machine are connected,
The system includes a processing unit capable of measuring the state of the mechanical device using the sensor, by executing a measurement task corresponding to a fulfilled event condition among multiple event conditions associated with multiple measurement tasks.
The aforementioned processing unit,
When two or more of the aforementioned multiple event conditions are met, priority processing can be executed to perform two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority.
A third screen is displayed that allows setting the priority of the measurement task based on the measurement data measured by the measurement task.
On the third screen, the measurement data is displayed in a graph.
An information processing device characterized by the following: The aforementioned priority processing is executed when the two or more event conditions are met simultaneously or substantially simultaneously.
The information processing apparatus according to any one of claims 1 to 24 . Gateway device and
Sensors for measuring the condition of mechanical equipment,
The system includes a node device connected to the aforementioned sensor and capable of transmitting measurement data to the gateway device via wireless or wired communication,
The node device is
The system includes a processing unit capable of measuring the state of the mechanical device using the sensor, by executing a measurement task corresponding to a fulfilled event condition among multiple event conditions associated with multiple measurement tasks.
The aforementioned processing unit,
When two or more of the aforementioned multiple event conditions are met, priority processing can be executed to perform two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority .
In the priority processing described above, if the two or more measurement tasks include at least two measurement tasks with the same priority, the at least two measurement tasks are executed in order of shortest execution time.
A system characterized by the following features. The system described in claim 26 ,
The aforementioned mechanical device,
Production equipment equipped with these features. An information processing method in which a processing unit executes a measurement task corresponding to a fulfilled event condition among a plurality of event conditions associated with a plurality of measurement tasks, and measures the state of a mechanical device using a sensor,
When two or more of the multiple event conditions are met, the processing unit executes priority processing to execute two or more measurement tasks corresponding to the two or more event conditions in order of decreasing priority .
If the processing unit, in the priority processing, includes at least two measurement tasks with the same priority among the two or more measurement tasks, it executes the at least two measurement tasks in order of shortest execution time.
An information processing method characterized by the following: The system of the production equipment described in claim 27 is used to manufacture articles while acquiring the state of the machinery and equipment.
A method for manufacturing an article characterized by the following: A program for causing a computer to execute the information processing method described in claim 28 . A computer-readable recording medium storing the program described in claim 30.