JP2016018372A - Program, prediction device, and prediction method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a program, a prediction device, and a prediction method capable of predicting a fault in a device for which it is difficult to acquire a duration in which electricity is turned on.SOLUTION: The program of one embodiment is a program used in a prediction device 3, the program making the prediction device 3 execute the process of: specifying one connected device 2 to which is correlated the information of the same component as a component whose information is correlated to an independent device 1 from among a plurality of connected devices 2; specifying an operating time, an elapsed time, and a fault time on and after the date and time at which the specified one connected device 2 is introduce; calculating a coefficient for calculating the operating time of the independent device on the basis of the specified operating time and elapsed time; calculating the operating time of the independent device 1 on the basis of the calculated coefficient and the elapsed time of the independent device; and calculating, on the basis of the calculated operating time of the independent device 1 and the fault time, a fault prediction time for predicting a time when the independent device 1 goes down.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a program for predicting a failure of a device, a prediction device, and a prediction method.

  2. Description of the Related Art Conventionally, there has been known a technique for acquiring an energization time indicating a time during which a component used in an apparatus is energized and predicting a failure based on the acquired energization time.

  For example, Patent Document 1 discloses a technique for predicting a failure based on an energization time and a lifetime that a component has.

JP 2007-199052 A

  However, since the conventional technique predicts a failure based on the energization time, there has been a problem that it is difficult to predict a failure of a device for which it is difficult to obtain the energization time.

  In one aspect, an object of the present invention is to provide a program, a prediction device, and a prediction method capable of predicting a failure of a device for which it is difficult to obtain an energization time.

  The program according to one aspect is a program used for a prediction device that predicts a time when an independent device that is independent of a communication network fails, and that is connected to a plurality of connection devices that are connected to the communication network. From the correspondence between the independent device and the information on the parts of the independent device and the correspondence between the plurality of connection devices and the information on the parts of the plurality of connection devices, the same as the information on the components associated with the independent device An operation indicating the time when the identified one connection device has been in operation since the date and time when the identified one connection device was introduced after identifying the one connection device associated with information of the component from the plurality of connection devices. Identifying the time, the elapsed time indicating the time after the date and time of introduction, and the failure time indicating the time from the date and time of introduction to the date and time when the identified one connected device fails, and the specified operating time and elapsed time Based on Calculate a coefficient for calculating the operating time of the independent device, calculate the operating time of the independent device based on the calculated coefficient and the elapsed time of the independent device, and based on the calculated operating time of the independent device and the failure time Then, a process of calculating a failure prediction time for predicting a failure time of the independent device is executed.

  According to one aspect, it is possible to predict a failure of a device for which it is difficult to acquire the energization time.

It is a schematic diagram which shows the outline | summary of a prediction system. It is a block diagram which shows the hardware group of an independent apparatus. It is a block diagram which shows the hardware group of a connection apparatus. It is a figure which shows an example of the data stored in connection information DB. It is a block diagram which shows the hardware group of a prediction apparatus. It is a figure which shows an example of the data stored in apparatus information DB. It is the flowchart which showed the process sequence of the prediction system in this embodiment. It is the flowchart which showed the process sequence of the prediction system in this embodiment. It is a figure which shows an example of the data stored in apparatus information DB in Embodiment 2. FIG. 6 is a flowchart illustrating a prediction system according to Embodiment 2. 10 is a block diagram showing a hardware group of a prediction device according to Embodiment 3. FIG. 10 is a functional block diagram of a prediction device according to Embodiment 3. FIG.

Embodiment 1
Hereinafter, the present embodiment will be described with reference to the drawings. FIG. 1 is a schematic diagram showing an outline of a prediction system. The prediction system shown in FIG. 1 includes an independent device 1, a connection device 2, and a prediction device 3. The connection device 2 and the prediction device 3 are connected to each other via a communication network N such as the Internet, a LAN (Local Area Network), or a mobile phone network. The connection device 2 includes a plurality of connection devices 2A, 2B, 2C, and the like, and transmits and receives information to and from the prediction device 3 via the communication network N.

  Below, the outline | summary of a prediction system is demonstrated. The independent device 1 is a device that operates independently from the communication network N, and is, for example, a computer or a power supply control device. The connection device 2 is a device connected to the communication network N, and is, for example, a computer or a power control device. The connection device 2 outputs various information such as operation time, temperature, or number of accesses to the prediction device 3. The independent device 1 and the connection device 2 in this embodiment are computers. The prediction device 3 is a device that monitors the state of the connection device 2 and predicts the time when the independent device 1 fails, and is, for example, a computer or a server computer. The prediction device 3 acquires various types of information from the connection device 2 and calculates the state of the independent device 1 based on the acquired various types of information.

  Details of the prediction system will be described below. FIG. 2 is a block diagram showing a hardware group of the independent device 1. The independent device 1 shown in FIG. 2 includes a CPU (Central Processing Unit) 11, a storage unit 12, a RAM 13, an input unit 14, and a display unit 15.

  The CPU 11 is connected to each part of hardware via a bus. The CPU 11 includes, for example, one or a plurality of CPUs or a multi-core CPU. The CPU 11 controls each part of the hardware according to the program 12P stored in the storage unit 12.

  The storage unit 12 is, for example, a hard disk or a large capacity memory. The storage unit 12 stores various data and programs 12P required when the CPU 11 performs processing.

  The RAM 13 is, for example, an SRAM (Static Random Access Memory), a DRAM (Dynamic Random Access Memory), a flash memory, or the like. The RAM 13 also functions as a storage unit, and temporarily stores various data generated when the CPU 11 executes various programs.

  The input unit 14 is an input device such as a mouse, a keyboard, or a touch panel, and outputs received operation information to the CPU 11. The display unit 15 is a liquid crystal display or an organic EL (Electro Luminescence) display.

  FIG. 3 is a block diagram illustrating a hardware group of the connection device 2. The connection device 2 illustrated in FIG. 3 includes a CPU 21, a storage unit 22, a RAM 23, an input unit 24, a display unit 25, a communication unit 26, and a time measuring unit 27. Since the operations and operations of the CPU 21, RAM 23, input unit 24 and display unit 25 of the connection device 2 are the same as the operations and operations of the CPU 11, RAM 13, input unit 14 and display unit 15 of the transmission device 1, description thereof is omitted.

  The storage unit 22 is, for example, an HDD (hard disk drive) or a large capacity memory. The storage unit 22 stores various data necessary for the CPU 21 to perform processing, a program 22P, and a connection information DB 221.

  The communication unit 26 is, for example, a wireless LAN card or a mobile phone communication module, and transmits / receives various information to / from the prediction device 3 via the communication network N. The time measuring unit 27 measures the date and time at the current time point, and outputs a time measurement result to the CPU 21 in accordance with a request from the CPU 21.

  FIG. 4 is a diagram illustrating an example of data stored in the connection information DB 221. The connection information DB 221 is a database that associates the connection device 2 with data related to the connection device 2. The connection information DB 221 includes a device name column, an introduction date column, a failure occurrence date column, a component information column, an elapsed time column, an operation time column, and the like. The name of the device is stored in the device name column. An introduction date indicating the date and time when the device is introduced is stored in the introduction date column. The failure occurrence date column stores the failure occurrence date indicating the date and time when the device failure occurred.

  Information on parts of the apparatus is stored in the part information column. The component is, for example, an HDD, a CPU, a RAM, a relay, or the like. The component information includes, for example, component temperature, HDD access count, HDD cache, memory usage rate, or relay operation count. The CPU 21 stores in advance the temperature of the parts, the number of HDD accesses, the HDD cache, the memory usage rate, or the number of relay operations in the storage unit 22 in advance. Alternatively, the CPU 21 may calculate the component temperature, the HDD access number, the HDD cache, the memory usage rate, or the number of relay operations by a calculation formula stored in the storage unit 22 in advance. The CPU 21 stores the calculated component temperature, HDD access count, HDD cache, memory usage rate, or relay operation count in the connection information DB 221. In addition, a component is not restricted to this embodiment, What is necessary is just the component in which the prediction apparatus 3 can preserve | save component information. Further, the component information is not limited to the present embodiment, and may be information regarding the component. The component information in this embodiment is the temperature of the HDD. For example, 30 is stored in the component information column. 30 indicates that the temperature of the HDD is 30 ° C.

  The elapsed time column stores an elapsed time indicating a time after the date and time when the apparatus is introduced. The operating time column stores an operating time indicating a time during which the apparatus has been operating since the date of introduction. Although the date is stored in the introduction date column and the failure occurrence date column of the connection information DB 221 in the present embodiment, time may be stored.

  The CPU 21 of the connection device 2 acquires various information such as the device name, introduction date, failure date, elapsed time, operation time, and component information of the connection device 2. The CPU 21 stores the acquired various information in the connection information DB 221. The introduction date string of the connection information DB 221 is stored in the storage unit 22 in advance.

  FIG. 5 is a block diagram illustrating a hardware group of the prediction device 3. The prediction device 3 illustrated in FIG. 5 includes a CPU 31, a storage unit 32, a RAM 33, an input unit 34, a display unit 35, a communication unit 36, and a time measuring unit 37. The operations and operations of the CPU 31, RAM 33, input unit 34, display unit 35, and timer unit 37 of the prediction device 3 are the same as the operations and operations of the CPU 21, RAM 23, input unit 24, display unit 25, and timer unit 27 of the connection device 2. Description is omitted because there are.

  The storage unit 32 is, for example, an HDD or a large capacity memory. The storage unit 32 stores various data required when the CPU 31 performs processing, a program 32P, and a device information DB 321.

  The communication unit 36 is, for example, a wireless LAN card or a mobile phone communication module, and transmits / receives various information to / from the connection device 2 via the communication network N.

  FIG. 6 is a diagram illustrating an example of data stored in the device information DB 321. The device information DB 321 is a database that associates the independent device 1 and the connection device 2 with various information. The device information DB 321 includes a device name column, an introduction date column, a failure occurrence date column, a component information column, an elapsed time column, an operation time column, and the like. The device name string introduction date column, failure occurrence date column, component information column, elapsed time column, and operation time column of the device information DB 321 are the device name column introduction date column, failure occurrence date column, component information column, elapsed time of the connection information DB 221. This is the same as the column and the operation time column, and the description is omitted for the sake of brevity.

  The CPU 31 acquires various information such as a device name, an introduction date, a failure occurrence date, an elapsed time, an operation time, and component information from the plurality of connection devices 2. The CPU 31 stores various information in the connection information DB 321. The CPU 31 acquires the current date and time at the time measuring unit 37. The CPU 31 reads the device information DB 321. The CPU 31 calculates the elapsed time of the independent device 1 by subtracting the introduction date from the current date. The CPU 31 stores the calculated elapsed time in the connection information DB 321. The device name string of the independent device 1 in the device information DB 321 is stored in advance. The component information sequence and the introduction date sequence associated with the independent device 1 in the device information DB 321 are stored in advance.

  The operation and operation of the prediction system in this embodiment will be described. The CPU 21 of the connection device 2 acquires various information such as the introduction date, failure date, elapsed time, operation time, and component information of the connection device 2.

  The CPU 21 stores the acquired various information in the connection information DB 221. The CPU 21 outputs various information to the prediction device 3. The CPU 31 acquires various types of information from the plurality of connection devices 2. The CPU 31 stores various information in the device information DB 321.

  The CPU 31 acquires the current date and time at the time measuring unit 37. The CPU 31 reads the device information DB 321. The CPU 31 calculates the elapsed time of the independent device 1 by subtracting the introduction date from the current date. The CPU 31 specifies the connection device 2 associated with the same component information as the component information associated with the independent device 1.

  The CPU 31 specifies the operating time and elapsed time of the specified connection device 2. The CPU 31 calculates a coefficient for calculating the operating time of the independent device 1 based on the specified operating time and elapsed time. For example, the CPU 31 calculates the coefficient by dividing the operating time by the elapsed time.

  Based on the failure occurrence date of the identified connection device 2, the CPU 31 identifies a failure time indicating the time from the date when the device in the connection device 2 was introduced to the date and time when the device failed. Specifically, the CPU 31 specifies the failure time of the connection device 2 by calculating the operation time until the specified failure date of the connection device 2.

  The CPU 31 calculates the operating time of the independent device 1 by adding the coefficient to the elapsed time of the independent device 1. CPU31 calculates the failure prediction time which estimated the time when the independent apparatus 1 fails based on failure time and operation time. Specifically, the failure prediction time is calculated by subtracting the operation time from the failure time. CPU31 displays on display part 35 based on failure prediction time, and ends processing.

  A specific operation and operation of the prediction system will be described with reference to the drawings. The CPU 21 of the connection device 2A has a device name “connection device 2A”, an introduction date “July 1, 2014”, a failure occurrence date “August 20, 2014”, part information “30”, an elapsed time “1200”, and an operation. Various information such as time “1000” is acquired. The CPU 21 of the connection device 2B has a device name “connection device 2B”, an introduction date “June 30, 2014”, a failure occurrence date “August 18, 2014”, component information “27”, an elapsed time “1248”, and an operation. Various information such as time “1048” is acquired.

  The CPU 21 of the connection device 2A stores various information in the connection information DB 221. The CPU 21 of the connection device 2B stores various information in the connection information DB 221. The CPU 21 of the connection device 2 </ b> A outputs various information to the prediction device 3. The CPU 21 of the connection device 2B outputs various information to the prediction device 3.

  The CPU 31 acquires various information from the connection devices 2A and 2B. The CPU 31 stores various information in the connection information DB 321 in association with the connection devices 2A and 2B.

  The CPU 31 acquires the current date and time “August 20, 2014” in the time measuring unit 37. The CPU 31 reads the device information DB 321. The CPU 31 calculates the elapsed time “600” of the independent device 1 by subtracting the introduction date “July 26, 2014” from the current date “August 20, 2014” and adding 24 hours to the subtracted value. The CPU 31 specifies the connection device 2A associated with the same component information “30” as the component information “30” associated with the independent device 1.

  The CPU 31 specifies the operation time “1000”, the elapsed time “1200”, and the failure occurrence date “August 20, 2014” of the specified connection device 2A. The CPU 31 calculates the coefficient “0.8333” by dividing the operating time “1000” by the elapsed time “1200”.

  The CPU 31 subtracts the introduction date “July 1, 2014” from the failure occurrence date “August 20, 2014” of the identified connection device 2A, and adds the subtracted value to 24 hours to obtain the failure time “1200”. Identify. The CPU 31 calculates the operating time “500” of the independent device 1 by adding the coefficient “0.8333” to the elapsed time “600” of the independent device 1. The CPU 31 calculates the failure prediction time “700” from the current date and time to the failure time by subtracting the operation time “500” from the failure time “1200”. The CPU 31 displays a message “The independent device 1 will fail in 700 hours” on the display unit 35 and ends the process.

  Next, a processing procedure of the prediction system will be described using a flowchart. 7 to 8 are flowcharts showing the processing procedure of the prediction system in the present embodiment. The CPU 21 of the connection device 2 acquires various information such as the device name, introduction date, failure occurrence date, component information, elapsed time, and operation time of the connection device 2 (step S1).

  CPU21 memorize | stores the acquired various information in connection information DB221 (step S2). CPU21 outputs various information to the prediction apparatus 3 (step S3). CPU31 acquires various information from the some connecting apparatus 2 (step S4). The CPU 31 stores various information in the device information DB 321 (step S5).

  The CPU 31 acquires the current date and time at the time measuring unit 37 (step S6). CPU31 reads apparatus information DB321 (step S7). The CPU 31 calculates the elapsed time of the independent device 1 by subtracting the introduction date from the current date (step S8). The CPU 31 identifies the connection device 2 associated with the same component information as the component information associated with the independent device 1 (step S9).

  The CPU 31 specifies the operating time, elapsed time, and failure occurrence date of the specified connection device 2 (step S10). The CPU 31 calculates a coefficient based on the specified operating time and elapsed time (step S11). For example, the CPU 31 calculates the coefficient by dividing the elapsed time by the operating time.

  The CPU 31 specifies the failure time of the connection device 2 based on the specified failure occurrence date of the connection device 2 (step S12). The CPU 31 calculates the operating time by adding the coefficient to the elapsed time of the independent device 1 (step S13). CPU31 calculates failure prediction time based on failure time and operation time (step S14). CPU31 displays on display part 35 based on failure prediction time (Step S15), and ends processing.

  According to the present embodiment, it is possible to predict a failure of the device for which it is difficult to acquire the energization time.

  According to the present embodiment, the operation time of the independent device 1 can be calculated by adding a coefficient to the elapsed time, and the failure prediction time can be calculated by subtracting the calculated operation time from the failure time. As a result, the failure prediction time of the independent device 1 can be calculated immediately.

  According to the present embodiment, a computer or a power control device is specified by specifying a device associated with the same component information as the component temperature, the HDD access count, the HDD cache, the memory usage rate, or the relay operation count. The prediction system can be applied to various devices such as.

  In this embodiment, the coefficient is calculated based on the operation time and the elapsed time. However, the CPU 11 may calculate the failure occurrence time based on the component information, and may calculate the coefficient based on the calculated failure occurrence time and elapsed time. . Specifically, the CPU 11 calculates a failure occurrence time by substituting component information into the Arrhenius model using the Arrhenius model, and calculates a coefficient by dividing the calculated failure occurrence time by the elapsed time. In the present embodiment, the failure time is calculated, but the failure probability may be calculated.

Embodiment 2
FIG. 9 is a diagram illustrating an example of data stored in the device information DB 321 according to the second embodiment. In the following, the configuration and operation other than those specifically described are the same as those of the first embodiment, and the description is omitted for the sake of brevity. The operation and operation of the prediction system in this embodiment will be described. The CPU 31 determines whether there is a connection device 2 associated with the same component information as the component information of the independent device 1. When the CPU 31 determines that there is no connection device 2 associated with the same component information as that of the independent device 1, the CPU 31 specifies a plurality of connection devices 2 at random.

  The CPU 31 specifies the operation time, elapsed time, and failure occurrence date of the plurality of connection devices 2. The CPU 31 calculates a coefficient based on the operating time and elapsed time of the specified plurality of connection devices 2. Specifically, the CPU 31 calculates an individual coefficient for calculating a coefficient by dividing each of a plurality of specified elapsed times by each of a plurality of operating times, and calculates an average value of the calculated individual coefficients. Calculate the coefficient. The CPU 31 specifies a plurality of failure times based on a plurality of failure occurrence dates. The CPU 31 calculates one failure time based on the plurality of failure times. Hereinafter, it is the same as that of Embodiment 1, and description is abbreviate | omitted for brevity.

  A specific operation and operation of the prediction system will be described with reference to FIG. The CPU 31 determines that there is no connection device 2 associated with the same component information as the component information “30” associated with the independent device 1. The CPU 31 specifies the connection devices 2A and 2B. The CPU 31 displays the elapsed time “1200”, the operation time “1000” and the failure occurrence date “August 20, 2014” of the connection device 2A, and the elapsed time “1248”, the operation time “1048” and the failure occurrence date “of the connection device 2B”. “August 18, 2014” is specified.

  The CPU 31 calculates the individual coefficient “0.8333” by dividing the operating time “1000” by the elapsed time “1200”. The CPU 31 calculates the individual coefficient “0.8397” by dividing the operating time “1048” by the elapsed time “1248”. The CPU 31 calculates the coefficient “0.8365” by calculating the average value of the individual coefficient “0.8333” and the individual coefficient “0.8397”.

  The CPU 31 subtracts the introduction date “July 1, 2014” from the failure occurrence date “August 20, 2014” of the identified connection device 2A, and adds the subtracted value to 24 hours to obtain the failure time “1200”. Identify. The CPU 31 subtracts the introduction date “June 30, 2014” from the failure occurrence date “August 18, 2014” of the identified connection device 2B, and adds the subtracted value to 24 hours to obtain the failure time “1176”. Identify.

  The CPU 31 calculates one failure time “1188” by calculating an average value of the failure time “1176” and the failure time “1200”. The CPU 31 calculates the failure prediction time using the calculated one failure time in the same manner as in the first embodiment. Hereinafter, it is the same as that of Embodiment 1, and description is abbreviate | omitted for brevity.

  FIG. 10 is a flowchart showing the prediction system according to the second embodiment. Since the process of step S1-15 is the same as that of the prediction system which concerns on the above-mentioned Embodiment 1, description is abbreviate | omitted for brevity. After completing the process of step S8, the CPU 31 determines whether there is a connection device 2 associated with the same component information as the component information associated with the independent device 1 (step S21). If the CPU 31 determines that there is a connection device 2 associated with the same component information as the component information associated with the independent device 1 (step S21: YES), the process proceeds to step S9. When the CPU 31 determines that there is no connection device 2 associated with the same component information as that associated with the independent device 1 (step S21: NO), the CPU 31 specifies a plurality of connection devices 2 at random (step S21). S22).

  The CPU 31 specifies the operation time, elapsed time, and failure date of the plurality of connection devices 2 (step S23). The CPU 31 calculates an individual coefficient for calculating a coefficient based on the operating time and elapsed time of the specified plurality of connection devices 2 (step S24). Specifically, the CPU 31 calculates the individual coefficient by dividing each of the plurality of specified elapsed times by each of the plurality of operating times. The CPU 31 calculates a coefficient based on the individual coefficient (step S25). Specifically, the CPU 31 calculates a coefficient by calculating an average value of the calculated individual coefficients.

  The CPU 31 specifies a plurality of failure times based on a plurality of failure occurrence dates (step S26). The CPU 31 calculates one failure time based on the plurality of failure times (step S27), and moves the process to step S13. Specifically, the CPU 31 calculates one failure time by calculating an average value of a plurality of failure times, and moves the process to step S13.

  In this embodiment, the coefficient is calculated by calculating the average value of the individual coefficients, but the coefficient calculation method is not limited to this embodiment. For example, the CPU 31 may calculate a coefficient by calculating a median value of a plurality of individual coefficients. In the present embodiment, one failure time is calculated by calculating the average value of the failure times, but the coefficient calculation method is not limited to this embodiment. For example, the CPU 31 may calculate one failure time by calculating a median value of a plurality of failure times.

  According to this embodiment, even when the CPU 31 cannot identify the same component information as the component information associated with the independent device 1, it is possible to predict a failure of the device.

  According to the present embodiment, the coefficient is calculated by calculating the average value of the individual coefficients. Thereby, the failure prediction time of the independent device 1 can be calculated immediately.

  According to this embodiment, the coefficient is calculated by calculating the median value of the individual coefficients. This makes it possible to calculate a failure prediction time with a high probability even when a part of failure time includes a value significantly different from other failure times due to a sudden accident or a user error.

Embodiment 3
Embodiment 3 of the present invention will be described below in detail with reference to the drawings showing the embodiment. FIG. 11 is a block diagram illustrating a hardware group of the prediction device 3 according to the third embodiment. In the following, the configuration and operation other than those specifically described are the same as those of the second embodiment, and the description is omitted for the sake of brevity.

  A program for operating the prediction device 3 includes a portable recording medium 38A such as a CD-ROM, a DVD (Digital Versatile Disc) disk, a memory card, or a USB (Universal Serial Bus) memory in a reading unit 38 such as a disk drive. You may read and memorize | store in the memory | storage part 32. FIG. Further, a semiconductor memory 38B such as a flash memory storing the program may be mounted in the prediction device 3. The program can be downloaded from another server (not shown) connected by the communication unit 36 via the communication network N such as the Internet. The contents will be described below.

  The prediction device 3 shown in FIG. 11 reads a program for executing the above-described various software processes from the portable recording medium 38A or the semiconductor memory 38B or downloads it from another server (not shown) via the communication network N. To do. The program is installed as a program 32P, loaded into the storage unit 32, and executed. This functions as the prediction device 3 described above.

  FIG. 12 is a functional block diagram of the prediction device 3 according to the third embodiment. When the CPU 31 executes the program 32P, the prediction device 3 operates as follows. The specifying unit 31A associates the independent device 1 or the plurality of connection devices 2 with the component information of the independent device 1 or the plurality of connection devices 2, and associates the same component information with the component information associated with the independent device 1. One connected device 2 is identified from the plurality of connection devices 2. The time specifying unit 31B indicates the operation time indicating the time that the connection device 2 has been operating from the date and time when the connection device 2 was introduced in the specified one connection device 2, and the elapsed time indicating the time that has elapsed since the date and time when the connection device 2 was introduced. The time and the failure time indicating the time from the date and time when the connection device 2 is introduced to the date and time when the connection device 2 fails are specified. The calculation unit 31C calculates a coefficient for calculating the operating time of the independent device 1 based on the specified operating time and elapsed time. The time calculation unit 31D calculates the operating time of the independent device 1 based on the calculated coefficient and the elapsed time of the independent device 1. The predicted time calculation unit 31E calculates a predicted failure time in which the time at which the independent device 1 fails is predicted based on the calculated operation time and failure time of the independent device 1.

Regarding the above embodiment, the following additional notes are disclosed.
(Appendix 1)
A program used for a prediction device that predicts a time when an independent device that is independent from a communication network fails, and that connects to a plurality of connection devices connected to the communication network,
In the prediction device,
Same as the information on the parts associated with the independent device from the correspondence between the independent device and the information on the parts of the independent device and the correspondence between the plurality of connection devices and the information on the parts of the plurality of connection devices. Identifying one connection device associated with the information of the plurality of connection devices,
Identified from the date and time when the identified one connected device was introduced, the operating time indicating the time that the identified one connected device was operating, the elapsed time indicating the time after the introduced date and time, and the date and time of introduction A failure time indicating the time until the date and time when one connected device fails,
Calculate a coefficient for calculating the operating time of the independent device based on the specified operating time and elapsed time,
Calculate the operation time of the independent device based on the calculated coefficient and the elapsed time of the independent device,
A program for executing a process of calculating a failure prediction time for predicting a failure time of the independent device based on the calculated operation time of the independent device and the failure time.
(Appendix 2)
The coefficient is a value obtained by dividing the specified operation time by the specified elapsed time,
The operating time of the independent device is a value obtained by adding the elapsed time of the independent device to the coefficient,
The program according to appendix 1, wherein the failure prediction time is a value obtained by subtracting an operation time of the independent device from the failure time.
(Appendix 3)
Determining whether or not the plurality of connection devices are associated with the same component information as the component information associated with the independent device;
When it is determined that the plurality of connection devices are not associated with the same component information as the component information associated with the independent device, a part or all of the plurality of connection devices is specified at random,
Identify each operating time, elapsed time, and failure time in some or all of the specified connected devices,
Calculating a plurality of individual coefficients for calculating the coefficient based on each specified operating time and elapsed time;
Calculate the coefficient based on the calculated multiple individual coefficients,
The program according to supplementary note 1 or supplementary note 2, wherein one failure time is calculated based on the plurality of failure times.
(Appendix 4)
The individual coefficient is a value obtained by dividing the specified operation time by the specified elapsed time,
The coefficient is an average value of the plurality of individual coefficients,
The program according to appendix 3, wherein the one failure time is an average value of the plurality of failure times.
(Appendix 5)
The individual coefficient is a value obtained by dividing the specified operation time by the specified elapsed time,
The coefficient is a median value of the plurality of individual coefficients,
The program according to appendix 3, wherein the one failure time is a median value of the plurality of failure times.
(Appendix 6)
The program according to any one of appendix 1 to appendix 5, wherein the component information is a component temperature, an HDD access count, an HDD cache, a memory usage rate, or a relay operation count.
(Appendix 7)
A prediction device that predicts a time when an independent device independent from a communication network fails and connects to a plurality of connection devices connected to the communication network,
Same as the information on the parts associated with the independent device from the correspondence between the independent device and the information on the parts of the independent device and the correspondence between the plurality of connection devices and the information on the parts of the plurality of connection devices. A specific unit that identifies one connection device associated with information of the plurality of connection devices;
After the date and time when the one connection device specified by the specifying unit is introduced, the operation time indicating the time when the one connection device specified by the specification unit is operating, and the elapsed time indicating the time after the introduction date and time, A time specifying unit for specifying a failure time indicating a time from the date and time of introduction to the date and time when the one connected device that has been specified fails; and
A calculating unit that calculates a coefficient for calculating the operating time of the independent device based on the operating time and the elapsed time specified by the time specifying unit;
A time calculation unit for calculating the operation time of the independent device based on the coefficient calculated by the calculation unit and the elapsed time of the independent device;
A prediction device comprising: a prediction time calculation unit that calculates a failure prediction time for predicting a time at which the independent device fails based on the operation time of the independent device calculated by the time calculation unit and the failure time.
(Appendix 8)
A prediction method in a prediction device that predicts a time when an independent device that is independent from a communication network fails, and connects to a plurality of connection devices that are connected to the communication network,
In the prediction device,
Same as the information on the parts associated with the independent device from the correspondence between the independent device and the information on the parts of the independent device and the correspondence between the plurality of connection devices and the information on the parts of the plurality of connection devices. Identifying one connection device associated with the information of the plurality of connection devices,
Identified from the date and time when the identified one connected device was introduced, the operating time indicating the time that the identified one connected device was operating, the elapsed time indicating the time after the introduced date and time, and the date and time of introduction A failure time indicating the time until the date and time when one connected device fails,
Calculate a coefficient for calculating the operating time of the independent device based on the specified operating time and elapsed time,
Calculate the operation time of the independent device based on the calculated coefficient and the elapsed time of the independent device,
A prediction method for executing a process of calculating a failure prediction time for predicting a time at which the independent device fails based on the calculated operation time of the independent device and the failure time.

  The embodiment disclosed this time is to be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the meanings described above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

1 Independent Device 2 Connection Device 3 Prediction Device 32P Program 221 Connection Information DB
321 Operation information DB

Claims (5)

A program used for a prediction device that predicts a time when an independent device that is independent from a communication network fails, and that connects to a plurality of connection devices connected to the communication network,
In the prediction device,
Same as the information on the parts associated with the independent device from the correspondence between the independent device and the information on the parts of the independent device and the correspondence between the plurality of connection devices and the information on the parts of the plurality of connection devices. Identifying one connection device associated with the information of the plurality of connection devices,
Identified from the date and time when the identified one connected device was introduced, the operating time indicating the time that the identified one connected device was operating, the elapsed time indicating the time after the introduced date and time, and the date and time of introduction A failure time indicating the time until the date and time when one connected device fails,
Calculate a coefficient for calculating the operating time of the independent device based on the specified operating time and elapsed time,
Calculate the operation time of the independent device based on the calculated coefficient and the elapsed time of the independent device,
A program for executing a process of calculating a failure prediction time for predicting a failure time of the independent device based on the calculated operation time of the independent device and the failure time. The coefficient is a value obtained by dividing the specified operation time by the specified elapsed time,
The operating time of the independent device is a value obtained by adding the elapsed time of the independent device to the coefficient,
The program according to claim 1, wherein the failure prediction time is a value obtained by subtracting an operation time of the independent device from the failure time. Determining whether or not the plurality of connection devices are associated with the same component information as the component information associated with the independent device;
When it is determined that the plurality of connection devices are not associated with the same component information as the component information associated with the independent device, a part or all of the plurality of connection devices is specified at random,
Identify each operating time, elapsed time, and failure time in some or all of the specified connected devices,
Calculating a plurality of individual coefficients for calculating the coefficient based on each specified operating time and elapsed time;
Calculate the coefficient based on the calculated multiple individual coefficients,
The program according to claim 1, wherein one failure time is calculated based on the plurality of failure times. A prediction device that predicts a time when an independent device independent from a communication network fails and connects to a plurality of connection devices connected to the communication network,
Same as the information on the parts associated with the independent device from the correspondence between the independent device and the information on the parts of the independent device and the correspondence between the plurality of connection devices and the information on the parts of the plurality of connection devices. A specific unit that identifies one connection device associated with information of the plurality of connection devices;
After the date and time when the one connection device specified by the specifying unit is introduced, the operation time indicating the time when the one connection device specified by the specification unit is operating, and the elapsed time indicating the time after the introduction date and time, A time specifying unit for specifying a failure time indicating a time from the date and time of introduction to the date and time when the one connected device that has been specified fails; and
A calculating unit that calculates a coefficient for calculating the operating time of the independent device based on the operating time and the elapsed time specified by the time specifying unit;
A time calculation unit for calculating the operation time of the independent device based on the coefficient calculated by the calculation unit and the elapsed time of the independent device;
A prediction device comprising: a prediction time calculation unit that calculates a failure prediction time for predicting a time at which the independent device fails based on the operation time of the independent device calculated by the time calculation unit and the failure time. A prediction method in a prediction device that predicts a time when an independent device that is independent from a communication network fails, and connects to a plurality of connection devices that are connected to the communication network,
In the prediction device,
Same as the information on the parts associated with the independent device from the correspondence between the independent device and the information on the parts of the independent device and the correspondence between the plurality of connection devices and the information on the parts of the plurality of connection devices. Identifying one connection device associated with the information of the plurality of connection devices,
Identified from the date and time when the identified one connected device was introduced, the operating time indicating the time that the identified one connected device was operating, the elapsed time indicating the time after the introduced date and time, and the date and time of introduction A failure time indicating the time until the date and time when one connected device fails,
Calculate a coefficient for calculating the operating time of the independent device based on the specified operating time and elapsed time,
Calculate the operation time of the independent device based on the calculated coefficient and the elapsed time of the independent device,
A prediction method for executing a process of calculating a failure prediction time for predicting a time at which the independent device fails based on the calculated operation time of the independent device and the failure time.

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