JP2003233688A - Obstacle occurrence prediction apparatus, obstacle occurrence prediction method and storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To detect potential obstacle occurrence by specifying an obstacle part from the maintenance history information and part composition information of an apparatus, and predicting an obstacle occurrence tendency. <P>SOLUTION: A maintenance subject part group specification part 11 specifies the maintenance subject part group set as the subject of preventive maintenance and post maintenance from the maintenance history information of a maintenance history information management part 7, and the part composition information of a part composition information management part 6. An obstacle occurrence tendency predicting part 12 predicts the obstacle occurrence tendency in every operation state of the maintenance subject part group by applying a statistical method for every maintenance history information which is classified by the operation history information of an operation history of an operation history information management part 8 to the specified maintenance subject part group. A comparing part 13 detects potential obstacle occurrence from the predicted result and the obstacle occurrence predicting information in every operation state of every component composed of the obstacle part managed by an obstacle occurrence prediction information management part 10. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a failure occurrence prediction device for equipment, a failure occurrence prediction method, and a storage medium storing a processing program thereof.

[0002]

2. Description of the Related Art Computers, electronic devices, and the like have a risk of initial failure when a new product is put on the market. It is necessary to quickly detect and monitor the failure occurrence tendency in the market for these various types of equipment. As an analysis method for monitoring the failure occurrence tendency of this equipment in the market, the ratio of the number of occurrences of failure to the number of operating equipment in the market is calculated, and if this failure rate exceeds the preset value, there is a large tendency for failure Has been adopted. However, even if the failure rate does not exceed the default value for the entire device, there are cases where failures due to specific failure modes or failed parts are on the rise, and it is necessary to grasp these trends early to improve device reliability. There is.

[0003] In order to identify a faulty part in this device and predict a fault occurrence tendency at an early stage, for example, Japanese Patent Laid-Open No. 7-26
As disclosed in Japanese Patent No. 2056, a failure occurrence tendency monitoring device that semi-automatically identifies failure areas from a field work record created by a computer maintenance worker, and monitors and analyzes future failure occurrence trends for each failure area is disclosed. Has been done.

[0004]

However, since the failure site is specified from the phenomenon name input by the maintenance worker, there is a drawback that the range of failure site specification is limited by variations in the phenomenon name. On the other hand, when predicting the failure occurrence tendency of each part from the maintenance data without specifying the failure part, whether the maintenance is due to the failure of that part or the secondary maintenance due to the failure of other parts, etc. There is a disadvantage that the discrimination becomes complicated. In addition, in the case of a device that affects the failure occurrence tendency depending on the operating state and usage method of the device, there is a disadvantage that it is not possible to accurately predict the failure occurrence tendency only by monitoring the failure occurrence tendency for each failure part. is there.

The present invention solves the above disadvantages by specifying a faulty part from equipment maintenance history information and component configuration information, and using a statistical method based on the maintenance history information for each operating state for the specified faulty part. By applying, predict the failure occurrence tendency,
A failure occurrence prediction device capable of detecting a potential failure occurrence from failure occurrence prediction information in each operating state of each part configured of a failure part, a failure occurrence prediction method, and a storage medium storing a processing program thereof. It is intended to be provided.

[0006]

A failure occurrence prediction apparatus according to the present invention stores maintenance history information management means for managing maintenance information generated by preventive maintenance and subsequent maintenance in the equipment market, and operation information of the equipment. An operation history information managing unit for managing, a component configuration information managing unit for managing component configuration information of the device, and a maintenance target component group that is a target of preventive maintenance and post-maintenance based on the maintenance history information and the component configuration information. The maintenance target component group specifying means and the maintenance target component group specified by the maintenance target component group specifying means are subjected to a statistical method for each maintenance history information stratified by the operation history information to perform the maintenance target component group. And a failure occurrence tendency predicting means for predicting a failure occurrence tendency in each operating state.

A second failure occurrence predicting apparatus according to the present invention is a maintenance history information managing means for managing maintenance information generated by preventive maintenance and a subsequent maintenance in an equipment market, and an operation for managing operation information of the equipment. History information management means,
A component configuration information management unit that manages the component configuration information of the device, a failure occurrence prediction information management unit that manages failure occurrence prediction information for each component of the device for each operating state of the device, the maintenance history information and the parts Based on the configuration information, the maintenance target parts group specifying means for specifying the maintenance target parts group subjected to the preventive maintenance and the subsequent maintenance, and the operation history information for the maintenance target parts group specified by the maintenance target parts group specifying means The failure occurrence tendency prediction means for predicting the failure occurrence tendency in each operating state of the maintenance target parts group by applying the statistical method for each layered maintenance history information and the maintenance target parts group predicted by the failure occurrence tendency prediction means There is a possibility that a failure may occur depending on the comparison means for comparing the failure occurrence prediction result with the failure occurrence prediction information managed by the failure occurrence prediction information management means and the comparison result of the comparison means. Characterized in that if with an alarm detecting means for determining whether.

The failure occurrence tendency predicting means uses cumulative hazard analysis as a statistical method, and the comparing means compares the unreliability functions of the results of the cumulative hazard analysis.

Another failure occurrence predicting apparatus according to the present invention is
The storage device includes a storage device and a central processing unit, and the storage device includes a maintenance history information management unit that manages maintenance information generated by preventive maintenance and subsequent maintenance in the equipment market, and an operation history that manages the operation information of the equipment. An information management unit, a component configuration information management unit that manages the component configuration information of the device, and a failure occurrence prediction information management unit that manages failure occurrence prediction information for each component that constitutes the device for each operating state of the device. Then, the central processing unit identifies the maintenance target component group that is the target of preventive maintenance and subsequent maintenance from the maintenance history information and the component configuration information, and classifies the identified maintenance target component group by the operation history information. A statistical method is applied to each of the separated maintenance history information to predict the failure occurrence tendency of each maintenance target component group in each operating state, and the predicted failure occurrence prediction result and failure occurrence prediction of the maintenance target component group By comparing the predicted error occurrence information managed by multicast management unit and judging whether failure may occur.

The failure occurrence predicting method according to the present invention specifies a maintenance target part group which is a target of preventive maintenance and post-maintenance based on the maintenance history information of the device and the part configuration information stored in advance, and specifies the specified maintenance. A statistical method is applied to each maintenance history information that is stratified by the operation history information for the target component group to predict the failure occurrence tendency in each operating state of the maintenance target component group, and the predicted failure occurrence of the maintenance target component group It is characterized in that whether or not there is a possibility of a failure is determined by comparing the prediction result with failure occurrence prediction information for each component that makes up the device, which is stored in advance for each operating state of the device.

The processing program of this failure occurrence prediction method is stored in a computer-readable storage medium to improve versatility.

[0012]

1 is a block diagram showing the structure of a failure occurrence predicting apparatus of the present invention. As shown in the figure, the failure occurrence prediction device 1 has an input device 2, a storage device 3, a processing device 4, and an output device 5. The input device 2 inputs information on each device that predicts the occurrence of a failure.

The storage device 3 has a parts configuration information management unit 6, a maintenance history information management unit 7, an operation history management unit 8, a device manufacturing information management unit 9, and a failure occurrence prediction information management unit 10. The component configuration information management unit 6 manages the configuration information of each component that constitutes each device that predicts the occurrence of a failure, and mainly includes connection information between components. Maintenance history information management unit 7
Manages historical information on preventive maintenance and post maintenance by equipment maintenance workers in the market. The data items to be managed include a maintenance history record ID, a model, a device ID, a maintenance date, a failure occurrence date, a phenomenon that occurred, a maintenance result, a maintenance target part, and the like. The operation history management unit 8 manages operation information of each device. The device manufacturing information management unit 9 manages the manufacturing information of each device, and stores information such as the manufacturing date of each device. The failure occurrence prediction information management unit 10 manages failure occurrence prediction information for each individual component according to the operating state of each device, which is represented in advance by an unreliability function.

The processing device 4 includes a maintenance target component group specifying unit 11
It has a failure occurrence tendency prediction unit 12, a comparison unit 13, and an alarm detection unit 14. The maintenance target component group identification unit 11 identifies the maintenance target component from the maintenance target component information in the maintenance history information managed by the maintenance history information management unit 7 and the information managed by the component configuration information management unit 6. The failure occurrence tendency prediction unit 12 layers the maintenance history information managed by the maintenance history information management unit 7 with the information of the operation history information management unit 8 for the maintenance target component identification group identified by the maintenance target component group identification unit 11. Then, the life distribution (unreliability function) is obtained for each maintenance target component group for each operating state by cumulative hazard analysis using the stratified information as input information. The comparison unit 13 compares the unreliability function for each maintenance target component group for each operating state predicted by the failure occurrence tendency prediction unit 12 and the unreliability function for each individual component managed by the failure occurrence prediction information management unit 10. A comparison is made for each life distribution parameter. As a result of the comparison of the life distribution parameters in the comparison unit 13, the alarm detection unit 14 compares the failure occurrence prediction result of the maintenance target component group with the failure occurrence prediction information of each operation status-based component corresponding to each component of the maintenance target component group. If none of the above applies, the alarm information is output to the output device 5 as a display device or a printing device.

Fault occurrence predicting apparatus 1 configured as described above
FIG. 2A schematically shows the component configuration information of the device managed by the component configuration information management unit 6 of FIG. The maintenance target component group 21 is hierarchically configured of components P1 to P7, and the maintenance target component group 22
Indicates that the parts P8 to P14 are hierarchically configured, and indicates the influence range of a failure in each of the parts P1 to P14. For example, as shown in FIG. 2B, in the maintenance history information,
If there is information that the parts P1, P2, P3, P10, and P14 have been maintained, by using the part configuration information of FIG.
1, P2, P3 constitute a first maintenance target component group and components P10, P14 constitute a second maintenance target component group.

FIG. 3 shows an unreliability function for each operating state of the equipment of the maintenance target component group predicted by the failure occurrence tendency prediction unit 12 in the comparison unit 13 and an operating state corresponding to each component of the maintenance target component group. It shows how the unreliability function, which is the failure occurrence prediction information for each different component, is compared. Figure 3
(A) and (b) are schematic representations of the individual unreliability functions of the respective parts P1, P2, P3 that make up the first maintenance target part group. This information is obtained in advance by technical research and testing, and is managed for each operating state of the equipment.

FIG. 3 (c) shows a failure occurrence tendency for the first maintenance target part group composed of parts P1, P2 and P3, using the maintenance history information stratified by the operating state 1 of the equipment as input information. The result of accumulative hazard analysis performed by the prediction unit 12 to obtain an unreliability function is schematically represented. Similarly, FIG. 3E is a schematic diagram showing a result of obtaining an unreliability function by performing cumulative hazard analysis in the failure occurrence tendency prediction unit 12 using the maintenance history information stratified by the operating state 2 of the device as input information. It is an expression. The horizontal axis represents the number of times the device has been operated or the power-on time of the device, and the vertical axis represents the degree of unreliability. The failure occurrence tendency can be predicted by the shape parameter m obtained as a result of this cumulative hazard analysis. That is, when the shape parameter m is 1, it indicates a random failure type, when the shape parameter m is greater than 1, it indicates an abrasion failure type, and when the shape parameter m is less than 1, it indicates an initial failure type.

In the comparison unit 13, for example, the information in FIG. 3D in the operating state 2 and the information in FIG.
The comparison with the individual information in (b) is performed using the shape parameter m. That is, the shape parameter m in FIG.
Originally, p123-2 should be a value close to any of the shape parameters mp1-2, mp2-2, and mp3-2 shown in FIG. Therefore, the values of each shape parameter mp1-2, mp2-2, mp3-2 are compared,
If a value close to any of the shape parameters is shown, it is determined that the result is as expected in advance and that the result is normal, and if not, an alarm is issued.

The operation of the fault occurrence predicting apparatus 1 will be described with reference to the flowchart of FIG. First, the maintenance target component group identification unit 11 acquires one record of maintenance history information from the maintenance history information management unit 7 (step S1), and generates a maintenance target component list from the acquired maintenance history record (step S2). In the case of the example shown in FIG.
A maintenance target part list including 1, P2, P3, P10, and P14 is generated. Next, the maintenance target parts group identification unit 11
Group the maintenance target parts list as a maintenance target parts group based on the parts configuration information managed by the parts configuration information management unit 6 (step S3). That is, in the example of FIG.
By using the component configuration information in (a), the maintenance target component group includes a first maintenance target component group including the components P1, P2, and P3 and a second maintenance target component including the components P10 and P14. Become a group. Then, the grouped maintenance target component group list information is primarily stored together with the maintenance history record ID and the device ID on which the maintenance is performed (step S4). This step S1 to step S4
By performing the process up to all records,
In the example of the first maintenance target part group, the data shown in FIG. 5A is temporarily stored (step S5).

The failure occurrence tendency predicting unit 12 stratifies all the maintenance history records in the maintenance target parts group that are temporarily stored for each operating state according to the operating history information managed by the operating history information managing unit 8 based on the device ID. (Step S
6). As a result of stratification, a maintenance history record is managed for each operating state as shown in FIG. Next, the failure occurrence tendency prediction unit 12 performs cumulative hazard analysis using the maintenance history information stratified for each operating state for each protection target component group (step S7). As the result information of the cumulative hazard analysis, in the example of FIG. 5B, the unreliability function is obtained for each of the operating state 1 and the operating state 2. The comparison unit 13 compares the obtained unreliability function and the unreliability function that is the failure occurrence prediction information for each component in each operating state that constitutes the maintenance target component group managed by the failure occurrence prediction information management unit 10. A comparison is made (step S8). This unreliability function comparison is shown in FIG.
As in the example shown by, the comparison is performed by comparing the shape parameter m of the unreliability function according to the operating state. Shape parameter m
The shape parameters obtained for the maintenance target component group are compared with the shape parameters of the respective components constituting the maintenance target component group, and as a result of this comparison, if none of them show a close value (step S9), The alarm detection unit 14 outputs the alarm information because the unexpected failure may occur (step S10). The processing from step S6 to step S9 is performed for all maintenance target component groups stratified by the operating state (step S11).

This series of processes can also be performed on a manufacturing month basis using information on the manufacturing month of the device managed by the device manufacturing information management section 9.

In the above description, the maintenance target component group specifying section 11, the failure occurrence tendency predicting section 12, the comparing section 13, and the alarm detecting section 14 provided in the processing unit 4 of the failure occurrence predicting apparatus 1 are stored in the storage device 3. Although the case has been described in which various processes are performed using each management information to predict the failure occurrence tendency, as shown in the block diagram of FIG.
1. Various processing programs executed by the failure occurrence tendency prediction unit 12, the comparison unit 13, and the alarm detection unit 14 are stored in an external storage medium 16 such as a magnetic memory or an optical memory, and the central processing unit 15 of the failure occurrence prediction device 1a stores the programs. The processing program stored in the external storage medium 16 is input / output interface 17
Alternatively, the central processing unit 15 may perform various processes by using the management information stored in the storage device 3 to predict the failure occurrence tendency. By thus performing various processes in the central processing unit 15 and predicting the failure occurrence tendency, the failure occurrence tendency can be predicted by using a general-purpose computer, and the failure occurrence tendency can be easily predicted.

[0023]

As described above, according to the present invention, the failure site is specified from the maintenance history information of the device and the component configuration information, and the failure site is not specified from the failure phenomenon. It is possible to specify the failure part without being affected by the contents, and to acquire information for predicting a potential failure occurrence tendency in each operating state of the device for the failure part.

Further, the failure portion is specified from the maintenance history information of the device and the component configuration information, and the failure occurrence tendency is predicted by applying a statistical method to the specified failure portion based on the maintenance history information for each operating state. Then, by detecting a potential failure occurrence from the predicted result and the failure occurrence prediction information in each operating state for each part configured of the failure part, the failure occurrence tendency of the device can be accurately predicted. .

Furthermore, in order to predict the failure occurrence tendency,
By using cumulative hazard analysis as a statistical method and comparing the unreliability functions of the results of cumulative hazard analysis,
The failure occurrence prediction can be performed based on the device life distribution prediction information, and the failure occurrence prediction for each component can be efficiently performed.

Further, the failure occurrence prediction of the device can be performed with a simple structure by performing the failure occurrence prediction of the device in the central processing unit using a preset processing program.

Further, the versatility can be enhanced by storing the processing program of the failure occurrence prediction method in a computer-readable storage medium.

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of a failure occurrence prediction device of the present invention.

FIG. 2 is a schematic diagram showing component configuration information of a device.

FIG. 3 is a schematic diagram showing an unreliability function for each operating state of a device.

FIG. 4 is a flowchart showing a failure occurrence prediction process.

FIG. 5 is an explanatory diagram showing grouped maintenance target component group list information.

FIG. 6 is a block diagram showing the configuration of another failure occurrence prediction device.

[Explanation of symbols]

1; failure occurrence prediction device, 2; input device, 3; storage device,
4; processing device, 5; output device, 6; parts configuration information management unit, 7; maintenance history information management unit, 8; operation history management unit,
9: Device manufacturing information management unit, 10; Failure occurrence prediction information management unit, 11; Maintenance target component group specifying unit, 12; Failure occurrence tendency prediction unit, 13; Comparison unit, 14; Alarm detection unit, 15;
Central processing unit, 16; external storage medium, 17; input / output interface.

Claims (6)

[Claims] 1. A maintenance history information management unit that manages maintenance information generated by preventive maintenance and a subsequent maintenance in a device market, an operation history information management unit that manages operation information of the device, and a component configuration of the device. A component configuration information management unit that manages information, a maintenance target component group identification unit that identifies a maintenance target component group that has been subject to preventive maintenance and subsequent maintenance from the maintenance history information and the component configuration information, and a maintenance target component group A failure occurrence tendency that predicts the failure occurrence tendency in each operating state of the maintenance target component group by applying a statistical method to each maintenance history information stratified by the operation history information for the maintenance target component group specified by the specifying means A failure occurrence prediction apparatus comprising: a prediction unit. 2. A maintenance history information management unit that manages maintenance information generated by preventive maintenance and a subsequent maintenance in a device market, an operation history information management unit that manages operation information of the device, and a component configuration of the device. A component configuration information management unit that manages information, a failure occurrence prediction information management unit that manages failure occurrence prediction information for each component that constitutes a device for each operating state of the device, and prevention from the maintenance history information and the component configuration information Maintenance target component group identification means for identifying the maintenance target component group subject to maintenance and post-maintenance, and maintenance for the maintenance target component group identified by the maintenance target component group identification means based on operation history information A statistical method is applied to each piece of history information, and a failure occurrence tendency prediction means for predicting the failure occurrence tendency in each operating state of the maintenance target parts group and a failure occurrence tendency prediction means are used for prediction. A comparison unit that compares the failure occurrence prediction result of the maintenance target component group with the failure occurrence prediction information managed by the failure occurrence prediction information management unit and the comparison result of the comparison unit determines whether a failure may occur. A failure occurrence predicting device, comprising: 3. The failure occurrence prediction apparatus according to claim 2, wherein the failure occurrence tendency prediction means uses cumulative hazard analysis as a statistical method, and the comparison means compares the unreliability functions of the results of the cumulative hazard analysis. 4. A maintenance history information management means for managing maintenance information generated by preventive maintenance and post-maintenance maintenance in a device market, the storage device having a storage device and a central processing unit, and operation information of the device. Operation history information management means for managing the device, component configuration information management means for managing the component configuration information of the device, and failure occurrence prediction information for managing failure occurrence prediction information for each component of the device for each operating state of the device. The central processing unit has a management means, identifies a maintenance target component group that is the target of preventive maintenance and subsequent maintenance from the maintenance history information and component configuration information, and identifies the maintenance target component group. A statistical method is applied to each maintenance history information stratified by the operation history information to predict the failure occurrence tendency of each maintenance target component group in each operating state, and the predicted failure occurrence prediction result of the maintenance target component group Failure prediction apparatus characterized by by comparing the predicted error occurrence information managed by the predicted error occurrence information management unit to determine whether a fault is likely to occur. 5. A maintenance target component group targeted for preventive maintenance and post-maintenance is specified from the maintenance history information of the device and the component configuration information stored in advance, and the operation history for the specified maintenance target component group is specified. A statistical method is applied to each maintenance history information stratified by the information to predict the failure occurrence tendency in each operating state of the maintenance target component group, and the predicted failure occurrence prediction result of the maintenance target component group and the operating state of the device in advance. A failure occurrence prediction method characterized by determining whether there is a possibility of a failure by comparing the failure occurrence prediction information for each component constituting the device stored for each. 6. A computer-readable storage medium storing a processing program of the failure occurrence prediction method according to claim 5.