JP2003054074A - Remaining life diagnostic system and method of diagnosing remaining life - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a remaining life diagnostic system capable of highly accurately estimating a remaining life by estimating a degree of deterioration in the way of going into malfunction when a collected object is reused. SOLUTION: There is disclosed the remaining life diagnostic system that judges whether or not a collected object is to be reused by estimating the degree of deterioration of the collected object when the collected object such as a collected product or a component thereof is to be reused. The remaining diagnostic system comprises a state quantity acquiring section 3 that acquires a state quantity of the product or the component to be estimated in a time series manner, a condition quantity history database 4 that stores the acquired state quantity as state quantity history data, a remaining life estimating section 6 that estimates the remaining life of the collected object by using the condition quantity history data corresponding to the state quantity of the collected object at the time when it is collected, and a reuse judging section 7 that judges whether or not the object is reused based on the estimated remaining life.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention collects a product used in the market and remanufactures the recovered product or a recovered product which is a component of the recovered product to remanufacture it. The present invention relates to a remaining life diagnosis method for diagnosing.

[0002]

2. Description of the Related Art In recent years, there has been an increasing international demand for protection of the global environment, and there is an increasing trend to collect and reuse products in the market. The number of recycling productions that are incorporated into products along with parts is increasing. Along with this, it is expected that the ratio of recycled or reused collected products collected from the market will further increase, while the evaluation technology for evaluating the degree of deterioration of collected products to judge whether or not to reuse them. Improvement is desired. Note that the remaining life is mentioned as a criterion for determining whether or not to reuse in the recycling process. Also,
In the field of reliability engineering, methods based on the distribution of failure rates, such as Weibull analysis and cumulative hazard analysis, have been used to estimate the remaining life. The "part selection method in a product recycling system" disclosed in Japanese Patent Laid-Open No. 10-34122 is a typical example of such a conventional technique. In this conventional technique, the useful life of each component is based on market quality information. Is statistically obtained using Weibull analysis.
Disassemble the recovered product, predict the remaining life of each part disassembled using the quality information and the service life, if the predicted remaining life is more than the product quality guarantee period, select as recyclable parts, It is supplied to the production line.

[0003]

However, in the above-mentioned conventional technique, since the variation in the market machine data increases as the number of times of reproduction increases, it is appropriate to focus on improving the reuse ratio, that is, using up. Not a method. An object of the present invention is to solve such a problem of the prior art, and specifically, when reusing a product and its components recovered from the market, the degree of deterioration in the middle of failure. Another object of the present invention is to provide a remaining life diagnosis system and a remaining life diagnosis method capable of evaluating the degree of deterioration of each component and performing highly accurate estimation of the remaining life by using the history information.

[0004]

In order to solve the above-mentioned problems, according to the invention of claim 1, the degree of deterioration of the recovered product or the recovered product which is a component thereof is reused. In the remaining life diagnosis system for determining whether to reuse the state product, the state amount acquisition means for acquiring the state amount of the target product or its component parts to be reused in time series, and the acquired Remaining life for estimating the remaining life of a collected product by using the state quantity history storage means for storing the state quantity as state quantity history data and the state quantity history data corresponding to the state quantity of the collected product at the time of collection It is characterized by comprising an estimating means and a reuse determining means for determining whether or not to reuse the estimated remaining life. According to a second aspect of the present invention, in the first aspect of the invention, as state quantity history data, a state quantity relating to a product or its constituent parts at a plurality of dates and times is stored for each product or each part. It is characterized by having done.
Further, in the invention described in claim 3, in the invention described in claim 1 or 2, the target product to be reuse-evaluated is a copying machine or a printer, and the state quantity is a parameter or configuration electronic information related to an output image. It is characterized in that it is configured to be a characteristic value of the circuit. Further, in the invention according to claim 4, when reusing a recovered product or a recovered product which is a component thereof, a remaining life diagnosis for evaluating the degree of deterioration of the recovered product and determining whether or not to reuse In the method, sampling the target product for reuse evaluation from the market,
Acquires the product configuration data of the sampled target product, acquires the component information whose state quantity should be acquired by referring to the acquired product configuration data, and acquires the state quantity of the component indicated by the acquired component information. It is characterized in that it is configured.

According to the fifth aspect of the present invention, whether or not to judge reuse by evaluating the degree of deterioration of the recovered product in the recycling process when reusing the recovered product or the recovered product which is a component of the recovered product. In the remaining life diagnosis method for determining, at the time of collection, the product configuration data of the recovered product is acquired, and the state quantity history data of the recovered product is acquired using the product configuration data,
Furthermore, the state quantity at the time of collection of the collected item is acquired, the remaining life of the collected item is estimated using the state quantity at the time of collection and the state amount history data, and whether or not to reuse from the estimated remaining life It is characterized in that it is configured to judge. Further, in the invention according to claim 6, in the invention according to claim 5, when estimating the remaining life of the collected product, a curve representing the time series change of the state quantity is automatically obtained from the history of the acquired state quantity. It is characterized in that it is configured. In the invention according to claim 7, in the invention according to claim 6, when estimating the remaining life of the collected product, the remaining life of the product is estimated by using the state quantity of the collected product at the time of collection and the curve. It is characterized in that it is configured to. In the invention according to claim 8, in the remaining life diagnosis method according to any one of claims 4 to 7, the target product for reuse evaluation is a copying machine or a printer, and a state quantity Is a parameter relating to an output image or a characteristic value of a constituent electronic circuit. Further, the invention according to claim 9 is characterized in that a program programmed according to the remaining life diagnosis method according to any one of claims 4 to 8 is stored in a storage medium storing the program.

[0006]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described in detail below with reference to the drawings. FIG. 1 is a configuration block diagram of a remaining life diagnosis system showing an embodiment of the present invention. As shown in the figure, the remaining life diagnosis system of this embodiment has a product information acquisition unit 1 that acquires product information J indicating a product P to be reused, and product configuration data in association with the product information J. A state information acquisition unit that obtains a product information database 2 to be stored, a state amount at the time of collection of a collected product, and a state amount history data that is time series data of the state amount for each product of the same type or its component parts. 3, a state quantity history database 4 for storing the state quantity history data, a data management unit 5 for storing, retrieving and managing data such as product configuration data and state quantity, a state quantity at the time of collection of collected products And the state quantity history data up to the present time are used to estimate the remaining life of the collected product, the remaining life estimation unit 6, and the reuse determination unit 7 that determines whether or not the estimated remaining life can be reused. Obtain. In this embodiment, the state quantity acquisition means, the state quantity history storage means, the remaining life estimation means, and the reuse determination means according to claim 1 are arranged in that order, respectively, in the state quantity acquisition part 3 and the state quantity history database 4. , The remaining life estimation unit 6 and the reuse determination unit 7. The product information acquisition unit 1, the state quantity acquisition unit 3, the data management unit 5, the remaining life estimation unit 6, and the reuse determination unit 7 are realized by a memory storing a program and a CPU that operates according to the program. . The product information database 2 and the state quantity history database 4 use, for example, a hard disk device as hardware. With such a configuration, the remaining life diagnosis system of this embodiment evaluates the degree of deterioration of the recovered product in the recycling process in which the product recovered from the market or its component parts is reused, and the product or the product is evaluated according to the evaluation result. It is determined whether the component is reused. The time series data of the state quantity may be test data such as a durability test or an acceleration test. The product is, for example, a copying machine or a printer, and the state quantity is, for example, a parameter relating to an output image in that case. Further, the product information acquisition unit 1 and the state quantity acquisition unit 3 are provided with a common keyboard and the like, and the product information and the state quantity are acquired by inputting data from the keyboard, for example. Alternatively, the product information acquisition unit 1 may be provided with a data communication control unit and input via a network.

FIG. 2 shows an operation flow when acquiring the state quantity at each time point in time series. Below, according to FIG.
The operation of acquiring the state quantity at each time point will be described. First, a worker is made to decide one or a plurality of individual products to be sampled from target models in the market (S1), and the product information acquisition unit 1 outputs product information (model information) indicating the target model to a keyboard or the like. And input to get (S
2). Subsequently, the data management unit 5 searches the product information database 2 for the product configuration data of the product corresponding to the acquired product information and acquires it (S3). Then, the component information indicating the component whose status quantity is to be collected, which is registered in the product configuration data, is acquired, and the status quantity acquisition unit 3 establishes a network for the status quantity acquisition target parts in the sampled individual product. The state quantity is automatically measured via the network, and the state quantity in the cumulative operating time at that time is acquired via the network (S4). The state quantity is a physical quantity such as force, torque, strain generated by the force, pressure, vibration, acoustic emission (AE), acceleration, displacement, or voltage of each part of the electronic circuit measured for each component, For example, in the case of a copying machine or printer, it is a parameter related to the output image. Not automatic measurement
For example, a service person may visit the site and measure the state quantity. In this case, the service person activates the product information acquisition unit 1 using the local terminal device. Thereby, the product information acquisition unit 1 causes the terminal device to input the product information indicating the target model and acquires the product information (S2), and then executes step S3 to measure the state quantity for the terminal device. Display the parts to be measured and the measurement method, and input the state quantity as the measurement result. Then, the data management unit 5 stores the state quantity associated with the cumulative operating time in the state quantity history database 4 as an attribute of the product information (S5). When the sampling for one model is completed, it is determined whether or not a predetermined model has been completed (S6), and if not completed (S6).
No in 6), and repeat from step S1 for the next model. Then, when the sampling is completed (“Yes” in S6), this operation flow is ended.

Next, the operation at the time of determination of reuse will be described with reference to FIG. Here, in the recycling process of reusing a product or its components collected from the market, first, product information (model information) of the product is acquired at the time of collection (S).
11). Then, the product configuration data of the product of the product information is retrieved / acquired (S12), and the state quantity history data is retrieved / acquired from the product configuration data (S13). further,
The state quantity acquisition unit 3 acquires the current (at the time of collection) state quantity of each component for which the state quantity of the product is to be acquired (S1).
4) From the state quantity history data and the state quantity at the time of collection, the remaining life of the collected product is estimated by a method described later (S15). And
Based on the estimated remaining life, it is determined whether or not to reuse (S1
6). FIG. 4 shows the data structure of product structure data. As shown in the figure, each component ID (component identification number) that uniquely identifies each component (subassembly) is associated with a plurality of child components that compose it, that is, a child component ID that uniquely identifies each component. It has been configured. With such a parent-child relationship, the parts that make up the entire product are managed. Here, the parent part (subassembly) may be a product (assembly), in which case the part ID is product information (model information) for identifying the product (model).
Further, in FIG. 4, the part number (part number) is a number for identifying each part type. For example, two individual parts always have different part IDs, but if they are the same part type, the part number is Will be the same. Further, FIG. 5 shows the configuration of the state quantity history data. As shown in the drawing, the state quantity at each date and time (corresponding to cumulative operating time) is set for each component ID that uniquely identifies each (individual) component. That is, the part I
A plurality of dates and times and state quantities at the respective dates and times are set for each D. This state quantity is, for example, the force, torque, strain generated by the force, pressure, vibration, acoustic emission (A
E), physical quantities such as acceleration, displacement, and the voltage of each part of the electronic circuit may change (deteriorate) with the operating time.

Next, the state quantity history data will be described. As shown in FIG. 6, among the state quantities of the component of interest (the component), characteristic values related to deterioration are x1 and x2,
Time series data is plotted in these two parameter spaces. In FIG. 6, date and time (corresponding to time and operating time) t
= Ts is an initial state, and t = Te indicates a failure state via the states at t = T1, T2, and T3. That is,
The initial value is represented by O, the value at the time of failure is represented by X, and the value in the middle is represented by ● (hereinafter the same). Here, X = (x1, x
2) and the state quantity at time t = Ti is represented by coordinates Xi. Then, Xs = F (Ts), that is, X1 = F (T1), X2 = F (T2), X3 = F (T
3), a smooth function X = F (t) at time t (Ts ≦ t ≦ Te) that satisfies Xe = F (Te) is calculated. A spline function may be used as the interpolation method here. The curve thus obtained represents a time-series change in the state quantity of the component of interest. However, such interpolation is not necessary when the state quantity can be continuously monitored as needed. In the above, when a certain product is repaired or parts are replaced during maintenance, the change in the state quantity of the product becomes discontinuous on the way of this (from X2 to X3 shown in FIG. 7). Part). Further, since there are variations in the characteristics of actual parts, when there are two parts of the same type (part number) (part 1, part 2), as shown in FIG. 8, the part 1 is X1s, X11, X1e, component 2 is X2
Follow different history curves X = F1 (t), X = F2 (t) such as s, T21, X22, X2e. When there are more parts, as shown in FIG. 9, the variation Gs at the initial stage and the variation Ge at the time of failure can be observed as a scatter diagram. In addition, failure analysis is performed at the time of collection,
A configuration in which failure modes are stratified is also possible. in this case,
As shown in FIG. 10, the position in the space at the time of failure is G1.
Groups such as e, G2e, and G3e can be grouped by mode. In the above, the coordinate axes may be the acquired characteristic values as they are, or may be subjected to appropriate scaling or coordinate conversion using the results of principal component analysis or discriminant analysis. It is also possible to visually evaluate and evaluate time-series data by mapping in a two-dimensional or three-dimensional space.

Steps S13, S14 and S shown in FIG.
15 will be described in more detail according to the operation flow shown in FIG. Note that here, the history curve X = F of a certain component
When (t) can be obtained, the remaining life when the state quantity of the same type (same part number) at the time of collection is Xb is estimated (see FIG. 11). First, the state quantity history data Xs,
X1 ,. ． ． Xe is read (taken out) (S21).
Then, the state quantity Xb at the time of collecting the collected parts is acquired (S
22). Then, Xs = F (Ts) and X1 = F (T
1) ,. ． ． , T such that Xe = F (Te) is satisfied
Smooth interpolation function of (Ts ≦ t ≦ Te) X = F (t)
Is calculated (S23). Then, when Ts ≦ t ≦ Te, t = Tr that minimizes d (F (t), Xb) is calculated, and the remaining life is calculated as remaining life = Te−Tr (S2).
4). However, d (Xi, Xj) is the distance between Xi and Xj. The distance may be based on the probability distribution in the state space shown in FIGS. 9 and 10. For example, the Mahalanobis distance with the inverse matrix of the covariance matrix as a metric can be considered. History curves X = Fi (t), i = 1, 2, ... For parts of the same type (part number). ． ． Figure 8
As shown in, there are as many samples as there are variations. At this time, in step S24, the remaining life is calculated by using Fi (t) instead of F (t) and calculating Fi (t) and d = Fi (t), Xb) and t = Tr. be able to. Further, as shown in FIG. 10, when the stratification for each failure mode is performed in advance by sampling, not only the remaining life of the recovered parts but also the failure mode are estimated by the method described above. be able to. Xb
The failure mode is estimated depending on which curve is close to. The state quantities treated up to this point were quantitative data, but in the case of qualitative data, they can be treated in the same way by the method in the quantification theory.

Next, referring to FIG. 13, a supplementary description will be given of a method of collecting state quantity history data in the case of the remaining life diagnosis system having a network configuration. It is assumed that the data on the component parts of the shipped product (product configuration data) is registered in the product data management server 14 in advance. In the remaining life diagnosis system having such a configuration, when collecting the state quantity of the product P1 such as a copying machine and a printer in the market, for example, the service person inputs the product information (model information) of the product P1 to the market machine data input terminal device 11 The market machine data management server 13 acquires the product configuration data from the product data management server 14 and causes the market machine data input terminal device 11 to display the target component for which the state quantity is to be acquired and the state quantity measurement method. Then, the serviceman measures the state quantity using the measuring instrument and inputs it using the market machine data input terminal device 11. Note that this data may be automatically acquired by a measuring device or the like attached to a market machine without human intervention. In this way, the acquired data is stored in the database of the market machine data management server 13 via the communication network 12. This market machine data management server 13 executes the operation flow shown in FIG. Note that this communication network is a LAN, a WAN, the Internet, or the like. Further, when the collected product P2 is collected from the market to the recycling factory, the collected machine data input / output terminal device 15 inputs the collected machine data such as the state quantity of the collected product P2. Note that this data may be automatically acquired by a measuring device or the like attached to the collected product P2 without human intervention. Figure 3
Recovery machine evaluation system 16 for executing the operation flow shown in FIG.
Makes an inquiry to the product data management server 14 and the market machine data management server 13 from the collected machine data, calculates the remaining life using the acquired data, and gives a work instruction to the collected machine data input / output terminal device 15 of the recycling factory. give. Although the case of determining the reusability of the components of the product has been described above, the reusability of the entire one product can be determined in the same manner. For example, when the product is a copying machine or a printer, state quantity history data is recorded with the output image quality as the state quantity, and the remaining life of the entire product is determined using the state quantity. Further, a program programmed according to the remaining life diagnosis method as described above is stored in a removable storage medium, and the storage medium is used in an information processing apparatus such as a personal computer which has not been able to perform the remaining life diagnosis according to the present invention. By mounting or by sending the program to the information processing apparatus via a network, the remaining life diagnosis according to the present invention can be performed in the information processing apparatus.

[0012]

As described above, according to the present invention,
According to the first and fifth aspects of the present invention, at the time of collection, the remaining life of the collected product is estimated by using the state quantity of the collected product and the corresponding state amount history data, and reused from the estimated remaining life. Since it is determined whether or not to do so, the degree of deterioration of each component is reflected in the remaining life estimation, and therefore,
The accuracy of remaining life estimation is improved, and highly accurate reuse determination can be performed. In the invention according to claim 2, in the invention according to claim 1, as the state quantity history data, the state quantities relating to the product or its component parts at a plurality of dates and times are stored for each product or each part. So
It is possible to know at which point in time series the state quantity of the collected product corresponds, and therefore, the remaining life can be estimated.
Further, in the invention described in claim 3, in the invention described in claim 1 or 2, the target product to be reuse-evaluated is a copying machine or a printer, and the state quantity is a parameter or configuration electronic information related to an output image. Since it is a characteristic value of the circuit, in the case of a copying machine or a printer, an output image satisfying the specifications can be obtained by using a recovered product that is determined to be reusable. Also,
In the invention according to claim 4, the target product to be reused is sampled from the market, the product configuration data of the sampled target product is acquired, and the state quantity is calculated by referring to the acquired product configuration data. Since the part information to be acquired is acquired and the state quantity of the part indicated by the acquired part information is acquired, it becomes possible to collect the state quantity history data for each part of the target product. In the invention of claim 6, in the invention of claim 5,
When estimating the remaining life of a collected item, a curve representing the time series change of the state amount is automatically obtained from the acquired state amount history, so the position on the curve closest to the state amount of the collected item is collected. It can be obtained as the position of the product in time series, and the remaining life can be automatically estimated from the position. In the invention according to claim 7, in the invention according to claim 6, when estimating the remaining life of the collected product, the remaining life of the product is estimated by using the state quantity of the collected product at the time of collection and the curve. Therefore, highly accurate estimation of the remaining life can be easily realized.

According to the invention of claim 8, claim 4 is
8. The residual life diagnosis method according to claim 7, wherein the target product to be reused is a copying machine or a printer, and the state quantity is a parameter related to an output image or a characteristic value of a constituent electronic circuit. Therefore, in the case of a copying machine or a printer, an output image satisfying the specifications can be obtained by using a recovered product that is determined to be reusable. Further, in the invention according to claim 9, the program programmed according to the remaining life diagnosis method according to any one of claims 4 to 8 is stored in, for example, a removable storage medium. Up to now, any one of claims 4 to 8
The information processing apparatus according to any one of claims 4 to 8 is mounted on an information processing apparatus, such as a personal computer, which has not been able to perform the remaining life diagnosis according to the invention described in the above section. The effect can be obtained.

[Brief description of drawings]

FIG. 1 is a system configuration diagram of a remaining life diagnosis system showing an embodiment of the present invention.

FIG. 2 is an operation flow chart of a remaining life diagnosis method showing an embodiment of the present invention.

FIG. 3 is another operational flowchart of the remaining life diagnosis method according to the embodiment of the present invention.

FIG. 4 is a data configuration diagram of a main part of the remaining life diagnosis system showing the embodiment of the present invention.

FIG. 5 is another data configuration diagram of the main part of the remaining life diagnosis system showing the embodiment of the present invention.

FIG. 6 is an explanatory diagram of a remaining life diagnosis method according to an embodiment of the present invention.

FIG. 7 is another explanatory diagram of the remaining life diagnosis method according to the embodiment of the present invention.

FIG. 8 is another explanatory diagram of the remaining life diagnosis method according to the embodiment of the present invention.

FIG. 9 is another explanatory diagram of the remaining life diagnosis method according to the embodiment of the present invention.

FIG. 10 is another explanatory diagram of the remaining life diagnosis method showing the embodiment of the present invention.

FIG. 11 is another explanatory diagram of the remaining life diagnosis method according to the embodiment of the present invention.

FIG. 12 is another operation flowchart of the remaining life diagnosis method according to the embodiment of the present invention.

FIG. 13 is a system configuration diagram of a remaining life diagnosis network system showing an embodiment of the present invention.

[Explanation of symbols]

1 Product Information Acquisition Department 2 product information database 3 State quantity acquisition unit 4 State history database 5 Data management department 6 Remaining life estimation part 7 reuse determination section 11 Market machine data input terminal device 12 Communication network 13 Market data management server 14 Product data management server 15 Recovery machine data input / output terminal device 16 Recovery machine evaluation system

Claims (9)

[Claims] 1. Reuse of a recovered product or a recovered product that is a component of the recovered product in a remaining life diagnosis system that evaluates the degree of deterioration of the recovered product and determines whether to reuse. State quantity acquisition means for acquiring the state quantity of the target product or its components to be evaluated in time series, state quantity history storage means for storing the acquired state quantity as state quantity history data, and at the time of collection Remaining life estimation means for estimating the remaining life of the collected goods using the state quantity history data corresponding to the collected goods and the re-judgment for determining whether or not to reuse the estimated remaining life. A remaining life diagnosis system, comprising: a use determination means. 2. The remaining life diagnosis system according to claim 1, wherein the state quantity history data is such that a state quantity relating to a product or its constituent parts at a plurality of dates and times is stored for each product or each part. The remaining life diagnosis system that is characterized. 3. The remaining life diagnosis system according to claim 1 or 2, wherein the target product for reuse evaluation is a copying machine or a printer, and the state quantity of a parameter or a constituent electronic circuit relating to an output image. A remaining life diagnosis system characterized by characteristic values. 4. A reuse life diagnosis method for evaluating the degree of deterioration of a recovered product when reusing a recovered product or a recovered product that is a component of the recovered product to determine whether or not to reuse the product. The target product to be evaluated is sampled from the market, the product configuration data of the sampled target product is acquired, the part information for which the state quantity is to be acquired is acquired by referring to the acquired product structure data, and the acquired A remaining life diagnosis method, characterized in that a state quantity of a component indicated by the component information is acquired. 5. A residual life diagnosis method for evaluating the degree of deterioration of a recovered product in a recycling process when reusing a recovered product or a recovered product that is a component of the recovered product to determine whether or not to make a reuse judgment. At the time of collection, the product configuration data of the collected product is acquired, the state quantity history data of the collected product is obtained using the product configuration data, and further, the state quantity at the time of collection of the collected product is obtained, and the collection is performed. A remaining life diagnosing method comprising estimating a remaining life of a collected product by using the state quantity at time and the state quantity history data, and determining whether to reuse the estimated remaining life. 6. The residual life diagnosis method according to claim 5, wherein when estimating the remaining life of a collected product, a curve representing a time series change of the status quantity is automatically obtained from the history of the acquired status quantities. Characteristic residual life diagnosis method. 7. The remaining life diagnosis method according to claim 6, wherein when estimating the remaining life of a collected product, the remaining life of the product is estimated by using the state quantity of the collected product at the time of collection and the curve. A remaining life diagnosis method characterized by 8. The remaining life diagnosis method according to claim 4, wherein the target product for reuse evaluation is a copying machine or a printer, and the state quantity relates to an output image. A remaining life diagnosis method, which is a parameter or a characteristic value of a constituent electronic circuit. 9. A remaining life diagnosis method, characterized in that a program programmed according to the remaining life diagnosis method according to claim 4 is stored in a storage medium storing the program.