WO2015145802A1

WO2015145802A1 - Asset management system and asset management method

Info

Publication number: WO2015145802A1
Application number: PCT/JP2014/072060
Authority: WO
Inventors: 貴志住吉; 裕也小松
Original assignee: 株式会社日立システムズ
Priority date: 2014-03-25
Filing date: 2014-08-22
Publication date: 2015-10-01
Also published as: JP6235947B2; JP2015185041A

Abstract

Provided is an asset management system for supporting statistical data processing by a non-expert. In the asset management system, an operating device executes: an asset classifying program for storing classification condition information classifying an asset on the basis of an asset name and attribute information in a classification result table; a parameter estimation program for estimating a parameter for performing asset-by-asset deterioration prediction on the basis of the classified classification result information; a restriction condition discrimination program for storing, in a discrimination result table, discrimination result information discriminated on the basis of the restriction condition information stored in the restriction condition list; a document output program for obtaining and outputting an estimation parameter by executing the above programs on the basis of an input instruction; and a user interface program for reading a standard document of a document template and outputting to a document table a document to which the estimation parameter has been applied by substituting a tab.

Description

Asset management system and asset management method

The present invention relates to an asset management system and an asset management method for managing and operating an asset such as a road social infrastructure maintained and managed by a local government using a computer system. The present invention relates to an asset management system and an asset management method capable of predicting repairs and updates.

In general, the asset management system, which is a computer system that manages and operates road social infrastructure maintained and managed by local governments, predicts the degree of asset deterioration based on inspection results and calculates the total repair cost (life cycle cost). Have. In this method of predicting the degree of asset deterioration in the asset management system, it is necessary to set the prediction coefficient to a logical and reasonable one. However, this deterioration level prediction requires a lot of noise in the inspection results of assets and the inspection results may not be sufficiently obtained. Often outsourced.

The following Patent Document 1 is cited as a document that describes a technology related to asset management of structures such as bridges according to the prior art. This Patent Document 1 includes input means for inputting inspection data on the deterioration state of a structure, calculation means for calculating a deterioration curve indicating the degree of deterioration with respect to the elapsed years from the input inspection data, input inspection data, An asset management system including display means for displaying a deterioration curve is described. In this technique, the calculation means extracts the elapsed data classification step for extracting the inspection data for each predetermined elapsed age section, the average deterioration degree calculating step for calculating the average of the deterioration degrees classified for each elapsed age section, By executing a deterioration curve calculation step of calculating a deterioration curve using the least square method from the average deterioration degree calculated for each year section, it is possible to predict deterioration of asset management of a structure such as a bridge.

JP 2008-291440 A

Generally, a small local government is required for asset management and longevity plans for road social infrastructure, and this small local government may not have sufficient budget and personnel. For this reason, in small local governments, a person who is not an expert in statistical data processing of an asset management system often selects a deterioration prediction method (formula or coefficient). In this case, since it is difficult for a person in charge of a small local government to effectively select a deterioration prediction method (formula or coefficient), the business is stagnant and an outsourcing cost increases when ordering outside.

The technique described in Patent Document 1 described above classifies inspection data for each structure type and part to determine the progress of deterioration, and calculates a deterioration curve by the least square method from the degree of deterioration classified and averaged for a certain number of elapsed years. Although a structure deterioration curve calculation system is described, it is not assumed that consistency cannot be obtained with the obtained deterioration curve, and there is a function to check consistency, a classification method and deterioration to ensure consistency. Since there is no user interface for repeating trial and error while changing the model, there is a problem that business support by a person (user) who is not an expert cannot be performed.

An object of the present invention is to provide an asset management system and an asset management method that can promote the spread of asset management and long-life plans by a function that supports statistical data processing by a user who is not an expert.

To achieve the above object, the present invention represents an asset database for storing asset information including an infrastructure asset name and a plurality of attribute information, an infrastructure asset name, an inspection year for checking the asset, and an asset state. Inspection database for storing inspection information of soundness level, asset classification condition list for storing classification condition information including an attribute name to which the asset belongs and a plurality of attribute conditions for the asset, and an algorithm / formula for predicting deterioration of the asset A deterioration prediction model list for storing deterioration prediction information including coefficients, a restriction condition list for storing constraint information including a plurality of constraint conditions for assets and the relationship of the plurality of constraint conditions, algorithms and mathematical formulas for users, Document template for storing a plurality of standard documents including tags for explaining a method for deriving a deterioration prediction model including coefficients, and the document template Document template element list that stores elements of referenced algorithms, mathematical formulas, and coefficients, a classification result table that stores classification result information including asset names for combinations of a plurality of attributes that are classification results, and a plurality of classification result tables An estimation parameter table for storing an estimation parameter for estimating a deterioration state for an attribute of the attribute, and a discrimination result table for storing discrimination result information for discriminating whether or not the relationship between the estimation parameter table and the plurality of estimation parameters satisfies consistency A storage device for storing a plurality of standard documents for explaining a method for deriving a deterioration prediction model for a user created by referring to the document template and the document template element list;
An arithmetic device that predicts asset repair and update by referring to the storage device and predicting asset deterioration;
Asset classification condition list display field, deterioration prediction model list display field, constraint condition list display field, asset classification condition list, deterioration prediction model list, restriction condition list, calculation start button, document output button, discrimination result display field, and document display field And a display device for displaying
An asset management system comprising:
The arithmetic unit is
An asset classification program for storing classification condition information obtained by classifying assets based on asset names and attribute information in a classification result table;
A parameter estimation program for estimating parameters for performing deterioration prediction for each asset based on the classification result information classified by the asset classification program;
A constraint condition determination program for storing determination result information determined based on the constraint condition information stored in the constraint condition list in a determination result table;
A document output program that reads the standard document of the document template, replaces the tags described in the standard document based on the constraint condition information, and outputs to the document table;
Based on the input instructions input by the user, the asset classification program, parameter estimation program, and constraint condition determination program are executed to obtain the estimated parameters, the document output program reads the standard document of the document template, and is described in the standard document A first feature is to execute a user interface program that replaces a tag based on constraint condition information and outputs the tag to a document table.

In the asset management system according to the first aspect of the present invention, the asset classification program includes:
A first step of acquiring an asset classification condition by a combination of an attribute name and an attribute value condition specified from the asset classification condition list;
A second step of acquiring asset information from the asset database based on the asset classification condition acquired in the first step;
A third step of generating intermediate data in which a label is added to the asset information acquired in the second step based on the asset classification condition acquired in the second step;
A fourth step of determining whether or not the next asset information is present in the asset classification condition list, and returning to the second step when it is determined that the asset classification condition list is present;
When it is determined that there is no next asset information in the fourth step, it is determined whether there is a next asset classification condition, and when it is determined that there is a fifth step, the fifth step returns to the first step;
When it is determined that there is no next asset classification condition in the fifth step, the asset information having the same label is grouped from the intermediate data, and the sixth step of storing in the classification result table is executed, whereby the classification result table The second feature is that it operates to store the classification result information.

In the asset management system according to the second aspect of the present invention, the parameter estimation program includes:
A seventh step of acquiring classification result information from the classification result table classified by the asset classification program;
An eighth step of acquiring a set of elapsed years and soundness levels corresponding to the asset name from the inspection database using the asset name included in the classification result information acquired in the seventh step as a key;
A ninth step of estimating the parameters of the deterioration prediction model from the set of elapsed years and soundness obtained in the eighth step based on the algorithm formula of the deterioration prediction model;
Determining whether or not there is next classification result information in the classification result table, and when it is determined that there is, a tenth step of returning to the seventh step;
The third feature is that the eleventh step of storing the parameter estimated from the ninth step in the estimated parameter table is executed.

In the asset management system according to the third aspect of the present invention, the constraint condition determination program includes:
A twelfth step of acquiring constraint condition information from the constraint condition list;
Among the label groups stored in the classification result table, a set of label groups that differ only in the attribute values described in the lower-level constraint conditions included in the constraint condition information acquired in step 12 is obtained from the estimated parameters in the estimated parameter table. 13th step;
A fourteenth step of obtaining a set of label groups that differ only in the attribute values obtained in the thirteenth step;
A fifteenth step for determining whether or not the label group acquired in the fourteenth step satisfies the relational condition with the upper constraint condition in the constraint condition acquired in the twelfth step;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step satisfies the relationship with the upper constraint condition, the sixteenth step of setting the determination result as “constraint condition”;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step does not satisfy the relationship with the upper constraint condition, the seventeenth step of setting the determination result as “does not satisfy the constraint condition”;
It is determined whether or not there is a next label group in the classification result table, and when it is determined that there is, an eighteenth step of returning to the fourteenth step;
A 19th step for returning to the twelfth step when it is determined that there is a next constraint when it is determined in the 18th step that there is no next label group;
A fourth feature is that when it is determined in the nineteenth step that there is no next constraint condition, a twentieth step of storing the determination result information in the determination result table is executed.

The present invention provides the asset management system according to the fourth feature, wherein the combination program is:
A 21st step of enumerating valid / invalid combination patterns of each element of the asset classification condition list and the deterioration prediction model list;
A 22nd step of obtaining the next combination from the combination set listed in the 21st step and setting whether the combination is valid or invalid;
A fifth feature is that the asset classification program, the parameter estimation program, and the constraint condition determination program are executed based on the setting of validity or invalidity in the twenty-second step.

Furthermore, the present invention provides an asset database for storing asset information including infrastructure asset names and a plurality of attribute information, an infrastructure asset name, an inspection year for inspecting the asset, and a health check indicating the state of the asset. It includes an inspection database for storing information, an asset classification condition list for storing classification condition information including attribute names to which the asset belongs and a plurality of attribute conditions for the asset, and algorithms, mathematical formulas, and coefficients for predicting asset deterioration Deterioration prediction model list for storing deterioration prediction information, restriction condition list for storing constraint information including relations between multiple constraints and multiple constraints on assets, and deterioration including algorithms, formulas and coefficients for users A document template for storing a plurality of standard documents including tags for explaining a prediction model derivation method, and an altem referenced by the document template Document template element list for storing elements of rhythms, mathematical formulas and coefficients, a classification result table for storing classification result information including asset names for combinations of a plurality of attributes as classification results, and a plurality of attributes for the classification result table An estimation parameter table for storing an estimation parameter for estimating a deterioration state, a determination result table for storing determination result information for determining whether the relationship between the estimation parameter table and the plurality of estimation parameters satisfies consistency, and A storage device for storing a document table for storing a plurality of standard documents for explaining a method for deriving a deterioration prediction model for a user created by referring to a document template and a document template element list, and referring to the storage device A computing device that predicts asset deterioration and repairs and updates assets, Production classification condition list display field, deterioration prediction model list display field, constraint condition list display field, asset classification condition list, deterioration prediction model list, restriction condition list, calculation start button, document output button, discrimination result display field, and document display field An asset management method using a computer system comprising a display device for displaying
In the arithmetic unit,
An asset classification program for storing classification condition information obtained by classifying assets based on asset names and attribute information in a classification result table;
A parameter estimation program for estimating parameters for performing deterioration prediction for each asset based on the classification result information classified by the asset classification program;
A constraint condition determination program for storing determination result information determined based on the constraint condition information stored in the constraint condition list in a determination result table;
A document output program that reads the standard document of the document template, replaces the tags described in the standard document based on the constraint condition information, and outputs to the document table;
Based on the input instructions input by the user, the asset classification program, parameter estimation program, and constraint condition determination program are executed to obtain the estimated parameters, the document output program reads the standard document of the document template, and is described in the standard document A sixth feature is to execute a user interface program that replaces a tag based on constraint condition information and outputs the tag to a document table.

Further, the present invention provides the asset management method according to the sixth feature, wherein the arithmetic device is an asset classification program,
A first step of acquiring an asset classification condition by a combination of an attribute name and an attribute value condition specified from the asset classification condition list;
A second step of acquiring asset information from the asset database based on the asset classification condition acquired in the first step;
A third step of generating intermediate data in which a label is added to the asset information acquired in the second step based on the asset classification condition acquired in the second step;
A fourth step of determining whether or not the next asset information is present in the asset classification condition list, and returning to the second step when it is determined that the asset classification condition list is present;
When it is determined that there is no next asset information in the fourth step, it is determined whether there is a next asset classification condition, and when it is determined that there is a fifth step, the fifth step returns to the first step;
When it is determined that there is no next asset classification condition in the fifth step, the asset information having the same label is grouped from the intermediate data, and the sixth step of storing in the classification result table is executed, whereby the classification result table The seventh feature is that the operation is performed so as to store the classification result information.

Further, the present invention provides the asset management method according to the seventh feature, wherein the arithmetic device is a parameter estimation program,
A seventh step of acquiring classification result information from the classification result table classified by the asset classification program;
An eighth step of acquiring a set of elapsed years and soundness levels corresponding to the asset name from the inspection database using the asset name included in the classification result information acquired in the seventh step as a key;
A ninth step of estimating the parameters of the deterioration prediction model from the set of elapsed years and soundness obtained in the eighth step based on the algorithm formula of the deterioration prediction model;
Determining whether or not there is next classification result information in the classification result table, and when it is determined that there is, a tenth step of returning to the seventh step;
The eighth feature is that the eleventh step of storing the parameter estimated in the ninth step in the estimated parameter table is executed.

Further, the present invention provides the asset management method according to the eighth feature, wherein the arithmetic device is a constraint condition determination program.
A twelfth step of acquiring constraint condition information from the constraint condition list;
Among the label groups stored in the classification result table, a set of label groups that differ only in the attribute values described in the lower-level constraint conditions included in the constraint condition information acquired in step 12 is obtained from the estimated parameters in the estimated parameter table. 13th step;
A fourteenth step of obtaining a set of label groups that differ only in the attribute values obtained in the thirteenth step;
A fifteenth step for determining whether or not the label group acquired in the fourteenth step satisfies the relational condition with the upper constraint condition in the constraint condition acquired in the twelfth step;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step satisfies the relationship with the upper constraint condition, the sixteenth step of setting the determination result as “constraint condition”;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step does not satisfy the relationship with the upper constraint condition, the seventeenth step of setting the determination result as “does not satisfy the constraint condition”;
It is determined whether or not there is a next label group in the classification result table, and when it is determined that there is, an eighteenth step of returning to the fourteenth step;
A 19th step for returning to the twelfth step when it is determined that there is a next constraint when it is determined in the 18th step that there is no next label group;
A ninth feature is that when it is determined in the nineteenth step that there is no next restriction condition, the twentieth step of storing the determination result information in the determination result table is executed.

The present invention provides the asset management method according to the ninth feature, wherein the arithmetic device is a combination program.
A 21st step of enumerating valid / invalid combination patterns of each element of the asset classification condition list and the deterioration prediction model list;
A 22nd step of obtaining the next combination from the combination set listed in the 21st step and setting whether the combination is valid or invalid;
A tenth feature is that the asset classification program, the parameter estimation program, and the constraint condition determination program are executed based on the setting of validity or invalidity in the twenty-second step.

An asset management system and an asset management method according to the present invention include an asset classification program for storing, in a classification result table, classification condition information for classifying an asset, and a deterioration prediction for each asset based on the classification result information. A parameter estimation program for estimating parameters, a constraint condition determination program for storing discrimination result information based on the constraint condition information stored in the constraint condition list in a discrimination result table, and a tag described in the standard document of the document template as a constraint condition A document output program that replaces the information based on the information and outputs it to the document table, and executes an asset classification program, a parameter estimation program, and a constraint determination program based on an input instruction input by a user (person in charge) The document output program Supports statistical data processing by non-professional users by reading the standard document of the plate, replacing the tags described in the standard document based on the constraint information, and executing the user interface program that outputs to the document table This function can promote the spread of asset management and long-life plans.

FIG. 1 is a diagram showing a configuration of an asset management system according to an embodiment of the present invention. FIG. 2 is a diagram showing the contents of the asset database according to the present embodiment. FIG. 3 is a diagram showing the contents of the inspection database according to the present embodiment. FIG. 4 is a diagram showing the contents of the asset classification condition list according to the present embodiment. FIG. 5 is a diagram showing an operation flow of the asset classification program according to the present embodiment. FIG. 6 is a diagram showing an example of intermediate data created by the asset classification program according to the present embodiment. FIG. 7 is a diagram for explaining the classification result according to the present embodiment. FIG. 8 is a diagram showing an operation flow of the parameter estimation program according to the present embodiment. FIG. 9 is a diagram for explaining a deterioration prediction model list according to the present embodiment. FIG. 10 is a diagram for explaining the parameter estimation method of the parameter estimation program according to the present embodiment. FIG. 11 is a diagram for explaining the estimation parameters according to the present embodiment. FIG. 12 is a diagram showing an operation flow of the constraint condition determination program according to the present embodiment. FIG. 13 is a diagram for explaining a constraint condition list according to the present embodiment. FIG. 14 is a diagram showing the contents of the discrimination result database according to the present embodiment. FIG. 15 is a diagram showing an example of a user interface screen according to the present embodiment. FIG. 16 is a diagram showing an example of a document template according to the present embodiment. FIG. 17 is a diagram for explaining document template elements according to the present embodiment. FIG. 18 is a diagram showing an operation flow of the combination program according to the present embodiment.

Next, an embodiment of an asset management system to which an asset management method according to the present invention is applied will be described in detail with reference to the drawings.
[Constitution]
As shown in FIG. 1, the asset management system according to the present embodiment includes an arithmetic device 11 that is a general CPU (Central Processing Unit), a storage device 12 that is a hard disk or a DRAM (Dynamic Random Access Memory), a keyboard, and the like. The input device 13 and an output device 14 such as a display are connected by a bus. The storage device 12 includes a program group indicated by reference numerals 21 to 26, a data group indicated by reference numerals 31 to 37, and reference numerals 41 to 44. The calculation result group shown is configured to be stored.
The present invention is not limited to these configurations. For example, a network input / output device may be provided in place of the input device 13 and the output device 14 and data input / output may be performed via an external device such as a client terminal via the network. good. Furthermore, the present invention may be configured such that a part or all of the data of the storage device 12 is arranged in an external storage device and data is read / written via a network.

The data group indicated by the reference numerals 31 to 37 has the following database and the like.
(1) An asset database 31 that stores asset information such as road social infrastructure maintained and managed by local governments.
(2) An inspection database 32 that stores asset information (for example, road pavement name) such as infrastructure, inspection year for inspection of the asset, and inspection information such as soundness indicating the state of the asset.
(3) An attribute name (for example, traffic volume, precipitation amount, speed limit) to which the asset (for example, road pavement) and a plurality of attribute conditions for the asset (for example, traffic value, precipitation value, speed limit) Asset classification condition list 33 for storing classification condition information including
(4) A deterioration prediction model list 34 storing deterioration prediction information including algorithms, mathematical formulas, and coefficients for predicting deterioration of assets.
(5) A plurality of constraints on the asset (for example, attribute “traffic volume / precipitation / restricted speed” for the soundness value for a predetermined number of years) and a relationship between the plurality of constraints (for example, the attribute “traffic for the year of soundness 1) A constraint condition list 35 that stores constraint condition information including a magnitude relationship with respect to “amount”.
(6) A document template 36 for storing a plurality of standard documents for explaining a method for deriving a deterioration prediction model including an algorithm, a mathematical formula, and a coefficient to the user.
(7) A document template element list 37 for storing elements such as algorithms, mathematical formulas, and coefficients referred to by the document template 36.

The calculation result group indicated by the reference numerals 41 to 44 has the following table and the like.
(1) A classification result table 41 that stores classification result information including asset names for a plurality of attributes (for example, combinations of traffic volume, precipitation, and speed limit) that are classification results.
(2) An estimation parameter table 42 that stores estimation parameters for estimating a degradation state for a plurality of attributes (for example, traffic volume, precipitation amount, speed limit) of the classification result table 41.
(3) A determination result table 43 that stores determination result information for determining whether the relationship between the estimation parameter table 42 of the deterioration prediction model and the plurality of estimation parameters satisfies consistency.
(4) A document table 44 for storing a plurality of documents for explaining a method for deriving a deterioration prediction model for a user created with reference to the document template 36 and the document template element list 37.

The program groups indicated by the reference numerals 21 to 26 are various programs for the computer to execute the asset management method according to the present embodiment, and include the following programs.
(1) An asset classification program 21 that stores, in the classification result table 41, classification result information obtained by classifying assets having the same label group based on classification condition information.
(2) A parameter estimation program 22 that estimates parameters for performing deterioration prediction for each asset based on the classification result information classified by the asset classification program 21.
(3) A constraint condition determination program 23 that stores the determination result information determined based on the constraint condition information stored in the constraint condition list 35 in the determination result table 43.
(4) A document output program 24 that reads the document template 36, replaces the tag described in the document template 36, and outputs it to the document table 44.
(5) The screen shown in FIG. 15 is displayed, and the asset classification program 21, the parameter estimation program 22, and the constraint condition determination program 23 are executed based on the input instruction input by the user to obtain appropriate estimation parameters and output the document. A user interface program 25 that reads a standard document of the document template 36 by executing the program 24, replaces a tag described in the document template 36, and outputs it to the document table 44.
(6) It is determined whether the combination set of each element of the asset classification condition list 33 and the deterioration prediction model list 34 is valid or invalid, and the asset classification program 21, the parameter estimation program 22, and the constraint condition determination based on the determination result A combination program that executes the program 23 and the document output program 24 and stores the estimated parameter, the determination result information, and the document information obtained by executing the document output program 24 in the estimated parameter table 42, the determination result table 43, and the document table 44, respectively. 26.

The program group is read into the arithmetic unit 11 as necessary and the contents are executed. The asset database 31, the inspection database 32, the asset classification condition list 33, the deterioration prediction model list 34, the constraint condition list 35, and the document template element list 37 are assumed to be tables of a relational database management system generally used in this embodiment. However, the present invention is not limited to these.

[Explanation of data group]
The asset database 31 stores one record for each asset target managed by the asset management system according to the present embodiment. For example, as shown in FIG. It is composed of the service year that indicates the year in which it was in service, the traffic volume (cars / day), the annual precipitation (mm), the speed limit (Km / h), and other item information when the asset is paved. The service name “Pavement 1-1” is stored as “1977”, the traffic volume is “3000 cars / day”, the annual precipitation is “1200 mm”, and the speed limit is “20 Km / h”. .

As shown in FIG. 3, the inspection database 32 includes item information such as an infrastructure name (for example, a road pavement name), an inspection year in which the asset is inspected, and a soundness level indicating the state of the asset. For example, the inspection year of the asset with the asset name “Pavement 1-1” is stored as “2012” and the soundness value is stored as “7.7”.

As shown in FIG. 4, the asset classification condition list 33 stores a plurality of attribute values for classifying assets, and stores, for example, the values of the following attributes.
(1) The attribute value condition 1 of the attribute name “traffic volume” is “X <5000” (traffic volume is less than 5000 cars / day), the attribute condition value 2 is “5000 <= X” (traffic volume is 5000 cars / day) Or more).
(2) The attribute value condition 1 of the attribute name “precipitation” is “X <500” (precipitation is less than 500 mm / day), and the attribute value condition 2 is “500 <= X <1000” (precipitation is 500 mm / day). And less than 1000 mm / day), and attribute value condition 3 is “1000 <= X” (precipitation is 1000 mm or less).
(3) The attribute value condition 1 of the attribute name “limit speed” is “0 <= X <20” (the limit speed is 20 km / h or less), and the attribute value condition 2 is “20 <= X <40” (the limit speed is 20 km / h or more and 40 km / h or less) and the attribute value condition 3 is “40 <= X” (the speed limit is less than 40 km / h).
The plurality of attribute value conditions indicate conditions that the field values of the asset database 31 for classifying the assets into

classifications

1, 2, and 3 should satisfy, and X is a variable.

The deterioration prediction model list 34 stores deterioration prediction information including an algorithm for predicting the deterioration of assets, mathematical formulas, and coefficients. For example, as shown in FIG. 9, the algorithm “least squares method (least squares method)” is used. “Y = aX + 10” and the coefficient is a.

As shown in FIG. 13, the restriction condition list 35 includes “restriction target 1” indicating values related to the classification parameters, “restriction target 2” indicating attribute names of the asset database 31, “restriction target 1”, and “restriction target 1”. “Relation” indicating the condition to be satisfied by “Constrained Object 2” (for example, “Forward” indicates that the magnitude relationship of each value is the same, and for “Reverse”, the magnitude relationship of each value is mismatched. The constraint condition information is stored.
In this restriction condition list 35, for example, the relationship between the “years until the soundness level 1” in the restriction condition 1 and the “traffic volume” in the restriction condition 2 is “reverse” (the restriction condition 1 “up to the soundness degree 1”). “Years” and constraint 2 “traffic volume” are in a conflicting relationship. For example, if “traffic volume” is small, “years to soundness level 1” becomes longer, and if “traffic volume” is large, “health level is 1” That the number of years is reduced).

The document template 36 stores a plurality of standard document information for explaining a method for deriving a deterioration prediction model including an algorithm, a mathematical expression, and a coefficient to the user. For example, as shown in FIG. 16, the document template 36 includes “deterioration prediction model selection method” and “asset classification” as “degradation prediction model derivation methods”, and “deterioration prediction model selection” is “deterioration prediction model”. A description of “list @ name” (@ indicates an arbitrary list name) and “deterioration prediction model @”, and details of “asset classification” are described.

The document template element list 37 describes elements such as algorithms, mathematical formulas, and coefficients that are referred to by the document template 36. 17, the document template element list 37 includes item information of a reference table, a tag name, a condition (expression), and a sentence (element). For example, the document template element list 37 includes a reference table “deterioration prediction model list”. The tag name “**” indicates that the sentence (element) whose condition is “# = 1” is “regression curve (quadratic expression)”.

The classification result table 41 stores classification result information that is an asset name for a combination of a plurality of attribute value conditions that are classification results. As shown in FIG. 7, this classification result table 41 has “asset names” for a plurality of “labels” as fields. For example, for the combination of “traffic volume 1” “precipitation 1” “restricted speed 1” Asset names “pavement 12-1, pavement 12-2...” Are stored.

The estimation parameter table 42 is for storing the parameters a and b of the algorithm of the deterioration prediction model estimated based on the asset classification. As shown in FIG. 11, a plurality of attributes ( For example, a plurality of “labels” and “parameters” are stored as fields for estimating a deterioration state with respect to traffic volume, precipitation amount, and speed limit.

The discrimination result table 43 stores the estimation parameters of the deterioration prediction model and discrimination result information that discriminates whether or not they satisfy the consistency, and as shown in FIG. 14, “not satisfied” as discrimination result information. Alternatively, “satisfied” is stored.

[Operation]
Next, the operation of the asset management system according to the present embodiment will be described. In the asset management system according to the present embodiment, the computing device 11 performs the above-described asset classification program 21, parameter estimation program 22, and constraint condition determination program 23 according to the operation of the input device 13 while the user refers to the display of the output device 14. By executing the functions of the document output program 24, the user interface program 25, and the combination program 26, asset deterioration is predicted and asset repair and update are predicted. Next, the operation of each program will be described. To do.

[Operation of asset classification program 21]
First, the asset management system according to the present embodiment executes the following steps shown in FIG. 5 by starting the asset classification program 21 when the asset management system is activated or when the user activates the asset management system 21 at an arbitrary timing. Operates to store the classification result information as shown in the classification result table 41 of FIG.
(1) Step S101 for acquiring the specified asset classification condition (combination of attribute name and attribute value condition) from the asset classification condition list 33.
(2) Step S102 for acquiring asset information from the asset database 31.
(3) Step S103 for generating intermediate data in which a label is added to the asset information acquired in Step S102 based on the asset classification condition acquired in Step S102.

This intermediate data is assigned to each asset as a classification result, and the asset information identified by the asset “Pavement 1-1” shown in FIG. 2 is classified using # 1 of the asset classification condition list 33 (FIG. 4). In this case, the <traffic volume> of the asset “Pavement 1-1” is 3000 units / day, and the label “traffic volume 1” is set to satisfy “X <5000” of <attribute value condition 1>. Created.

(4) Step S104 that determines whether or not there is next asset information and returns to Step S102 when it is determined that there is.
(5) When it is determined in step S104 that there is no next asset, it is determined whether or not there is a next asset classification condition. When it is determined that there is a next asset, step S105 returns to step S101.
(6) When it is determined in step S105 that there is no next asset classification condition (after processing of all asset classification conditions is completed), a label group in which asset information with the same label is grouped from the intermediate data is classified Step S106 for storing the result information in the classification result table 41.

The classification result information shown in FIG. 7 stored by executing these steps stores an “asset name” list corresponding to a plurality of “labels” (“label group”) as a field of the classification result. For example, the classification result information shown in FIG. 7 includes a combination condition of “traffic volume 1”, “precipitation 1” and “limit speed 1” (traffic volume is 5000 vehicles / day or less and precipitation is 500 mm / day or less and Assets that are categorized as an attribute value condition with a speed limit of 20 km / h or less are asset names “pave 12-1, pave 12-2...”, “Traffic volume 1” and “precipitation 1” Assets classified as “Limited speed 2” combined conditions (attribute value condition with traffic volume of 5000 vehicles / day or less, precipitation of 500 mm / day or less and speed limit of 20 to 40 km / h), asset name “Pavement” 18-1, pavement 18-2, etc. ”, and a combination condition of“ traffic volume 1 ”,“ precipitation 1 ”and“ limit speed 3 ”(traffic volume is 5000 vehicles / day or less and precipitation is 500 mm / Attribute value condition that is less than a day and speed limit is 40km / h or more) That assets, asset name "paving 14-1, paving 14-2..." Is stored as.

[Operation of Parameter Estimation Program 22]
Next, in the asset management system according to the present embodiment, the parameter estimation program 22 is activated when the asset management system is activated or by a user at an arbitrary timing, and the following steps are executed as shown in FIG.
(1) Step S201 for obtaining classification result information from the classification result table 41 classified by the asset classification program 21.
(2) The “asset name” included in the classification result information acquired in step S201 and the “asset name” stored in the inspection database 32 are combined to acquire a set R of “elapsed years” and “soundness”. Step S202.

The “soundness” acquired in step S202 is the value of the “soundness” field of the inspection database 32, and the “elapsed years” is the number of years from the service of the asset to the inspection. The value of the “service year” field obtained by combining with the “asset name” of the asset database 31 from the value of the “field”. Note that the method of acquiring “elapsed years” and “soundness” according to the present invention is not limited to the above-described method, and for example, an “elapsed year” field is stored in the inspection database 32 and the values are directly stored. It may be a technique used as an elapsed year.

(3) Step S203 for estimating the parameters of the deterioration prediction model from the algorithm expression of the deterioration prediction model and the combination (set R) of “elapsed years” and “soundness” obtained by the above-described steps.
(4) Step S204 that determines whether or not there is a next classification and returns to Step S204 when it is determined that there is.
(5) Step S205 for storing each parameter estimated in Step S203 in the estimated parameter table 42.

The contents of the degradation prediction model list 34 for performing the algorithm estimation in step S203 include, for example, “least squares method” and “maximum likelihood estimation ( (Maximum likelihood estimation) ”. In this “least square method”, “y = aX + 10” and “y = aX ² + bX + 10” are set, and the “maximum likelihood estimation” equation is “P (X, Y) = n (X, Y) / n (X) "is set. In this example, in the graph shown in FIG. 10, when the algorithm of the deterioration prediction model is the least square method and the mathematical expression is “y = aX ² + bX + 10”, the above-described parameter estimation method obtains a circle in the graph. The curves in the graph in which the combinations of the elapsed years and the soundness are plotted are the curves when the coefficients a and b of the mathematical formula are obtained by the least square method.

The estimation parameter table 42 estimated in step S203 is for storing the parameters a and b of the deterioration prediction model algorithm estimated based on the asset classification. As shown in FIG. 11, the estimation parameter table 42 has a plurality of “label groups” and “parameters” (numerical values of coefficients) as fields, and a plurality of attributes (for example, traffic / precipitation) of the classification result table 41. A plurality of “labels” and “parameters” are stored as fields for estimating a deterioration state with respect to (quantity / speed limit).

[Operation of Restriction Condition Determination Program 23]
Furthermore, the asset management system according to the present embodiment starts the constraint condition determination program 23 when the asset management system is started or by the user at an arbitrary timing, and the constraint condition determination program 23 executes the next step shown in FIG. To do.
(1) Step S301 for obtaining constraint condition information from the constraint condition list 35 (FIG. 13).
(2) Among the label groups stored in the classification result table 41, a set of label groups that differ only in the attribute values described in the constraint condition 2 (subordinate constraint conditions) included in the constraint condition information acquired in step S301. Step S302 for obtaining. In this step 302, for example, when the constraint condition 2 is “precipitation”, # 1, # 4, and # 7 in FIG. 11 differ only in precipitation, and the traffic volume and the speed limit are the same. Only different label groups with the same traffic volume and speed limit are obtained.
(3) Step S303 of acquiring a set of label groups that differ only in the attribute values obtained in Step S302.
(4) Step S304 for determining whether or not the label group acquired in Step S303 satisfies the “relationship” condition with the constraint condition 1 (upper constraint condition) in the constraint condition acquired in Step S301.

In step S304, whether or not the “relationship” condition of the constraint condition 1 of the acquired label group is satisfied is determined, for example, for the label group # 1, # 4, and # 7. If the relationship is reciprocal, the number of years up to soundness level 1 is determined by solving X in the mathematical formula (1 = aX ² + bX + 10) as the value of constraint condition 1.

(5) Step S305 in which, when it is determined in step S304 that the constraint condition acquired in S301 satisfies the “relationship” condition of constraint condition 1, the determination result is set to “constraint condition”.
(6) Step S306 in which, when it is determined in step S304 that the constraint condition acquired in S301 does not satisfy the “relation” condition of the constraint condition 1, the determination result is set to “do not satisfy the constraint condition”.
(7) It is determined whether or not there is a next label group, and when it is determined that there is, step S307 returns to step S303.
(8) When it is determined in step S307 that there is no next label group, step S308 returns to step S301 when it is determined whether there is a next constraint condition.
(9) Step S309 in which determination result information is stored in the determination result table 43 (FIG. 14) when it is determined in step S308 that there is no next constraint condition.

Whether or not the constraint condition in step S304 is satisfied is determined by, for example, obtaining the value (Bn) from the asset database 31 when the constraint condition 2 is precipitation, and whether these values have a reciprocal relationship. (I.e., if Ai >> <Aj at any i, j, is Bi <> Bj (compound order))?

As described above, the asset management system according to the present embodiment can easily obtain the estimation parameter of the deterioration prediction model and the determination result information for determining whether both satisfy the consistency, using the asset database 31 and the inspection database 32. Can do.

The user interface program 25 displays a user interface screen on the output device 14 for the user. As shown in FIG. 15, the user interface screen displayed by the user interface program 25 includes an asset classification condition list display column 53, a deterioration prediction model list display column 54, and a constraint condition list display column 55 arranged at the top of the screen. The contents of the asset classification condition list 33, the deterioration prediction model list 34, and the constraint condition list 35 are displayed in the respective columns 53 to 55, and the calculation start button 61, the document output button 62, and the determination result are displayed at the bottom of the screen. A display field 73 and a document display field 74 are arranged. When any item in the asset classification condition list display field 53, the deterioration prediction model list display field 54, or the constraint condition list display field 55 on the user interface screen is designated by the user, the user interface program 25 Select whether to enable or disable the specified item.

The user interface program 25 executes the asset classification program 21, the parameter estimation program 22, and the constraint condition determination program 23 in order when the calculation start button 61 is pressed by the user. At this time, each program operates as follows only for items specified by the user as valid in the asset classification condition list display field 53, the deterioration prediction model list display field 54, and the constraint condition list display field 55.
The constraint condition determination program 23 is
(1) The contents of the output discrimination result table 43 are displayed in the discrimination result display field 73.
(2) The user refers to the discrimination result display field 73 and specifies the items in the asset classification condition list display field 53, the deterioration prediction model list display field 54, and the constraint condition list display field 55, and then presses the calculation start button 61 By repeatedly pressing the button, an appropriate estimation parameter is obtained.
(3) When the user presses the document output button 62, the document output program 24 reads the document template 36, replaces the tags described in the document template 36, and outputs the contents of the document table 44 in the document display column 74. When the user presses the combination button 63, the combination program 26 is executed.

As shown in FIG. 16, the document template 36 read by the document output program 24 includes “deterioration prediction model list @ name” and “deterioration prediction model @ description” including “deterioration prediction model list”, asset classification conditions and classification. It has item information of “asset classification” including the result and parameters of each classification. The document template 36 is a portion in which the tag in FIG. 1 is surrounded by <>, and this tag describes a table identifier and an attribute identifier, and refers to a value of an arbitrary table (database, list, intermediate result). Can do. For example, in the case of tag ** asset classification condition: attribute name>, the table identifier is “asset classification condition” and the attribute identifier “attribute name”, and the value of the attribute name field of the asset classification condition list 33 is output. * Indicates that a plurality of values are output as a list. As this document template 36, an arbitrary sentence other than the contents described in the table can be defined, selected according to the execution result of the program, and reflected in the document template. Here, for a tag including @ as in <deterioration prediction model list @name>, a sentence is selected with reference to the document template element list 37.

The document template element list 37 includes item information such as a reference table, a tag name, a condition (expression), and a sentence (element) as shown in FIG. In the illustrated example of the document template element list 37, a sentence (element) whose condition for the tag name of the reference table “deterioration prediction model list” is “# = 1” is “regression curve (linear expression)”. Is described. In the document output program 24, when the fields are <reference table>, <tag name>, <condition>, and <sentence>, and the tag <deterioration prediction model list @name>, the <reference table> is set as “deterioration prediction”. Model list ”is extracted, and records # 1, # 2, and # 3 whose <tag name> is“ name ”are extracted, and records that satisfy the conditions indicated in the <condition> field of each record are extracted as“ deterioration prediction models ”. If it is included in the deterioration prediction model list 34 indicated by “list”, the value of the <sentence> field is output.

[Combination program 26 operation]
The combination program 26 activated by the user pressing the combination button 63 executes the following operation as shown in FIG.
(1) Step S601 for listing valid / invalid combination patterns of each element of the asset classification condition list 33 and the deterioration prediction model list 34.
Since the asset classification condition list 33 in this step S601 can designate valid / invalid for each item, the number of combination patterns is 2 to the power of the number of items, and only one of the items in the degradation prediction model list 34 is valid and the others are invalid. Therefore, the number of combination patterns is equal to the number of items, and thus the total number of combinations is “2 (the number of items in the asset classification condition list)” × (the number of items in the degradation prediction model list 34).
Execute.

(2) Step S602 that acquires the next combination from the combination set listed in step S601 and sets whether the combination is valid or invalid.
(3) Based on the validity / invalidity setting in step S602, the asset classification program 21, the parameter estimation program 22, the constraint condition determination program 23, and the document output program 24 are executed and obtained by executing the document output program 24. An estimated parameter, discrimination result information, and document information are stored in the estimation parameter table 42, discrimination result table 43, and document table 44, respectively (step S603).
(4) Step S604 in which it is determined whether or not there is a next combination, and when it is determined that there is a next combination, the process returns to Step S602.

(5) When it is determined in step S604 that there is no next combination (determination that all the combination processes are completed), each information (estimated parameter, determination result) stored in the estimated parameter table 42, the determination result table 43, and the document table 44 Information, document information) is applied with consistency criteria, and the combination with the highest consistency is selected (step S605).
(6) Step S606 that adopts the estimated parameter, discrimination result information, and document information of the combination selected in step S605 and stores them in the estimation parameter table 42, discrimination result table 43, and document table 44, respectively.

The consistency criterion in step S605 includes, for example, the number of items that the determination result information does not satisfy the constraint condition of the attribute value condition, the number of lines of document information, the number of characters, the amount of recorded information (consumed memory), or a combination thereof. It is assumed that the consistency is high when the number of items that do not satisfy this constraint is small or the document size is small.

The asset management system according to the present embodiment adopts the combination estimation parameter, the determination result information, and the document information selected in step S605 of the combination program 26, and reflects them in the user interface of FIG. As a result, this asset management system does not require the user to select the asset classification condition list 33 or the deterioration prediction model list 34, and uses the result of automatically performing selection that is considered highly consistent. Supports statistical data processing by non-expert users and promotes the spread of asset management and long-life plans.

The present invention not only estimates the parameters of a deterioration prediction model for road social infrastructure maintained by local governments, but also provides a reasonable statistical model while classifying, estimating and verifying data with insufficient quantity and accuracy from various viewpoints. Can be used for computer systems that need to

11 arithmetic units, 12 storage units, 13 input units, 14 output units,
21 asset classification program, 22 parameter estimation program,
23 constraint condition determination program, 24 document output program,
25 user interface programs, 26 combination programs,
31 asset database, 32 inspection database, 33 asset classification condition list,
34 degradation prediction model list, 35 constraint condition list, 36 document template,
37 document template element list, 41 classification result table,
42 Estimated parameter table, 43 Discrimination result table, 44 Document table,
53 asset classification condition list display field, 54 deterioration prediction model list display field,
55 constraint list display field, 61 calculation start button, 62 document output button,
63 Combination buttons, 73 Discrimination result display field, 74 Document display field

Claims

Asset database for storing asset information including asset name and multiple attribute information of infrastructure (Social infrastructure), infrastructure asset name, inspection year for checking the asset, and health check information indicating the state of the asset Degradation prediction including an inspection database to be stored, an asset classification condition list storing classification condition information including attribute names to which the asset belongs and a plurality of attribute conditions for the asset, and an algorithm / formula / coefficient for predicting the deterioration of the asset A deterioration prediction model list for storing information, a restriction condition list for storing constraint information including a plurality of constraint conditions for the asset and the relationship between the plurality of constraint conditions, and a deterioration prediction model including an algorithm, a mathematical expression, and a coefficient for the user Document template for storing a plurality of standard documents including tags for explaining a derivation method, and the document Document template element list for storing elements of algorithms, mathematical formulas, and coefficients referred to in the template, a classification result table for storing classification result information including asset names for combinations of a plurality of attributes as classification results, and the classification result table A determination parameter table for storing an estimation parameter for estimating a deterioration state for a plurality of attributes of the image, and a determination result information for determining whether a relationship between the estimation parameter table and the plurality of estimation parameters satisfies consistency A storage device for storing a result table and a document table for storing a plurality of standard documents for describing a method for deriving a deterioration prediction model for a user created by referring to the document template and the document template element list;
An arithmetic device that predicts asset repair and update by referring to the storage device and predicting asset deterioration;
Asset classification condition list display field, deterioration prediction model list display field, constraint condition list display field, asset classification condition list, deterioration prediction model list, restriction condition list, calculation start button, document output button, discrimination result display field, and document display field And a display device for displaying
An asset management system comprising:
The arithmetic unit is
An asset classification program for storing classification condition information obtained by classifying assets based on asset names and attribute information in a classification result table;
A parameter estimation program for estimating parameters for performing deterioration prediction for each asset based on the classification result information classified by the asset classification program;
A constraint condition determination program for storing determination result information determined based on the constraint condition information stored in the constraint condition list in a determination result table;
A document output program that reads the standard document of the document template, replaces the tags described in the standard document based on the constraint condition information, and outputs to the document table;
Based on the input instructions input by the user, the asset classification program, parameter estimation program, and constraint condition determination program are executed to obtain the estimated parameters, the document output program reads the standard document of the document template, and is described in the standard document An asset management system that executes a user interface program that replaces tags based on constraint information and outputs them to a document table.
The asset classification program is
A first step of acquiring an asset classification condition by a combination of an attribute name and an attribute value condition specified from the asset classification condition list;
A second step of acquiring asset information from the asset database based on the asset classification condition acquired in the first step;
A third step of generating intermediate data in which a label is added to the asset information acquired in the second step based on the asset classification condition acquired in the second step;
A fourth step of determining whether or not the next asset information is present in the asset classification condition list, and returning to the second step when it is determined that the asset classification condition list is present;
When it is determined that there is no next asset information in the fourth step, it is determined whether there is a next asset classification condition, and when it is determined that there is, a fifth step that returns to the first step of the step;
When it is determined that there is no next asset classification condition in the fifth step, the asset information having the same label is grouped from the intermediate data, and the sixth step of storing in the classification result table is executed, whereby the classification result table The asset management system according to claim 1, wherein the asset management system is operable to store the classification result information in.
The parameter estimation program is
A seventh step of acquiring classification result information from the classification result table classified by the asset classification program;
An eighth step of acquiring a set of elapsed years and soundness levels corresponding to the asset name from the inspection database using the asset name included in the classification result information acquired in the seventh step as a key;
A ninth step of estimating the parameters of the deterioration prediction model from the set of elapsed years and soundness obtained in the eighth step based on the algorithm formula of the deterioration prediction model;
Determining whether or not there is next classification result information in the classification result table, and when it is determined that there is, a tenth step of returning to the seventh step;
The asset management system according to claim 2, wherein the eleventh step of storing the parameter estimated from the ninth step in an estimated parameter table is executed.
The constraint condition determination program is
A twelfth step of acquiring constraint condition information from the constraint condition list;
Among the label groups stored in the classification result table, a set of label groups that differ only in the attribute values described in the lower-level constraint conditions included in the constraint condition information acquired in step 12 is obtained from the estimated parameters in the estimated parameter table. 13th step;
A fourteenth step of obtaining a set of label groups that differ only in the attribute values obtained in the thirteenth step;
A fifteenth step for determining whether or not the label group acquired in the fourteenth step satisfies the relational condition with the upper constraint condition in the constraint condition acquired in the twelfth step;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step satisfies the relationship with the upper constraint condition, the sixteenth step of setting the determination result as “constraint condition”;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step does not satisfy the relationship with the upper constraint condition, the seventeenth step of setting the determination result as “does not satisfy the constraint condition”;
It is determined whether or not there is a next label group in the classification result table, and when it is determined that there is, an eighteenth step of returning to the fourteenth step;
A 19th step for returning to the twelfth step when it is determined that there is a next constraint when it is determined in the 18th step that there is no next label group;
The asset management system according to claim 3, wherein when it is determined in the nineteenth step that there is no next restriction condition, a twentieth step of storing the determination result information in the determination result table is executed.
The combination program is
A 21st step of enumerating valid / invalid combination patterns of each element of the asset classification condition list and the deterioration prediction model list;
A 22nd step of obtaining the next combination from the combination set listed in the 21st step and setting whether the combination is valid or invalid;
5. The asset management system according to claim 4, wherein the asset classification program, the parameter estimation program, and the constraint condition determination program are executed based on the setting of validity or invalidity in the twenty-second step.
An asset database that stores asset information including infrastructure asset names and multiple attribute information, and an inspection database that stores infrastructure asset names, inspection years for checking the assets, and health check information indicating the state of the assets And an asset classification condition list that stores classification condition information including the attribute name to which the asset belongs and a plurality of attribute conditions for the asset, and deterioration prediction information including an algorithm, a mathematical expression, and a coefficient for predicting the deterioration of the asset. Describes a degradation prediction model list, a constraint list that stores constraint conditions including multiple constraints and multiple constraint conditions for assets, and a method for deriving a degradation prediction model that includes algorithms, formulas, and coefficients for users A document template for storing a plurality of standard documents including a tag to be used, an algorithm and a mathematical expression referred to by the document template, Document template element list that stores a number of elements, a classification result table that stores classification result information including asset names for combinations of a plurality of attributes that are classification results, and estimates degradation states for a plurality of attributes of the classification result table An estimation parameter table for storing an estimation parameter for determining, a determination result table for storing determination result information for determining whether the relationship between the estimation parameter table and the plurality of estimation parameters satisfies consistency, the document template, and the document A storage device for storing a document table for storing a plurality of standard documents for explaining a method for deriving a deterioration prediction model for a user created with reference to the template element list, and asset deterioration with reference to the storage device A computing device that makes predictions to predict asset repairs and updates, and asset classification condition lists Display field, deterioration prediction model list display field, constraint condition list display field, asset classification condition list, deterioration prediction model list, constraint condition list, calculation start button, document output button, discrimination result display field, and document display field An asset management method using a computer system comprising a display device,
In the arithmetic unit,
An asset classification program for storing classification condition information obtained by classifying assets based on asset names and attribute information in a classification result table;
A parameter estimation program for estimating parameters for performing deterioration prediction for each asset based on the classification result information classified by the asset classification program;
A constraint condition determination program for storing determination result information determined based on the constraint condition information stored in the constraint condition list in a determination result table;
A document output program that reads the standard document of the document template, replaces the tags described in the standard document based on the constraint condition information, and outputs to the document table;
Based on the input instructions input by the user, the asset classification program, parameter estimation program, and constraint condition determination program are executed to obtain the estimated parameters, the document output program reads the standard document of the document template, and is described in the standard document An asset management method for executing a user interface program that replaces a tag based on constraint information and outputs the tag to a document table.
The computing device is an asset classification program,
A first step of acquiring an asset classification condition by a combination of an attribute name and an attribute value condition specified from the asset classification condition list;
A second step of acquiring asset information from the asset database based on the asset classification condition acquired in the first step;
A third step of generating intermediate data in which a label is added to the asset information acquired in the second step based on the asset classification condition acquired in the second step;
A fourth step of determining whether or not the next asset information is present in the asset classification condition list, and returning to the second step when it is determined that the asset classification condition list is present;
When it is determined that there is no next asset information in the fourth step, it is determined whether there is a next asset classification condition, and when it is determined that there is a fifth step, the fifth step returns to the first step;
When it is determined that there is no next asset classification condition in the fifth step, the asset information having the same label is grouped from the intermediate data, and the sixth step of storing in the classification result table is executed, whereby the classification result table The asset management method according to claim 6, wherein the asset management method is operated so as to store classification result information.
The arithmetic device is a parameter estimation program,
A seventh step of acquiring classification result information from the classification result table classified by the asset classification program;
An eighth step of acquiring a set of elapsed years and soundness levels corresponding to the asset name from the inspection database using the asset name included in the classification result information acquired in the seventh step as a key;
A ninth step of estimating the parameters of the deterioration prediction model from the set of elapsed years and soundness obtained in the eighth step based on the algorithm formula of the deterioration prediction model;
Determining whether or not there is next classification result information in the classification result table, and when it is determined that there is, a tenth step of returning to the seventh step;
The asset management method according to claim 7, wherein the eleventh step of storing the parameter estimated from the ninth step in an estimated parameter table is executed.
The arithmetic unit is a constraint condition determination program,
A twelfth step of acquiring constraint condition information from the constraint condition list;
Among the label groups stored in the classification result table, a set of label groups that differ only in the attribute values described in the lower-level constraint conditions included in the constraint condition information acquired in step 12 is obtained from the estimated parameters in the estimated parameter table. 13th step;
A fourteenth step of obtaining a set of label groups that differ only in the attribute values obtained in the thirteenth step;
A fifteenth step for determining whether or not the label group acquired in the fourteenth step satisfies the relational condition with the upper constraint condition in the constraint condition acquired in the twelfth step;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step satisfies the relationship with the upper constraint condition, the sixteenth step of setting the determination result as “constraint condition”;
In the fifteenth step, when it is determined that the constraint condition acquired in the twelfth step does not satisfy the relationship with the upper constraint condition, the seventeenth step of setting the determination result as “does not satisfy the constraint condition”;
It is determined whether or not there is a next label group in the classification result table, and when it is determined that there is, an eighteenth step of returning to the fourteenth step;
A 19th step for returning to the twelfth step when it is determined that there is a next constraint when it is determined in the 18th step that there is no next label group;
The asset management method according to claim 8, wherein when it is determined in the nineteenth step that there is no next constraint condition, a twentieth step of storing the determination result information in the determination result table is executed.
The arithmetic unit is a combination program,
A 21st step of enumerating valid / invalid combination patterns of each element of the asset classification condition list and the deterioration prediction model list;
A 22nd step of obtaining the next combination from the combination set listed in the 21st step and setting whether the combination is valid or invalid;
The asset management method according to claim 9, wherein the asset classification program, the parameter estimation program, and the constraint condition determination program are executed based on the setting of validity or invalidity in the twenty-second step.