JP6235947B2 - Asset management system and asset management method - Google Patents

Description

  The present invention relates to an asset management system and an asset management method for managing and operating assets such as road social infrastructure maintained and managed by local governments using a computer system, and in particular, predicting asset deterioration and predicting repair or update of assets. Asset management system and asset management method.

  In general, an asset management system that manages and operates road social infrastructure maintained and managed by local governments using a computer system predicts the degree of asset deterioration based on inspection results, and calculates total repair costs (life cycle costs). It is necessary to use theoretical and reasonable mathematical formulas and coefficients in the method for predicting the degree of deterioration, and when the asset inspection results include a lot of noise or the inspection results are sufficiently obtained. When it is not possible to do so, it is a work that requires specialized knowledge, and it is known that such work is often entrusted to specialists such as consultants.

  In addition, the following patent document is mentioned as a document describing the technology related to asset management of a structure such as a bridge according to the prior art, and this patent document 1 is an input for inputting inspection data of the deterioration state of the structure. Means for calculating a deterioration curve indicating the degree of deterioration with respect to the elapsed years from the input inspection data, and a display means for displaying the input inspection data and the deterioration curve. An elapsed age classifying unit that is extracted for each elapsed age section, an average degradation degree calculating unit that calculates the average of the degradation levels classified for each elapsed age section, and an average degradation degree that is calculated for each elapsed age section. A structure deterioration curve calculation system that can predict deterioration of asset management of structures such as bridges by a deterioration curve calculation unit that calculates the deterioration curve using multiplication. There has been described.

JP 2008-291440 A

  In general, asset management and longevity plans for road social infrastructure are now required by small local governments and may not be fully implemented due to budget and personnel issues. It is difficult for a person to effectively select a deterioration prediction method (formulas and coefficients), which causes a problem that the business itself stagnate and leads to an increase in outsourcing costs.

  The technique described in the above-mentioned Patent Document 1 classifies inspection data by structure type or part and determines deterioration progress, 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. The structure degradation curve calculation system is described, but it is not assumed that consistency with the obtained degradation curve can not be obtained, the function to check consistency, classification method to ensure consistency, etc. A user interface for repeating trial and error while changing a deterioration model or the like is not provided, and there is a possibility that it is not possible to provide business support by a person or user who is not an expert.

  The object of the present invention is to solve the above-mentioned problems caused by the prior art, and to promote the spread of asset management and long-life plans by the function of supporting statistical data processing by non-expert users. It is to provide an asset management system and an asset management method that can be used.

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 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 and a plurality of constraint conditions for assets, and algorithms and mathematical formulas for users And a 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 A document template element list for storing elements of algorithms, mathematical formulas, and coefficients referred to in FIG. 4, a classification result table for storing classification result information including asset names for combinations of a plurality of attributes that are classification results, Discrimination result for storing an estimation parameter table for storing an estimation parameter for estimating a deterioration state for a plurality of attributes, and discrimination result information for discriminating whether the relationship between the estimation parameter table and the plurality of estimation parameters satisfies consistency A storage device for storing a table and 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 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 in the fourth step that there is no next asset information, it is determined whether or not there is a next asset classification condition, and when it is determined that there is a fifth step, the 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;
When it is determined in the eighteenth step that there is no next label group, it is determined whether or not there is a next constraint, and when it is determined that there is a nineteenth step that returns to the twelfth step;
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 Degradation prediction model list for storing deterioration prediction information, constraint condition list for storing constraint condition information including relations between multiple constraint conditions and multiple constraint conditions for assets, and algorithms, formulas and coefficients for users A document template for storing a plurality of standard documents including tags for explaining a method for deriving a deterioration prediction model, and an application referred to by the document template A document template element list for storing elements of a algorithm, a mathematical expression, and a coefficient; a classification result table for storing classification result information including asset names for combinations of a plurality of attributes that are 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 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 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 in the fourth step that there is no next asset information, it is determined whether or not there is a next asset classification condition, and when it is determined that there is a fifth step, the 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;
When it is determined in the eighteenth step that there is no next label group, it is determined whether or not there is a next constraint, and when it is determined that there is a nineteenth step that returns to the twelfth step;
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.

  The asset management system and the asset management method according to the present invention include an asset classification program in which a computing device stores classification condition information obtained by classifying assets based on asset names and attribute information in a classification result table, and the asset classification program classifies the asset classification program. A parameter estimation program for estimating parameters for performing deterioration prediction for each asset based on classification result information, and a constraint for storing discrimination result information determined based on constraint condition information stored in a constraint condition list in a discrimination result table Assets based on a condition determination program, a document output program that reads a standard document of a document template, replaces tags described in the standard document based on constraint condition information, and outputs them to a document table, and an input instruction input by the user Classification program, parameter estimation program and constraints A user interface program that obtains estimated parameters by executing a separate program, reads the standard document of the document template by the document output program, replaces the tags described in the standard document based on the constraint condition information, and outputs to the document table By executing it, it is possible to promote the spread of asset management and long-life plans by the function of supporting statistical data processing by users who are not experts.

The figure for demonstrating the structure of the asset management system by embodiment of this invention. The figure for demonstrating the asset database by this embodiment. The figure for demonstrating the inspection database by this embodiment. The figure for demonstrating the asset classification condition list | wrist by this embodiment. The operation | movement flowchart of the asset classification program by this embodiment. The figure which shows the example of intermediate data produced by the asset classification program by this embodiment. The figure for demonstrating the classification result by this embodiment. The operation | movement flowchart of the parameter estimation program by this embodiment. The figure for demonstrating the degradation prediction model list by this embodiment. The figure for demonstrating the parameter estimation method of the parameter estimation program by this embodiment. The figure for demonstrating the estimation parameter by this embodiment. The operation | movement flowchart of the constraint condition discrimination | determination program by this embodiment. The figure for demonstrating the constraint condition list | wrist by this embodiment. The figure for demonstrating the discrimination | determination result database by this embodiment. The figure which shows the example of a user interface screen by this embodiment. FIG. 6 is a diagram showing an example of a document template according to the present embodiment. The figure for demonstrating the document template element by this embodiment. The operation | movement flowchart of the combination program by this embodiment.

Hereinafter, 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 the 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. In addition, a part or all of the data in the storage device 12 may be arranged in an external storage device so that data can be read and written via a network.

  The data group includes an asset database 31 for storing asset information such as road social infrastructure maintained by the local government, an asset name (for example, a road pavement name) such as infrastructure, and an inspection year for inspecting the asset. Inspection database 32 for storing inspection information such as soundness level indicating the state of the asset, attribute names (for example, traffic volume, precipitation amount, speed limit) to which the asset (for example, road pavement) belongs, and a plurality of attributes for the asset Asset classification condition list 33 for storing classification condition information including conditions (for example, traffic value, precipitation value, speed limit value), and deterioration including algorithms, mathematical formulas, and coefficients for predicting asset deterioration A deterioration prediction model list 34 for storing prediction information, a plurality of constraints on assets (for example, attributes “traffic volume / precipitation / restricted speed” for soundness values for a predetermined number of years) and a plurality of constraints A constraint condition list 35 for storing constraint condition information including the relationship of (for example, the magnitude relationship with respect to the attribute “traffic volume” with respect to the year of soundness level 1), and a deterioration prediction model including algorithms, mathematical formulas, and coefficients for the user A document template 36 for storing a plurality of standard documents for explaining a derivation method, and a document template element list 37 for storing elements such as algorithms, mathematical formulas, and coefficients referred to by the document template 36 are provided.

  The calculation result group includes 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; An estimation parameter table 42 for storing an estimation parameter for estimating a degradation state for a plurality of attributes (for example, traffic volume, precipitation amount, speed limit), an estimation parameter table 42 for a degradation prediction model, and a plurality of estimation parameters A determination result table 43 for storing determination result information for determining whether a relationship satisfies consistency, and a method for deriving a deterioration prediction model for a user created by referring to the document template 36 and the document template element list 37 will be described. A document table 44 for storing a plurality of documents to be recorded.

  The program group is various programs for the computer to execute the asset management method according to the present embodiment, and the classification result information obtained by classifying the assets having the same label group based on the classification condition information in the classification result table 41. Asset classification program 21 to be stored, parameter estimation program 22 for estimating parameters for performing deterioration prediction for each asset based on the classification result information classified by the asset classification program 21, and constraints stored in the constraint condition list 35 The constraint condition determination program 23 that stores the determination result information determined based on the condition information in the determination result table 43, and the document output that reads the document template 36, replaces the tag described in the document template 36, and outputs it to the document table 44 Program 24 and asset classification conditions shown in FIG. List display field 53, deterioration prediction model list display field 54, constraint condition list display field 55, calculation start button 61, document output button 62, combination button 63, program discrimination result display field 73, and document display field 74 , 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 the document output program 24 executes the document template 36. A user interface program 25 that reads the standard document, replaces the tags described in the document template 36, and outputs them to the document table 44.

  The program group is read into the arithmetic unit 11 as necessary and the contents thereof are executed, and 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, the document template element The list 37 assumes a table of a relational database management system generally used in the present embodiment, but the present invention is not limited to these.

[Database table configuration]
The asset database 31 stores one record for each asset target managed by the asset management system according to the present embodiment. As shown in FIG. 2, the asset name for uniquely identifying the asset and the asset are used. For example, an asset that consists of the service year that represents the year in which the property was poured, the traffic volume (vehicles / day), the annual precipitation (mm), the speed limit (km / h), and other item information when the asset is paved. The name “Pavement 1-1” is in service year “1977”, the traffic volume is “3000 cars / day”, the annual precipitation is “1200 mm”, and the speed limit is “20 km / h”. Yes.

  As shown in FIG. 3, the inspection database 32 inspects each item information such as an asset name such as infrastructure (for example, a road pavement name), an inspection year for inspecting the asset, and a soundness level indicating the state of the asset. The information is stored as information. 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. For example, the attribute value condition 1 of the attribute name “traffic volume” is “X < 5000 ”(traffic volume is less than 5000 vehicles / day), attribute condition value 2 is“ 5000 <= 5000 ”(traffic volume is 5000 vehicles / day or more), and attribute value condition 1 of the attribute name“ rainfall ”is“ X <500 (precipitation is less than 500 mm / day), attribute value condition 2 is “500 <= X <1000” (precipitation is 500 mm / day or more and less than 1000 mm / day), and attribute value condition 3 is “1000 <=. X ”(precipitation is 1000 mm or less), attribute value condition 1 of attribute name“ restricted speed ”is“ 0 <= X <20 ”(restricted speed is 20 km / h or less), and attribute value condition 2 is“ 20 < = X <40 "(the speed limit is 20 km / h or more and 40 km / h or less ), It is stored attribute value condition 3 is "40 <= X" (less than the speed limit 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 algorithms, mathematical formulas, and coefficients for predicting asset deterioration. For example, as shown in FIG. y = aX + 10 ”, and the fact that the coefficient is a is stored.

  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. For example, the relationship between the “years until the soundness level 1” in the constraint condition 1 and the “traffic volume” in the constraint condition 2 is “reverse” ( Restriction condition 1 “years to soundness level 1” and restriction condition 2 “traffic volume” are in a conflicting relationship. For example, if “traffic volume” is small, “years to soundness level 1” becomes longer and “traffic volume” ”Is a relationship that reduces the“ years to soundness level 1 ”) Stores.

  The document template 36 stores 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. As shown in FIG. As the derivation method, “selection of deterioration prediction model” and “asset classification” are required, and “selection of deterioration prediction model” is “deterioration prediction model list @ name” (@ indicates any list name) and “deterioration”. This is a description of the “prediction model @” and stores details of “asset classification”.

  The document template element list 37 stores elements such as algorithms, mathematical formulas, and coefficients referred to by the document template 36. As shown in FIG. 17, a reference table, a tag name, a condition (formula), and a sentence ( For example, a sentence (element) whose condition is “# = 1” for the tag name “name” in the reference table “deterioration prediction model list” is “regression curve (primary)”. Is stored.

  The classification result table 41 stores classification result information which is an asset name for a combination of a plurality of attribute value conditions which are classification results. As shown in FIG. For example, asset names “pavement 12-1, pavement 12-2...” For combinations of “traffic volume 1” “precipitation 1” “restricted speed 1” 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 the 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 asset classification program 21, parameter estimation program 22, constraint condition determination program 23, and the like described above in response to an operation by 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 prediction is performed to predict asset repair and update. Next, the operation of each program will be described. .

[Operation of asset classification program 21]
First, in the asset management system according to the present embodiment, the asset classification program 21 is activated when the asset management system is activated or at any timing by the user, and the asset classification designated from the asset classification condition list 33 as shown in FIG. Step S101 for obtaining a condition (combination of attribute name and attribute value condition), Step S102 for obtaining asset information from the asset database 31, and the asset information obtained in Step S102 based on the asset classification condition obtained in Step S102. The asset information stored in the asset database 31 (FIG. 2) is classified based on the classification condition information of # 1 to # 3 in the asset classification condition list 33 (FIG. 4) by executing the step S103 for adding a label. Operates to create intermediate data.

  This intermediate data is assigned to each asset as a classification result as a label. In the example shown in the figure, asset information identified by the asset “Pavement 1-1” is classified using # 1 of the asset classification condition list 33. The <traffic volume> of the asset “Pavement 1-1” is 3000 units / day, and is created so as to set the label “traffic volume 1” to satisfy “X <5000” of <attribute value condition 1>. .

  Next, the asset classification program 21 according to the present embodiment determines whether or not there is the next asset information. When it is determined that there is the next asset, step S104 returns to step S102, and there is no next asset by the step S104. When it is determined that there is a next asset classification condition, step S105 returns to step S101 when it is determined that there is a next asset classification condition, and when it is determined that there is no next asset classification condition (step S105) ( By executing step S106 for storing a group of labels obtained by grouping asset information having the same label from the intermediate data in the classification result table 41 as classification result information after the processing of all asset classification conditions is completed. 7 operates to store classification result information as shown in the classification result table 41 of FIG.

  This classification result information has an “asset name” list corresponding to a plurality of “labels” as a field of the classification result. For example, a combination condition of “traffic volume 1” “precipitation 1” “restricted speed 1” (traffic Assets categorized under the conditions of 5,000 vehicles / day or less, precipitation of 500 mm / day or less and speed limit of 20 km / h or less) are the asset names “Pave 12-1, Pave 12-2,. ”,“ Traffic volume 1 ”,“ precipitation 1 ”, and“ limit speed 2 ”assets (attributes where the traffic volume is 5000 vehicles / day or less, precipitation is 500 mm / day or less, and the speed limit is 20 to 40 km / h) Assets classified under the condition of (value condition) are asset names “Pave 18-1, Pave 18-2...”, “Traffic volume 1” “Precipitation 1” “Speed limit 3” (Traffic volume is 5000) Table / day or less, precipitation is 500 mm / day or less, and the speed limit is Assets that are classified in terms of 0km / h or more attribute values conditions) 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 at the time of activation of the asset management system or at any timing by the user, and the classification result classified by the asset classification program 21 as shown in FIG. Step S201 for obtaining the classification result information from the table 41, the “asset name” included in the classification result information obtained in the step S201 and the “asset name” stored in the inspection database 32 are combined, and “elapsed years” is obtained. Step S202 for obtaining the set R of “soundness” is executed.

  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.

  Next, the parameter estimation program 22 according to the present embodiment calculates the parameters of the degradation prediction model from the algorithm formula of the degradation prediction model and the combination (set R) of “elapsed years” and “soundness” obtained by the above steps. Step S203 for determining the next classification, whether or not there is the next classification, step S204 for returning to step S201 when it is determined that the respective parameters estimated from step S203 are stored in the estimation parameter table 42 Step S205 is executed.

The contents of the deterioration prediction model list 34 for performing the algorithm estimation in step S203 include, for example, “least square method” and “maximum likelihood estimation” as algorithms as processing procedures, as shown in FIG. “Y = ax + 10” and “y = ax ² + bx + 10” are set as mathematical formulas of the “square method”, and “P (X, Y) = n (X, Y) / n (X)” is established as the mathematical formula of “maximum likelihood estimation”. 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 formula is “y = ax ² + bx + 10”, the parameter estimation method described above is The curve in the graph plotting the combination of the number of years and the soundness with which the mark is obtained is a curve when the coefficients a and b of the mathematical formula are obtained by the method of least squares.

  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, and as shown in FIG. It has “label group” (label group) and “parameter” (numerical value of coefficient), and estimates the deterioration state for a plurality of attributes (for example, traffic volume, precipitation amount, speed limit) of the classification result table 41. A plurality of “labels” and “parameters” are stored as fields for this purpose.

[Operation of restriction condition determination program 23]
Furthermore, in the asset management system according to the present embodiment, the constraint condition determination program 23 is started when the asset management system is started or by a user at an arbitrary timing, and the constraint condition determination program 23 has a constraint condition list as shown in FIG. Step S301 for obtaining the constraint condition information from 35 (FIG. 13), and among the label groups stored in the classification result table 41, the constraint condition 2 (subordinate constraint condition) included in the constraint condition information obtained in Step S301. Step S302 for obtaining a set of label groups that differ only in the attribute values described (for example, when the constraint condition 2 is “rainfall”, # 1, # 4, and # 7 in FIG. Since the speed limit is the same, such a label group is obtained), and the attribute value obtained in step S302 Step S303 for acquiring a set of different label groups, and whether the label group acquired in Step S303 satisfies the “relationship” condition with the constraint condition 1 (higher constraint condition) in the constraint condition acquired in Step S301 And step S304 for determining whether or not.

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 until the soundness level 1 is determined by solving x in the formula (1 = ax ² + bx + 10) as the value of constraint condition 1.

  Next, when the constraint condition determination program 23 according to the present embodiment determines that the constraint condition acquired in S301 in step S304 satisfies the “relationship” condition of the constraint condition 1, the determination result is “a constraint condition is satisfied”. Step S305, and when it is determined that the constraint condition acquired in S301 in step S304 does not satisfy the “relation” condition of constraint condition 1, the determination result is set to “does not satisfy the constraint condition”. If it is determined whether there is a next label group, step S307 returns to step S303 when it is determined that there is a next label group, and if it is determined in step S307 that there is no next label group, Step S308 returns to Step S301 when it is determined whether or not there is, When it is judged that there is no next constraint in said step S308, it operates to perform the steps S309 to store the determination result information on the determination result table 43 (FIG. 14).

  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 to the user on the output device 14, and the user interface screen displayed by the user interface program 25 is arranged at the top of the screen as shown in FIG. An asset classification condition list display field 53, a deterioration prediction model list display field 54, and a constraint condition list display field 55 are arranged, and the asset classification condition list 33, the deterioration prediction model list 34, and the restriction condition list are arranged in these fields 53 to 55, respectively. 35, the calculation start button 61, the document output button 62, the discrimination result display field 73, and the document display field 74 are arranged at the bottom of the screen, and the user arranges the asset classification condition list display field 53 and the deterioration prediction model. When any item in either the list display field 54 or the constraint condition list display field 55 is designated It can be selected to enable or disable of the specified item.

  When the calculation start button 61 is pressed by the user, the user interface program 25 sequentially executes the asset classification program 21, the parameter estimation program 22, and the constraint condition determination program 23. At this time, each program executes the asset classification condition. After being operated so as to perform processing using only items designated as valid by the user in the list display column 53, the deterioration prediction model list display column 54, and the constraint condition list display column 55, it is output by the constraint condition determination program 23. The contents of the discrimination result table 43 are displayed in the discrimination result display column 73, and the user refers to the discrimination result display column 73 to display the asset classification condition list display column 53, the deterioration prediction model list display column 54, and the constraint condition list display column 55. By repeatedly pressing the calculation start button 61 following the designation of each item, appropriate estimation parameters can be obtained. Next, when the user presses the document output button 62, the document output program 24 is executed, and the document output program 24 reads the document template 36 and replaces the tags described in the document template 36. The contents of the document table 44 to be output are displayed in the document display field 74, and 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. The result has a “asset classification” including parameters and parameters of each classification, and the tag in the figure is a portion surrounded by <>. This tag describes a table identifier and an attribute identifier, and an arbitrary table (database, List, intermediate result) values can be referenced. For example, in the case of ** asset classification condition: attribute name, the table identifier “asset classification condition” and attribute identifier “attribute name” are output, 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.

  This document template element list 37 has item information of a reference table, a tag name, a condition (formula), and a sentence (element) as shown in FIG. 17, for example, a tag of the reference table “deterioration prediction model list” It is stored that a sentence (element) with a name “name” and a condition “# = 1” is “regression curve (linear expression)”, and the fields are <reference table>, <tag name>, < In the case of a tag having <condition> and <sentence> and <deterioration prediction model list @name>, first, record # 1, in which <reference table> is "deterioration prediction model list" and <tag name> is "name" Extract # 2 and # 3. When a record that satisfies the condition indicated in the <condition> field of each record is included in the deterioration prediction model list 34 indicated by the “deterioration prediction model list”, the value of the <sentence> field is output. .

[Combination program 26 operation]
The combination program 26 activated when the user presses the combination button 63 enumerates the valid / invalid combination patterns of the elements of each list of the asset classification condition list 33 and the deterioration prediction model list 34 as shown in FIG. S601 is executed. 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. Therefore, the total number of combinations is “(2 (the number of items in the asset classification condition list)) × (the number of items in the deterioration prediction model list 34).

  Next, the combination program 26 obtains the next combination from the combination set enumerated in step S601, sets whether the combination is valid or invalid, and based on the valid / invalid 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 the estimated parameter, the determination result information, and the document information obtained by executing the document output program 24 are determined from the estimated parameter table 42. Step S603 stored in each of the result table 43 and the document table 44 and whether or not there is a next combination are determined. When it is determined that there is a next combination, step S604 is returned to step S602.

  Further, when the combination program 26 determines in step S604 that there is no next combination (determined that all the combination processes have been completed), the information stored in the estimated parameter table 42, the determination result table 43, and the document table 44 ( (Step S605 for applying the consistency standard to the estimated parameters, discrimination result information, and document information) to select the combination with the highest consistency, the estimation parameter of the combination selected in Step S605, the discrimination result information, and the document information. And operate to execute step S606 for storing in the estimated parameter table 42, the discrimination result table 43, and the 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 discrimination result information, and the document information selected in step S605 of the combination program 26, and reflects them in the user interface of FIG. Statistical data processing by a user who is not an expert by using a result of automatically selecting a selection that is considered to be highly consistent without selecting an asset classification condition list 33 or a deterioration prediction model list 34 And promote the spread of asset management and long-life plans.

  The present invention not only estimates the parameters of deterioration prediction models for road social infrastructure maintained by local governments, but also provides an appropriate statistical model while classifying, estimating and verifying data with insufficient quantity and accuracy from various viewpoints. It can be used for scenes that need to be requested.

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 (10)

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. A degradation prediction model list, a constraint list storing constraint information including a plurality of constraint conditions and a plurality of constraint conditions for an asset, and a degradation prediction model derivation method including an algorithm, a mathematical expression, and a coefficient for a user Document template for storing a plurality of standard documents including tags for explanation, algorithms and mathematical formulas referred to by the document template Document template element list that stores coefficient elements, classification result table that stores classification result information including asset names for combinations of multiple attributes that are classification results, and estimation of degradation status for multiple 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 a 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 a tag based on constraint condition information and outputs the tag 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 in the fourth step that there is no next asset information, it is determined whether or not there is a next asset classification condition, and when it is determined that there is a fifth step, the 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 system according to claim 1, wherein the asset management system operates to store classification result information. 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 in 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;
When it is determined in the eighteenth step that there is no next label group, it is determined whether or not there is a next constraint, and when it is determined that there is a nineteenth step that returns to the twelfth step;
4. 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. A degradation prediction model list, a constraint list storing constraint information including a plurality of constraint conditions and a plurality of constraint conditions for an asset, and a degradation prediction model derivation method including an algorithm, a mathematical expression, and a coefficient for a user Document template for storing a plurality of standard documents including tags for explanation, algorithms and mathematical formulas referred to by the document template Document template element list that stores coefficient elements, classification result table that stores classification result information including asset names for combinations of multiple attributes that are classification results, and estimation of degradation status for multiple 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 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
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 comprising: executing a user interface program that replaces a tag based on constraint condition 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 in the fourth step that there is no next asset information, it is determined whether or not there is a next asset classification condition, and when it is determined that there is a fifth step, the 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 7. The asset management method according to claim 6, wherein the asset management method is operated so as to store the 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;
When it is determined in the eighteenth step that there is no next label group, it is determined whether or not there is a next constraint, and when it is determined that there is a nineteenth step that returns to the twelfth step;
9. 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;
10. 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.

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