KR20240024670A - Method for managing waterworks assets - Google Patents

Abstract

The method of managing the water supply assets by predicting the appropriate replacement time for old water supply assets and establishing an investment plan in an optimal manner according to an embodiment of the present disclosure is to classify the target assets into one of the facility asset group and the pipeline asset group. Step, classifying the facility asset group into different module groups considering the characteristics and functions of the assets and considering future upgrade flexibility, status for the target asset in different ways depending on the asset group into which the target asset is classified. Obtaining evaluation results and remaining lifespan, setting level of service (LoS) items and key performance indicators (KPI) according to classified asset groups, quantifying asset relevance, and obtaining LoS values for each module; A step of obtaining a business risk level (BRE) based on the probability of future failure (PoF) and the resulting degree of damage (CoF) based on the asset condition assessment results, and the remaining lifespan (RUL) and target service level information (LoS) ), calculating the investment priority (RPN) based on the business risk level (BRE), deriving the optimal improvement plan (ORDM), and establishing an investment plan for the target asset, and based on the results derived at each stage This may include presenting an asset management portfolio for key assets and establishing asset management direction and strategy.

Description

{METHOD FOR MANAGING WATERWORKS ASSETS}

The technical idea of the present disclosure relates to a water supply asset management method, and more specifically, by distinguishing between facility assets and pipeline assets in consideration of the characteristics and functions of the assets, and predicting the timely replacement time for old assets and assets using different evaluation methods. It's about how to manage.

The obsolescence of infrastructure built or created in the past has rapidly increased, and management methods to replace outdated infrastructure are difficult. Looking specifically, it is necessary to systematically identify the asset status in order to manage facility assets and pipeline assets, but there were difficulties in identifying the asset status.

An asset management system for such infrastructure can be expressed as a decision-making process and framework during the life cycle of acquisition, operation, maintenance, evaluation, and replacement of assets. In other words, the asset management system can include the organization, manpower, and costs for efficient asset management at the whole life level as all infrastructure is created.

In other words, the asset management system defines the level of service required in all processes of building and operating infrastructure, establishes short- and long-term plans through decision-making on the costs that may be incurred for this, and secures the optimal budget and distributes costs. Through this, the most reasonable maintenance operation plan can be proposed.

Conventional asset management systems use methods to evaluate the remaining lifespan of facilities or assess asset value, but all facilities are organically connected, and determining replacement priority based on simple physical remaining lifespan is a realistic method for replacing individual infrastructure. There were aspects that did not correspond to the actual asset management situation.

Meanwhile, registered patent publication “10-1567774” describes a water supply asset management system, but the asset is evaluated in different ways according to various module types classified according to the characteristics of the asset and factors influencing asset condition evaluation, and individual replacement planning is performed. There are aspects in which an embodiment that establishes cannot be presented.

Republic of Korea Patent No. 10-156774 (Application date: November 11, 2015)

The problem that the technical idea of the present disclosure seeks to solve is to provide a method related to logic developed in each step to manage assets using different evaluation methods according to different types of assets.

A method of managing the assets by establishing a replacement investment plan for the assets according to an embodiment of the present disclosure includes the steps of classifying the target assets into one of a facility asset group and a pipeline asset group, according to the asset group into which the target assets are classified. Developing an asset ledger for the target asset using different methods, evaluating the asset status based on various data entered into the asset ledger, and obtaining the remaining life, and determining the business risk based on the status evaluation results for the target asset. It may include the step of acquiring, and calculating the investment priority for the target asset based on the remaining life, target service level information, and the business risk, and establishing an investment plan in an optimal way.

According to one embodiment, the step of classifying the target asset includes, when the target asset is classified into the facility asset group, classifying the target asset into one of a plurality of module groups according to the module type and the module group. This may include developing and updating the asset ledger by acquiring different combinations of module data.

According to one embodiment, the step of assessing the asset condition and obtaining the remaining life includes, when the target asset is classified into the facility asset group, obtaining a condition evaluation result of the target asset based on influence factors for each facility asset module. It may include predicting the remaining lifespan of the target asset classified into the facility asset group based on the step and the condition evaluation result.

According to one embodiment, the step of obtaining the remaining life includes, when the target asset is classified into the pipeline asset group, the remaining life of the target asset based on a plurality of remaining life derivation models in physical, economic, and functional aspects. It may include the step of predicting lifespan.

According to one embodiment, the step of predicting the remaining life includes dividing the specifications and sections of the pipeline assets by performing a system analysis on the pipeline asset group, and damaging the target asset based on the divided specifications and sections. It may include the step of predicting the extent and cost of damage.

According to one embodiment, the step of establishing the investment plan includes a plurality of investment plan groups in which the target assets are classified into different individual priorities based on the target service level information, the business risk, and the remaining life. It may include a step of classifying one of the following.

The asset management method according to the technical idea of the present disclosure can manage assets to match the asset characteristics by evaluating the assets using different evaluation methods when managing assets with different characteristics. Accordingly, the asset management method of the present disclosure can evaluate the status of assets based on scientific analysis techniques and rational decision-making logic based on various data, predict risks, and establish an optimized replacement plan for aged assets. .

In addition, the asset management method of the present disclosure can efficiently establish an asset management plan by performing the steps of assessing the current status of assets, setting service levels, analyzing risk, optimal investment planning, and establishing long-term financial resources strategies by reflecting the characteristics of the assets. You can.

The effects that can be obtained from the exemplary embodiments of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned are common knowledge in the technical field to which the exemplary embodiments of the present disclosure belong from the following description. It can be clearly derived and understood by those who have it. That is, unintended effects resulting from implementing the exemplary embodiments of the present disclosure may also be derived by those skilled in the art from the exemplary embodiments of the present disclosure.

1 is a block diagram showing the configuration of an asset management device according to an embodiment of the present disclosure.
Figure 2 is a flowchart showing a method of establishing an asset management plan in different ways by classifying target assets into a plurality of groups according to an embodiment of the present disclosure.
Figure 3 is a flowchart illustrating a method of updating an asset ledger when a target asset is classified as a facility asset according to an embodiment.
FIG. 4 is a diagram illustrating data types for generating status evaluation results of different facility asset modules according to an embodiment.
Figure 5 is a flow chart illustrating a method of obtaining remaining life and business risk from facility assets according to one embodiment.
6 is a flow diagram illustrating how an investment plan is established in facility assets according to one embodiment.
Figure 7 is a flow chart illustrating a method of obtaining remaining life and business risk from pipeline assets according to an embodiment.
Figure 8 is a flow chart illustrating a method for establishing an investment plan for pipeline assets according to an embodiment.
Figure 9 is a flow chart illustrating a method of establishing an investment plan for pipeline assets selected as ORDM targets according to an embodiment.
Figures 10 and 11 are diagrams showing a portfolio of assets created according to an embodiment.
Figure 12 is a flowchart showing the process of establishing an asset management plan for each asset by creating an asset portfolio according to an embodiment.
Figure 13 is a diagram summarizing the steps for managing assets with US EPA 5 Core, 10 Step according to an embodiment of the present disclosure.
FIG. 14 is a diagram summarizing the concept and performance utilization of the present disclosure specifically presented for the embodiment of FIG. 13.

이하, 첨부한 도면을 참조하여 본 개시의 실시 예에 대해 상세히 설명한다.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

Figure 1 is a block diagram showing the configuration of an asset management device 10 according to an embodiment of the present disclosure.

Referring to FIG. 1, the asset management device 10 according to an embodiment of the present disclosure may include an input/output device 100, a processor 200, and a memory 300. The asset management device 10 can evaluate the current state of the target asset in the processor 200 based on data received through the input/output device 100, analyze the remaining life, and analyze the remaining lifespan in the memory 300. The data may be stored, at least temporarily.

In an embodiment, the components of the asset management device 10, the input/output device 100, the processor 200, and the memory 300 may be implemented as a single semiconductor chip, for example, the asset management device 10 ) can be implemented as a system on a chip (SoC). However, the present invention is not limited thereto, and the asset management device 10 may be implemented with a plurality of semiconductor chips. In one embodiment, the asset management device 10 may be implemented with an application processor 200 mounted on a mobile device.

The input/output device 100 may receive input data from a user or an external source and output data processing results of the asset management device 10. The input/output device 100 may be implemented using at least one of a touch screen panel, a keyboard, and various types of sensors. In an embodiment, the input/output device 100 may collect information around the asset management device 10. For example, the input/output device 100 includes at least one of various types of sensing devices such as an imaging device, an image sensor, a LIDAR (light detection and ranging) sensor, an ultrasonic sensor, an infrared sensor, or receives a sensing signal from the device. You can receive it. In an embodiment, the input/output device 100 may sense or receive an image signal from outside the asset management device 10 and convert the sensed or received image signal into image data, that is, an image frame. The input/output device 100 may store the image frame in the memory 300 or provide it to the processor 200.

The processor 200 may control the overall operation of the asset management device 10. As an example, the processor 200 may be a central processing unit (CPU). The processor 200 may include one core (Single Core) or may include multiple cores (Multi-Core). The processor 200 may process or execute programs and/or data stored in the RAM and memory 300. For example, the processor 200 may control various functions of the asset management device 10 by executing programs stored in the memory 300.

The memory 300 is a storage location for storing data, and can store, for example, an operating system (OS), various programs, and various data. The memory 300 may be DRAM, but is not limited thereto. The memory 300 may include at least one of volatile memory 300 or non-volatile memory. Non-volatile memory 300 includes read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable and programmable ROM (EEPROM), flash memory 300, phase-change RAM (PRAM), It may include Magnetic RAM (MRAM), Resistive RAM (RRAM), Ferroelectric RAM (FRAM), etc. The volatile memory 300 may include Dynamic RAM (DRAM), Static RAM (SRAM), Synchronous DRAM (SDRAM), etc. In addition, in one embodiment, the memory 300 includes a hard disk drive (HDD), solid-state drive (SSD), compact flash (CF), secure digital (SD), micro secure digital (Micro-SD), and mini- It can be implemented as a storage device such as SD (Mini Secure Digital), xD (extreme digital), or Memory Stick.

The asset management device 10 according to an embodiment of the present disclosure may classify the target asset into one of a facility asset group and a pipeline asset group based on information input to the input/output device 100. The asset management device 10 can evaluate the status of classified target assets, obtain remaining lifespan, set target service level information, and obtain business risk. The asset management device 10 may establish an investment plan for target assets based on the acquired business risk and target service level information.

At this time, the asset management device 10 of the present disclosure may evaluate the value of the target asset using different evaluation methods depending on whether the target asset is classified into the facility asset group or the pipeline asset group. In addition, the asset management device 10 may establish an investment plan for the target asset in different ways depending on the classified asset group. The asset management device 10 can evaluate the current state of the asset using various methods depending on the asset type rather than a standardized asset evaluation method, and thus can accurately calculate the remaining life for each asset type.

Hereinafter, this specification will be described with reference to FIG. 1.

Figure 2 is a flowchart showing a method of establishing an asset management plan in different ways by classifying target assets into a plurality of groups according to an embodiment of the present disclosure.

Referring to FIG. 2, the asset management device 10 of the present disclosure can determine the type of input target asset and establish an asset management plan using different evaluation models according to the determined type of target asset.

In step S100, the asset management device 10 may classify the target asset into either a facility asset group or a pipeline asset group. The target asset may be data that is subject to asset status evaluation by inputting the asset lot number, asset name, asset module type, and asset-related data as a set through the input/output device 100. Once the investment plan for the target asset is established, the asset management device 10 can next select the asset input through the input/output device 100 as the target asset. The asset management device 10 may create an asset ledger by listing assets classified into groups. A method of the asset management device 10 generating an asset ledger will be described later through FIGS. 3 and 4 .

According to one embodiment, the asset management device 10 may receive asset inventory registered in WFM and obtain diagnosis result information through technical diagnosis, safety diagnosis, insulation diagnosis, pump motor performance diagnosis, etc. In addition, the asset management device 10 can collect data within the system, such as regular inspection, repair and maintenance, replacement, and failure history. The asset management device 10 may create an asset ledger based on acquired and collected data and information.

In step S200, when the target asset is classified into a facility asset group, the asset management device 10 may establish an asset management plan based on the asset evaluation model for each module. The module-specific asset evaluation model may be a model that evaluates the current status and remaining life of the asset based on different standards for each module by receiving data required for the module type when the asset management device analyzes the module type of the facility asset. .

In step S300, when the target asset is classified into a pipeline asset group, the asset management device 10 may establish an asset management plan based on a plurality of remaining lifespan derivation models. The plurality of remaining life derivation models are models that calculate the remaining life of the target asset in different ways, and may be models that calculate the physical remaining life, functional remaining life, and economic remaining life of the target asset in different ways.

The asset management device 10 according to an embodiment of the present disclosure may obtain the remaining lifespan for the target asset in different ways depending on the classified asset group. The asset management device 10 can evaluate the current asset status according to various evaluation criteria divided by asset group, and can predict the remaining life by applying various techniques depending on the importance of the asset and the quantity/quality of data.

Figure 3 is a flowchart illustrating a method of updating an asset ledger when a target asset is classified as a facility asset according to an embodiment.

Referring to FIG. 3, when the target asset is classified as a facility asset, the asset management device 10 can determine the module type of the target asset and update the asset ledger by adding the target asset to the preset asset ledger. The asset ledger may be data in which asset inventory and maintenance history integrated management information based on asset class standards are mapped. According to one embodiment, the asset management device 10 may manage asset data using an asset ledger as a table to which a series of asset data sets are mapped. The asset management device 10 can be used as basic data for establishing an asset management plan, such as evaluating the condition of the asset and predicting the remaining lifespan, based on attribute information and maintenance history.

In step S211a, the asset management device 10 may obtain specifications and attribute information of the target asset. According to one embodiment, the asset management device 10 may receive an inventory of assets registered in the system.

In step S211b, the asset management device 10 may receive the results of on-site inspection and diagnosis of the target asset. At this time, the results received by the asset management device 10 are quantified information about the target asset, and may be information received by a manager who inspected and diagnosed on site, illustratively, technical diagnosis, precise safety diagnosis, This may be a report on the results of insulation diagnosis, pump motor performance diagnosis, etc.

In step S211c, the asset management device 10 may obtain accident and maintenance history for the target asset. Accident and maintenance history may be data already registered and in operation in the asset management system, such as regular inspection, repair maintenance, and replacement failure history. According to one embodiment, the asset management device 10 may obtain accident and maintenance history for the target asset by searching the asset lot number in the asset management system.

In step S212, the asset management device 10 may classify the target asset into one of a plurality of module groups according to the module type. At this time, the asset management device 10 may extract requested data corresponding to the classified module group from the received data. Data corresponding to a classified module group may consist of different data combinations for each module group.

In step S213, the asset management device 10 may update the asset ledger by adding the module group of the target asset and the corresponding data to the asset ledger. According to one embodiment, the asset management device 10 may update the asset ledger by setting the next input asset as the target asset after completing the establishment of an investment plan for the target asset. However, the asset management device of the present disclosure may update the asset ledger. (10) is not limited to this, and data related to the input target assets may be collectively updated in the asset ledger.

According to one embodiment, the asset management device 10 may generate a condition evaluation result of the target asset based on a combination of data for each different module group and derive the remaining lifespan based on a regression model. In addition, the asset management device 10 may calculate the business risk based on a combination of data for each different module group. A method by which the asset management device 10 obtains the condition evaluation result, remaining life, and business risk using different data combinations will be described later with reference to FIG. 5.

FIG. 4 is a diagram illustrating data types for generating status evaluation results of different facility asset modules according to an embodiment.

Referring to FIG. 4, the asset management device 10 according to an embodiment of the present disclosure can designate target assets classified as facility asset groups into different module groups according to module types, and provide different data according to the designated module groups. You can request a combination. According to one embodiment, the asset management device 10 may request necessary data from the user according to a designated module group, or may extract and manage only necessary data according to a designated module group from among the received data.

Illustratively, when the target asset is classified as a structural module among the facility asset group, the asset management device 10 requests covering thickness, carbonation residual depth, chloride content, compressive strength, and rebar corrosion as data related to the target asset. You can. When the asset management device 10 receives the target asset classified as a structure module and the cover thickness, carbonation residual depth, chloride content, compressive strength, and rebar corrosion degree of the target asset, it maps and stores the data and the target asset. You can.

If the target asset is classified as a pump module among the facility asset groups, the asset management device 10 may request vibration, head, bearing temperature, and pump efficiency as data related to the target asset. In a similar way, the asset management device 10 may request different data combinations according to the module group into which the target asset is classified, as in the embodiment of FIG. 3, but the data combination corresponding to the module group of the present disclosure is as shown in FIG. 3 It may not be limited to.

According to one embodiment, the asset management device 10 may map and store the lot number of the target asset to the received data, and when data corresponding to the lot number is received multiple times at regular time intervals, the lot number and Data can be mapped and stored for each time information. Illustratively, the asset management device 10 may receive a first data set at a first time in response to the target asset, and may receive a second data set at a second time a certain time later than the first time. there is. In this case, the certain time may be after at least one year has passed, but the certain time in the present disclosure may not be limited thereto. The asset management device 10 may store the first data set in correspondence with the lot number of the target asset and the first time, and store the second data set in correspondence with the lot number of the target asset and the second time.

Figure 5 is a flow chart illustrating a method of obtaining remaining life and business risk from facility assets according to one embodiment.

Referring to FIG. 5, when the target asset is classified into a facility asset group, the asset management device 10 of the present disclosure can generate a condition evaluation result of the target asset and derive the remaining life based on the condition evaluation result. .

In step S221, the asset management device 10 may generate a condition evaluation result of the target asset based on the data set updated with the asset ledger for the target asset. The condition evaluation result may be quantified information considering the asset condition and operational performance, and at this time, the asset management device 10 may obtain the condition evaluation result by calculating a data set related to the target asset.

The asset management device 10 according to an embodiment of the present disclosure may generate a condition evaluation result based on a combination of data classified by module group of facility assets. Illustratively, referring to FIG. 4, when the target asset is classified as a structure module, the asset management device 10 provides condition evaluation results based on coating thickness, carbonation residual depth, chloride content, compressive strength, and reinforcing bar corrosion. can be created.

Looking specifically, the influence factors required for generating condition evaluation results for each module group may be pre-designated in different combinations, and the asset management device 10 may be designated according to the number of years of use, operational performance, reliability/availability, and maintainability. Condition evaluation results can be generated based on influencing factors. The service life is used to determine the deteriorated state according to the service life of the asset, and the asset management device 10 can be used to obtain a condition evaluation result through the service life compared to the standard service life set for each module group. Operational performance impact factors are intended to identify deteriorated conditions due to asset performance decline, and can be used to obtain condition evaluation results using items and standards established according to the characteristics of each module group.

The reliability/availability impact factor is intended to determine the frequency with which an asset failure occurs over a certain period of time, and can be expressed as a percentage of the time the asset can perform a given function. Illustratively, the asset management device 10 may determine reliability/availability influencing factors through the average failure interval time. The maintainability impact factor is intended to determine the ability to restore failed assets to a normal state and can be determined through the average failover time.

In step S222, the asset management device 10 may derive the remaining lifespan of the target asset based on the condition evaluation result.

If the target asset is classified into a facility asset group, the asset management device 10 obtains a condition evaluation result of the target asset based on the influence factors for each facility asset module, and the object classified into the facility asset group based on the condition evaluation result. The remaining life of an asset can be predicted. By way of example, facility asset modules may include structures, pumps, valves, motors, substation/transformer and control panels, operators, instrumentation, sludge collectors, chemical injectors, ozone generators, dehydrators, agitators, and filter media. Influence factors may be composed of a combination of data collected through the input/output device 100, and may be composed of different data combinations for each facility asset module.

According to one embodiment, the asset management device 10 collects current state scores according to the number of years of use of assets grouped in the same module group as the target asset, and based on the current state scores according to the collected number of years of use, the corresponding module You can create a group decay curve model. The decay curve model may be a model created by a regression equation using the current state score according to the number of years of use.

The asset management device 10 may set the remaining life as the number of years in which the current state score falls below the existing score minus the current number of years of use in the decay curve model. Exemplarily, the asset management device 10 determines the number of years of use at which the current state score falls below the existing score in the decay curve model to be 10 years, and when the current number of years of use is obtained as 8 years, the remaining lifespan is 2 years. It can be derived as:

In step S223, the asset management device 10 may set target service level information. Target service level information may be level information set in consideration of the service level required from social, environmental, and economic aspects (Triple Bottom Line; TBL) and the organization's capabilities (manpower, budget, technology, etc.). In particular, service level items can be classified by key performance indicators (KPIs) such as quantity, water quality, and energy.

Specifically, the asset management device 10 can determine to what service level the target asset will be raised to in the future. At this time, the target service level information may be information determined based on data such as who the user of the target asset is, how much it is being used, and how much budget can be secured.

According to another embodiment of the present invention, the target service level information includes a step of deriving service level items and setting key performance indicators, a step of deriving the relevance of modules and assets related to the set service level items, and a step of deriving the relevance of the modules and assets related to the set service level items. Steps for generating scores may be included.

In step S224, the asset management device 10 may predict the probability of failure (PoF) based on the state evaluation result of the target asset generated in step S221.

In step S225, the asset management device 10 may calculate the degree of environmental, social, and economic damage when a failure occurs based on the target service level information set in step S223. The degree of environmental, social, and economic damage may also be referred to as Consequence of Failure (CoF).

In step S226, the asset management device 10 may obtain a business risk level based on the predicted probability of occurrence of a failure for the target asset and the degree of damage expected when a failure occurs. Business risk may be referred to as Business Risk Exposure (BRE). According to one embodiment, the asset management device 10 may calculate the business risk by multiplying the probability of occurrence of a failure, the result of failure propagation, and the reserve ratio (Red).

According to one embodiment, the asset management device 10 may create a Failure Mode and Effect Analysis (FMEA) library for each module group and perform FMEA analysis for each module group. The asset management device 10 may perform FMEA analysis and then calculate the business risk. Specifically, the asset management device 10 may perform FMEA analysis by considering the impact on the entire system when a corresponding module fails. According to one embodiment, when calculating the business risk, the asset management device 10 can identify the module group into which the target asset is classified, and calculate the business risk by applying the preset importance for each module group as a weight. Illustratively, when the first module group is set to have higher importance in the system than the second module group, the asset management device 10 includes the target asset in the first module group than when the target asset is included in the second module group. In this case, the business risk can be calculated by applying a higher weight.

6 is a flow diagram illustrating how an investment plan is established in facility assets according to one embodiment.

Referring to FIG. 6, when the asset management device 10 completes generating condition assessment results for target assets classified as facility assets, deriving remaining lifespan, setting target service level information, and obtaining business risk, You can prioritize multiple target assets, classify investment plan groups, and establish an investment plan for each investment plan group.

In step S231, the asset management device 10 may establish an investment plan for the target asset based on target service level information, remaining life of the target asset, and business risk. Specifically, the asset management device 10 may select an investment priority (Risk Priority Number (RPN)) based on target service level information, remaining lifespan of the target asset, and business risk.

In step S232, the asset management device 10 may implement an optimal improvement plan (ORDM) for each type of failure based on investment priorities. Specifically, the asset management device 10 can create a decision tree and derive an optimal improvement plan for each failure type of the target asset based on the business risk and the decision tree.

In step S233, the asset management device 10 may determine one of the short-term investment plan group and the mid- to long-term investment plan group as a result of deriving the optimal improvement plan for each type of failure. The asset management device 10 can be classified into one of a plurality of investment plan groups classified according to individual priority as a result of deriving the optimal improvement plan. As an example, the asset management device 10 may determine whether to set the target asset to a short-term investment plan group or a mid- to long-term investment plan group as a result of deriving the optimal improvement plan.

In step S234, the asset management device 10 may calculate a mid- to long-term required budget based on asset status based on the classified investment plan group, and based on the calculated mid- to long-term required budget, calculate an appropriate fee to secure insufficient funds. Data can be presented. In addition, the asset management device 10 may present an asset management portfolio (inspection, maintenance, replacement, improvement and disposal) for key assets based on the asset management analysis results. The asset management device 10 can be used to establish asset management direction and strategy at the organizational level as well as unit assets through establishing an asset management plan. A method by which the asset management device 10 of the present disclosure presents an asset management portfolio will be described later with reference to FIGS. 10 and 11.

In the above, when the asset management device 10 classifies the target asset as a facility asset, a method of establishing an investment plan has been described. Hereinafter, when the asset management device 10 classifies the target asset as a pipeline asset, Describe how to establish an investment plan.

Figure 7 is a flow chart illustrating a method of obtaining remaining life and business risk from pipeline assets according to an embodiment.

Referring to FIG. 7, when the target asset is classified into a pipeline asset group, the asset management device 10 of the present disclosure can obtain a plurality of remaining lifespans based on a plurality of remaining lifespan derivation models. At this time, the asset management device 10 may obtain one of the plurality of remaining lifespans as the final remaining lifespan. The asset management device 10 can obtain the business risk for the target asset by setting target service level information and determining the target section.

In step S311a, the asset management device 10 may analyze the system of pipeline assets including the target asset. The system of pipeline assets may be pre-registered in the facility management system. According to one embodiment, the asset management device 10 may structure the supply system by considering the pipeline supply system and facilities of the target area.

According to one embodiment, the asset management device 10 can predict the probability of failure and the extent of damage to pipeline assets for each section, and divide pipeline assets in the target area to calculate business risk. By way of example, the asset management device 10 may divide pipeline assets based on branch points. However, the example in which the asset management device 10 of the present disclosure divides pipeline assets is not limited to this.

In step S311b, the asset management device 10 may diagnose target assets classified into a pipeline asset group and generate history data for the target assets. At this time, the history data may be data that has been diagnosed multiple times for the target asset, and may further include pipeline accident history data. According to one embodiment, the asset management device 10 may generate historical data for each pipe asset structured based on pipe type, pipe diameter, and branch point.

In step S311c, the asset management device 10 can derive the extent of damage and cost when the pipe is damaged. The asset management device 10 can calculate the extent of damage suffered due to pipeline asset failure and the cost of the damage based on the single influence factor. Water supply influencing factors may include, by way of example, customer capacity, facility capacity, operating capacity, H.W.L., L.W.L., water level, average daily supply, average residence time, total demand during the restoration work period, landscape, topography, and standard restoration time.

In step S311d, the asset management device 10 may calculate the construction cost based on site conditions. Construction costs can be divided into direct costs, indirect costs, and social costs. Direct costs can be divided into pipe damage repair costs and water outage damage costs, while social costs can include traffic congestion costs and water quality prevention costs.

The asset management device 10 may perform the steps S311a to S311d simultaneously or sequentially. If performed sequentially, the order of the processed steps may not be limited to a specific order. there is.

In step S312, the asset management device 10 may obtain a plurality of remaining lifespans based on a plurality of remaining lifespan derivation models. According to one embodiment, the remaining life derivation model may include a physical remaining life derivation model, an economic remaining life derivation model, and a functional remaining life derivation model. In other words, the asset management device 10 can derive a plurality of remaining lifespans using the Failure Mode technique, and the plurality of remaining lifespans are mutually exclusive in terms of capacity, physical (Mortality), functional (LoS), and economic (Efficiency). The remaining lives may be assessed in other ways. However, according to one embodiment, the asset management device 10 may determine the previously acquired remaining life data as the remaining life in terms of capacity that must be accompanied by demand prediction.

In step S313, the asset management device 10 may obtain one of a plurality of types of remaining lifespan as the final remaining lifespan. Illustratively, when the asset management device 10 acquires a physical remaining life, a functional remaining life, and an economic remaining life, one of these may be determined as the final remaining life. According to one embodiment, the asset management device 10 may determine the earliest remaining lifespan among a plurality of types of remaining lifespan as the final remaining lifespan.

The asset management device 10 may determine the target section based on the location of the target asset in the pipeline system. According to one embodiment, the asset management device 10 may identify a location in the layered pipeline system data to calculate the importance of the target asset in the pipeline system.

When calculating the remaining lifespan of a plurality of pipeline assets in a pipeline system including the target asset, the asset management device 10 may identify pipeline assets whose remaining lifespan is less than or equal to a preset reference value. The asset management device 10 may determine a target section for which an investment plan needs to be established based on the identified pipeline assets.

In step S314, the asset management device 10 may predict the probability of failure (PoF) based on a physical remaining lifespan derivation model. In step S315, the asset management device 10 can predict the degree of damage (CoF) resulting from the occurrence of a failure.

In step S316, the asset management device 10 may obtain a business risk level based on the probability of occurrence of a failure of the target asset and the degree of damage resulting from the occurrence of the failure. At this time, the asset management device 10 can calculate the business risk for the target section that requires establishment of an investment plan. The asset management device 10 can calculate the business risk based on the probability of occurrence of failure (PoF), consequence of failure (CoF), and redundancy of the target asset. According to one embodiment, the asset management device 10 can predict the probability of occurrence of a failure and the result of failure propagation of a target asset predicted in the future based on the condition evaluation score.

Figure 8 is a flowchart illustrating a method for establishing an investment plan for a plurality of assets including a target asset according to an embodiment.

Referring to FIG. 8, the asset management device 10 of the present disclosure can establish an investment plan for target assets by setting target service level information and obtaining business risk. The asset management device 10 can establish an investment plan for multiple assets including the target asset, calculate the mid- to long-term budget based on asset status, and present basic data for calculating appropriate fees to secure insufficient financial resources. Accordingly, the asset management device 10 can present a portfolio of facility assets and pipeline assets, and can be used to establish asset management direction and strategy.

In step S321, the asset management device 10 may determine investment priorities based on target service level information and business risk of the target asset. The asset management device 10 can calculate investment priorities by adding quantified target service level information and business risk. According to one embodiment, the asset management device 10 may calculate investment priorities by assigning different weights to target service level information and business risk of target assets.

In step S322, the asset management device 10 may obtain the final remaining lifespan of a plurality of assets including the target asset. Illustratively, when the asset management device 10 acquires a physical remaining life, a functional remaining life, and an economic remaining life, one of these may be determined as the final remaining life. According to one embodiment, the asset management device 10 may determine the earliest remaining lifespan among a plurality of types of remaining lifespan as the final remaining lifespan.

In step S323, the asset management device 10 may list up assets based on investment priorities for a plurality of assets including the target asset, and select an ORDM target asset from among the listed assets. According to one embodiment, the asset management device 10 may select assets whose scored investment priorities are equal to or higher than the standard score as ORDM targets. Assets subject to ORDM may be assets that require detailed investigation to establish an investment plan, and the asset management device 10 may suggest an optimal improvement plan for the assets subject to ORDM.

In step S324, the asset management device 10 may establish an investment plan by deriving an optimal maintenance strategy according to the classified investment plan group. As an example, the asset management device 10 may determine an investment plan year for a plurality of assets and calculate the total expected cost for each investment plan year. An exemplary annual cost calculation may be as shown in the table below.

Item (KRW 100 million) 2023 2024 2025 2026 2027 Total cost 220 205 240 210 200 Maintenance 60 60 60 60 60 OPEX(Repair) 90 105 110 90 100 CAPEX (Refurbish, Replace) 70 40 70 60 40

Figure 9 is a flow chart illustrating a method of establishing an investment plan for pipeline assets selected as ORDM targets according to an embodiment.

Referring to FIG. 9, the asset management device 10 of the present disclosure can classify target assets into one of a plurality of investment plan groups according to the remaining lifespan, and when set as a mid- to long-term investment plan group, improve old pipes according to the evaluation grade. An investment plan can be established in any of the following ways: and stabilization project establishment.

In step S331, the asset management device 10 may determine whether the remaining life is greater than the reference value. At this time, the remaining life may be the final remaining life calculated in FIG. 7.

In step S332a, the asset management device 10 may set the target asset to a mid- to long-term investment plan group if the remaining life is greater than the first reference value, and in step S332b, the remaining life is less than the first reference value. In this case, the target asset can be set as a short-term investment plan group. In other words, the asset management device 10 can be classified into a short-term investment plan group in which an investment plan is set to replace the target asset when the remaining life is short.

In step S333, the asset management device 10 may determine whether the functional life and economic life are greater than the second reference value. The second reference value may be the remaining lifespan, which is a standard for not having water disconnection in the event of a pipeline accident due to emergency water supply based on functional lifespan and economic lifespan. According to one embodiment, the asset management device 10 may determine that there is no number of disconnections in the event of a pipeline accident because the functional life and economic life are infinitely divergent.

In step S334a, the asset management device 10 may calculate an evaluation grade using the first data combination when it is determined that the functional life and economic life exceed the second reference value. The first data combination may be a combination of data that directly evaluates the pipe condition. According to one embodiment, the first data combination may be a combination of data that can be obtained from the target asset to evaluate the current state of the pipeline.

In step S334b, the asset management device 10 may calculate the evaluation grade using the second data combination when the functional life and economic life are less than or equal to the second reference value. According to one embodiment, the second data combination may be a data combination in which the first data combination further includes data necessary for review of the stabilization project. The data required for review of the stabilization project may be data on the possibility of double-tracking the pipeline, the existence of a pipeline capable of emergency connection, and the presence of a storage tank.

In steps S335a and S335b, the asset management device 10 may determine an evaluation grade based on the obtained data combination and compare the evaluation grade with the reference grade. According to one embodiment, the asset management device 10 may determine the evaluation grade by inputting the acquired data combination data into a preset formula.

In step S336a, if the evaluation grade is higher than the standard grade, the asset management device 10 may establish an old pipe improvement business plan for the target asset. According to one embodiment, if the evaluation grade is lower than or equal to the reference grade, the asset management device 10 may classify the target asset into a mid- to long-term investment plan group. An old pipe improvement project may be a plan to perform replacement work on the target asset.

In step S336b, the asset management device 10 may establish an old pipe improvement business plan and a stabilization business plan for the target asset when the evaluation grade is higher than the standard grade. In step S336c, the asset management device 10 may establish a stabilization business plan for the target asset when the evaluation grade is lower than or equal to the reference grade.

The asset management device 10 according to an embodiment of the present disclosure can determine the type of investment plan group according to the remaining life of the target asset and establish a detailed plan according to the functional life, economic life, and evaluation grade. The investment plan establishment method of FIG. 8 is one embodiment, and the asset management device 10 of the present disclosure establishes a detailed plan using information acquired about the target asset, such as target service level information, business risk, and remaining life. Any method can be included.

Figures 10 and 11 are diagrams showing a portfolio of assets created according to an embodiment.

10 and 11, the asset management device 10 of the present disclosure organizes asset attributes and maintenance history, asset condition evaluation, asset remaining life, asset LoS relevance, asset risk analysis, and optimal investment plan information. It can be presented as a portfolio. The embodiment of FIG. 10 is a diagram showing an asset portfolio presented for individual assets, and the embodiment of FIG. 11 is a diagram showing an asset portfolio presented for all key assets installed in a business.

The asset management device 10 can present individual asset basic information, maintenance history and cost data, and field diagnosis results included in the asset ledger as asset attribute and maintenance history information, as well as asset failure type, asset condition evaluation level, and Condition evaluation logic and asset condition evaluation results can be presented as asset condition assessment information. The asset management device 10 can present individual asset standard decay curve model, standard model life and predicted life, and asset predicted remaining life as asset remaining life information, and asset relevance by LoS item and LoS goal achievement rate related to asset LoS. It can also be presented as information. The asset management device 10 can present asset business risk calculation logic, FMEA library, and Risk Matrix as asset risk analysis information, and can present individual replacement priority calculation results and OPEX/CAPEX list for each asset as optimal investment plan information. You can.

Figure 12 is a flowchart showing the process of establishing an asset management plan for each asset by creating an asset portfolio according to an embodiment.

Referring to FIG. 12, the asset portfolio created in the asset management device 10 can be used to establish a step-by-step high-level asset management plan. The higher levels can be arranged in the following order: workplace level, regional level, and water management office. The asset portfolio includes asset-specific asset management information, asset properties and maintenance history information, condition evaluation information, remaining life information, LoS relevance information, business risk information, individual replacement priority information, and investment plan (CAPEX/OPEX) information. It can be included.

If the created asset portfolio is provided for establishing an asset management plan at the business site level, comprehensive asset management information at the process level can be created. Comprehensive asset management information at the process level may include comprehensive condition evaluation information, remaining life distribution map, business risk matrix, and investment plan information.

When a business-level asset management plan is established, investment plans and necessary budget requests can be provided to establish a regional-level asset management plan, and a regional-level asset management plan can be established based on comprehensive process-level asset management information. If process unit asset management comprehensive information is provided, asset management comprehensive information at the business site (water intake/purified water/pressurization) unit can be created. Comprehensive asset management information at the business site level may include comprehensive status assessment information, business risk matrix, and investment plan information.

When a district-level asset management plan is established, investment plans and necessary budget requests can be provided to establish the water management office asset management plan, and the water management office asset management plan can be established based on comprehensive asset management information at the business site level. If comprehensive asset management information at the business site level is provided, comprehensive asset management information at the business site/region level can be created. Comprehensive asset management information at the business/region level may include investment plan information.

In the above method, investment plan information at the business/region level can be collected from multiple businesses and regions, and the water management office can reflect regional budget policy based on the investment plan information at the business/region level, Regions can reflect business-level budget policies based on business-level investment plan information.

FIG. 13 is a diagram summarizing the steps for managing assets by applying US EPA 5 Core, 10 Step according to an embodiment of the present disclosure, and FIG. 14 shows the concept of the present disclosure specifically presented for the embodiment of FIG. 13 and This is a drawing summarizing the results and utilization.

An embodiment of the present disclosure may be an embodiment that embodies the 5 Core 10 Step asset management manual presented by the US Environmental Protection Agency (EPA). Looking specifically, the manual provided by US EPA presented asset management methods comprehensively and abstractly, and was an asset management method that did not reflect the current state of domestic infrastructure. In contrast, the asset management method of the present disclosure uses the asset management manual provided by the US EPA as a guideline, but there are differences in the specific method from the above-described method.

According to one embodiment, the asset management method of the present disclosure can derive the remaining life and business risk for facility assets and pipeline assets using different evaluation methods, and can derive remaining life and business risk in different ways based on the derived remaining life and business risk. You can establish an asset management plan by dividing investment plan groups.

In addition, the asset management method of the present disclosure can determine the status of the asset by obtaining different data combinations for each module of the facility asset. The asset management method of the present disclosure can obtain a decay curve model for each module and obtain the remaining life based on the decay curve model corresponding to each module.

Therefore, the asset management method of the present disclosure is intended to provide a specific method for evaluating assets with a combination of data that matches the domestic infrastructure situation and establishing an asset management plan accordingly.

As above, exemplary embodiments have been disclosed in the drawings and specification. Although embodiments have been described in this specification using specific terms, this is only used for the purpose of explaining the technical idea of the present disclosure and is not used to limit the meaning or scope of the present disclosure as set forth in the claims. . Therefore, those skilled in the art will understand that various modifications and other equivalent embodiments are possible therefrom. Therefore, the true technical protection scope of the present disclosure should be determined by the technical spirit of the attached patent claims.

Claims (3)

In the method of managing the water supply assets by predicting the appropriate replacement time for old water supply assets and establishing an investment plan in an optimal way,
Classifying the target asset into one of a facility asset group and a pipeline asset group;
Evaluating the asset status of the target asset in different ways by considering the characteristics of the asset and condition evaluation influence factors according to the asset group into which the target asset is classified, and calculating the remaining lifespan;
Setting level of service (LoS) items and key performance indicators (KPI) according to the classified asset group and quantifying asset relevance to obtain LoS values for each module;
Obtaining a business risk level (BRE) based on the probability of occurrence of failure (PoF) and the resulting predicted degree of damage (CoF) for the target asset; and
Calculating an investment priority (RPN) for the target asset based on the remaining life (RUL), service level information (LoS), and the business risk, and establishing an investment plan with an optimal method (ORDM); and
Creating an asset management portfolio for core assets including the target asset based on the established investment plan and establishing an asset management strategy
Asset management method including. According to paragraph 1,
The step of classifying the target assets is,
When the target asset is classified into the facility asset group corresponding to structures and facilities, classifying the target asset into one of a plurality of module groups according to the module type; and
Updating the asset ledger by acquiring different combinations of module data for each module group.
An asset management method comprising: According to paragraph 1,
The step of evaluating the asset condition and calculating the remaining life is,
When the target asset is classified into the facility asset group, obtaining a condition evaluation result of the target asset using quantitative and qualitative methods based on various influencing factors for each facility asset module; and
Predicting the remaining lifespan of the target asset classified into the facility asset group based on the condition evaluation result
An asset management method comprising: