JP2014016691A - Equipment maintenance and management support system, and method for the same - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system that quantifies states and values of existing assets and, on the basis of demand for equipment renewal and information on financial ins and outs, supports planning of appropriate maintenance and management of water supply and sewerage services and renewal programs from a medium-to-long term viewpoint.SOLUTION: An equipment maintenance and management support system S captures into a computer system 100 various equipment information, inspection and maintenance data, monitoring data and plant data inputted from water supply and sewerage service facilities 200 according to a monitoring schedule or at random, and stores them into a database 10. Quantitative equipment health is evaluated and statistical remaining useful life is calculated by diagnostic prediction of deterioration on the basis of inspection, maintenance and monitoring data; according to a risk level set for each equipment item, equipment renewal demand and cost are evened out in strict observance of budgetary restrictions and appropriately updated, and demand planning is thereby supported.

Description

  The present invention quantifies the state and value of existing assets, and provides a maintenance management support system capable of appropriate maintenance management and renewal planning of water and sewage business from a medium- to long-term perspective from facility replacement demand and financial balance information, and its Regarding the method.

  Up to now, the water and sewage business has been developing large-scale facilities and equipment with the main purpose of spreading and improving capacity. Water and sewage facilities that were developed from the period of high economic growth to the Showa 50s account for the majority of aging facilities over 30 to 40 years, and performance and structural deterioration progressed. The demand for renewal / renovation is thought to be concentrated.

  In addition, water business revenues have been on a downward trend, and public works expenses have been restrained, making it difficult to allocate sufficient budget for maintenance and facility maintenance. Securing a budget for increased investment has become a major issue for water and sewage utilities.

  For this reason, there is a need for efficient management that prolongs the life of aging equipment and management methods that standardize (optimize) the concentration of renewal demand periods. These are quantitative measures such as the fiscal balance outlook and renewal demand outlook. There is an urgent need to establish a maintenance management method based on the indicators.

  As an international standard process in the field of maintenance management (asset management), the movement to establish the ISO 55000 series is becoming active. In Japan, the Ministry of Health, Labor and Welfare / Health Bureau Water Supply Division issued a “Guide on Asset Management Methods for Water Supply Business” in July 2009, and the Ministry of Land, Infrastructure, Transport and Tourism / In September 2011, the National Land Conservation Bureau Sewerage Department issued a “Guideline on Draft Stock Management Methods (Draft)”.

JP 2005-327201 A JP 2006-323741 A

  The prior art described in [Patent Document 1] can set the inspection / maintenance work execution time for equipment or equipment, and improve the reliability of the equipment or equipment. However, it is not possible to determine the inspection / maintenance time of equipment that greatly affects the water quality level, which is one of the important management indicators for water and sewage facilities, or the priority of preventive maintenance work to prevent shutdown due to failure There is.

  In the prior art described in [Patent Document 2], a deterioration diagnosis of a bridge material, which is also a representative of a huge structure, is performed by applying a known deterioration model evaluation formula. Etc. are diverse, such as concrete structures, large machinery / electrical equipment, pumps, measuring instruments, sensors, etc., not only the deterioration of materials, but also the influence of semiconductor elements, high-performance materials, etc. that make up electronic circuits are considered There is a need.

  Generally, parts and elements that make up machinery and electricity are formulated based on manufacturer recommended values under specific constraints or environments, but the type of damage is limited, and degradation is limited. Since the distribution of the is not considered, a state that does not match the actual situation occurs. Therefore, it is thought that the accuracy of degradation prediction will not improve unless the defects of both degradation models are complemented, such as building a statistical degradation model based on actual measurement values after grasping the actual degradation situation through inspection work and monitoring. It is done.

  The maintenance management method for equipment in Japan has traditionally been based on the concept of time-planned maintenance based on the legal service life, but the quality and durability of the parts and units that make up the equipment have also improved. Yes, even if the service life is exceeded, there is no major problem and the proportion of facilities operating in a healthy state is increasing. The reality is that the financial situation of the water and sewage business entity has become very strict, and this is just a passive situation that led to the difficulty of securing a sufficient budget for renewal. It's not management.

  For this reason, in recent years, the concept of preventive maintenance to prevent failure and stoppage of equipment by carrying out appropriate inspection and maintenance work has been highlighted, and appropriate measures must be taken to implement proactive equipment management. Has been demanded.

  There are two types of equipment maintenance: preventive maintenance as described above and post-maintenance where measures are taken after failure or trouble occurs. The higher the ratio of preventive maintenance costs to the total cost of equipment maintenance, the more appropriate It can be said that equipment management is being implemented. However, the conditions for implementing preventive maintenance include advanced inspections such as various inspection operations for monitoring the operational status of equipment, collection of plant data by sensing, equipment health diagnosis based on the data, and prediction of useful life. Establishment of analysis means is indispensable, and there are many issues to be cleared such as enormous cost required for collecting the data.

  In addition, considering the social impact of the equipment being shut down, if post-maintenance is not allowed after a failure or trouble has occurred, or equipment that is in a state that is difficult to monitor, take action based on time-planned maintenance. Flexible decision-making is necessary.

  Usually, water supply and sewerage enterprises develop human resources for maintaining facilities and maintain the management level in accordance with operation and management manuals. However, in the management of water and sewage systems and the maintenance of water quality, abnormal events and troubles may occur due to the effects other than those normally sensed. For these, it is considered that rational measures are taken to maintain and improve the service level of the water and sewage business by utilizing the practical knowledge accumulated as management know-how. In other words, it is no exaggeration to say that the know-how accumulated by many skilled people over the years has contributed to the normal operation and management of equipment. For this reason, it is important to take measures to maintain the management level within the station before the number of skilled staff with the know-how decreases.

  As mentioned above, the asset management of water and sewage business entities is urgently required to understand the operating status for equipment maintenance and to create an environment where the person in charge can make a uniform and reasonable judgment. It is recommended to apply a seamless information system including inheritance. Moreover, avoiding the situation where equipment maintenance costs are concentrated in a specific fiscal year based on the tightening fiscal balance and prospects for renewal demand that is expected to continue to increase in the future, realize cost leveling from a medium- to long-term perspective It is becoming important to establish maintenance management methods.

  The present invention is an invention for solving the above-mentioned problems, and is a technique for quantitatively diagnosing the soundness of the equipment by obtaining monitoring data and the like related to the equipment installed in the water and sewage facility. Establishing a theoretical or statistical deterioration model by statistically analyzing deterioration diagnosis prediction technology that predicts when the facility can guarantee its function, and data related to facilities that have been able to prolong life based on the deterioration diagnosis prediction result It is an object of the present invention to provide an equipment maintenance management work support system that can be used, and a method thereof.

  In order to achieve the above object, the present invention comprises a storage means for storing a database, a computer system provided with arithmetic processing means, and an information network for performing information communication between the computer system and the water and sewage facility. In the facility maintenance management support system for facilities and equipment to be managed, a database that stores equipment information managed in the water supply and sewerage facilities, and information on inspection work or maintenance work, and inspection / maintenance data that stores inspection data and maintenance data Various process data (including water quality, flow rate, pressure, etc.) acquired from the monitoring control system (for example, monitoring control server) of the water and sewage facilities according to the monitoring cycle determined for each data by the information database and data collection processing Process information database that stores measurement values) and information on equipment failures. Soundness information evaluated for each facility based on a failure information database that stores the details of alarms that occurred in each facility and alarm occurrence date and time, and various process data, water quality related data, or various data obtained from inspection / maintenance work Degradation information database that stores deterioration prediction information diagnosed for each facility based on process data, water quality-related data, or various data obtained through monitoring, and facility failure or trouble occurrence Risk assessment database that stores risk information calculated based on frequency and operational impact, and various costs required from planning for equipment installation to installation, daily maintenance and removal / update Information and a cost information database that stores financial data for water and sewage utilities. A data processing unit that collects various process data, a soundness processing unit that evaluates the soundness of equipment, a deterioration diagnosis prediction processing unit that performs prediction of equipment deterioration diagnosis, and the frequency of occurrence of failures or troubles A risk evaluation processing unit that evaluates risk from the degree of impact and a cost leveling processing unit that equalizes the cost of renewal demand that occurs every fiscal year. By calculating the useful life and deterioration diagnosis, the cost of renewal demand that can occur every fiscal year is calculated, and the cost is leveled under the constraint condition and the financial balance is supported from the medium- to long-term perspective.

  In order to achieve the above object, the present invention includes a storage unit for storing a database, a computer system including an arithmetic processing unit, and an information network for performing information communication between the computer system and a water and sewage facility. In the facility maintenance management work support method for facilities and facilities managed by the sewer business, using the storage means, creating a database for storing facility information managed in the water and sewage facilities, inspection work or maintenance work A monitoring cycle determined for each data from a monitoring control system (for example, a monitoring control server) for water and sewage facilities by creating an inspection / maintenance information database for storing information, inspection data and maintenance data, and data collection processing Store various process data (measured values including water quality, flow rate, pressure, etc.) Create a process information database, create a failure information database that stores information about equipment failures and details of alarms that occurred in the facility and information on the date and time of occurrence of alarms, and obtain various process data, water quality related data, or inspection / maintenance work. Create a health assessment database that stores health information evaluated for each facility based on the various data obtained, deterioration diagnosed for each facility based on process data, water quality related data, or various data obtained by monitoring Create a deterioration diagnosis information database to store prediction information, create a risk assessment database to store risk information calculated based on the frequency of occurrence of equipment failures or troubles and impact on operations, and plan for equipment installation , Equipment installation, daily maintenance Creating a cost information database for storing various cost information required for removal and renewal and financial data of water and sewage business entities, and collecting various process data using the arithmetic processing means・ Evaluating equipment soundness, predicting equipment deterioration diagnosis, evaluating risk based on frequency and impact of failures or troubles, and leveling renewal demand costs generated every year By calculating the theoretical useful life by quantitatively grasping the equipment state and deterioration diagnosis, the renewal demand cost that can occur every year is calculated, and the cost under the constraint condition is calculated. Achieve leveling and support for sound fiscal balance from a medium- to long-term perspective.

  According to the present invention, a wide range of equipment such as mechanical equipment, electrical equipment, various measuring equipment, pipelines, etc. included in water and sewage facilities are targeted, evaluation of soundness required for maintenance and prediction of deterioration diagnosis, etc. Therefore, it is possible to evaluate the risk, and it is possible to estimate the cost required for the update and optimize the cost based on the update demand time calculated from the result.

The functional block diagram which shows the basic form of an equipment maintenance management work support system. Explanatory drawing which shows the outline | summary of the storage item of each database. The flowchart which shows the process sequence regarding the soundness evaluation of an installation. Explanatory drawing which shows the outline | summary of the soundness division | segmentation number and the state level number of each data item. Explanatory drawing which shows the outline | summary of the state level division | segmentation of a qualitative reference | standard. The flowchart which shows the process sequence regarding deterioration diagnosis prediction of an installation. Explanatory drawing which shows the advanced procedure of the degradation diagnostic method. Explanatory drawing which shows a risk consideration type lifetime evaluation. The flowchart which shows the process sequence regarding the risk evaluation of an installation. Explanatory drawing which shows the level classification table of failure occurrence probability. Explanatory drawing which shows the level classification table of a social influence degree. Explanatory drawing which shows the conversion table from soundness-> occurrence frequency. The flowchart which shows the process sequence regarding cost leveling. Explanatory drawing which shows the procedure (update advance sending) of cost leveling. Explanatory drawing which shows the procedure of cost leveling (I carry out an update advance and advancing simultaneously).

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is a functional block diagram showing a basic form of an equipment maintenance management business support system. In this embodiment, a water and sewage facility will be described as an example of a water facility. The management business support system 500 includes a computer system 100 and a water supply or sewerage facility 200.

  The computer system 100 is connected to a water supply or sewerage facility 200 having a process for generating purified water from raw water or processing from sewage to treated water via an information network 210, and from the monitoring control server 201, the water purification facility Receives a plurality of process data of the water treatment facility.

  The computer system 100 includes a data input unit 1, an information display unit 2, a database 10 (storage unit), and an arithmetic processing unit 20.

  The data input means 1 is used to input necessary information to the database 10 in the computer system 100, and can be configured using a normal computer keyboard or the like. The information display means 2 is for displaying a series of management operation contents performed in each process on the basis of the contents of the database 10 to the management / operator of the water and sewage facility. Etc. can be configured.

  The database 10 includes an equipment information database 11, an inspection / maintenance information database 12, a plant information database 13, a failure information database 14, a soundness evaluation information database 15, a deterioration diagnosis information database 16, a risk evaluation information database 17, and a cost information database 18. Prepare.

  The arithmetic processing means 20 includes a data collection processing unit 21, a soundness evaluation processing unit 22, a deterioration diagnosis prediction processing unit 23, a risk evaluation processing unit 24, and a cost leveling processing unit 25.

Database configuration
FIG. 2 is an explanatory diagram showing an outline of items stored in each database. This will be described with reference to FIG. The equipment information database stores information on facilities, equipment, and equipment owned and managed by water and sewage business entities, and includes information on equipment names, specifications, specifications, installation time (year), and installation locations. Input by means 1.

  The inspection / maintenance information database 12 includes an execution schedule of equipment inspection / maintenance work and various measurement data or monitoring data obtained at the time of inspection / maintenance execution. The data input means 1 or the data collection processing unit 21 performs monitoring control server Obtained from 201 and stored. The data is an important index for predicting the soundness of equipment and deterioration diagnosis, and is used as data for accurately grasping the operating state.

  The plant information database 13 includes water quality analysis items, water quality analysis results, measurement locations, measurement dates and times in each process in the water and sewage facilities, and results of water quality inspections and monitoring data performed during the management and operation of the water and sewage facilities 200 Is recorded and used to collect and store data necessary for periodic hazard analysis and review of management standards.

  The failure information database 14 includes information related to equipment failure, alarm occurrence date and time, and details of the alarm, and the operation history performed on the raw water or sewage 202 in the water and sewage facility 200 is recorded over time, and the operation is performed. The process (processing process) is recorded, and the alarm output date and time when the plant data of the water and sewage facility 200 is detected to be out of the reference value range and alarm contents are recorded.

  In the soundness evaluation information database 15, soundness evaluation information for facilities evaluated based on inspection / maintenance data and plant data, monitoring data, and water quality data related to the facilities is recorded. As evaluation information, a plurality of data items (for example, temperature, vibration frequency, cumulative operation time, water leakage, etc.) indicating the operating state of each equipment are set according to threshold values set from a qualitative or quantitative viewpoint. Leveling is performed, and quantitative soundness for the equipment is obtained by statistical methods or multivariate analysis. In addition, intermediate generation data (leveled data item group) in the soundness evaluation process is also included.

  The deterioration diagnosis information database 16 records deterioration diagnosis information for facilities evaluated based on inspection / maintenance data and plant data, monitoring data, and water quality data regarding the facilities. The specific contents are the degree of deterioration of equipment with respect to age, the period during which the equipment guarantees the minimum functionality, and the probability of transition from each soundness level modeled by statistical methods to another soundness level. is there.

  The risk evaluation information database 17 includes the risk information evaluated for each facility, the frequency of occurrence of equipment failures or troubles necessary for the risk assessment, and the society in terms of management operation when the equipment is stopped due to the failure. Effects information is stored. The risk information is a quantitative index applied as a management level in a department that manages the operation of equipment, and serves as a risk management guideline for normal and continuous operation of water and sewage facilities. On the other hand, when an update is required due to the aging of the equipment, it is also applied as a judgment index when determining the priority of the update in a situation where the constraint condition of the budget related to the update is received.

  The cost information database 18 includes equipment cost (equipment unit price, etc.), cost information on maintenance items and spare parts, and planning for equipment introduction, equipment installation cost, running cost necessary for maintenance, equipment removal / update. Life cycle cost information required by the time, fiscal balance data and update demand data of the water and sewage business entity are stored.

[Details of each processing unit]
Next, each part of the processing means 20 will be described with reference to FIG.
The data collection processing unit 21 collects equipment-related measurement data, monitoring data, water quality analysis results, and plant data (including alarm history) of the water and sewage facility 200 transmitted from the monitoring control server 201 via the information network 210. , Each has a function of storing in the inspection / maintenance information database 12 and the process information database 13.

  The processing steps of the soundness evaluation processing unit 22 will be described with reference to the flowchart of the soundness evaluation processing in FIG.

  This is a process of quantitatively evaluating the soundness of each facility managed and operated in the water and sewage facilities. First, in step S101, the soundness evaluation processing unit 22 acquires the equipment specification data from the equipment information database 11, In step S102, inspection / maintenance data and monitoring data are acquired from the inspection / maintenance information database 12 and the plant information database 13.

  Next, in step S103, the soundness evaluation processing unit 22 divides the inspection / maintenance data and the monitoring data into N-level (N: variable setting) state levels. Is to match.

  FIG. 4 shows the relationship between the number of soundness classifications, the state level classification of the inspection / maintenance data and the monitoring data, and the setting procedure.

Procedure (1):
Determine the number of soundness divisions (N stages: variable from 1 to N, which matches the state level division number).

    However, it is defined that the greater the health level, the higher the health level.

Procedure (2):
Set qualitative or quantitative criteria to divide state levels by data item.

    However, it is defined that the larger the number of state levels, the better the state.

Procedure (3):
The state level of each data item is integrated, and the power root of the integrated value is defined as the soundness level.

  FIG. 5 shows a procedure in the case where the state level of each data for evaluating the soundness cannot be divided according to a quantitative standard.

Procedure (1):
If the state level is possible or not (binary judgment), it does not match the number of soundness divisions 5,
State levels 5 and 2 are defined as “permitted” and state level 1 is defined as “impossible”.

Procedure (2):
Set (arbitrary) the qualitative criteria of state levels 5 to 2 in which the determination is defined as “possible”.

  Next, in step S104, the soundness evaluation processing unit 22 performs a correlation check between the inspection / maintenance data and the monitoring data. For example, when the water pump is operated at 50% or 100% of the rating, the frequency and heat generation of the pump are different. That is, when monitoring data in a state where it is operating at a high output is applied, it may be determined that the monitoring data is in a bad state in the state level classification of the monitoring data. Therefore, it is necessary to exclude transient monitoring data, which is detected only when operating in a high output state, from the soundness evaluation target.

  However, if data under high-power operating conditions are excluded, data for soundness evaluation will be missing, and soundness evaluation will be impossible, so data items that tend to deteriorate state levels under the relevant operating conditions The data level that is equal to or higher than the specified correlation level is determined to be “normal” and the soundness level evaluation is performed.

  Specifically, in the data items having a high degree of correlation, the monitoring data at the timing when the high output operation state is finished and switched to the normal level operation state, and the monitoring in the normal level state before entering the high output operation state Compared with data, if the deviation between the data is within the specified allowable range, the monitoring data at the time of high output operation is determined as transient state data, and the state level data for evaluating the soundness level Not applicable. Monitoring data at the time when the high output operation is completed is applied to the soundness evaluation.

  However, in this case, the regular management target in the water and sewage facilities is the measured data during high-power operation.

  In step S <b> 104, the soundness evaluation processing unit 22 performs statistical analysis of inspection / maintenance data and monitoring data, evaluates the soundness of each facility, and stores the evaluation information in the soundness evaluation information database 15. As shown in FIG. 4, the soundness evaluation calculation method is obtained by integrating the state level data and obtaining the nth root of the integrated value (n: the number of items of the integrated state level data).

  The processing steps of the deterioration diagnosis prediction processing unit 23 will be described with reference to the flowchart of the deterioration diagnosis prediction process of FIG. This is a process of diagnosing and predicting how fast the soundness of each equipment managed and operated in the water and sewage facilities will deteriorate, and the quantitative evaluation calculated by the soundness evaluation processing unit 22 Apply information.

  First, in step S201, the deterioration diagnosis prediction processing unit 23 acquires equipment specification data from the equipment information database 11, and in step S202, inspection / maintenance data and monitoring data are obtained from the inspection / maintenance information database 12 and the plant information database 13. get.

  Next, in step S203, the deterioration diagnosis prediction processing unit 23 compares the number of samples of inspection / maintenance information or monitoring data acquired to perform deterioration diagnosis. This is a comparison for selecting whether to adopt the deterioration diagnosis based on the legal service life of step S204 or to apply the deterioration model of step S205 and to execute the deterioration simulation. The threshold value for the number of data used as a reference is uniquely set for each facility to be diagnosed. When the number of sample data is greater than the reference value, deterioration diagnosis is performed by using a simulation to which the deterioration model of S205 is applied. When the number of sample data is smaller than the reference value, a deterioration diagnosis based on the legal useful life in step S204 is performed.

  The deterioration diagnosis step S204 based on the legal service life and the deterioration simulation step S205 applying the deterioration model will be described with reference to an advanced procedure of the deterioration diagnosis method in FIG. In step S <b> 204, the deterioration diagnosis prediction processing unit 23 performs deterioration diagnosis based on the legal service life determined for each facility acquired from the facility information database 11. In this method, it is difficult to monitor the state of the equipment, and when the state level data of the equipment cannot be acquired regularly, the concept of time-planned maintenance is used to plan and implement the equipment update. When the importance of the equipment or the effect of a shutdown due to a failure is significant, it is desirable to renew the equipment within the legal life.

  Next, in step S205, the deterioration diagnosis prediction processing unit 23 performs deterioration diagnosis using a theoretical deterioration formula or a known statistical deterioration model (Weibull, Markov model) acquired from the deterioration diagnosis information database 16, In order to establish a dynamic deterioration model, a huge amount of inspection / maintenance information, plant data, and monitoring data are required. Whereas the theoretical model is a formulation of deterioration in a local range where theoretical validity is ensured without considering the influence of uncertain factors, the statistical deterioration model is inspection / maintenance data, monitoring data, etc. Therefore, it is possible to perform deterioration diagnosis in accordance with the actual situation in consideration of the influence of uncertain factors or heterogeneous parameters that cannot be grasped. However, the theoretical model and the statistical model also have drawbacks and cannot generally indicate the state of deterioration. Therefore, it is necessary to establish a model that complements both drawbacks.

  In step S206, the service life of the equipment is predicted from the diagnosis results obtained by the respective methods in step S204 and step S205. Deterioration diagnosis based on the legal service life is a hypothetical idea that the deterioration progresses at a certain rate with the passage of time, but the actual situation is that even if the legal service life is exceeded, there is no functional problem with the equipment operating. There are many. Therefore, it is possible to evaluate a practical service life depending on how accurately the state level of the facility is grasped and statistical analysis such as inspection / maintenance data or monitoring data is performed.

  The advancement of the deterioration diagnosis means shown in FIG. 7 shows a procedure for establishing a deterioration prediction model by performing statistical analysis by accumulating monitoring data and the like.

  In addition, by carrying out inspections and maintenance work to restore proper health monitoring and soundness, it is possible to support the monitoring data and realize a sound normal operation even when the legal service life is exceeded. It becomes. The theoretical or statistical useful life result predicted by the deterioration model is stored in the deterioration diagnosis information database 16 and becomes feedback information when the deterioration model simulation is executed in step S205.

  Next, in step S207, soundness level recovery information for each facility at the time of performing the inspection / maintenance work is acquired from the inspection / maintenance information database 12 and the soundness evaluation information database 15, and the deterioration of the equipment due to aging and the inspection / maintenance work are performed. It is possible to diagnose the state of restoration of soundness due to the implementation and to assist in planning the life extension of the equipment. The service life prediction based on the deterioration diagnosis in step S206 and the life extension evaluation by the inspection / maintenance execution in step S207 are performed repeatedly as necessary, and the soundness level when a plurality of periodic inspections and maintenance work are performed. It is possible to predict deterioration diagnosis in view of recovery and deterioration states.

  Fig. 8 shows the risk-considered useful life evaluation. By conducting inspection and maintenance work, the soundness of the equipment is restored, but the expected useful life varies depending on how the degree of restoration is understood. In the evaluation of the service life, the deterioration curve with the highest point of recovery and the deterioration curve with the lowest point of recovery have a longer service life when the highest point is used and the service life when the lowest point is used. The number of years becomes shorter than the service life when the highest point is adopted.

  In other words, if the soundness level is estimated to be high, the risk is large (the result is that deterioration is progressing faster than predicted, and there is a high possibility of failure and trouble occurring before maintenance and renewal). If the estimate is low, the service life is evaluated to be short, leading to the implementation of advance maintenance or renewal based on safety considerations. If the accuracy of the restoration of soundness is improved by accumulating long-term inspection / maintenance data, monitoring data, and sophistication of deterioration diagnosis, the deterioration curve is shifted upward and the life expectancy is extended. It is also possible to consider

  Therefore, the risk that comprehensively considers the importance of the equipment managed in the water and sewage facilities, the social impact at the time of outage, or the application of a high-accuracy degradation model based on inspection / maintenance data and monitoring data, etc. By setting, in the life extension evaluation process by the inspection / maintenance in step S207, the range of the highest point to the lowest point of the restoration level of the soundness is shifted up and down according to the risk value, and the result The theoretical and statistical service life obtained from the above can be provided as reference information for equipment maintenance work.

  The processing steps of the risk evaluation processing unit 24 will be described with reference to the flowchart of the deterioration diagnosis prediction processing in FIG. Assess the quantitative risk level of each facility managed and operated in the water and sewage facilities from the probability of failure, trouble occurrence (or soundness), and the degree of social impact caused by the shutdown of the facility. This is a process for diagnosing and predicting how fast the soundness deteriorates, and the quantitative evaluation information calculated by the soundness evaluation processing unit 22 is applied. The risk level is sometimes adopted as a quantitative management index in the operation and maintenance department of equipment, and is a guideline for maintaining normal maintenance of water and sewage facilities. On the other hand, when an update is necessary due to the aging of the equipment, it is also applied as a judgment index when determining the priority of the update under the constraint condition of the update budget.

  First, in step S301, the risk evaluation processing unit 24 acquires equipment specification data from the equipment information database 11, and selects data to be adopted as the failure occurrence frequency in the data selection process in step S302. It is assumed that whether the selection data is a failure occurrence probability based on the actual value or the soundness level is selected as an alternative index is initially registered as control information.

  Because large-scale facilities tend to have a large social impact at the time of outage, maintenance work such as renewal or overhaul may be performed before a failure occurs, and there is no data to calculate the failure probability In some cases, it may not be possible to obtain the frequency of occurrence, which is also a parameter for risk assessment.

  In order to solve the above problem, paying attention to the fact that the failure occurrence probability becomes higher according to the aging, the soundness evaluated in the soundness evaluation processing unit 22 is applied as an alternative index of the failure occurrence frequency. The processing contents will be described in step S304.

  Next, in step S303, the risk evaluation processing unit 24 acquires a failure occurrence record for each facility from the failure information database 14, calculates the failure occurrence probability, and then classifies the level.

  FIG. 10 explains the failure occurrence probability level classification, and FIG. 11 explains the social influence level classification.

  FIG. 10 shows a level classification in which the probability of occurrence of a failure is divided into N levels (in this case, 5 levels), and the failure occurrence probability is calculated from the actual data of the failure or trouble. It is assumed that the number of divisions, the threshold value of the failure occurrence period, and the level value can be arbitrarily set in view of the characteristics of the equipment, the role in operation, and the like.

  In addition, although the level value is a continuous five-stage numerical value here, the number of levels does not need to be a continuous value because of the nature that the risk is evaluated by the product of the influence level.

  For example, it is assumed that the risk evaluation values for the following two types of facilities are A or B.

Risk of equipment A: Occurrence frequency 5 x Influence level 1 = 5
Risk of equipment B: occurrence frequency 1 × impact 5 = 5
In the above case, it is also necessary to strengthen the monitoring for the equipment B that has the same risk, but has a great influence when a failure or trouble occurs. In this way, it is not realistic to manage the level value as a continuous number from the viewpoint of risk management for equipment where the risk is the same level, but the probability of failure occurrence or the degree of influence is extremely biased. Absent. Therefore, when strengthening management when the failure occurrence probability or the degree of influence is extremely high, it is desirable to subdivide and manage the level value, and it is necessary to consider the situation where the level value is weighted.

  FIG. 11 shows the level classification of the social influence level. Also in this level classification, as in FIG. 10, the discontinuous value is set for each level according to the influence degree rather than setting the level value continuously. However, it is desirable to have a form suitable for the actual risk assessment, such as by giving weights, but by giving weights to both the occurrence frequency and the degree of influence, the risk value becomes wider, On the other hand, care must be taken because it may complicate management. Therefore, it is necessary to consider an operation suitable for the management operation, such as subdividing only one of the level values.

  Next, processing steps in the case where the soundness level is applied as an alternative index of the occurrence probability in step S304 will be described with reference to the conversion table from soundness level to occurrence frequency in FIG.

  As described above, when the data for calculating the failure occurrence probability does not exist, paying attention to the fact that the failure occurrence probability becomes higher according to the aging, the soundness evaluated by the soundness evaluation processing unit 22 Apply degree and convert to occurrence frequency.

  The frequency of occurrence corresponding to the number of classifications of soundness is defined, but when detailed risk assessment is performed, the level value is set in detail, for example, according to the actual state of management operation.

  Next, in step S305, risk assessment is performed in consideration of the social impact. The social impact level is set in the impact level classification table of FIG. 11. The risk for each facility is evaluated based on the frequency of occurrence calculated in step S303 or step S304 and the product of the social impact level table. It is stored in the information database 17. The above risk assessment method is based on the sum of the occurrence frequency (or health level) and social impact level. Other than this method, a matrix with the occurrence frequency (or health level) and social impact level as parameters is created, It is also possible to uniquely define risk levels suitable for management operations on the matrix.

  The processing steps of the cost leveling processing unit 25 will be described with reference to the flowchart of the cost leveling processing in FIG.

  First, in step S401, update time information for each equipment managed and operated in the water supply and sewerage facility is obtained from the equipment information database 11, and in step S402, life cycle cost information for each equipment is obtained from the cost information database 18. get. This life cycle cost includes costs related to the acquisition of equipment, running costs related to maintenance and operation of equipment, costs related to inspection and maintenance, and costs related to equipment removal and renewal.

  In order to obtain a prospect of future update demand, in step S403, the update demand cost for each facility is integrated. For each unit of equipment, the renewal time and the running cost required until the renewal time are clear from the life cycle cost acquired above, so that future renewal demand costs can be tabulated every year.

  However, since the asset valuation amount varies from fiscal year to fiscal year depending on economic conditions, a deflator calculation that applies the deflator for the base year in the next step S404 and converts the nominal value of the asset value to the real asset value of the base year. I do. The deflator is acquired from the cost information database 18.

  In step S404, the result of accumulating the necessary cost based on the update demand of each year and the future budget forecast information that gives the budget constraint conditions of each year are acquired from the cost information database 18, and whether or not future update demand costs can be covered. A comparison determination is performed in step S405.

  As a result of the cost determination in step S405, if the aggregated update demand cost for each year satisfies the budget constraint condition, an update plan is made based on the result. However, if the budget constraint condition is not satisfied, the update is postponed, and the cost leveling is performed so that the update demand cost for the current year falls within the range of the budget constraint given.

  FIG. 14 illustrates the risk level-considering cost leveling process in step S406 with reference to the cost leveling procedure (update destination).

  The risk evaluation processing unit 24 performs risk evaluation for each facility, and the risk information can be acquired from the risk information database 16. In FIG. 14, there are eight items to be updated in year N, A to H, and the risk level decreases in the order of A → H. The principle of cost leveling is to give priority to renewal to those with a high risk level, so there are four top renewal cases: A, B, C, and D. The four cases F, F, G, and H are not fully budgeted and will be postponed to the (N + 1) year.

  In addition, F, F, G, and H, which are postponed renewal cases here, are not subject to preferential renewal in the (N + 1) fiscal year. Is determined. In FIG. 14, the re-evaluation cases E, F, G, and H have a higher risk after re-evaluation, but the renewal cases K and L have a higher risk than H. The result will be postponed to the fiscal year. In this way, the risk in the forward year is implemented each time, and the priority is always determined by the risk evaluation according to the latest state level.

  Next, refer to the procedure for cost leveling (update postponed and forwarded at the same time) for processing when the cost of renewal demand for the current year is significantly below the budget constraint due to cost leveling (update postponed) in FIG. To explain.

  In FIG. 15, in the plan for fiscal year N, renewal projects D, E, and F are not within budget constraints before cost leveling, so the above three projects, D, E, and F, are postponed to fiscal year (N + 1). (However, the update case D cannot be divided).

  At this time, since the cost of the renewal project D is large, the renewal demand cost in the N year is significantly reduced against the budget constraint in the N year. Therefore, it is determined from the viewpoint of a margin of cost whether or not the update cases E and F, which are considered to be postponed to the initial (N + 1) year, can be set as the update case for the N year.

  In the accumulated result after leveling shown in FIG. 15, the update cases E and F were allocated to the margin value generated by postponing the update case D to the (N + 1) year. If there is a deviation between (and still possible to stack), it is determined whether or not the renewal-scheduled item in (N + 1) year before leveling can be advanced.

  In this case, the deviation ΔC between the budget constraint and the renewal demand cost is calculated, and the renewal projects scheduled after the (N + 1) fiscal year and satisfying the conditions within the deviation ΔC are ordered in descending order of risk level. To search. FIG. 15 shows a case in which G, which is positioned as the highest priority renewal case in (N + 1) year, is incorporated as a renewal case in N year on the assumption that the condition is met. As a result, G is deleted from the renewal cases in the (N + 1) fiscal year after leveling, and the renewal cases H, I, J, K, and L are accumulated next to the renewal case D. As a result of the incorporation of D, K and L, which are renewal projects with a low risk level, are postponed to the next (N + 2) fiscal year and thereafter.

  After the renewal demand cost is settled within the range of the budget constraint set for each year by the risk level consideration type cost leveling process in step S406, in step S407, the optimal management of the facilities managed and operated in the water and sewage facilities It is possible to create and present a renewal demand plan.

  According to the above embodiment, it is intended for a wide range of equipment such as mechanical equipment, electrical equipment, various measuring equipment, pipes, etc. installed in the water and sewage facilities, and quantitatively required for the maintenance of these equipment. Determining the degree of soundness and predicting deterioration diagnosis based on various monitoring data acquired by condition monitoring, and risk evaluation based on failure occurrence probability and social impact using actual values or soundness as alternative indicators are possible, and calculated from the results Based on the renewal demand period, the future outlook for renewal demand cost, and when the cost exceeds the budget constraints, the cost can be leveled by postponing the renewal demand period, moving forward, etc. It will be possible to support the optimization of equipment maintenance work.

  Further, by adopting a Web system configuration, it is possible to quickly refer to quantitative results (monitoring results, various analysis results, etc.) input for each related department on-line. And, by grasping the quantitative evaluation process of equipment status, the grounds for setting up the renewal demand plan in the water supply and sewerage facilities become clear, and the maintenance based on the uniform evaluation criteria that does not depend on the individual ability of the person in charge Equipment maintenance management work support method that can be expected to be effective as a technical succession support means that can improve the situation where it is necessary to rely on the know-how of skilled workers and support the operation of inexperienced personnel, while building a management system Can be provided.

1 Data input means 2 Information display means 10 Database (storage means)
11 Facility Information Database 12 Inspection / Maintenance Information Database 13 Plant Information Database 14 Failure Information Database 15 Soundness Evaluation Information Database 16 Deterioration Diagnosis Information Database 17 Risk Evaluation Information Database 18 Cost Information Database 20 Arithmetic Processing Unit 21 Data Collection Processing Unit 22 Soundness Evaluation processing unit 23 Degradation diagnosis processing unit 24 Risk evaluation processing unit 25 Cost leveling processing unit 100 Computer system 200 Water supply or sewerage facility 201 Monitoring control server 202 Raw water or sewage 203 Processing step 204 Pumping facility 205 Purified water or treated water 210 Information network 500 Equipment maintenance management support system

Claims (10)

In the facility maintenance management support system for facilities and equipment managed by the water and sewage business,
Data input means;
Information display means;
A computer system comprising storage means for storing a database and arithmetic processing means;
An information network for performing information communication between the computer system and a water and sewage facility;
In the storage means,
Information on facilities, equipment, and equipment owned and managed by the water and sewage facilities is stored; equipment information database for storing information on equipment names, specifications, specifications, installation time (year), installation locations;
An inspection / maintenance information database for storing various inspection data or monitoring data obtained at the time of the inspection / maintenance operation and the inspection / maintenance work schedule of equipment in the water and sewage facility,
From each process of the water and sewage facilities, a plant information database for storing various management data (measured values including water quality, flow rate, pressure, etc.) acquired in accordance with the monitoring cycle determined for each data,
Information on equipment failure of the water and sewage facilities, failure information database storing alarm contents,
The health assessment information database for storing the health assessment information for the equipment evaluated based on the inspection / maintenance data concerning the equipment operating state of the water and sewage facility, and the plant data and monitoring data and water quality data concerning the equipment,
A deterioration diagnosis information database for storing deterioration diagnosis information for facilities evaluated based on the inspection / maintenance data of the water and sewage facilities, and plant data, monitoring data and water quality data regarding the facilities;
Risk information evaluated for each facility of the water and sewage facilities, equipment failure necessary for the risk assessment or frequency of occurrence of trouble, and social impact information from the viewpoint of management operation when the equipment is stopped due to failure A risk assessment information database for storing
Necessary for the life span from equipment installation to maintenance management to equipment removal / renewal from the cost for each equipment of the water and sewage facilities (cost of equipment, etc.), cost information on maintenance and spare parts, and planning for equipment introduction A cost information database for storing cost information is stored,
The arithmetic processing means includes
Data processing unit for collecting inspection / maintenance information data of equipment related to water supply or sewerage facilities, plant information data indicating the operating state of equipment from the monitoring control server via the information network,
Based on the information in the equipment information database, the inspection / maintenance information database, and the plant information database, based on a plurality of state monitoring data items for each equipment managed in the water and sewage facilities, a quantitative soundness is evaluated by a statistical method. A soundness evaluation processing unit,
Accumulate inspection / maintenance information data and plant information data, predict by statistical analysis how the equipment health will deteriorate over time, and continue management of water and sewage facilities Therefore, a deterioration diagnosis prediction processing unit that predicts the operation limit time of the equipment that can provide a minimum function,
In order to continue normal operation of water and sewage facilities based on the equipment failure stored in the failure information database or the frequency of occurrence of trouble and the social impact information from the viewpoint of management operation when the equipment is stopped due to failure A risk assessment processing unit that evaluates the quantitative risk level when determining the priority of equipment renewal,
From the life cycle cost of each equipment stored in the equipment information database and cost information database, the equipment cost for each fiscal year that will be required in the future will be accumulated, and the renewal demand forecast for the medium and long-term equipment and the renewal demand cost for each fiscal year Is provided with a cost leveling processing unit that calculates the advancement of the update time or the postponement determination so that it falls within the budget for the equipment update. In the equipment maintenance management business support system according to claim 1,
The soundness evaluation processing unit
Obtain equipment specification data from the equipment information database,
Obtain inspection / maintenance and monitoring data from the inspection / maintenance information database and plant information database,
Define the level of inspection / maintenance data and monitoring data items as many as the number of health classifications, and calculate the quantitative health level for each facility from the data classified by the level of qualitative or quantitative criteria. Equipment management work support system characterized by presentation. In the equipment maintenance management business support system according to claim 1,
The deterioration diagnosis prediction processing unit
Obtain equipment specification data from the equipment information database,
Obtain inspection / maintenance and monitoring data from the inspection / maintenance information database and plant information database,
Compare the reference number of data for selecting the deterioration diagnosis method set in advance with the actual number of samples of the inspection / maintenance and monitoring data, and if it is less than the reference value, use the legal useful life as a base. Deterioration diagnosis method based on time-planned maintenance is adopted, and if the number of measured samples is larger than the reference value, a deterioration diagnosis method based on state monitoring maintenance that applies a deterioration model is adopted,
Predict the service life of each equipment from the deterioration diagnosis result by the legal service life or the deterioration diagnosis result by the deterioration model simulation.
When the inspection / maintenance and monitoring data are accumulated and it is possible to grasp the deterioration tendency and characteristics of the equipment with the passage of time, it is possible to make statistical analysis from the evaluation method of the useful life based on the legal useful life. Advancing the degradation diagnosis method into a degradation model,
Evaluate the theoretical and statistical useful life when the restoration of the soundness of the equipment or the relaxation of the deterioration speed can be realized by carrying out inspection and maintenance work, and predict the number of years (period) that the function provided by the equipment can be guaranteed. The facility maintenance management support system characterized in that the predicted useful life can be selected according to the risk from the viewpoint of facility management operation of the water and sewage facilities. In the equipment maintenance management business support system according to claim 1,
The risk assessment processing unit
Obtain equipment specification data from the equipment information database,
As the frequency of occurrence required for risk assessment, select whether to adopt failure occurrence probability based on measured data or to adopt soundness as an alternative index,
When adopting the failure occurrence rate, referring to a table related to the occurrence period and level value set according to the definition of failure occurrence probability, determine the quantitative weight of the failure occurrence probability,
When adopting the soundness as an alternative index of occurrence frequency, referring to the table for converting the soundness evaluated for each facility in the soundness evaluation processing unit into the occurrence frequency, Quantitative weights are determined, and the risk for each facility is evaluated from the frequency of occurrence calculated by either method and the social impact at the time of facility failure.
A facility maintenance management support system, which is presented as a guideline for determining risks in management and operation at water and sewage facilities, or postponement and advancement of equipment replacement demand projects. In the equipment maintenance management business support system according to claim 1,
The cost leveling processing unit
From the equipment information database, obtain update time information for each equipment,
From the cost information database, obtain the life cycle cost for each facility,
Accumulate renewal demand costs for each year,
From the cost information database, obtain deflator information and past actual cost information of equipment accumulated as an update demand item,
Deflator calculation converts past nominal costs into real costs based on the base year,
Determine whether the total amount of substantial renewal demand costs accumulated for each year is within the budget amount for the year,
If the total value of the renewal demand costs exceeds the range of the budget amount, for each renewal demand item accumulated in the year,
Considering the risks evaluated by the risk assessment process, postpones those with low risk to the next fiscal year or later, and leveled the renewal demand cost so that the total value of the new demand cost for that fiscal year falls within the budget amount. Carried out,
When the update demand item is postponed, the cost of the postponed item is large, and the total amount of the update demand cost in the current year and a large cost deviation ΔC in the budget amount (however, the budget amount <the total update demand cost) ) Occurs, extract the high-risk and high-risk and non-exceeding cost deviation ΔC from the renewal demand projects that are going to be postponed, and carry forward the renewal demand projects for the current year A facility maintenance management support system characterized by supporting the creation of an appropriate renewal plan. Storage means for storing a database;
A computer system equipped with arithmetic processing means;
An information network for information communication between the computer system and the water and sewage facility, and a facility and management facility support method for facilities managed by the water and sewage business,
For the storage means,
Creating an equipment information database for storing and storing equipment specification data owned and managed by the water and sewage facilities;
Creating an inspection / maintenance information database that stores the execution schedule of the inspection / maintenance work of equipment in the water and sewage facility and various measurement data or monitoring data obtained at the time of the inspection / maintenance;
Creating a plant information database for storing water quality inspection results and monitoring data from each process of the water and sewage facilities,
Creating a failure information database for storing information on equipment failures in the water and sewage facilities, alarm contents;
Creating a soundness evaluation information database for storing soundness evaluation information for equipment related to the equipment operating state of the water and sewage facilities;
Creating a deterioration diagnosis information database for storing deterioration diagnosis information for the facilities of the water and sewage facilities;
Creating a risk evaluation information database for storing risk information evaluated for each facility of the water and sewage facilities;
Creating a cost information database for storing cost information for each facility of the water and sewage facilities;
For the computer system,
Collecting inspection / maintenance information data of equipment related to waterworks or sewerage facilities, plant information data indicating the operating state of equipment from the monitoring control server via the information network,
Based on the information in the equipment information database, the inspection / maintenance information database, and the plant information database, based on a plurality of state monitoring data items for each equipment managed in the water and sewage facilities, a quantitative soundness is evaluated by a statistical method. To do,
Accumulate inspection / maintenance information data and plant information data, predict by statistical analysis how the equipment health will deteriorate over time, and continue management of water and sewage facilities In order to predict the operation limit period of the equipment that can provide the minimum functions,
In order to continue normal operation of water and sewage facilities based on the equipment failure stored in the failure information database or the frequency of occurrence of trouble and the social impact information from the viewpoint of management operation when the equipment is stopped due to failure Assessing risk management indicators and quantitative risk levels when determining the priority of equipment renewal,
From the life cycle cost of each equipment stored in the equipment information database and cost information database, the equipment cost for each fiscal year that will be required in the future will be accumulated, and the renewal demand forecast for the medium and long-term equipment and the renewal demand cost for each fiscal year However, the equipment maintenance management business support method is characterized in that the update time is advanced or the postponed judgment is calculated so that the cost is within the budget for equipment update. In the equipment maintenance management work support method of claim 6,
Obtain equipment specification data from the equipment information database,
Obtain inspection / maintenance and monitoring data from the inspection / maintenance information database and plant information database,
Define the level of inspection / maintenance data and monitoring data items as many as the number of health classifications, and calculate the quantitative health level for each facility from the data classified by the level of qualitative or quantitative criteria. Equipment management work support method characterized by presenting. In the equipment maintenance management work support method of claim 6,
Obtain equipment specification data from the equipment information database,
Obtain inspection / maintenance and monitoring data from the inspection / maintenance information database and plant information database,
Compare the reference number of data for selecting the deterioration diagnosis method set in advance with the actual number of samples of the inspection / maintenance and monitoring data, and if it is less than the reference value, use the legal useful life as a base. Deterioration diagnosis method based on time-planned maintenance is adopted, and if the number of measured samples is larger than the reference value, a deterioration diagnosis method based on state monitoring maintenance that applies a deterioration model is adopted,
Predict the service life of each equipment from the deterioration diagnosis result by the legal service life or the deterioration diagnosis result by the deterioration model simulation.
When the inspection / maintenance and monitoring data are accumulated and it is possible to grasp the deterioration tendency and characteristics of the equipment with the passage of time, it is possible to make statistical analysis from the evaluation method of the useful life based on the legal useful life. Advancing the degradation diagnosis method into a degradation model,
Evaluate the theoretical and statistical useful life when the restoration of the soundness of the equipment or the relaxation of the deterioration speed can be realized by carrying out inspection and maintenance work, and predict the number of years (period) that the function provided by the equipment can be guaranteed. An equipment maintenance management business support method characterized in that the predicted service life can be selected according to the risk from the viewpoint of equipment management operation of the water and sewage facilities. In the equipment maintenance management work support method of claim 6,
Obtain equipment specification data from the equipment information database,
As the frequency of occurrence required for risk assessment, select whether to adopt failure occurrence probability based on measured data or to adopt soundness as an alternative index,
When adopting the failure occurrence rate, referring to a table related to the occurrence period and level value set according to the definition of failure occurrence probability, determine the quantitative weight of the failure occurrence probability,
When adopting the soundness as an alternative index of occurrence frequency, referring to the table for converting the soundness evaluated for each facility in the soundness evaluation processing unit into the occurrence frequency, Quantitative weights are determined, and the risk for each facility is evaluated from the frequency of occurrence calculated by either method and the social impact at the time of facility failure.
A facility maintenance management support method characterized in that it is presented as a guideline for determining risk in management and operation in water and sewage facilities, or postponement or advancement of facility replacement demand projects. In the equipment maintenance management work support method of claim 6,
From the equipment information database, obtain update time information for each equipment,
From the cost information database, obtain the life cycle cost for each facility,
Accumulate renewal demand costs for each year,
From the cost information database, obtain deflator information and past actual cost information of equipment accumulated as an update demand item,
Deflator calculation converts past nominal costs into real costs based on the base year,
Determine whether the total amount of substantial renewal demand costs accumulated for each year is within the budget amount for the year,
If the total value of the renewal demand costs exceeds the range of the budget amount, for each renewal demand item accumulated in the year,
Considering the risks evaluated by the risk assessment process, postpones those with low risk to the next fiscal year or later, and leveled the renewal demand cost so that the total value of the new demand cost for that fiscal year falls within the budget amount. Carried out,
When the update demand item is postponed, the cost of the postponed item is large, and the total amount of the update demand cost in the current year and a large cost deviation ΔC in the budget amount (however, the budget amount <the total update demand cost) ) Occurs, extract the high-risk and high-risk and non-exceeding cost deviation ΔC from the renewal demand projects that are going to be postponed, and carry forward the renewal demand projects for the current year A facility maintenance management support method characterized by supporting the creation of an appropriate renewal plan.