JP6733004B1 - Equipment and parts failure evaluation device and failure evaluation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To appropriately perform maintenance effectiveness evaluation of equipment or parts in equipment, improve equipment reliability and reduce maintenance cost. SOLUTION: From a collection condition designating unit 11 for designating a collection condition for evaluating a failure of a device or a part in equipment, and a failure record 1 of the device or the part, a failure case of the device or the part satisfying the collection condition is extracted. The failure case extracting unit 12, the failure classification information adding unit 13 for adding the failure classification information for classifying the characteristics of the failure including the failure cause in the failure case to the failure case with reference to the failure record, and the equipment exist in the equipment. Using the data collection means 14 for collecting the data 3 necessary for the failure evaluation of the device or the part satisfying the collection condition from the information 2 of the device or the part, and the data necessary for the failure evaluation and the failure classification information, the device or the part And a plurality of analysis means for calculating and analyzing a failure occurrence probability for a failure case of a component. [Selection diagram] Figure 1

Description

Embodiments of the present invention relate to a failure evaluation apparatus for equipment and parts, which evaluates failures of equipment or parts in equipment, and a failure evaluation method for equipment and parts.

In a large-scale system such as a plant such as a power plant or a transportation machine, in order to maintain the reliability of the system, its constituent subsystems, facilities, equipment, etc. must be properly maintained. For the maintenance of equipment, as specified in JIS, etc., time-planned maintenance (TBM) that regularly performs overhauls and inspections, and parameters related to equipment deterioration and failure are observed, and according to the state There are three types of maintenance methods: condition monitoring maintenance (CBM) that performs overhaul and inspection, etc., and post-maintenance maintenance (BDM) that repairs when a device failure is discovered or when there is a loss of function. By appropriately combining these maintenance methods according to the importance and characteristics of the equipment, it becomes possible to maintain system reliability and suppress repair costs and production loss.

Heretofore, various attempts have been made as an optimum determination method of a maintenance method. For example, in the US aviation industry, the military, etc., a failure characteristic (time-dependent curve of failure rate) is obtained from an investigation of failure and deterioration of a huge number of mechanical parts, and the above-mentioned It is being examined whether the maintenance method is appropriate. As a result, the TBM induces so-called tampering with most of the machinery and equipment, resulting in an increase in maintenance costs and loss costs, while the CBM provides optimum maintenance that ensures both reliability and maintenance costs. It has been clarified that this is a system, and it was introduced 30 to 40 years ago in Japan, mainly in the steel and chemical industries.

However, in the current maintenance of nuclear power plants, as a preventive maintenance for most of the equipment, TBM that performs equipment overhaul and inspection at a fixed cycle is carried out, and most of the overhaul and inspection are performed by the plant. It is carried out during the periodic inspection of. With TBM, the cycle of overhaul and inspection must be set to be extremely short for the original life of the equipment, which causes so-called over-maintenance, which increases maintenance costs, and overhaul and inspection is performed regardless of the deterioration state of the equipment. Therefore, there is a problem that it is easy to cause so-called tampering which causes a failure in the disassembling/assembling process for a device that has not deteriorated. In addition, many operations are concentrated during the periodic inspections for several months, so the process is complicated and troubles are likely to occur, and the regular inspection process cannot be shortened, so the plant operation rate is improved. There is also the problem that it is difficult.

CBM is a system that determines the timing of overhaul and inspection by periodically monitoring the data indicating the deterioration state of equipment such as vibration and temperature, and reduces the above-mentioned troubles caused by tampering and occurs during operation of equipment. This is effective in early detection of sudden failures that occur. The reason why the effect of CBM is very large is as follows.

First, the failure characteristics of mechanical equipment and parts have a high initial failure rate, then enter a stable period (random failure period), and this stable period is very long (the number of failures due to wear deterioration is very small and human error Because of many failures). Secondly, the failure characteristics of mechanical equipment and parts differ greatly even in the same model until the start of the wear failure period. Further, even if the device has a deterioration characteristic in which the failure rate increases with time, if the deterioration can be monitored, more efficient and reliable maintenance can be performed than the TBM.

On the other hand, the TBM must be set whenever there is a time-dependent degradation in which the CBM is not possible, ie the state cannot be monitored. Therefore, optimizing the TBM cycle for such equipment is important for securing the reliability of the plant and suppressing the maintenance cost, as in the introduction of the CBM. In general, it is ideal to perform maintenance by optimally combining TBM and CBM according to individual characteristics and importance of plants and equipment. Here, the degree of importance is set by a technique such as reliability-oriented maintenance (described later).

In recent years, optimization of maintenance methods including reliability-oriented maintenance (RCM) and condition monitoring maintenance (CBM), which have a proven record in other industries such as petrochemicals and nuclear power plants in the United States, has been attempted. In addition, the inspection system at a nuclear power plant requires “conservation effectiveness evaluation” (JEAG 4210) that evaluates and reviews the TBM cycle and method, the applicability of CBM, etc. based on actual data.

This maintenance effectiveness evaluation evaluates from the maintenance record and breakdown record of the plant and equipment whether maintenance that maintains the function of the plant and equipment is properly performed, and whether there are any flaws in the maintenance method or cycle. It is a thing. In this maintenance effectiveness evaluation, it is required to confirm that the maintenance is being performed effectively, but it is confirmed that the maintenance results are good, and that the cycle of overhaul and inspection has a margin for the deterioration speed of the equipment. It is also possible to extend the cycle when permitted.

In addition, a device chart management method that comprehensively determines the device state can be applied by combining state monitoring data in the CBM or TBM of equipment or parts of equipment such as a plant and various inspection data during overhaul inspection. In this equipment chart management method, a huge amount of data is processed to determine pass/fail, so as a means for supporting the huge amount of data, a threshold is set for each data to perform primary screening, thereby reducing manpower. Has been planned. However, since the threshold setting work itself becomes enormous, a threshold setting support method has been proposed. In addition, a method of supporting the setting of device importance by reliability-oriented maintenance (RCM) has been proposed.

Furthermore, the data evaluation in the maintenance effectiveness evaluation and the data of the huge amount of equipment installed in the plant are efficiently processed, and the equipment that is a candidate for simplifying the maintenance is efficiently extracted based on this processed data. At the same time, equipment that is suspected to have an error in maintenance is also extracted, and a detailed data analysis using graphs and equipment deterioration characteristics are combined and evaluated to optimize the equipment maintenance method. A method for supporting the effectiveness evaluation of the equipment maintenance method is also proposed.

On the other hand, attempts have been made to reduce the failure rate by setting the optimal maintenance cycle of the equipment by evaluating the frequency of failures that have occurred in the equipment. In the evaluation of the effectiveness of the equipment maintenance method described above, the quality data of the maintenance of the equipment is used to judge the quality of the maintenance status.However, if the failure rate is used, statistically based on the operation results of the equipment of the same model. From this point of view, it is possible to judge the quality of the maintenance situation across the entire plant or a plurality of devices. This is because, for example, for a device operated and maintained under a certain condition, the condition can be improved so as to reduce the failure rate by comparing the condition with the failure rate.

Here, the failure rate is, based on the general knowledge of reliability engineering, using the mean time between failures (MTBF), failure rate=1/MTBF, MTBF=(system operation time)/(failure within the above operation time) Number of times). That is, the failure rate can be calculated by statistically processing the record of the operating state of the equipment in the facility. For example, a technique has been disclosed for the purpose of calculating the failure rate, predicting the service life of equipment and parts, and providing an optimal maintenance cycle. In the field of nuclear power generation, the failure rate is used as an input for probabilistic safety evaluation.

International Publication No. 2012/157040 JP, 2009-217718, A

However, as described above, the so-called tampering damage caused by the overhaul and inspection performed by the TBM is caused by human error or the like, and is not directly related to the operating time of the system. Therefore, in the evaluation based only on the failure rate based on the mean time between failures (MTBF), the failure due to human error and the failure due to the deterioration depending on the time of the equipment are treated in the same row, and the cause of the failure and the planning of the countermeasure are planned. May cause discrepancies. Therefore, an evaluation based only on the failure rate does not lead to improvement in maintenance, and an evaluation that truly reduces the number of failures of the system cannot be performed.

Also, in order to reduce failures due to deterioration that tends to occur over time (for example, failures that have a clear relationship between operating time and failure occurrence, such as the progress of corrosion that occurs in pumps that handle corrosive fluids), It is sufficient to set the maintenance cycle based on the failure rate and the failure rate, but for the failure without time tendency (non-time-dependent failure), it is necessary to remove the cause event. It is necessary to evaluate the relationship with the occurrence. However, in the failure evaluation using the failure rate based on the operating time of the equipment and the number of failures as described above, it is possible to properly evaluate the relationship between the failure-causing event and the failure occurrence for the non-time-dependent failure. Can not.

The embodiment of the present invention has been made in consideration of the above circumstances, and it is possible to appropriately perform maintenance effectiveness evaluation of a device or a part in equipment, improve equipment reliability, and reduce maintenance cost. An object of the present invention is to provide a failure evaluation device and a failure evaluation method for equipment and parts.

A failure evaluation apparatus for facility equipment/parts according to an embodiment of the present invention includes a collection condition designating unit for designating a collection condition for evaluating a failure of a device or a component in the facility, and a failure record of the equipment or the component, Failure case extraction means for extracting a failure case for the device or the part satisfying a condition, and a failure caused by aged deterioration and a failure caused by human error for classifying characteristics of the failure including a failure cause in the failure case From the information on the device or the part existing in the equipment, the device or the condition satisfying the collecting condition A failure occurrence probability for the failure case of the device or the part using the data collection means for collecting the data necessary for the failure evaluation of the part and the data necessary for the failure evaluation and the failure classification information. A plurality of analyzing means for calculating and analyzing, and a selecting means for selecting the analyzing means that matches the failure classification information from the plurality of analyzing means, the selecting means adding to the failure case The recognizing means for recognizing the fault classification information thus selected and the analyzing means adapted to the fault classification information recognized by the recognizing means are selected, and the selected analyzing means is associated with the fault case. Distribution means for allocating the data necessary for failure evaluation and the failure classification information, and the failure occurrence probability for the failure case of the device or the component by the analysis means selected by the selection means. Is configured to calculate and analyze, the failure occurrence probability calculated and analyzed by the analysis means, if the failure is a failure due to aging deterioration, the operating time of the device or part and the failure at this operating time It is a failure rate calculated based on the number of times, and when the failure is caused by human error, the number of operations that may cause the human error in the arbitrary period of the equipment or parts and the human error. It is characterized in that it is a failure occurrence probability calculated based on the number of occurrences of mistakes .

A failure evaluation method for facility equipment/parts according to an embodiment of the present invention includes a collection condition designating step of designating a collection condition for assessing a failure of a device or a component in equipment by a collection condition designating means , Aged deterioration for classifying the characteristics of the failure including the cause of the failure in the failure case extraction step for extracting the failure case for the device or the part satisfying the collection condition from the failure record by the failure case extraction means. Fault classification information including a fault caused by a fault and a fault caused by a human error , the fault classification information adding means adds the fault classification information to the fault case with reference to the fault record, and the fault classification information existing in the facility is added. A data collecting step of collecting data necessary for evaluating the failure of the device or the part satisfying the collecting condition from the information of the device or the part by data collecting means , data necessary for the evaluation of the failure, and the failure. Selection of selecting the analysis means that matches the failure classification information by a selection means from a plurality of analysis means that calculates and analyzes a failure occurrence probability for the failure case of the device or the part using the classification information a step, by the analyzing means selected by said selecting means, have a, an analysis step of analyzing calculates the failure probability to the failure cases of the device or the component, said selection means, said A recognition unit that recognizes the failure classification information added to the failure case and an analysis unit that matches the failure classification information recognized by the recognition unit are selected, and the failure case is set to the selected analysis unit. And a distribution unit that distributes the data necessary for evaluation of the failure and the failure classification information associated with the failure occurrence probability calculated and analyzed by the analysis unit is a failure caused by aged deterioration. In this case, it is a failure rate calculated based on the operating time of the device or part and the number of failures in this operating time.If the failure is due to human error, any of the devices or parts It is characterized in that it is a failure occurrence probability calculated on the basis of the number of operations that may cause the human error in the period and the number of times the human error has occurred .

According to the embodiments of the present invention, it is possible to appropriately perform maintenance effectiveness evaluation for a device or a part in a facility, improve the reliability of the facility, and reduce maintenance costs.

The block diagram which shows the structure in the failure evaluation apparatus of the equipment and component which concerns on 1st Embodiment. Explanatory drawing which mainly shows the data required for evaluation of the failure which the data collection means of FIG. 1 collected. FIG. 2 is a block diagram showing the configuration of the analyzing means and the selecting means of the analyzing means of FIG. 1. FIG. 3 is a chart showing a specific example of data required for evaluation of the failure in FIG. 2. Explanatory drawing which mainly shows the data required for the evaluation of the failure which the data collection means in the failure evaluation apparatus of the equipment device/part concerning 2nd Embodiment collected. The block diagram which shows the structure of the analysis means and the selection means of an analysis means in the failure evaluation apparatus of the equipment and parts shown in FIG.

Hereinafter, modes for carrying out the present invention will be described with reference to the drawings.
[A] First embodiment (FIGS. 1 to 4)
FIG. 1 is a block diagram showing the configuration of a failure evaluation device for facility equipment/parts according to the first embodiment. The equipment device/part failure evaluation apparatus 10 shown in FIG. 1 includes a failure record 1 and equipment or parts existing in the equipment in order to appropriately perform maintenance effectiveness evaluation of the equipment or parts in equipment such as a power plant. From the information 2 (maintenance record, operation time, etc.), the failure occurrence probability is calculated according to the characteristics of the failure including the cause of failure, analyzed, and evaluated. The equipment/parts failure evaluation apparatus 10 includes a collection condition designating means 11, a failure case extracting means 12, a failure classification information adding means 13, a data collecting means 14, an analyzing means 15, an analyzing means selecting means 16, and an analyzing means. It has a result storage means 17 and an output means 18.

Here, the maintenance effectiveness evaluation is performed appropriately based on the maintenance record and the breakdown record 1 of the equipment such as the plant, or the equipment and parts constituting the equipment, to maintain the function of the equipment, the equipment or the parts. It is to evaluate whether or not there are any deficiencies in the maintenance method and cycle.

The failure record 1 is recorded in a ledger or database by paper or electronic means as nonconformity management information in a general plant. In this failure record 1 (nonconformance management information), the status of failure (increase in vibration, decrease in flow rate, etc.), time series of failure, cause of failure (aging deterioration, human error, etc.), measures against failure, horizontal deployment, etc. are recorded. Has been done.

The information 2 of the equipment or parts existing in the facility (for example, plant) is the maintenance record, the operating time, the design information, the usage condition, the facility information and the like. The maintenance record is data indicating the content and result of maintenance such as when and how many times the maintenance of the device or part related to the failure was performed, the contractor, and the like. Specifically, the maintenance record is stored in a report of disassembly and inspection of equipment or parts performed in regular inspections, a status monitoring report which is a result of monitoring the operation status of the equipment, and the like. For example, as shown in FIG. 4, the maintenance record of the pump is vibration measurement of each part and analysis of lubricating oil as state monitoring during normal operation, and replacement of consumable parts, non-destructive inspection of impeller, pressure resistant part as disassembly and inspection. Such as non-destructive inspection.

The operating time is, for example, an operating time of a device or a part related to a failure, a calendar time after the installation of the device or the part, particularly a time after replacement of the part causing the failure. For example, the operating time of the pump is the actual operating time of the pump or the calendar time after the pump is installed. Further, the design information is design information of a device or a part related to the failure. For example, pump design information includes a pump model, manufacturer, rated performance, etc., and is generally recorded in an equipment ledger or an equipment management system.

The use condition is a condition such as a use environment or load of a device or a part related to the failure. For example, the usage conditions of the pump are the internal fluid of the pump and the operating load (such as the constant operating load and the immediate standby load in preparation for troubles), which are generally recorded in the facility ledger and the facility management system. The facility information includes the owner (department in charge) of the device or part related to the failure, device number, part number, plant information, and the like.

The collection condition designating means 11 carries out a collection condition designating step for designating, through an engineer or the like, a collection condition for evaluating a failure of a device or a component in equipment such as a plant. This collection condition is any one device or one part, a plurality of devices or parts having a common attribute, equipment of the entire plant, etc. Including collection time. Specifically, the collection condition is one of the attributes of the device (eg, pump) (eg, centrifugal pump) and a fixed collection period.

As shown in FIGS. 1 and 2, the failure case extraction unit 12 determines a failure for a device or a part that satisfies a collection condition (for example, a centrifugal pump, a fixed collection period) based on a failure record 1 of the device or a part in equipment such as a plant. The failure case extraction step of extracting cases 1 to m is executed. In the failure case extracting step performed by the failure case extracting unit 12, for example, a centrifugal pump and a fixed collection period are set as collection conditions, and “vibration increase” as one failure case and “flow rate decrease” as another failure case. Each applicable device or part is extracted from the failure record 1. Further, in this failure case extraction step, the same failure may occur under the same collection condition. Therefore, failure cases 1 to m are not limited to different cases, and the same failure case is plural. Including cases.

The failure classification information adding means 13 adds the failure classification information a1 to am for classifying the characteristics of the failure (including the cause of the failure) in the failure case to each of the failure cases 1 to m with reference to the failure record 1. The failure classification information adding step is executed. The failure classification information includes, for example, failures due to aging of devices and parts and failures due to human error (for example, operator error in maintenance work, design error or manufacturing error in manufacturing machine or parts, operation error in operation). Device operation failure). Also, if a human error is the starting point of deterioration that has progressed for a certain period of time and is manifested as a failure, it is not aged deterioration but is classified as a human error or another failure different from aged deterioration or human error. Classify.

If the collection condition is a centrifugal pump and the failure case is "vibration increase", for example, a failure in which vibration increases due to the life of parts such as bearings is classified as a failure due to aged deterioration, and it is caused by an assembly and adjustment error in disassembly and inspection. Then, the failure with increased vibration is classified as a failure caused by human error.

In the failure record 1, usually, the cause of the failure or information serving as a clue to the failure is described. Therefore, the failure classification information adding unit 13 adds the failure classification information a1 to am to each of the failure cases 1 to m by referring to the failure record 1. The fault classification information a1 to am is added by an appropriate algorithm, AI (artificial intelligence) method, or human system.

The reason why clearly classifying the characteristics of a failure including the cause of the failure by the failure classification information adding unit 13 contributes to the improvement of maintenance is as follows. In other words, if the failure rate and the mean time between failures (MTBF) are evaluated by equating the failure due to human error with the failure due to aging deterioration, the replacement interval of the equipment or parts becomes too short, resulting in over maintenance. Because there is a possibility that Further, if the cause of human error is inherent in the replacement work of the equipment or parts, the replacement work interval will be shortened and the occurrence of failures will be increased. Furthermore, by equating a failure caused by human error with a failure caused by deterioration over time, it may not be possible to pay attention to the cause of human error.

The data collection means 14 uses information 2 (that is, maintenance records, operating hours, design information, usage conditions, facility information, etc.) of equipment or parts existing in facilities such as plants to collect conditions (for example, a centrifugal pump and a fixed collection period). The data 3 necessary for the evaluation of the failure is collected for each of the devices or parts satisfying the condition (4), and the data collection step is performed to associate the data 3 required for the evaluation of the failure with each of the failure cases 1 to m. The information 3 required for the above-mentioned failure evaluation is data necessary for calculation and analysis of the failure occurrence probability described later, and includes maintenance records b1 to bm, operating hours c1 to cm, design information d1 to dm, and usage conditions e1 to em. , Equipment information f1 to fm, etc., and a specific example thereof is shown in FIG.

For example, when the collection condition includes a centrifugal pump and the failure case is “vibration increase”, the data 3 required for failure evaluation is that the failure classification is due to aged deterioration in which vibration increases due to the life of the device or part. At the time of failure, at least the operating time (operating time in FIG. 4) is required to calculate the failure rate described later, and the failure classification is a failure caused by human error in which vibration increases due to an assembly adjustment error at the time of overhaul and inspection. In the case of, at least the number of maintenances (the number of overhauls and inspections in FIG. 4) for calculating the failure occurrence probability described later is necessary.

In addition, the data collection unit 14 may perform the other operation if the failure occurrence probability is calculated by the analysis unit 15 for an attribute other than the attribute (for example, centrifugal pump) that is the collection condition for the device or the component as described later. Information regarding the attribute of is also collected from the information 2 of the equipment or parts existing in the facility. For example, when the analyzing unit 15 calculates and analyzes the failure occurrence probability for each contractor, the data collecting unit 14 determines the contractor (the contractor in FIG. 4) from the information 2 of the equipment or parts existing in the facility. Collect data.

The selecting means 16 of the analyzing means selects the analyzing means 15 that matches the failure classification information a1 to am from the plural (for example, n) existing analyzing means 15, and the recognizing means 16A as shown in FIG. And a distribution means 16B. The recognition means 16A is for recognizing the failure classification information a1 to am added to the failure cases 1 to m, and is configured by software means or human system.

The distribution means 16B selects the analysis means 15 that matches the failure classification information a1 to am recognized by the recognition means 16A, and evaluates the failures associated with the failure cases 1 to m by the selected analysis means 15. The necessary data 3 and the failure classification information a1 to am are distributed. Here, there are a plurality of analysis means 15, and as described later, each analysis means 15 calculates the failure occurrence probability corresponding to the failure classification (for example, failure due to aging deterioration, failure due to human error, etc.). Is different. Therefore, the distribution unit 16B selects the analysis unit 15 having a failure occurrence probability calculation method that matches the failure classification information a1 to am.

The analysis unit 15 uses the data 3 and the failure classification information a1 to am necessary for the failure evaluation to calculate and analyze the failure occurrence probabilities for the failure cases 1 to m of the equipment or parts by a statistical method. The step is executed, and there are a plurality of steps according to the failure classification information. Each of the analysis means 15 has a different failure occurrence probability calculation method, and the analysis means 15 selected by the selection means 16 of the analysis means calculates and analyzes the failure occurrence probability corresponding to each of the failure classification information a1 to am. To do.

That is, for a failure due to aged deterioration of a device or a component, for example, a failure due to aged deterioration in which vibration is increased due to the life of the device or a component, one analysis unit 15 determines the failure rate as the failure occurrence probability to the device or the component. It is calculated and analyzed based on the operating time of parts and the number of failures in this operating time.
Failure rate = (number of failures in the operating time of the device or part) / (above operating time of the device or part)

Further, with respect to a failure of a device or a part due to a human error, for example, a failure due to a human error in which vibration is increased due to an assembly/adjustment error in disassembly and inspection, the other analysis means 15 uses the failure occurrence probability as the failure occurrence probability. Is calculated and analyzed based on the number of operations that may cause human error and the number of times human error has occurred in any period of equipment or parts.
Failure probability = (number of human error occurrences) / (number of operations that may cause human error above)

Further, in the calculation and analysis of the failure occurrence probability (failure rate, failure occurrence probability) by the analysis means 15, one specific device or one part as a collection condition, or a common attribute such as a centrifugal pump is used. It is implemented for a plurality of devices and a plurality of parts provided. Furthermore, the analysis unit 15 determines other attributes other than the attribute (for example, the model such as a centrifugal pump) that is a collection condition in the device or the component, such as the maintenance contractor, the type of the internal fluid of the pump, or the like of the device or the component. Failure probability may be calculated and analyzed for failure cases 1 to m (vibration increase, flow rate decrease, etc.). Data relating to attributes other than the above-mentioned attributes which are the collection conditions are collected by the data collecting means 14 from the information 2 of the equipment or parts existing in the facility and are associated with the failure cases 1 to m of the equipment or parts. Is used.

The failure occurrence probability calculated and analyzed by the analysis unit 15 based on the failure classification information a1 to am as described above is stored in the analysis result storage unit 17 as the analysis result. Further, the output unit 18 outputs and displays the analysis result (probability of failure) stored in the analysis result storage unit 17.

With the above configuration, according to the first embodiment, the following effect (1) is achieved.
(1) As shown in FIG. 1 and FIG. 2, the failure evaluation apparatus 10 for facility equipment/parts fails according to the failure characteristics (failure classification) of the equipment or parts in the equipment such as a plant, including the cause of the failure. Occurrence probability is calculated and analyzed. That is, the analysis means 15 in the equipment/component failure evaluation apparatus 10 obtains the failure rate as the failure occurrence probability when the failure is classified as a failure due to the aged deterioration of the equipment or the component, and the failure is a human error. If the failure is classified as a failure due to, the failure occurrence probability is obtained as the failure occurrence probability, and each is analyzed and evaluated.

As a result, the maintenance effectiveness of equipment such as a plant can be properly evaluated, and the maintenance cycle including the replacement of equipment or parts can be optimized to prevent so-called over-maintenance, so that the maintenance cost can be reduced. In addition, since the characteristics of the device including the cause of the failure are clarified, the failure can be improved, and so-called tampering can be suppressed by optimizing the maintenance cycle, so that the reliability of the equipment can be improved.

[B] Second embodiment (FIGS. 5 and 6)
FIG. 5 is an explanatory diagram mainly showing the data necessary for the failure evaluation collected by the data collecting means in the failure evaluation device for facility equipment/parts according to the second embodiment. In the second embodiment, the same parts as those in the first embodiment are designated by the same reference numerals as those in the first embodiment to simplify or omit the description.

The failure evaluation device 20 for facility equipment/parts of the second embodiment is different from the failure evaluation device 20 of the first embodiment in that the data 5 required for evaluation of failures collected by the data collection means 21 in association with the failure cases 1 to m. In addition to the data related to the failed device or component (that is, the data 3 required for the failure evaluation of the first embodiment; the “data related to the failed device or component” is represented by reference numeral 3 in the second embodiment), This is the point that the data 4 regarding the same type of equipment or component that has the same type or use condition as the faulty equipment or component but does not fail is included. Here, the same type or use condition means that the model is the same, such as a centrifugal pump, or the internal fluid flowing in the pump is the same.

That is, the data collection means 21 uses the information 2 of the equipment or parts existing in the equipment even if no failure case is extracted from the failure record 1 by the failure case extraction means 12 for the equipment or parts satisfying the collection condition. For devices or parts that satisfy the collection condition, data 4 regarding similar devices or parts that have not failed is collected.

As described above, in addition to the data 3 related to the failed device or part, the data 5 necessary for the failure evaluation includes the same kind of non-failed device or part with the same type or use condition as the failed device or part. 6 includes data 4 relating to these, the analysis means 22 is required for evaluation of the failure including data 3 relating to these failed devices or parts and data 4 relating to non-faulty similar devices or parts. The failure occurrence probability is calculated and analyzed using various data 5 and the failure classification information a1 to am.

That is, when the failure is a failure due to the aged deterioration of the device or the component, the analysis unit 22 calculates and analyzes the failure rate based on the operating time of the device or the component and the number of failures in the operating time. As the above-mentioned operating time, the sum of the operating time in the data 3 regarding the failed device or component and the operating time in the data 4 regarding the same type of device or component that has not failed is used.

Further, when the failure is a failure of the device or the part caused by the human error, the analysis means 22 determines the number of operations (for example, overhaul and inspection) that may cause the human error of the device or the part in an arbitrary period and the human error. The failure probability is calculated and analyzed based on the number of mistakes made. As the number of works that may cause human error, the number of works in the data 3 relating to the failed device or part and the number of works The sum of the above-mentioned number of times of work in the data 4 regarding the same type of non-equipment or parts is used.

Further, when analyzing the failure occurrence probability for an attribute other than the attribute that is the collection condition for the device or part, the analysis unit 22 further includes the data 3 regarding the failed device or part and the same type of device that has not failed or The failure occurrence probability is calculated and analyzed using the data 5 necessary for the failure evaluation including the data 4 regarding the parts and the failure classification information a1 to am.

With the above configuration, the second embodiment also has the same effect as the effect (1) of the first embodiment, and also has the following effect (2).

(2) The analysis unit 22 includes data 3 regarding a failed device or part, data 4 regarding a similar device or part that has the same type or usage condition as the failed device or part but has not failed, and the failure classification information a1. ~ Am is used to calculate and analyze the failure probability. In this way, by analyzing the failure occurrence probability for the same type of equipment or part including the failed equipment or part, it is possible to evaluate the failure for each of the same type of equipment or part.

Although some embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention, and the replacements and changes thereof can be performed. Is included in the scope and gist of the invention, and is also included in the invention described in the claims and its equivalent scope.

1...Failure record, 2...Information of equipment or parts existing in equipment, 3...Data required for failure evaluation, 4...Data relating to similar equipment or parts that have not failed, 5...Data required for failure evaluation 10... Failure evaluation device for equipment/parts, 11... Collection condition designating means, 12... Failure case extracting means, 13... Failure classification information adding means, 14... Data collecting means, 15... Analyzing means, 16... Analyzing means Selection means, 16A... Recognition means, 16B... Sorting means, 20... Failure evaluation device for equipment/parts, 21... Data collecting means, 22... Analysis means, 1-m... Failure cases, a1-am... Failure classification information

Claims (5)

Collection condition designating means for designating collection conditions for evaluating a failure of equipment or parts in equipment,
Failure case extraction means for extracting a failure case for the device or the part satisfying the collection condition from the failure record of the device or the part;
Fault classification information including a fault due to aged deterioration and a fault due to human error for classifying characteristics of a fault including a fault cause in the fault case is added to the fault case with reference to the failure record. Failure classification information adding means,
Data collection means for collecting data necessary for evaluation of the failure of the device or the part satisfying the collection condition from the information of the device or the part existing in the facility,
A plurality of analysis means for calculating and analyzing a failure occurrence probability for the failure case of the device or the part by using the data necessary for the evaluation of the failure and the failure classification information;
Selecting means for selecting the analyzing means that matches the failure classification information from among the plurality of analyzing means,
The selecting means selects a recognizing means for recognizing the failure classification information added to the failure case and an analyzing means suitable for the failure classification information recognized by the recognizing means, and the selected analysis. The means has a distribution means for allocating the data necessary for evaluation of a failure associated with the failure case and the failure classification information,
The analyzing unit selected by the selecting unit is configured to calculate and analyze the failure occurrence probability for the failure case of the device or the component ,
The failure occurrence probability calculated and analyzed by the analysis unit is a failure rate calculated based on the operating time of the device or part and the number of failures in this operating time when the failure is a failure due to aging deterioration. If the failure is a failure caused by human error, it is calculated based on the number of operations that may cause the human error and the number of times the human error occurs in any period of the device or part. A failure evaluation device for equipment and parts, which is characterized by the probability of failure occurrence . The equipment/parts failure evaluation apparatus according to claim 1, wherein the data collection means is configured to associate the data necessary for the failure evaluation, which is collected based on the collection conditions, with the failure case. The analysis means is configured to be able to calculate and analyze a failure occurrence probability for a failure case of the device or the component with respect to an attribute other than the attribute that is a collection condition in the device or the component. A failure evaluation device for equipment and parts according to claim 1 or 2 . The data necessary for the evaluation of the failure associated with the failure case by the data collection means includes, in addition to the data on the failed device or part, the same type or use condition as the failed device or the part, or the failure condition. 4. The failure evaluation device for facility equipment/parts according to any one of claims 1 to 3 , wherein data relating to the same type of equipment or part that does not exist is included. A collection condition designating step of designating a collection condition for assessing a failure of a device or a part of equipment by a collection condition designating means ,
A failure case extraction step of extracting a failure case of the device or the part satisfying the collection condition from a failure record of the device or the part by a failure case extracting means ;
For classifying the characteristics of the failure including the failure cause in the failure case, the failure classification information including the failure due to aged deterioration and the failure due to human error is referred to by the failure classification information adding unit. Failure classification information adding step to be added to the failure case,
A data collecting step of collecting data necessary for evaluating the failure of the device or the part satisfying the collecting condition from the information of the device or the part existing in the facility by a data collecting means ;
From among the plurality of analyzing means for calculating and analyzing the failure probability to the failure cases of the device or the component by using the data and the fault classification information necessary for evaluation of the fault, it matches the fault classification information A selecting step of selecting the analyzing means by the selecting means,
By the analyzing means selected by said selecting means, have a, an analysis step of analyzing calculates the failure probability to the failure cases of the device or the component,
The selecting means selects a recognizing means for recognizing the failure classification information added to the failure case and an analyzing means suitable for the failure classification information recognized by the recognizing means, and the selected analysis. The means has a distribution means for allocating the data necessary for evaluation of a failure associated with the failure case and the failure classification information,
The failure occurrence probability calculated and analyzed by the analysis unit is a failure rate calculated based on the operating time of the device or part and the number of failures in this operating time when the failure is a failure due to aging deterioration. If the failure is a failure caused by human error, it is calculated based on the number of operations that may cause the human error and the number of times the human error occurs in any period of the device or part. A failure evaluation method for equipment/parts, which is characterized by a failure probability .

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