JP2020181468A - Failure evaluation device and failure evaluation method for facility equipment and components - Google Patents

Abstract

To appropriately evaluate the maintenance effectiveness of equipment or components in a facility to improve facility reliability and reduce maintenance costs.SOLUTION: A failure evaluation device comprises: collection condition specification means 11 that specifies collection conditions for evaluating equipment or components failure in a facility; failure case extraction means 12 that extracts failure cases for equipment or components that meet the collection conditions from a failure record 1 for the equipment or components; failure classification information addition means 13 that adds to failure cases, with reference to the failure record, failure classification information for classifying failure characteristics including failure causes in failure cases; data collection means 14 that collects data 3 required for failure evaluation of the equipment or components that meet the collection conditions from information 2 of equipment or components existing in the facility; and a plurality of analytical means that calculate and analyze failure occurrence probabilities for failure cases of equipment or components using the data and failure classification information required for failure evaluation.SELECTED DRAWING: Figure 1

Description

An embodiment of the present invention relates to a failure evaluation device for equipment / parts for evaluating a failure of equipment or parts in equipment, and a failure evaluation method for equipment / 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 components such as subsystems, equipment, and equipment must be appropriately maintained. For equipment maintenance, as stipulated by JIS, etc., time-planned maintenance (TBM), in which overhauls and inspections are performed on a regular basis, and parameters related to equipment deterioration and failure are observed, and depending on the condition. There are three types of maintenance methods: condition monitoring maintenance (CBM), which performs overhaul and inspection, and post-maintenance (BDM), which repairs equipment when a failure is found or a function is lost. By appropriately combining these maintenance methods according to the importance and characteristics of the equipment, it is possible to maintain the reliability of the system and suppress repair costs and production loss.

Conventionally, various attempts have been made as the optimum method for determining the maintenance method. For example, in the aviation industry and the military in the United States, failure characteristics (time change curve of failure rate) are obtained from investigations of failures and deterioration of a huge number of mechanical parts, and the above-mentioned which of the above is used according to the failure characteristics. Examination is being made as to whether the maintenance method is appropriate. As a result, TBM induces so-called tampering with most machinery and equipment, leading to an increase in maintenance costs and loss costs, while CBM is optimal maintenance that achieves both reliability assurance and maintenance cost control. It has been clarified that it is a method, and it was introduced in Japan 30 to 40 years ago mainly in the steel industry and the chemical industry.

However, in the current maintenance of nuclear power plants, TBM is carried out as preventive maintenance for most of the equipment, and the equipment is overhauled and inspected at fixed intervals, and most of the overhauls are done in the plant. It is carried out during the regular inspection of. In TBM, the cycle of overhaul and inspection must be set very short with respect to the original equipment life, so there is a problem that maintenance cost increases due to so-called over-maintenance, and overhaul inspection is performed regardless of the deterioration state of the equipment. Therefore, there is a problem that so-called tampering that causes a failure in the disassembly / assembly process is likely to occur in a device that has not deteriorated. In addition, since many operations are concentrated during the regular inspection for several months, the process is complicated and troubles are likely to occur, and the periodic inspection process cannot be shortened, so the plant operation rate is improved. There is also the problem that it is difficult.

CBM is a method of determining the overhaul inspection time by periodically monitoring data indicating the deterioration state of the equipment such as vibration and temperature, and it occurs during the operation of the equipment and the reduction of failures due to the above-mentioned tampering. It is effective in detecting sudden failures at an early stage. There are the following reasons why the effect of CBM is so great.

First, regarding the failure characteristics of machinery and equipment, the initial failure rate is high, and then the stable period (accidental failure period) is entered, and this stable period is very long (there are very few failures due to wear deterioration, and human error. This is because there are many failures due to). Secondly, the failure characteristics of mechanical equipment and parts differ greatly in the time required to enter the wear failure period even for the same model. 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 than TBM can be performed.

On the other hand, if there is a time-dependent degradation in which CBM is not possible, that is, the state cannot be monitored, TBM must be set. Therefore, optimizing the TBM cycle for such equipment is important for ensuring plant reliability and controlling maintenance costs, as is the case with the introduction of CBM. In general, it is ideal to perform maintenance by optimally combining TBM and CBM according to the individual characteristics and importance of plants and equipment. Here, the importance is set by a method of reliability-oriented maintenance (described later) or the like.

In recent years, attempts have been made to optimize maintenance methods including reliability-oriented maintenance (RCM) and condition monitoring maintenance (CBM), which have been proven in other industries such as petrochemicals and nuclear power plants in the United States. In addition, the inspection system at nuclear power plants requires a "maintenance effectiveness evaluation" (JEAG4210) that evaluates and reviews the TBM cycle and method, the applicability of CBM, etc. based on actual data.

This maintenance effectiveness evaluation evaluates whether maintenance that maintains the functions of the plant and equipment is properly performed, and whether there are any deficiencies in the maintenance method and cycle, etc., based on the maintenance record and failure record of the plant and equipment. It is a thing. In this maintenance effectiveness evaluation, it is required to confirm that the maintenance is performed effectively, but if the maintenance results are recognized as good and the cycle of overhaul and inspection has a margin for the deterioration rate of the equipment. It is also possible to extend the cycle when permitted.

Further, it is possible to apply an equipment chart management method for comprehensively determining the equipment condition by combining the condition monitoring data in CBM or TBM of equipment or parts of equipment such as a plant and various inspection data at the time of overhaul. In this equipment chart management method, a huge amount of data is processed to judge whether it is good or bad. Therefore, as a means to support the huge amount of data processing, manpower can be reduced by setting a threshold value for each data and performing primary screening. It is planned. However, since the threshold setting work itself becomes enormous, a threshold setting support method has also been proposed. In addition, a method has been proposed to support the setting of device importance by reliability-oriented maintenance (RCM).

Furthermore, the evaluation of data in the maintenance effectiveness evaluation and the data of the huge amount of equipment installed in the plant are efficiently processed, and based on this processed data, candidate equipment for simplifying maintenance is efficiently extracted. At the same time, equipment that is suspected of having an error in maintenance is also extracted, and the equipment maintenance method is optimized by performing an evaluation that combines detailed data analysis using graphs and deterioration characteristics of the equipment. A method to support the effectiveness evaluation of the equipment maintenance method has also been proposed.

On the other hand, attempts have been made to reduce the failure rate by setting the optimum maintenance cycle of the device by evaluating the frequency of failures that occur in the device. In the effectiveness evaluation of the above-mentioned equipment maintenance method, the quality of the maintenance status is judged by using the maintenance record data of the device, but if the failure rate is used, it is statistically based on the operation record of the same model of equipment. From this point of view, it is possible to judge the quality of the maintenance status of the entire plant or across multiple devices. This is because, for example, for equipment that is operated and maintained under certain conditions, the conditions can be improved so as to reduce the failure rate by comparing the conditions with the failure rate.

Here, the failure rate is determined from the general knowledge of reliability engineering by using the mean time between failures (MTBF), failure rate = 1 / MTBF, MTBF = (system operating time) / (failure within the above operating 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 equipment. For example, a technique for calculating this failure rate, predicting the life of equipment and parts, and giving an optimum maintenance cycle is disclosed. 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-A-2009-217718

However, as described above, the occurrence of so-called tampering due to the overhaul conducted by TBM is caused by human error or the like, and is not directly related to the operating time of the system. For this reason, in the evaluation based only on the failure rate based on the mean time between failures (MTBF), failures due to human error and failures due to time-dependent deterioration of equipment are treated in the same line, and causes and countermeasures for failures are planned. May cause a discrepancy. Therefore, the evaluation based only on the failure rate does not lead to the improvement of maintenance, and the evaluation that truly reduces the number of failures of the system cannot be performed.

In addition, in order to reduce failures due to time-prone deterioration (for example, failures that have a clear relationship between operating time and failure occurrence, such as the progress of corrosion that occurs in a pump that handles corrosive fluid), operating time It is sufficient to set the maintenance cycle based on the failure rate, but it is necessary to remove the causative event for failures that do not have a time tendency (non-time dependent failure), and for that purpose, the causal event and failure are not the above-mentioned failure rate. It is necessary to evaluate the relationship with the outbreak. However, in the failure evaluation using the failure rate based on the operating time of the device and the number of occurrences of the failure as described above, it is possible to properly evaluate the relationship between the failure cause 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-mentioned circumstances, and can appropriately evaluate the maintenance effectiveness of the equipment or parts in the equipment, improve the reliability of the equipment, and reduce the maintenance cost. It is an object of the present invention to provide a failure evaluation device and a failure evaluation method for equipment / parts.

The equipment / equipment failure evaluation device according to the embodiment of the present invention is the collection condition designating means for designating the collection conditions for evaluating the failure of the equipment or parts in the equipment, and the collection based on the failure record of the equipment or parts. The failure case extraction means for extracting a failure case for the device or the component satisfying the conditions and the failure classification information for classifying the characteristics of the failure including the cause of the failure in the failure case are provided with reference to the failure record. A data collecting means for collecting the data necessary for evaluating the failure of the device or the component satisfying the collection condition from the failure classification information adding means added to the case and the information of the device or the component 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 component, and a plurality of the analysis means, using the data necessary for the evaluation of the failure and the failure classification information. It has a selection means for selecting the analysis means suitable for the failure classification information, and the analysis means selected by the selection means causes the failure with respect to the failure case of the device or the component. It is characterized in that it is configured to calculate and analyze the probability of occurrence.

The failure evaluation method for equipment / parts according to the embodiment of the present invention is described from the collection condition designation step for designating the collection conditions for evaluating the failure of the equipment or parts in the equipment and the failure record of the equipment or parts. The failure case extraction step for extracting a failure case for the device or the component satisfying the collection condition and the failure classification information for classifying the failure characteristics including the failure cause in the failure case are described with reference to the failure record. Data collection that collects data necessary for evaluating the failure of the device or component that satisfies the collection condition from the failure classification information addition step to be added to the failure case and the information of the device or the component existing in the facility. It is characterized by having a step and an analysis step of calculating and analyzing a failure occurrence probability for the failure case of the device or the component by using the data necessary for the evaluation of the failure and the failure classification information. It is something to do.

According to the embodiment of the present invention, it is possible to appropriately evaluate the maintenance effectiveness of the equipment or parts in the equipment, improve the reliability of the equipment, and reduce the maintenance cost.

The block diagram which shows the structure in the failure evaluation apparatus of the equipment | part which concerns on 1st Embodiment. The explanatory view which mainly shows the data necessary for the evaluation of the failure collected by the data collecting means of FIG. The block diagram which shows the structure of the analysis means of FIG. 1 and the selection means of analysis means. The figure which shows the specific example of the data necessary for the evaluation of the failure of FIG. Explanatory drawing which mainly shows the data necessary for the evaluation of the failure collected by the data collecting means in the failure evaluation apparatus of the equipment / part which concerns on 2nd Embodiment. FIG. 5 is a block diagram showing a configuration of an analysis means and a selection means of the analysis means in the failure evaluation device for equipment / parts shown in FIG.

Hereinafter, embodiments 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 a configuration in a failure evaluation device for equipment / parts according to the first embodiment. The failure evaluation device 10 for equipment / parts shown in FIG. 1 has a failure record 1 and the equipment or parts existing in the above equipment in order to appropriately evaluate the maintenance effectiveness of the equipment or parts in the equipment such as a power plant. The failure occurrence probability is calculated from the information 2 (maintenance record, operation time, etc.) according to the characteristics of the failure including the cause of the failure, analyzed, and evaluated. Then, the failure evaluation device 10 of the equipment / component 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 analysis means 15, an analysis means selection means 16, and an analysis. It is configured to include a result storage means 17 and an output means 18.

Here, the maintenance effectiveness evaluation is carried out appropriately from the maintenance record and failure record 1 of the equipment such as the plant, or the equipment and parts constituting this equipment, to maintain the function of the equipment, equipment or parts. It evaluates whether it is damaged, whether there are any defects in the maintenance method or cycle, and so on.

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

Information 2 of equipment or parts existing in equipment (for example, a plant or the like) is maintenance record, operation time, design information, usage conditions, equipment information, and the like. The maintenance record is data showing the contents and results of maintenance, the contractor, etc., such as when and how many times the maintenance of the equipment or parts related to the failure was performed. Specifically, the maintenance results are stored in a report of overhaul of equipment or parts carried out in periodic inspections, a condition monitoring report which is the result of monitoring the operating condition of the equipment, and the like. For example, as shown in FIG. 4, the maintenance results of the pump are vibration measurement of each part and analysis of lubricating oil as condition monitoring during normal operation, replacement of consumable parts as overhaul, non-destructive inspection of impeller, and pressure resistant part. Non-destructive inspection etc.

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

The usage conditions are conditions such as the usage environment and load of the equipment or parts related to the failure. For example, the operating conditions of the pump are the internal fluid of the pump and the operating load (constant operating load, immediate standby load in case of trouble, etc.), which are generally recorded in the equipment ledger or the equipment management system. In addition, the equipment information includes the owner (department in charge) of the equipment or parts related to the failure, the equipment number, the part number, the plant information, and the like.

The collection condition designating means 11 implements a collection condition designating step of designating a collection condition for evaluating a failure of equipment or parts in equipment such as a plant through an engineer or the like. This collection condition is an arbitrary one device or one part, a plurality of devices or a plurality of parts having a common attribute, a facility of the entire plant, and the like, and further, a predetermined set arbitrarily set. Includes collection time. Specifically, this collection condition is one of the attributes of the device (for example, a pump) (for example, a centrifugal pump) and a certain collection period.

As shown in FIGS. 1 and 2, the failure case extraction means 12 fails in a device or part that satisfies the collection conditions (for example, a centrifugal pump, a certain collection period) from the failure record 1 of the device or part in the equipment such as a plant. The failure case extraction step for extracting the cases 1 to m is carried out. In the failure case extraction step carried out by the failure case extraction means 12, for example, the collection condition is set to a centrifugal pump and a fixed collection period, and "vibration increase" as one failure case and "flow rate decrease" as another failure case. Extract the corresponding equipment or parts from the failure record 1. Further, in this failure case extraction step, the same failure may occur under the same collection conditions. Therefore, the failure cases 1 to m are not limited to the cases where they are different, and there are a plurality of the same failure cases. Including cases.

The failure classification information adding means 13 adds failure classification information a1 to am for classifying failure characteristics (including the cause of failure) in a failure case to each of the failure cases 1 to m with reference to the failure record 1. The failure classification information addition step is carried out. Failure classification information includes, for example, failures caused by aging deterioration of equipment and parts, failures caused by human error (for example, worker mistakes in maintenance work, design mistakes and manufacturing mistakes in manufacturing machines or parts, and operation operations. (Failure to operate the device, etc.). In addition, those that have deteriorated for a certain period of time starting from human error and have become apparent as failures are classified as human error rather than aged deterioration, or are different from aged deterioration or human error. It is classified.

If the collection condition is a centrifugal pump and the failure case is "increased vibration", for example, a failure with increased vibration due to the life of parts such as bearings is classified as a failure due to aged deterioration, and the cause is an assembly adjustment error in overhaul. Failures with increased vibration are classified as failures caused by human error.

The failure record 1 usually contains information on the cause of the failure or a clue to the failure. Therefore, the failure classification information adding means 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 failure classification information a1 to am is added by an appropriate algorithm, AI (artificial intelligence) method, or a human system.

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

The data collecting means 14 collects information 2 (that is, maintenance record, operation time, design information, usage conditions, equipment information, etc.) of equipment or parts existing in equipment such as a plant, and collects conditions (for example, a centrifugal pump and a certain collection period). ) Is collected for each of the devices or parts satisfying the above conditions, and a data collection step is performed in which the data 3 required for the evaluation of the failure is associated with each of the failure cases 1 to m. The information 3 necessary for the evaluation of the above-mentioned failure is the data necessary for the calculation and analysis of the failure occurrence probability described later, and is the maintenance record b1 to bm, the operation time c1 to cm, the design information d1 to dm, and the usage conditions e1 to em. , Equipment information f1 to fm, etc., and specific examples thereof are shown in FIG.

For example, when the collection condition includes a centrifugal pump and the failure case is "increased vibration", the data 3 required for failure evaluation is due to the aged deterioration in which the failure classification increases the vibration due to the life of the equipment or parts. In the event of a 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 a human error in which vibration increased due to an assembly adjustment error during overhaul. In this case, at least the number of maintenances (the number of overhauls in FIG. 4) for calculating the failure occurrence probability described later is required.

Further, when the data collecting means 14 calculates the failure occurrence probability for the attributes other than the attributes (for example, the centrifugal pump) which are the collecting conditions in the device or the component by the analysis means 15 as described later, the data collecting means 14 is used. Information on the attributes of is also collected from information 2 of the equipment or parts existing in the equipment. For example, when the analysis means 15 calculates and analyzes the failure occurrence probability for each contractor, the data collection means 14 is a contractor (ordering contractor in FIG. 4) from the information 2 of the equipment or parts existing in the equipment. Collect data.

The analysis means 16 selects the analysis means 15 that matches the failure classification information a1 to am from among a plurality of (for example, n) analysis means 15, and as shown in FIG. 3, the recognition means 16A And has a sorting means 16B. The recognition means 16A recognizes the failure classification information a1 to am added to the failure cases 1 to m, and is composed of software means or a human system.

The sorting means 16B selects the analysis means 15 that matches the failure classification information a1 to am recognized by the recognition means 16A, and the selected analysis means 15 is used to evaluate the failure associated with the failure cases 1 to m. Necessary data 3 and failure classification information a1 to am are distributed. Here, there are a plurality of analysis means 15, and as will be described later, each analysis means 15 is a failure occurrence probability calculation method corresponding to a failure classification (for example, a failure due to aged deterioration, a failure due to human error, etc.). Is different. Therefore, the sorting means 16B selects the analysis means 15 provided with the failure occurrence probability calculation method that matches the failure classification information a1 to am.

The analysis means 15 analyzes by calculating and analyzing the failure occurrence probability for the failure cases 1 to m of the equipment or parts by a statistical method using the data 3 necessary for the failure evaluation and the failure classification information a1 to am. The steps are carried out, and there are a plurality of steps according to the failure classification information. Each of the analysis means 15 has a different calculation method of the failure occurrence probability, and the analysis means 15 selected by the analysis means selection means 16 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 caused by aged deterioration of a device or a part, for example, a failure caused by aged deterioration in which vibration increases due to the life of the device or a part, one analysis means 15 determines the failure rate as a failure occurrence probability of the device or the part. Calculate and analyze based on the operating time of parts and the number of failures during this operating time.
Failure rate = (number of failures during operating time of equipment or parts) / (above operating time of equipment or parts)

Further, for 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 of overhaul, the other analytical means 15 has a failure occurrence probability as a failure occurrence probability. Is calculated and analyzed based on the number of operations that may cause human error and the number of human error occurrence in an arbitrary period of the device or part.
Failure probability = (number of human error occurrences) / (number of operations that may cause human error)

Further, the calculation and analysis of the failure occurrence probability (failure rate, failure occurrence probability) by the analysis means 15 have common attributes such as one specific device or one component as a collection condition, or, for example, a centrifugal pump. It is carried out for a plurality of equipped devices and a plurality of parts. Further, the analysis means 15 describes the attributes other than the attributes (for example, a model such as a centrifugal pump) that are the collection conditions in the equipment or parts, for example, the contractor who performed the maintenance, the type of the internal fluid of the pump, and the equipment or parts. The failure occurrence probability may be calculated and analyzed for failure cases 1 to m (vibration increase, flow rate decrease, etc.). Data related to attributes other than the above-mentioned collection conditions are collected from the information 2 of the equipment or parts existing in the equipment by the data collecting means 14, 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 means 15 based on the failure classification information a1 to am as described above is stored in the analysis result storage means 17 as the analysis result. Further, the output means 18 outputs and displays the analysis result (fault occurrence probability) stored in the analysis result storage means 17.

Since it is configured as described above, according to the first embodiment, the following effect (1) is obtained.
(1) As shown in FIGS. 1 and 2, the equipment / component failure evaluation device 10 fails according to the failure characteristics (fault classification) including the cause of the failure of the equipment or parts in the equipment such as a plant. The probability of occurrence is calculated and analyzed. That is, the analysis means 15 in the failure evaluation device 10 for equipment / parts obtains the failure rate as the failure occurrence probability when the failure is classified as a failure due to aged deterioration of the device or part, and the failure is a human error. When it is classified as a failure caused by, the failure occurrence probability is obtained as the failure occurrence probability, and each is analyzed and evaluated.

As a result, maintenance effectiveness evaluation of equipment such as a plant can be appropriately performed, a maintenance cycle including replacement of equipment or parts can be optimized, and so-called over-maintenance can be prevented, so that maintenance cost can be reduced. In addition, the characteristics of the device including the cause of the failure can be clarified to improve the failure, and by optimizing the maintenance cycle, so-called tampering can be suppressed, 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 data necessary for evaluation of a failure collected by a data collecting means in a failure evaluation device for equipment / parts according to a second embodiment. In this 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 difference between the failure evaluation device 20 for equipment / parts of the second embodiment from the first embodiment is that the data 5 required for failure evaluation collected in association with the failure cases 1 to m by the data collecting means 21. In addition to the data related to the failed device or component (that is, the data required for the failure evaluation of the first embodiment; the “data related to the failed device or component” in the second embodiment is represented by reference numeral 3). The point is that data 4 relating to a device or part of the same type that has not failed and has the same type or usage conditions as the device or part that has failed is included. Here, the same type or usage condition means a case where 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 collecting means 21 describes the above from the information 2 of the equipment or part existing in the equipment even when the failure case is not extracted from the failure record 1 by the failure case extracting means 12. For devices or parts that meet the collection conditions, collect data 4 related to devices or parts of the same type that have not failed.

As described above, in addition to the data 3 related to the failed device or part, the data 5 required for the failure evaluation includes the same type or non-failed device or part having the same type or usage conditions as the failed device or part. When the data 4 related to is included, as shown in FIG. 6, the analysis means 22 is necessary for the evaluation of the failure including the data 3 related to these failed devices or parts and the data 4 related to the same type of devices or parts that have not failed. The failure occurrence probability is calculated and analyzed by using the data 5 and the failure classification information a1 to am.

That is, when the failure is a failure caused by aged deterioration of the device or component, the analysis means 22 calculates and analyzes the failure rate based on the operating time of the device or component and the number of failures during this operating time. As the 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, the analysis means 22 indicates the number of operations (for example, overhaul) and man-made work (for example, overhaul) that may cause a human error in an arbitrary period of the device or part when the failure is a failure of the device or part caused by the human error. The failure occurrence probability is calculated and analyzed based on the number of times of error occurrence, but the number of operations that may cause the above-mentioned human error includes the above-mentioned number of operations in the data 3 regarding the failed device or part and the failure. The sum of the number of operations described above in the data 4 regarding the same type of equipment or parts is used.

Further, even when the analysis means 22 analyzes the failure occurrence probability for attributes other than the attributes that are the collection conditions in the device or component, the data 3 regarding the failed device or component and the same type of device or device that has not failed or The failure occurrence probability is calculated and analyzed using the data 5 required for failure evaluation including the data 4 related to the parts and the failure classification information a1 to am.

Since it is configured as described above, 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 means 22 includes data 3 relating to the failed device or part, data 4 relating to the same type or component that does not fail and has the same type or usage conditions as the failed device or part, and failure classification information a1. The failure occurrence probability is calculated and analyzed using ~ am. In this way, by analyzing the failure occurrence probability of the same type of device or component including the failed device or component, it is possible to evaluate the failure for each of the same type of device or component.

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 gist of the invention, and their replacements and changes can be made. Is included in the scope and gist of the invention, and is also included in the invention described in the claims and the equivalent scope thereof.

1 ... Failure record, 2 ... Information on equipment or parts existing in the equipment, 3 ... Data required for failure evaluation, 4 ... Data on the same type of equipment or parts that have not failed, 5 ... Data required for failure evaluation 10, 10 ... Failure evaluation device for equipment / parts, 11 ... Collection condition designation means, 12 ... Failure case extraction means, 13 ... Failure classification information addition means, 14 ... Data collection means, 15 ... Analysis means, 16 ... Analysis means Selection means, 16A ... Recognition means, 16B ... Sorting means, 20 ... Equipment / parts failure evaluation device, 21 ... Data collection means, 22 ... Analysis means, 1 to m ... Failure cases, a1 to am ... Failure classification information

The equipment / equipment failure evaluation device according to the embodiment of the present invention is the collection condition designating means for designating the collection conditions for evaluating the failure of the equipment or parts in the equipment, and the collection based on the failure record of the equipment or parts. A failure case extraction means for extracting failure cases for the device or the component satisfying the conditions, and a failure due to aged deterioration and a failure due to human error for classifying the characteristics of the failure including the cause of the failure in the failure case. The device or the device that satisfies the collection condition from the failure classification information adding means for adding the failure classification information including the above to the failure case with reference to the failure record and the information of the device or the component existing in the facility. Failure occurrence probability for the failure case of the device or the component using the data collection means for collecting the data necessary for the failure evaluation of the component, the data necessary for the failure evaluation, and the failure classification information. It has a plurality of analysis means for calculating and analyzing, and a selection means for selecting the analysis means suitable for the failure classification information from the plurality of the analysis means, and the selection means is added to the failure case. A recognition means for recognizing the fault classification information and the analysis means suitable for the fault classification information recognized by the recognition means are selected, and the selected analysis means is associated with the failure case. The failure occurrence probability with respect to the failure case of the device or the component by the analysis means selected by the selection means , which has a distribution means for distributing data necessary for failure evaluation and the failure classification information. The failure occurrence probability calculated and analyzed by the analysis means is the operating time of the device or component and the failure in this operating time when the failure is caused by aged deterioration. It is a failure rate calculated based on the number of times, and when the failure is a failure caused by a human error, the number of operations and the artificial error that may cause the human error in an arbitrary period of the device or part. It is characterized in that it is a failure occurrence probability calculated based on the number of occurrences of mistakes .

The failure evaluation method for equipment / parts according to the embodiment of the present invention includes a collection condition designation step for designating a collection condition for evaluating a failure of equipment or parts in equipment by a collection condition designation means, and the device or the part. Aged deterioration for classifying the failure case extraction step for extracting failure cases from the failure record for the device or the component satisfying the collection condition by the failure case extraction means and the failure characteristics including the failure cause in the failure case. A failure classification information addition step that adds failure classification information including a failure caused by a failure and a failure caused by a human error to the failure case by referring to the failure record by the failure classification information adding means, and the above-mentioned equipment existing in the facility. A data collection step of collecting data necessary for evaluating the failure of the device or the component satisfying the collection condition from the information of the device or the component by a data collecting means , data necessary for evaluating the failure, and the failure. Selection by the selection means to select the analysis means suitable for the failure classification information from a plurality of analysis means for calculating and analyzing the failure occurrence probability for the failure case of the device or the component 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 means for recognizing the failure classification information added to the failure case and the analysis means matching the failure classification information recognized by the recognition means are selected, and the selected analysis means is used with the failure case. The failure occurrence probability calculated and analyzed by the analysis means is a failure caused by aged deterioration, which has data necessary for evaluation of the failure associated with the above and a distribution means for distributing the failure classification information. In this case, it is a failure rate calculated based on the operating time of the device or component and the number of failures in this operating time. If the failure is a failure caused by a human error, any of the devices or parts It is characterized in that it is a failure occurrence probability calculated based on the number of operations that may cause the human error and the number of occurrences of the human error in the period .

Claims (7)

Collection condition specification means for specifying collection conditions for evaluating the failure of equipment or parts in equipment, and
A failure case extraction means for extracting a failure case for the device or the component satisfying the collection condition from the failure record of the device or the component.
Failure classification information adding means for adding failure classification information for classifying failure characteristics including the cause of failure in the failure case to the failure case with reference to the failure record.
A data collecting means for collecting data necessary for evaluating the failure of the device or the component satisfying the collection condition from the information of the device or the component 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 component by using the data necessary for the evaluation of the failure and the failure classification information.
It has a selection means for selecting the analysis means suitable for the failure classification information from the plurality of analysis means.
A failure evaluation device for equipment / parts, which is configured to calculate and analyze the failure occurrence probability for the failure case of the device or the component by the analysis means selected by the selection means. .. The selection means selects a recognition means for recognizing the failure classification information added to the failure case and an analysis means suitable for the failure classification information recognized by the recognition means, and the selected analysis means is used. The failure evaluation device for equipment / parts according to claim 1, further comprising data necessary for evaluating a failure associated with the failure case and a sorting means for sorting the failure classification information. The failure occurrence probability calculated and analyzed by the analysis means is a failure rate calculated based on the operating time of the device or component and the number of failures in this operating time when the failure is a failure caused by aged deterioration. If the failure is caused by a human error, the failure is calculated based on the number of operations that may cause the human error and the number of occurrences of the human error in an arbitrary period of the device or part. The failure evaluation device for equipment / parts according to claim 1 or 2, which is characterized by an occurrence probability. The equipment / component according to any one of claims 1 to 3, wherein the data collecting means is configured to associate the data necessary for the evaluation of the failure collected based on the collection conditions with the failure case. Failure evaluation device. The analysis means is characterized in that it is possible to calculate and analyze a failure occurrence probability for a failure case of the device or the component for attributes other than the attribute that is a collection condition in the device or the component. The failure evaluation device for equipment / parts according to any one of claims 1 to 4. In addition to the data related to the failed device or part, the data required for the failure evaluation associated with the failure case by the data collecting means includes the same type or usage condition as the failed device or part, and the failure. The failure evaluation device for equipment / parts according to any one of claims 1 to 5, wherein data relating to the same type of equipment or parts is included. A collection condition specification step that specifies collection conditions for assessing equipment or component failures in equipment, and
A failure case extraction step for extracting a failure case for the device or the component satisfying the collection condition from the failure record of the device or the component, and a failure case extraction step.
The failure classification information addition step for adding the failure classification information for classifying the characteristics of the failure including the cause of the failure in the failure case to the failure case with reference to the failure record,
A data collection step of collecting data necessary for evaluating the failure of the device or the component satisfying the collection condition from the information of the device or the component existing in the facility.
Equipment and equipment characterized by having an analysis step of calculating and analyzing a failure occurrence probability for the failure case of the device or the component by using the data necessary for the evaluation of the failure and the failure classification information. -Part failure evaluation method.

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