JP7664870B2 - Equipment reliability and maintenance cost prediction device and equipment reliability and maintenance cost prediction method - Google Patents

Description

Embodiments of the present invention relate to an equipment reliability and maintenance cost prediction device that predicts the reliability and maintenance cost of equipment, and an equipment reliability and maintenance cost prediction method.

In order to maintain the reliability of large-scale systems such as power plants and transportation machinery, the subsystems, facilities, and equipment (collectively referred to as "equipment") that are the components of the system must be properly maintained. As specified in JIS and other standards, there are three types of maintenance methods for equipment maintenance: time-planned maintenance (TBM), which involves periodic disassembly and inspection; condition-based maintenance (CBM), which involves observing parameters related to the deterioration and failure of the equipment and disassembly and inspection according to the condition; and corrective maintenance (BDM), which involves repairs when a failure is discovered or a loss of function is detected in the equipment. 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 reduce repair costs and production losses.

Traditionally, various attempts have been made to determine the optimal method of maintenance. For example, in the US aviation industry and military, a huge number of machine parts have been surveyed for failures and deterioration to determine the time-varying failure rate curve, and based on this, consideration has been given to which of the above-mentioned maintenance methods are most appropriate. As a result, it has been revealed that TBM induces so-called tinkering with most machinery and equipment, resulting in increased maintenance costs and loss costs, whereas CBM is the optimal maintenance method that ensures reliability while reducing maintenance costs. In Japan, it has been introduced 30 to 40 years ago, mainly in the steel and chemical industries.

However, in the current maintenance of domestic nuclear power plants, TBM is carried out as preventive maintenance for most equipment, in which the equipment is disassembled and inspected at set intervals, and most of this disassembly is carried out during regular plant inspections. With TBM, the intervals for disassembly and inspection must be set very short compared to the original lifespan of the equipment, which results in so-called over-maintenance and high maintenance costs. In addition, because disassembly and inspection is carried out regardless of the deterioration state of the equipment, there is a tendency for so-called tampering to occur, whereby breakdowns occur during the disassembly and assembly process of equipment that is not degraded. In addition, because much of the work is carried out in a concentrated manner over the course of several months during regular inspections, the process becomes complicated and troubles are likely to occur, and because the regular inspection process cannot be shortened, there are also problems with it being difficult to improve the plant's operating rate.

In recognition of these problems, efforts are being made to optimize maintenance methods, including reliability-based maintenance (RCM), which has been proven in other industries such as petrochemicals and in nuclear power plants in the United States, condition-based maintenance (CBM), and TBM cycle extensions that do not result in over-maintenance. In addition, the inspection system for nuclear power plants requires a "maintenance effectiveness assessment" (JEAC 4209, JEAG 4210) in which the TBM cycle and methods, the applicability of CBM, etc. are evaluated and revised based on actual data.

This maintenance effectiveness evaluation evaluates whether the maintenance that maintains the functionality of a plant or equipment is being performed appropriately and whether there are any defects in the maintenance method or cycle based on the maintenance record and failure record of the plant or equipment. This maintenance effectiveness evaluation requires confirmation that maintenance is being performed effectively, but if the maintenance record is deemed good and the TBM cycle, such as overhaul and inspection, is deemed to have sufficient margin for the rate of deterioration of the equipment, it is possible to extend the cycle. For example, the time trend of changes in the amount of wear of parts obtained from each overhaul of a certain piece of equipment is evaluated, and it is determined that the current overhaul and inspection cycle is short enough for the amount of wear to reach the failure criterion, and that no various failures have occurred for a long period of time, and the overhaul and inspection cycle is then extended.

Patent No. 6733004 International Publication No. WO 2008/155982

On the other hand, there are also attempts to reduce the failure rate by setting an optimal maintenance cycle for the equipment by evaluating the frequency of failures that occur in the equipment. In the above-mentioned maintenance effectiveness evaluation of facility equipment, the maintenance status of the equipment is judged to be good or bad using the maintenance record data of the equipment. However, if the failure rate is used in the maintenance effectiveness evaluation, it is possible to judge the quality of the maintenance status of the entire plant or multiple equipment from a statistical perspective based on the operating record of equipment of the same model. This is because, for example, for equipment operated and maintained under certain conditions, by comparing the conditions with the failure rate, it is possible to improve the conditions to reduce the failure rate. As a method for carrying out this evaluation with high accuracy, Patent Document 1 proposes a method of analyzing the causes of failure by dividing them into aging deterioration (wear-out failures) and human error, etc.

Patent Document 2 also proposes a method for considering optimal maintenance management by simulating predictions of reliability and costs based on the estimated performance and degradation state from the results of signal monitoring for each piece of equipment, and the recovery of performance and degradation state through subsequent maintenance. With this method, it becomes possible to predict the optimal maintenance method by searching for the optimal point between the increase in costs and the increase in reliability that comes from increasing the frequency of maintenance.

In the aforementioned maintenance effectiveness evaluation, data trends are generally evaluated based on multiple overhauls and inspections over a period ranging from several years to several decades, and a decision is made to extend the cycle or transition to CBM if the current TBM cycle is deemed to have sufficient margin for the rate of deterioration. However, there are no quantitative evaluation criteria, such as an evaluation of the reliability of the equipment after the change, expected maintenance costs, or expected failure recovery costs, to clarify this judgment, and as a result, the cycle has not been extended or a transition to CBM has not been made. In particular, it is difficult to determine what the cycle should be after the change.

Furthermore, accurately evaluating failure rates can contribute to decisions to reduce the frequency of human error. However, unless the failure rate is evaluated as a function of time, there are no quantitative evaluation criteria for evaluating the reliability of the equipment after the change, the expected maintenance costs, the expected costs of repairing the equipment from failure, etc., and as a result, the cycle has not been extended or a transition to CBM has not been made. In particular, it is difficult to deal with the risk of failure due to human error and to determine how long the maintenance cycle should be after the change. Furthermore, unless the evaluation also includes the increased risk of human error in maintenance and the risk of increased costs of repairing the equipment from failure rates predicted overall, it will not serve as a guide for selecting the optimal maintenance method and frequency.

The embodiment of the present invention has been made in consideration of the above circumstances, and aims to provide an equipment reliability and maintenance cost prediction device and equipment reliability and maintenance cost prediction method that can select a maintenance method that can improve equipment reliability and reduce maintenance costs.

The reliability and maintenance cost prediction device for equipment in an embodiment of the present invention includes an evaluation target setting means for specifying and setting equipment to be evaluated for reliability, maintenance cost, and failure recovery cost in a facility, a failure rate input means for inputting a reference value for the probability of failure and failure rate for each failure type of the equipment, a maintenance characteristic input means for inputting the relationship between the maintenance method, maintenance method, and operation of the equipment and the failure rate, a cost input means for inputting the standard maintenance cost for preventive maintenance of the equipment and the standard failure recovery cost required for recovery when a failure occurs in the equipment, a basic condition creation unit for creating basic conditions for the evaluation of the equipment by combining each input value input from each input means, an operation and maintenance performance input means for inputting the operation and maintenance performance of the equipment, an operation and maintenance schedule input means for inputting the operation and maintenance schedule of the equipment, a plotting means for arranging the operation and maintenance performance and the schedule of the equipment in time, and each value in the basic condition and the values input by the operation and maintenance performance input means and the operation and maintenance schedule input means. The simulation means inputs the results and schedule of the operation and maintenance of the equipment, calculates a time function of the equipment failure rate and a time function of the maintenance cost based on the results and schedule of the operation and maintenance of the equipment, and calculates the expected value of the failure restoration cost as a time function and arranges it in time; an evaluation condition input means specifies a period for evaluating the reliability, maintenance cost, and failure restoration cost of the equipment, changes the maintenance or operation schedule arranged in time by the plotting means, and further changes the basic conditions when the simulation means calculates the time function of the failure rate, the time function of the maintenance cost, and the time function of the expected value of the failure restoration cost; and a display unit that displays in time at least one of the results and schedule of the maintenance and operation arranged in time by the plotting means, the time function of the failure rate, the time function of the maintenance cost, and the time function of the expected value of the failure restoration cost calculated and arranged by the simulation means.

The method for predicting reliability and maintenance costs of equipment in an embodiment of the present invention includes an evaluation target setting step in which an evaluation target setting means specifies and sets equipment to be evaluated for reliability, maintenance costs, and failure recovery costs in a facility; a failure rate input step in which a failure rate input means inputs a reference value of a failure occurrence probability and a failure rate for each failure mode of the equipment; a maintenance characteristic input step in which a maintenance characteristic input means inputs a relationship between each of the maintenance method, maintenance method, and operation of the equipment and the failure rate; and a maintenance characteristic input step in which a maintenance characteristic input means inputs a standard maintenance cost related to preventive maintenance of the equipment and a failure recovery cost required for recovery when a failure occurs in the equipment. a cost input step in which a cost input means inputs a standard cost; a basic condition creation step in which a basic condition creation unit creates basic conditions for evaluating the equipment by combining each input value input from each of the input steps; an operation and maintenance result input step in which an operation and maintenance result input means inputs the operation and maintenance result of the equipment; an operation and maintenance schedule input step in which an operation and maintenance schedule input means inputs the operation and maintenance schedule of the equipment; a plotting step in which a plotting means arranges the operation and maintenance results and the schedule in time; a simulation step of inputting a reliability evaluation value, the maintenance cost, and the operation and maintenance results and the plan input in the operation and maintenance plan input step, calculating a time function of the failure rate of the equipment and a time function of the maintenance cost based on the operation and maintenance results and the plan, and calculating an expected value of the failure restoration cost as a time function and arranging them in time; an evaluation condition input step in which an evaluation condition input means specifies a period for evaluating the reliability, maintenance cost, and failure restoration cost of the equipment, changes the maintenance or operation plan arranged in time in the plot step, and further changes the basic conditions when the time function of the failure rate, the time function of the maintenance cost, and the time function of the expected value of the failure restoration cost are calculated in the simulation step; and a display step in which a display unit displays in time at least one of the maintenance and operation results and the plan arranged in time in the plot step, the time function of the failure rate, the time function of the maintenance cost, and the time function of the expected value of the failure restoration cost calculated and arranged in the simulation step.

According to an embodiment of the present invention, it is possible to select a maintenance method that can improve equipment reliability and reduce maintenance costs.

1 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a first embodiment; 4 is a table showing an example of an evaluation target device set as an evaluation target by the evaluation target setting means of FIG. 1 . 2 is a table showing an example of the failure rates of initial failures, random failures, and wear-out failures of the evaluation target device inputted by the failure rate input means of FIG. 1 . 2 is a table showing an example of a failure rate for each failure mode (failure form) of an evaluation target device inputted by the failure rate input means of FIG. 1 . 2 is a table showing an example of a case where the failure rate of the evaluation target device inputted by the failure rate input means of FIG. 1 is set for each component part. FIG. 2 is an explanatory diagram showing an example of the relationship between the failure rate for each failure mode of the device to be evaluated inputted by the failure rate input means in FIG. 1 and each failure rate of initial failures, random failures, and wear-out failures. 2 is a table showing an example of the relationship between the maintenance method, maintenance method, and operation of the evaluation target device inputted by the maintenance characteristic input means of FIG. 1 and the failure rate. 2 is a graph showing an example of a reference value of a failure rate inputted by a failure rate input unit of FIG. 1 . 9 is a graph showing the relationship between the early failure rate and the maintenance method shown in FIG. 8 . 9 is a graph showing the relationship between the wear-out failure rate and the maintenance method in FIG. 8 . 9 is a graph showing that the early failure rate of FIG. 8 is reduced by the maintenance method; 2 is a table showing an example of an evaluation target device, its failure rate reference value (reference failure rate), maintenance method, the effect of the maintenance method on the failure rate, standard maintenance cost, etc., created by the basic condition creation unit of FIG. 1 . 2 is an explanatory diagram showing an example in which the results and plans of operation and maintenance (contents, dates) generated by the plotting means in FIG. 1 are plotted based on a time axis; FIG. 2 is an explanatory diagram showing an example of a time function of a failure rate calculated by the simulation means of FIG. 1 in accordance with the results and schedule of maintenance and operation plotted on a time axis. FIG. 2 is an explanatory diagram showing an example of a time function of maintenance costs calculated by the simulation means of FIG. 1 in accordance with the maintenance and operation results and schedules plotted on a time axis. FIG. 2 is an explanatory diagram showing an example of a time function of an expected value of a failure restoration cost calculated by the simulation means of FIG. 1 based on a failure rate according to the maintenance and operation results and schedule plotted on a time axis. FIG. 11 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a second embodiment. FIG. 18 is an explanatory diagram showing an example in which the evaluation condition input means of FIG. 17 changes the scheduled cycle of maintenance (overhaul inspection) and the plot means plots the cycle. FIG. 18 is an explanatory diagram showing an example in which the simulation means of FIG. 17 calculates a time function of a predicted failure rate in response to a change in a scheduled cycle of maintenance (disassembly and inspection). FIG. 18 is an explanatory diagram showing an example in which the simulation means in FIG. 17 calculates a time function of a predicted maintenance cost and a time function of an expected value of a failure restoration cost in response to a change in a scheduled cycle of maintenance (overhaul inspection). 18 is a graph showing an example of a cumulative failure rate value, a cumulative maintenance cost value, and a cumulative expected value of failure restoration cost calculated by the cumulative evaluation means in FIG. 17, with the scheduled cycle of maintenance (disassembly and inspection) plotted on the horizontal axis. FIG. 18 is an explanatory diagram showing an example of a time function of predicted failure rates calculated by the simulation means of FIG. 17 according to maintenance (condition monitoring) methods having different effects. FIG. 18 is an explanatory diagram showing an example of a comparison between a time function of a predicted maintenance cost calculated by the simulation means of FIG. 17 according to a maintenance (condition monitoring) method having different effects and costs and a time function of an expected value of a failure restoration cost. 18 is a graph showing an example of a comparison of a cumulative failure rate, a cumulative maintenance cost, and an expected cumulative failure restoration cost calculated according to the status monitoring period based on the difference in effect and cost between two status monitoring methods by the simulation means of FIG. 17 , with the horizontal axis representing the status monitoring period. FIG. 13 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a third embodiment. FIG. 13 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a fourth embodiment. FIG. 27 is a block diagram showing a case where a plurality of devices set by the evaluation target setting means of FIG. 26 are connected in series. FIG. 27 is a block diagram showing a case where a plurality of devices set by the evaluation target setting means of FIG. 26 are connected in parallel. FIG. 27 is an explanatory diagram for explaining improvement in maintenance by the cumulative evaluation means in FIG. 26 calculating and predicting a time function of the availability rate, which is an index of system reliability, from the failure rates of a plurality of devices.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
[A] First embodiment (FIGS. 1 to 16)
Fig. 1 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to the first embodiment. The equipment reliability and maintenance cost prediction device 10 shown in Fig. 1 is for appropriately determining a maintenance method and a maintenance system for equipment in facilities such as a plant or a large-scale transportation system, and is configured with an evaluation target setting means 11, a failure rate input means 12, a maintenance characteristic input means 13, a cost input means 14, a basic condition creation unit 15, an operation and maintenance performance input means 16, an operation and maintenance schedule input means 17, a plotting means 18, an evaluation condition input means 19, a simulation means 20, and a display unit 21.

The evaluation target setting means 11 specifies and sets the evaluation target equipment, which is the equipment that is the subject of the evaluation of the reliability, maintenance costs, and failure recovery costs of the facility (evaluation target setting step). At this time, classification information including the model of the equipment is also input as necessary. In a plant, etc., these pieces of equipment and models are basically information managed in an equipment ledger, equipment management system, etc. An example is shown in Figure 2.

The failure rate input means 12 inputs the probability of failure and the reference value of the failure rate as a function of time according to the failure type (failure mode) of the device to be evaluated (failure rate input step). The reference value of the failure rate input by this failure rate input means 12 is input by an operator using electronic means, or is input from a database that stores the time function of the failure rate for each failure type set in advance for each model.

Here, the failure modes are classified into three categories: initial failure, random failure, and wear-out failure, and the failure rate of each is input. An example of this is shown in FIG. 3. The parameters that define the failure rate as a function of time are, for example, a shape parameter and a scale parameter when the failure rate is given by a Weibull distribution. In addition, instead of using three categories, the failure mode that leads to the loss of function of the evaluation target equipment may be subdivided within a identifiable range and input as shown in FIG. 4. Furthermore, for example, the failure that occurs in the evaluation target equipment may be expanded to the component level and events and input, as shown in FIG. 5. The reference value of the failure rate is calculated, estimated, assumed, etc. by some means other than this embodiment, and is, for example, statistically calculated from the failure, operation, and maintenance records of the same model at a power plant or factory where the evaluation target equipment is located.

The example in Figure 6 is an example of subdividing the failure modes that lead to loss of function of the evaluation target equipment shown in Figure 4 to an identifiable extent. As shown in Figure 6, the defect rate when a certain part is replaced in the evaluation target equipment, or failures caused by human error during the installation work, are initial failures, while failures caused by the influence of other equipment during normal operation of the evaluation target equipment or failures caused by operator error are accidental failures, and deterioration during normal use is a wear-out failure.

The maintenance characteristic input means 13 inputs the relationship between the maintenance method, maintenance method, and operation of the equipment to be evaluated and the failure rate of the failure type (maintenance characteristic input step). The relationship between the maintenance method, maintenance method, and operation of the equipment to be evaluated and the failure rate of the failure type input by this maintenance characteristic input means 13 is input by an operator using electronic means to indicate how the reference value of the failure rate changes depending on the effect that each of the maintenance method, maintenance method, and operation has on the failure rate of the equipment to be evaluated, or is input from a database in which the relationship is preset for each model.

Here, the relationship between the maintenance method, the maintenance method, the operation, and the failure rate of the failure type refers to the effect that various maintenance methods, the maintenance methods, and the operation of the equipment to be evaluated have on the occurrence of failures, that is, the extension or shortening of the lifespan, and the prevention or induction of failures, and is, for example, the following (a) to (f). (a) Restoration by regular and appropriate replacement of deteriorated parts (initialization of the failure rate of wear-out failures), (b) Reduction of the failure rate of accidental failures by status monitoring, (c) Occurrence of initial failures due to assembly errors accompanying the replacement of parts, (d) Occurrence of initial failures due to manufacturing errors in the factory accompanying the replacement of parts, (e) Reduction of the failure rate of accidental failures by daily maintenance such as refueling, (f) Stopping the progress of wear by stopping operation, etc. In this embodiment, the failure rate is expressed by predicting what will happen to the failure rate due to maintenance, preservation, and operation using the reference value of the failure rate input by the failure rate input means 12. This is explained below.

First, the relationship between the maintenance method, maintenance method, and operation and the change in failure rate is created for each model; an example is shown in Figure 7. In this way, a table is created that takes into account the model and the characteristics of the failures that occur in that model, regarding how the failure rates of initial failures, random failures, and wear-out failures (deterioration over time) are affected by each maintenance method, maintenance method, and operation. The meaning of Figure 7 is as follows.

The standard failure rates for initial failures, random failures, and wear-out failures input by the failure rate input means 12 are generally as shown in Figure 8. As shown in Figure 8, the failure rates can be calculated separately for initial failures (initial failure failure rate B), random failures (random failure failure rate C), and wear-out failures (wear-out failure failure rate D) by analyzing the causes, and the sum of these is the equipment failure rate A. It is known that the change in failure rate over time varies greatly for each model.

Here, FIG. 9 is a conceptual explanation of the induction of early failures by maintenance method 1 (disassembly and inspection) illustrated in FIG. 7. As shown in FIG. 9, the implementation of maintenance method 1 returns the failure rate B of early failures to its initial value (the value at t=0, which is the reference value of the failure rate). FIG. 10 is a conceptual explanation of the return of wear-out failures by maintenance method 1 illustrated in FIG. 7, where the implementation of maintenance method 1 returns the failure rate D of wear-out failures to its initial value (the value at t=0, which is the reference value of the failure rate). FIG. 11 is a conceptual explanation of the decrease in the failure rate B of early failures by maintenance method 2 (monitoring the operating state of the equipment) illustrated in FIG. 7, where the failure rate decreases over the entire time t relative to the reference value of the failure rate B of early failures (symbol F in FIG. 11). The same applies to accidental failures and wear-out failures, and the increase in the failure rate naturally follows the opposite change.

The cost input means 14 inputs the standard costs for the maintenance or repair of the equipment to be evaluated (cost input step). For example, the standard failure recovery cost required to restore (repair) the equipment when it breaks down, the standard maintenance cost required for preventive maintenance such as monitoring the equipment and regular disassembly and inspection, and the estimated costs in the event that an equipment failure leads to production disruption in the entire plant or that explanations to government agencies or media coverage are required are also input. These standard costs are input as unit prices, such as one maintenance or monitoring session or annual costs.

The standard maintenance costs for preventive maintenance of the evaluated equipment and the standard failure recovery costs when a failure occurs in the evaluated equipment, which are input by this cost input means 14, are input by an operator for each evaluated equipment by electronic means or input from a database.

As shown in FIG. 12, the basic condition creation unit 15 combines the equipment name, equipment number, and other equipment information that identifies the equipment, information on the model to which the equipment belongs, the failure rate reference value input from the failure rate input means 12, the relationship between the maintenance method, maintenance method, and operation input from the maintenance characteristic input means 13 and the failure rate, and the standard maintenance cost for preventive maintenance input from the cost input means 14, the standard cost for failure recovery when a failure occurs, and the expected cost required for production interruption and explanation to government agencies, etc., and defines the correspondence between them as the basic conditions for the evaluation of the equipment to be evaluated (basic condition creation step). This basic condition defines the basis for the relationship between technical maintenance and failure, and the relationship between maintenance, failure, and cost, and links the maintenance performed on the equipment to be evaluated with its purpose, side effects, and cost.

In this embodiment, the reference failure rate (reference value of failure rate) is calculated for each model using statistical means. The impact on the failure rate of implementing a certain maintenance method is also given as knowledge for each model. Therefore, these (reference failure rate, impact on failure rate) are information related to the model. In contrast, the impact when the evaluated equipment breaks down is determined by the importance of the equipment to the plant, so the amount of damage caused by production interruption, the cost of dealing with government agencies, etc. are specific to the equipment. In addition, the maintenance costs and repair costs of the evaluated equipment are information related to the part unit price and labor hours specific to the equipment (for example, the same model of pump differs between large and small pumps and between manufacturers), so they are information specific to the equipment determined by the identification of the equipment.

Furthermore, the relationship between maintenance or operation, failure rate, and maintenance costs is as follows. For example, while monitoring the operating status of the equipment being evaluated can reduce the failure rate by detecting abnormalities early, monitoring costs are incurred. On the other hand, in an overhaul inspection, the replaced parts are returned to new, and deterioration over time can be restored to the initial value, but initial failures can be induced due to work errors during disassembly and assembly. In addition to the costs of overhaul inspection, overhaul inspection also entails the risk of incurring costs for dealing with initial failures, and furthermore, by stopping the monitoring of the equipment's operating status, which was previously done, early detection of abnormalities is no longer possible, which can lead to an increase in the failure rate.

The operation and maintenance record input means 16 inputs the record of operation and maintenance of the equipment to be evaluated (operation and maintenance record input step). The operation and maintenance record of the equipment to be evaluated input by this operation and maintenance record input means 16 is the content, date and time of implementation, and period, and is input by the operator by electronic means or input from a database. These operation and maintenance records are basically information managed in a maintenance ledger or maintenance management system at the plant, etc.

The operation and maintenance schedule input means 17 inputs the schedule for operation and maintenance of the equipment to be evaluated (operation and maintenance schedule input step). The operation and maintenance schedule for the equipment to be evaluated input by this operation and maintenance schedule input means 17 includes the contents and the planned date and time and period for implementation, and is input by an operator using electronic means or input from a database. These operation and maintenance schedules are basically information managed as plans in a maintenance ledger or maintenance management system in a plant, etc.

The plotting means 18 plots the actual (history) and schedule of the operation and maintenance (contents, dates) of the evaluation target equipment in a process-like manner based on the time axis, based on the operation and maintenance results of the evaluation target equipment input from the operation and maintenance results input means 16, the operation and maintenance schedule of the evaluation target equipment input from the operation and maintenance schedule input means 17, and the conditions (described below) input from the evaluation condition input means 19 (plotting step). An example of this is shown in FIG. 13.

The evaluation condition input means 19 inputs an evaluation period for evaluating the reliability and maintenance costs of the equipment to be evaluated, and further changes the operation and maintenance content and implementation timing schedule input from the operation and maintenance schedule input means 17 (evaluation condition input step). That is, the evaluation condition input means 19 specifies the period for evaluating the reliability, maintenance costs, and failure recovery costs of the equipment to be evaluated, changes the maintenance or operation schedule arranged in time by the plot means 18, and further changes the basic conditions when the time function of the failure rate, the time function of the maintenance costs, and the time function of the expected value of the failure recovery costs are calculated by the simulation means 20.

Furthermore, the evaluation condition input means 19 allows the operator to change at least one of the operation and maintenance schedules of the evaluation target equipment arranged in the plot means 18. The evaluation condition input means 19 also allows the operator to change the reference value of the failure rate of the evaluation target equipment under the basic conditions input to the simulation means 20 from the basic condition creation unit 15, the relationship between the maintenance method, maintenance method, and operation and the failure rate, the standard maintenance cost for preventive maintenance of the evaluation target equipment, and the standard failure recovery cost when a failure occurs in the evaluation target equipment.

The simulation means 20 inputs the values of the basic conditions created by the basic condition creation unit 15 and the operation and maintenance results and plans input from the operation and maintenance results input means 16 and the operation and maintenance plan input means 17, calculates a time function of the failure rate of the evaluation target equipment based on the operation and maintenance results and plans of the evaluation target equipment, and a time function of the maintenance costs, and calculates the expected value of the failure recovery costs as a time function and arranges them in time (simulation step).

In other words, the simulation means 20 first refers to the correspondence between the failure rate and the cost and the maintenance method, maintenance method, and operation created by the basic condition creation unit 15, and calculates and arranges the time function of the failure rate of the evaluation target equipment (including the time function of the predicted failure rate) calculated based on the reference value of the failure rate in accordance with the maintenance and operation results and plans plotted on the time axis by the plotting means 18. An example is shown below.

For example, when an overhaul inspection is performed and major parts are replaced with new ones, as shown in Figures 9 and 10, the failure rate D of wear-out failures returns to the origin at the time of the overhaul inspection, and the risk of initial failures (initial failure rate B) is induced. In addition, by monitoring the condition of the equipment being evaluated while it is in operation, it is possible to reduce the initial failure rate B (symbol F in Figure 11) as shown in Figure 11. The extent of this reduction varies depending on the frequency of monitoring and the effectiveness of fault detection. The range of this increase or decrease can be set by statistical evaluation or the judgment of the engineer. This effect occurs for all initial failures, accidental failures, and wear-out failures.

FIG. 14 shows an example in which the time function of the failure rate is calculated and arranged for the maintenance and operation results and schedules plotted by the plotting means 18. In FIG. 14, the time function of the failure rate for the past results (history) and schedules for operation and maintenance is calculated and arranged with the evaluation implementation time as the boundary. Symbol B is the failure rate of early failure, symbol C is the failure rate of accidental failure, symbol D is the failure rate of wear-out failure, and symbol A is the sum of them (failure rate of the evaluation target device). Naturally, the right side of the evaluation time is the predicted value. The reason why the past failure rate is also calculated as the subject of the evaluation in this embodiment is because the influence of past operation and maintenance remains. For example, on January 10, 2019, when the main body was last replaced, the failure rates B, C, and D returned to their initial values, and the influence remains at the evaluation time. By changing the monitoring frequency of the operating state from once a month to twice a month at this evaluation time, it can be expected that all failure rates will decrease with the evaluation time as the boundary, and the opportunity for early failure B to occur will decrease by reducing the frequency of disassembly and inspection.

Below is an example of how to calculate the relationship between the reference value of the failure rate and operation and maintenance. Let the reference value of the time function of the failure rate be λ(t). In the Weibull distribution described above, the failure rate of initial failures is maximum at λ(0) and decreases monotonically as time t passes, the failure rate of random failures is a constant value regardless of time t, and the failure rate of wear-out failures is minimum at λ(0) and then increases monotonically as time t passes.

For example, monitoring the operating state of the equipment being evaluated increases the likelihood of detecting failures at the symptom stage, thereby decreasing the failure rate. In this regard, if the failure rate after operating state monitoring is "after λ", then after λ(t) = coefficient x λ(t), and the effect of operating state monitoring can be expressed by increasing or decreasing the coefficient depending on the effectiveness and frequency of operating state monitoring in terms of the failure rate. In addition, when maintenance such as "main unit replacement" is performed as shown in Figure 14, the failure rates B and D of initial failures and wear-out failures return to t = 0, and when an overhaul inspection is performed, the failure rate B of initial failures returns to the value of t = 0, making it possible to express the reference value of the failure rate by positioning it from the above-mentioned maintenance point.

In addition, the simulation means 20 refers to the correspondence between the maintenance method, maintenance method, and operation, and the failure rate and cost created by the basic condition creation unit 15, and calculates and arranges the time function of the maintenance cost of the evaluation target equipment (including the time function of the predicted maintenance cost) in accordance with the maintenance and operation results and plans plotted on the time axis by the plotting means 18. An example is shown in FIG. 15. As shown in FIG. 15, the maintenance cost is calculated on the time axis according to the date and time of its implementation. This makes it possible to predict the cost of preventive maintenance. This can be achieved by simply arranging the unit price for disassembly inspection, for example, or the unit price per implementation period for operation status monitoring or daily inspection, in accordance with the implementation of preventive maintenance. Naturally, if the frequency of monitoring the operation status of the evaluation target equipment is increased, the price for that amount can be calculated based on the unit price.

Furthermore, in the simulation means 20, by referring to the failure rate calculated as described above and the correspondence between the maintenance method, maintenance method, operation (operation) and each of the costs created by the basic condition creation unit 15, it is possible to calculate (predict) the time function of the expected value of the failure recovery cost of the evaluation target equipment. Here, the repair cost at the time of failure of the evaluation target equipment, the cost of responding to reports to government agencies, etc., and the loss due to production interruption, etc., which are included in the basic conditions created by the basic condition creation unit 15, are used to calculate the expected value of the failure recovery cost of the evaluation target equipment. Since these are input as the cost per failure in the cost input means 14, the time function of the expected value of the failure recovery cost is calculated by weighting it by the time function of the predicted failure rate calculated by the simulation means 20. For example, when the time function of the predicted failure rate of the evaluation target equipment is μ(t), the time function of the expected value of the failure recovery cost is μ(t) × (the sum of the repair cost, the cost of responding to reports to government agencies, etc., and the loss due to production interruption). An example of the expected value of this failure recovery cost as a time function is shown in Figure 16 as the expected value of failure recovery cost G.

The display unit 21 displays at least one of the results and plans of maintenance and operation arranged over time by the plotting means 18, the time function of failure rate (including the time function of predicted failure rate) calculated and arranged by the simulation means 20, the time function of maintenance cost (including the time function of predicted maintenance cost), and the time function of expected value of failure recovery cost over time (display step).

As configured as above, the first embodiment provides the following effect (1).
(1) The simulation means 20 calculates the time function of the failure rate of the equipment to be evaluated in the facility, the time function of the maintenance cost, and the time function of the expected value of the failure restoration cost, making it possible to calculate (predict) the failure rate, maintenance cost, and expected value of the failure restoration cost of the equipment to be evaluated by selecting the maintenance method, maintenance method, and their frequency for the equipment to be evaluated. This makes it possible to select an optimal maintenance method that can improve the reliability of the equipment and reduce the maintenance cost.

[B] Second embodiment (FIGS. 17 to 24)
17 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to the second embodiment. In the second embodiment, the same parts as those in the first embodiment are denoted by the same reference numerals as those in the first embodiment, and the description thereof will be simplified or omitted.

The equipment reliability and maintenance cost prediction device 25 shown in FIG. 17 quantitatively evaluates the differences due to different maintenance methods and maintenance methods and their cycles when appropriately determining the maintenance method and maintenance method for equipment in facilities such as plants and large-scale transportation systems, and differs from the first embodiment mainly in the configurations of the evaluation condition input means 26, simulation means 27, and cumulative evaluation means 28.

The evaluation condition input means 26 changes the values of the basic conditions created by the basic condition creation unit 15 and input to the simulation means 27 based on the specified conditions. The specified conditions are the parameters whose values are to be changed and the range of the changes. The specified conditions are intended to provide prediction conditions that include the reference failure rate (reference value of the failure rate) created by the basic condition creation unit 15, the effect of the maintenance method on the failure rate, and the standard maintenance cost, which are all uncertain factors.

For example, the following examples are possible for the parameters input in the basic condition creation unit 15 shown in FIG. 12. That is, (a) taking into account the statistical uncertainty of the reference failure rate, two parameters of the Weibull distribution are specified as parameters to be changed, and their upper and lower limits and increment widths are specifically given. (b) To take into account the uncertainty of the effect of the maintenance method (monitoring of the operating state), α of "reference failure rate x α" shown in FIG. 12 is specified as a parameter to be changed, and its upper and lower limits and increment widths are specifically given. (c) To take into account changes in future labor costs and repair material purchasing costs, the corresponding value of the standard maintenance cost is specified as a parameter to be changed, and its upper and lower limits and increment widths are specifically given.

The above are merely examples, but instead of upper and lower limits, you can also give the center value of the parameter to be changed. Also, when there are multiple parameters to be changed, the specified condition is the method of combination. This combination method refers to whether to try all the possible ranges of change for each of the multiple parameters, or to only a portion of them.

When the conditions to be changed relate to scheduled maintenance or repair, the evaluation condition input means 26 changes the information (cycle, scheduled date) related to the specified maintenance or repair, and the plot means 18 changes the plot according to the information related to the scheduled maintenance or repair. For example, when changing the cycles of overhaul inspection, daily inspection, operational status monitoring, and oil replenishment of the equipment to be evaluated, upper and lower limits and intervals are given for the range of change of these cycles, and these plots in the "Schedule" portion of Figure 13 are changed. For example, when a date for overhaul inspection is given, the plots in the "Schedule" portion of Figure 13 are changed according to that date.

The simulation means 27 calculates a time function of the predicted failure rate for each of the "schedules" plotted according to the above-mentioned upper and lower limits, step widths, and scheduled dates in the same manner as in the first embodiment, calculates a time function of the predicted maintenance costs, and calculates (predicts) a time function of the expected value of the failure restoration costs. FIG. 18 shows an example in which the evaluation condition input means 26 changes the overhaul inspection cycle in FIG. 13 from 1 to 20 years, and the plot means 18 plots the changes. FIG. 19 shows an example in which the simulation means 27 calculates a time function of the predicted failure rate, and FIG. 20 shows an example in which the simulation means 27 calculates a time function of the predicted maintenance costs and a time function of the expected value of the failure restoration costs.

The simulation means 27 includes a cumulative evaluation means 28. When the cycles of disassembly and inspection, daily inspection, monitoring of the operating state, and oil supply of the evaluation target equipment are changed, the cumulative evaluation means 28 integrates the time function of the predicted failure rate, the time function of the predicted maintenance cost, and the time function of the expected value of the failure restoration cost output from the simulation means 27 for each of the plotted "schedules" in accordance with the upper and lower limits and intervals of the change range of these cycles to obtain the cumulative failure rate value, the cumulative maintenance cost value, and the cumulative expected value of the failure restoration cost, and sets each of these cumulative values and the value of the basic condition at that time. This makes it possible to obtain the cumulative failure rate value, the cumulative maintenance cost value, and the cumulative expected value of the failure restoration cost for the basic condition in accordance with the upper and lower limits and intervals of the change range of the cycles when the cycles of disassembly and inspection, daily inspection, monitoring of the operating state, and oil supply of the evaluation target equipment are changed. By displaying this on the display unit 21, it becomes possible to evaluate the cumulative failure rate value L, cumulative maintenance cost value M, and cumulative expected failure restoration cost value N, as shown in FIG. 21, and to find the basic conditions that optimize each of these cumulative values L, M, and N.

In Fig. 21, the vertical axis represents three cumulative values (cumulative failure rate L, cumulative maintenance cost M, and expected cumulative failure restoration cost N) calculated using the above-mentioned process for each point at which the overhaul inspection cycle is changed in increments from the upper limit to the lower limit. Note that the range of change in the overhaul inspection cycle is not limited to a continuous change using upper and lower limits and increments as described above, but may also be discrete values or items.

In addition, if the basic conditions changed by the evaluation condition input means 26 affect the failure rate, unit price of maintenance cost, etc., the calculation method of each time function of the failure rate prediction, maintenance cost prediction, and expected value of failure recovery cost in the simulation means 27 is adjusted. The accumulation evaluation means 28 calculates the accumulated failure rate value, the accumulated maintenance cost value, and the accumulated expected value of failure recovery cost based on each of these time functions in the same manner as described above, and displays the changed basic conditions and each accumulated value as a set on the display unit 21, making it possible to evaluate each accumulated value and find the conditions that optimize them.

For example, if the method of monitoring the operating state is changed, as described in the first embodiment, if the failure rate after monitoring is "λ after", then λ after (t) = coefficient × λ(t), and this coefficient can be increased or decreased depending on the monitoring method (the effectiveness of that method in detecting abnormalities). Also, as described in the first embodiment, maintenance costs can be calculated based on the unit cost and failure rate for each monitoring method.

Figures 22 and 23 are examples in which the simulation means 27 predicts a time function of failure rate and a time function of maintenance cost using two condition monitoring methods with different effectiveness and costs. As shown in Figure 22, the simulation means 27 calculates a time function of predicted failure rate by expressing the effects of the two condition monitoring methods by changing the coefficients using the method described above, and expresses that condition monitoring method 1 has a lower failure rate than condition monitoring method 2. On the other hand, as shown in Figure 23, the simulation means 27 calculates a time function of predicted maintenance cost based on the failure rate prediction result in Figure 22 and the difference in unit price between condition monitoring method 1 and condition monitoring method 2.

The cumulative evaluation means 28 varies the above-mentioned coefficients when the monitoring frequency is changed between condition monitoring method 1 and condition monitoring method 2 (increasing the monitoring frequency increases the possibility of detecting a failure in its early stages and reduces the failure rate, so the coefficient is reduced), and integrates the resulting increase in maintenance costs (naturally, this will be a multiple of the unit price) using the above-mentioned method, making it possible to calculate the cumulative value of maintenance costs. An example of this is shown in Figure 24. Figure 24 compares the cumulative failure rate L, cumulative maintenance cost M, and expected cumulative failure restoration cost N for the monitoring cycle when only the monitoring cycle is changed between condition monitoring methods 1 and 2 and all other conditions are the same.

As configured as above, the second embodiment provides the following effect (2).
(2) When the maintenance method or method is changed, the simulation means 27 calculates a time function of the predicted failure rate, a time function of the predicted maintenance cost, and a time function of the expected value of the failure restoration cost, and the accumulation evaluation means 28 calculates the accumulated failure rate value, the accumulated maintenance cost value, and the expected accumulated failure restoration cost value. Therefore, by comparing the above-mentioned time functions due to changes in the maintenance method or method and comparing the above-mentioned accumulated values, it is possible to select the optimal maintenance method and method.

[C] Third embodiment (FIG. 25)
25 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to the third embodiment. In the third embodiment, the same parts as those in the first embodiment are denoted by the same reference numerals as those in the first embodiment, and the description thereof will be simplified or omitted.

The equipment reliability and maintenance cost prediction device 30 shown in FIG. 25 quantitatively evaluates the differences due to different maintenance methods and maintenance methods and their cycles when appropriately determining the maintenance method and maintenance method for equipment in facilities such as plants and large-scale transportation systems, or compares the time function of the predicted failure rate, the time function of the predicted maintenance cost, and the time function of the expected value of the failure recovery cost for multiple evaluation target equipment, or predicts the reliability of the system or group to which the evaluation target equipment belongs, the reliability of the model unit or responsibility division to which the evaluation target equipment belongs, and the maintenance cost and failure recovery cost, and mainly differs from the first embodiment in the configuration of the evaluation target setting means 31 and the cumulative evaluation means 32.

The evaluation target setting means 31 specifies and sets multiple devices to be evaluated. At this time, classification information including the model of the device is also input as necessary. Here, for each of the multiple devices to be evaluated that have been specified, the simulation means 20 calculates a time function of the predicted failure rate and a time function of the predicted maintenance cost in the same manner as in the first embodiment, and calculates (predicts) a time function of the expected value of the failure recovery cost.

The simulation means 20 includes a cumulative evaluation means 32. This cumulative evaluation means 32 displays on the display unit 21 the time function of the predicted failure rate, the time function of the predicted maintenance cost, and the time function of the expected value of the failure restoration cost for each of the multiple devices to be evaluated, superimposed on the time axis. This makes it possible to compare the failure rates and maintenance costs of the multiple devices to be evaluated, and to compare the priority order of maintenance for the multiple devices to be evaluated.

The cumulative evaluation means 32 may also take the sum, based on the time axis, of the time function of the predicted maintenance costs and the time function of the expected value of the failure recovery costs for each of the multiple evaluation target devices set by the evaluation target setting means 31. This makes it possible to predict the expected values of maintenance costs and failure recovery costs in categories such as the entire plant or all the devices managed by a certain section.

As configured as above, the third embodiment provides the following effect (3).
(3) The cumulative evaluation means 32 displays the time function of the predicted failure rate, the time function of the predicted maintenance cost, and the time function of the expected value of the failure restoration cost calculated for each of the multiple evaluation target devices set by the evaluation target setting means 31, superimposed on the time axis as a reference, and also displays the time function of the predicted maintenance cost and the time function of the expected value of the failure restoration cost for each of the multiple evaluation target devices, summed up on the time axis as a reference. This makes it possible to compare and set the priority of maintenance implementation for the multiple evaluation target devices, and to predict the maintenance cost for the entire plant including the multiple evaluation target devices or for all of the multiple evaluation target devices.

[D] Fourth embodiment (FIGS. 26 to 29)
26 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to the fourth embodiment. In the fourth embodiment, the same parts as those in the first embodiment are denoted by the same reference numerals as those in the first embodiment, and the description thereof will be simplified or omitted.

The equipment reliability and maintenance cost prediction device 40 shown in FIG. 26 evaluates the reliability of the system, system, facility, plant, or large-scale transportation system as a whole (hereinafter, these are referred to as the system), which is the higher-level concept to which the equipment to be evaluated belongs, when appropriately determining the maintenance method and maintenance system for equipment in facilities such as a plant or a large-scale transportation system, and differs from the first embodiment mainly in the configurations of the evaluation target setting means 41, evaluation condition input means 42, and cumulative evaluation means 43.

The evaluation target setting means 41 specifies and sets multiple evaluation target devices belonging to one of the higher-level systems whose reliability is to be evaluated. At this time, classification information including the model of the device is also input as necessary. In addition, in a plant or the like, multiple devices are specified without omissions based on, for example, an equipment ledger or EAM system. For the multiple evaluation target devices specified here, the simulation means 20 calculates a time function of the predicted failure rate in the same manner as in the first embodiment.

The evaluation condition input means 42 stores and sets a formula (system reliability evaluation formula) for calculating the availability rate, which is an index of the reliability of the system, in the cumulative evaluation means 43 provided in the simulation means 20. This formula takes the time function of the predicted failure rate of multiple evaluation target devices as an input, and the cumulative evaluation means 43 calculates the time function of the availability rate for each time according to the above formula. When the time functions of the predicted failure rate of each of the multiple evaluation target devices are λ1(t), λ2(t), λ3(t), λ4(t) ... λn(t), the above calculation formula takes these λ1(t), λ2(t), λ3(t), λ4(t) ... λn(t) as inputs, and combines them with addition, subtraction, multiplication, division, coefficient multiplication, and other functions. For example, by using knowledge of reliability engineering, it becomes possible to predict the reliability (availability) of the entire system as a calculation formula that combines the time functions of the predicted failure rates of each of the multiple evaluation target devices.

As shown in Figure 27, when devices 1, 2, and 3 are connected in series and the system is normal when each of them is normal, if the availability rate of the entire system at a certain time t is R(t), then R(t) = (1 - λ1(t)) (1 - λ2(t)) (1 - λ3(t)). Also, as shown in Figure 28, when devices 1, 2, and 3 are connected in parallel and the system is normal when any one of them is normal, if the availability rate of the entire system at a certain time t is R1(t), then R1(t) = 1 - λ1(t) λ2(t) λ3(t).

In this way, in the fourth embodiment, by easily incorporating reliability engineering knowledge into the actual equipment and evaluating the system reliability (operation rate) as a function of time, it becomes possible to consider optimal maintenance, including the timing of its implementation. This concept is shown in Figure 29. The time function of the predicted failure rate for each of multiple devices to be evaluated is used as input, and the operation rate, which is an index of the reliability of the entire system, is used as output, and the timing of the input of maintenance resources can be evaluated based on changes in this operation rate.

As configured as above, the fourth embodiment provides the following effect (4).
(4) The evaluation condition input means 42 sets a formula (system reliability evaluation formula) for calculating the availability rate, which is an index of the system reliability, in the cumulative evaluation means 43. This cumulative evaluation means 43 predicts and evaluates the reliability (availability rate) of a system constituted by the multiple evaluation target devices as a function of time, based on the system reliability evaluation formula, using as input a time function of the predicted failure rate of each of the multiple evaluation target devices set by the evaluation target setting means 41. This makes it possible to consider optimal maintenance for the system, including the timing of its implementation.

Although several 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, substitutions, changes, and combinations can be made without departing from the gist of the invention. Furthermore, such substitutions, changes, and combinations are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims.

10...Equipment reliability and maintenance cost prediction device, 11...Evaluation target setting means, 12...Failure rate input means, 13...Maintenance characteristic input means, 14...Cost input means, 15...Basic condition creation unit, 16...Operation and maintenance performance input means, 17...Operation and maintenance schedule input means, 18...Plotting means, 19...Evaluation condition input means, 20...Simulation means, 21...Display unit, 25...Equipment reliability and maintenance cost prediction device, 26...Evaluation condition input means, 27...Simulation means, 28...Cumulative evaluation means, 30...Equipment reliability and maintenance cost prediction device, 31...Evaluation target setting means, 32...Cumulative evaluation means, 40...Equipment reliability and maintenance cost prediction device, 41...Evaluation target setting means, 42...Evaluation condition input means, 43...Cumulative evaluation means

Claims (16)

an evaluation target setting means for designating and setting devices to be evaluated for reliability, maintenance cost, and failure recovery cost in the facility;
a failure rate input means for inputting a reference value of a failure occurrence probability and a failure rate for each failure mode of the device;
a maintenance characteristic input means for inputting a relationship between each of the maintenance method, maintenance method, and operation of the equipment and the failure rate;
a cost input means for inputting a standard maintenance cost relating to preventive maintenance of the device and a standard failure recovery cost required for recovery when a failure occurs in the device;
a basic condition creating unit that creates basic conditions for evaluating the device by combining the input values input from the input means;
An operation and maintenance performance input means for inputting the operation and maintenance performance of the equipment;
An operation and maintenance schedule input means for inputting a schedule for operation and maintenance of the device;
a plotting means for plotting the actual results and the schedule of the operation and maintenance of the equipment in time;
a simulation means for inputting each value within the basic conditions and the operation and maintenance results and plans inputted via the operation and maintenance result input means and the operation and maintenance plan input means, and calculating a time function of the failure rate of the equipment and a time function of the maintenance cost based on the operation and maintenance results and plans of the equipment, and calculating an expected value of a failure restoration cost as a time function and allocating it in time;
an evaluation condition input means for specifying a period for evaluating the reliability, maintenance cost, and failure recovery cost of the equipment, changing the schedule of maintenance or operation arranged in time by the plotting means, and further changing the basic conditions when the time function of the failure rate, the time function of the maintenance cost, and the time function of the expected value of the failure recovery cost are calculated by the simulation means;
and a display unit that displays, over time, at least one of the results and plans of maintenance and operation arranged over time by the plotting means, the time function of the failure rate calculated and arranged by the simulation means, the time function of the maintenance cost, and the time function of the expected value of the failure restoration cost. The equipment reliability and maintenance cost prediction device according to claim 1, characterized in that when the equipment to be evaluated is set by the evaluation target setting means, the model to which the equipment belongs can be specified. The equipment reliability and maintenance cost prediction device according to claim 1 or 2, characterized in that the failure rate reference value input by the failure rate input means is input by an operator using electronic means, or is input from a database that stores the time function of the failure rate for each failure type that is set in advance for each model. The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 3, characterized in that the relationship between the equipment maintenance method, maintenance method, and operation and the failure rate input by the maintenance characteristic input means is configured so that an operator inputs by electronic means how the reference value of the failure rate changes depending on the effect of each of the maintenance method, maintenance method, and operation on the equipment failure rate, or inputs from a database in which the relationship is preset for each model. The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 4, characterized in that the standard maintenance cost for preventive maintenance of the equipment and the standard failure recovery cost when a failure occurs in the equipment, which are input by the cost input means, are input by an operator for each of the equipment by electronic means or are input from a database. The device for predicting equipment reliability and maintenance costs according to any one of claims 1 to 5, characterized in that the basic conditions created by the basic condition creation unit are created as basic conditions by combining an equipment name, equipment number, and other equipment information that identifies the equipment with information on the model to which the equipment belongs, as well as by combining information specific to the equipment with information related to the model to which the equipment belongs. The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 6, characterized in that the operation and maintenance records of the equipment inputted to the operation and maintenance record input means are the contents thereof and the date and time when they were performed, and the operation and maintenance schedule of the equipment inputted to the operation and maintenance schedule input means are the contents thereof and the date and time when they are scheduled to be performed, and that the operation and maintenance records and operation and maintenance schedules are inputted by an operator by electronic means or from a database. The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 7, characterized in that the plotting means is configured to plot the operation and maintenance results and schedule contents and time inputted by the operation and maintenance results inputting means and the operation and maintenance schedule inputting means on a time axis. The equipment reliability and maintenance cost prediction device according to claim 8, characterized in that the simulation means is configured to calculate a time function of the equipment failure rate based on the basic conditions created by the basic condition creation unit in accordance with the maintenance and operation records and schedules plotted on a time axis by the plotting means. The equipment reliability and maintenance cost prediction device according to claim 9, characterized in that the simulation means is configured to calculate a time function of maintenance costs based on basic conditions created by a basic condition creation unit in accordance with the maintenance and operation results and schedules plotted on a time axis by a plotting means, and to calculate a time function of an expected value of failure recovery costs based on the calculated equipment failure rate and the basic conditions. The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 10, characterized in that the evaluation condition input means allows an operator to change at least one of the operation and maintenance schedules of the equipment arranged in the plot means, and also allows an operator to change the reference value of the failure rate of the equipment under the basic conditions input from the basic condition creation unit to the simulation means, the relationship between the failure rate and each of the maintenance method, maintenance method, and operation, the standard maintenance cost related to the preventive maintenance of the equipment, and the standard failure recovery cost when a failure occurs in the equipment. The simulation means includes a cumulative evaluation means,
an evaluation condition input means for varying values of the basic conditions created by the basic condition creating unit based on the specified conditions, a plotting means for plotting each of the values on a time axis, and a simulation means for calculating a time function of a prediction of the equipment failure rate, a time function of a prediction of the maintenance cost, and a time function of an expected value of the failure restoration cost based on the result, and outputting each of these time functions to said cumulative evaluation means;
The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 11, characterized in that the cumulative evaluation means is configured to integrate a time function of the prediction of the failure rate, a time function of the prediction of the maintenance cost, and a time function of the expected value of the failure restoration cost over an evaluation period to obtain a cumulative failure rate value, a cumulative maintenance cost value, and a cumulative expected value of the failure restoration cost, set these cumulative values and the values of the basic conditions at that time as a set, and arrange at least one of the cumulative failure rate value, the cumulative maintenance cost value, and the cumulative expected value of the failure restoration cost on a graph with the changed value of the basic condition as an axis and display the graph superimposed on a display unit. the evaluation target setting means sets a plurality of devices, and the simulation means calculates a time function of a prediction of a failure rate, a time function of a prediction of a maintenance cost, and a time function of an expected value of a failure restoration cost for the plurality of devices;
The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 11, characterized in that the cumulative evaluation means provided in the simulation means is configured to display on a display unit, the time function of the predicted failure rate for a plurality of the equipment, the time function of the predicted maintenance cost, and the time function of the expected value of the failure recovery cost, superimposed on a time axis. The evaluation target setting means sets a plurality of devices, and the simulation means calculates a time function of a predicted maintenance cost and a time function of an expected value of a failure restoration cost for the plurality of devices,
The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 11, characterized in that the cumulative evaluation means provided in the simulation means is configured to sum up the time function of the predicted maintenance costs for a plurality of the equipment and the time function of the expected value of the failure recovery costs based on a time axis and display the sum on a display unit. the evaluation target setting means sets a plurality of devices, and the evaluation condition input means sets a calculation formula having a time function of a prediction of a failure rate of the plurality of devices as an input to a cumulative evaluation means provided in a simulation means;
The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 11, characterized in that the cumulative evaluation means is configured to calculate a time function of an availability rate, which is a calculation result using a time function of the predicted failure rate of the equipment as an input, in accordance with the calculation formula, and to display the time function of the availability rate on a display unit. an evaluation target setting step in which an evaluation target setting means designates and sets a device to be the target of evaluation of reliability, maintenance cost, and failure recovery cost in the facility;
a failure rate input step in which a failure rate input means inputs a reference value of a failure occurrence probability and a failure rate for each failure mode of the device;
a maintenance characteristic input step in which a maintenance characteristic input means inputs a relationship between each of the maintenance method, maintenance method, and operation of the equipment and the failure rate;
a cost input step in which a cost input means inputs a standard maintenance cost related to preventive maintenance of the device and a standard failure recovery cost required for recovery when a failure occurs in the device;
a basic condition creating step in which a basic condition creating unit creates basic conditions for evaluating the device by combining each input value input from each input step;
An operation and maintenance performance input step in which operation and maintenance performance input means inputs the operation and maintenance performance of the equipment;
An operation and maintenance schedule input step in which an operation and maintenance schedule input means inputs an operation and maintenance schedule for the equipment;
a plotting step in which a plotting means arranges the actual results and the schedule of the operation and maintenance of the equipment in time;
a simulation step in which a simulation means inputs each value within the basic conditions and the operation and maintenance results and the plan input in the operation and maintenance result input step and the operation and maintenance plan input step, calculates a time function of the failure rate of the equipment based on the operation and maintenance results and the plan of the equipment, and a time function of the maintenance cost, and calculates an expected value of a failure restoration cost as a time function and arranges them in time;
an evaluation condition input step in which an evaluation condition input means specifies a period for evaluating the reliability, maintenance cost, and failure recovery cost of the equipment, changes the schedule of maintenance or operation arranged in time in the plot step, and further changes the basic conditions when the time function of the failure rate, the time function of the maintenance cost, and the time function of the expected value of the failure recovery cost are calculated in the simulation step;
a display step in which a display unit displays, over time, at least one of the results and plans of maintenance and operation arranged over time in the plot step , the time function of the failure rate calculated and arranged in the simulation step, the time function of the maintenance cost, and the time function of an expected value of the failure restoration cost.

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