JP2023108670A - Device and method for predicting reliability and maintenance cost of apparatus - Google Patents

Abstract

To provide a device and method for predicting reliability and maintenance costs of an apparatus, which can improve reliability of a facility and reduce maintenance costs.SOLUTION: A device 10 for predicting reliability and maintenance costs of an apparatus includes evaluation object setting means 11, failure rate input means 12, maintenance characteristic input means 13, cost input means 14, a basic condition generation unit 15, operation and maintenance record input means 16, operation and maintenance schedule input means 17, plotting means 18, evaluation condition input means 19, and simulation means 20. The simulation means 20 calculates a time function of a failure rate of the apparatus based on records and schedules of operation and maintenance, a time function of maintenance costs, and a time function of an expected value of failure recovery costs and locates them with respect to time. The evaluation condition input means 19 designates an evaluation period and changes the schedule of maintenance or operation located with respect to time by the plotting means 18.SELECTED DRAWING: Figure 1

Description

TECHNICAL FIELD Embodiments of the present invention relate to equipment reliability and maintenance cost prediction apparatuses and equipment reliability and maintenance cost prediction methods for predicting equipment reliability and maintenance costs.

In large-scale systems such as plants such as power plants and transportation machinery, in order to maintain the reliability of the system, subsystems, facilities, equipment, etc. ) must be properly maintained. For maintenance of equipment, as stipulated in JIS, etc., time-planned maintenance (TBM), in which periodic overhauls are performed, and parameters related to deterioration and failure of equipment are observed, and depending on the condition, There are three types of maintenance methods: condition-based maintenance (CBM), in which overhauls are performed, etc., and breakdown maintenance (BDM), in which repairs are performed when a failure is found in equipment or when there is a loss of function. By appropriately combining these maintenance methods according to the degree of importance and characteristics of the equipment, it is possible to maintain the reliability of the system and reduce repair costs and production losses.

Conventionally, various attempts have been made to determine the optimum maintenance method. For example, in the U.S. aviation industry, military, etc., investigations of failures and deterioration of a huge number of mechanical parts were conducted to obtain a time-varying curve of failure rates. Consideration is being made. As a result, TBM induces so-called tampering with most machinery and equipment, leading to increased maintenance and loss costs. It has been clarified that it is a method, and it has been introduced in Japan, mainly in the steel and chemical industries, 30 to 40 years ago.

However, in the current maintenance of nuclear power plants in Japan, TBM is carried out as preventive maintenance for most of the equipment. carried out during inspection. In TBM, the cycle of disassembly inspection must be set very short compared to the original equipment life. Therefore, there is a problem that so-called tampering and destruction, which causes failures during the process of disassembling and assembling devices that are not deteriorated, is likely to occur. In addition, most of the work is carried out intensively during regular inspections that last for several months, so the process is complicated and troubles are likely to occur. There is also the problem that it is difficult to

Since such problems are recognized, reliability-oriented maintenance (RCM), which has a proven track record in other industries such as petrochemicals and nuclear power plants in the United States, condition-based maintenance (CBM), and TBM cycle extension that does not lead to overmaintenance Attempts have been made to optimize conservation schemes, including In addition, in the inspection system at nuclear power plants, "maintenance effectiveness evaluation" (JEAC4209, JEAG4210) is required to evaluate and review the cycle and method of TBM, applicability of CBM, etc. based on actual data. .

This maintenance effectiveness evaluation evaluates whether the maintenance to maintain the functions of the plant and equipment is being performed appropriately, and whether there are any deficiencies in the maintenance method and cycle based on the maintenance results and failure records of the plant and equipment. It is. In this maintenance effectiveness evaluation, it is required to confirm that the maintenance is being carried out effectively, but the maintenance results are recognized as good, and the TBM cycle of disassembly inspections, etc. has a margin for the deterioration rate of the equipment. It is possible to extend the period when it is recognized that For example, by evaluating the time trend of changes in the amount of wear of a part obtained for each overhaul of a certain piece of equipment, it is possible to determine whether the current overhaul cycle is sufficiently short before the amount of wear reaches the failure criteria, and for a long period of time. It is determined that various failures have not occurred over the years, and the overhaul cycle is extended.

Japanese Patent No. 6733004 WO2008/155982

On the other hand, attempts have also been made to reduce the failure rate by setting the optimum maintenance cycle for the equipment by evaluating the frequency of failures occurring in the equipment. In the maintenance effectiveness evaluation of the facility equipment described above, the quality of the maintenance status is determined using the performance data of the maintenance 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 across the entire plant and multiple pieces of equipment from a statistical viewpoint based on the operating results of the same model of equipment. This is because, for example, by comparing failure rates with equipment that is operated and maintained under certain conditions, the conditions can be improved so as to reduce the failure rates. As a method for performing this evaluation with high accuracy, Patent Document 1 proposes a method of analyzing the cause of failure by classifying it into aged deterioration (wear failure) and human error.

In addition, based on the performance and deterioration state estimation results obtained from the results of signal monitoring for each device, the optimum reliability and cost prediction simulations are performed based on the restoration of performance and deterioration state due to subsequent maintenance. A method for examining maintenance management is also proposed in Patent Document 2. According to this method, it is possible to predict the optimum maintenance method by searching for the optimum point of increase in cost and reliability by increasing the frequency of maintenance.

In the above-mentioned maintenance effectiveness evaluation, the transition of data such as overhaul inspections performed multiple times over several years to over ten years is generally evaluated, and it is evaluated that the current TBM cycle has sufficient margin for the deterioration speed. It determines the lengthening of the cycle and the transition to CBM. However, there are no quantitative evaluation criteria such as the evaluation of the reliability of the equipment after the change, the expected maintenance cost, the expected failure recovery cost, etc. to clarify this judgment. has not been migrated to In particular, it is difficult to determine how long the cycle should be after the change.

Accurate evaluation of the failure rate can also contribute to decisions for reducing 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, and the expected failure recovery costs. and no transition to CBM. In particular, it is also difficult to determine how to deal with the risk of failure due to human error and what the maintenance cycle after the change should be. Furthermore, unless the increased risk of human error in maintenance and the increased risk of failure recovery costs based on the prediction of the overall failure rate are included in the evaluation, it will not serve as a guideline for selecting the optimal maintenance method and frequency.

The embodiments of the present invention have been made in consideration of the above circumstances, and are a reliability and maintenance cost prediction apparatus for equipment that can select a maintenance method that can improve the reliability of equipment and reduce maintenance costs. , and equipment reliability and maintenance cost prediction methods.

An equipment reliability and maintenance cost prediction apparatus according to an embodiment of the present invention includes evaluation target setting means for designating and setting equipment to be evaluated for equipment reliability, maintenance cost, and failure recovery cost; Failure rate input means for inputting failure occurrence probability and failure rate reference values for each failure mode, and maintenance characteristics input means for inputting the 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 maintenance standard cost for preventive maintenance of said equipment and a failure recovery standard cost required for recovery when a failure occurs in said equipment, and combining each input value input from each input means, a basic condition creation unit for creating basic conditions for evaluation of the equipment; operation and maintenance record input means for inputting operation and maintenance results for the equipment; and operation and maintenance schedule input means for inputting operation and maintenance schedules for the equipment. , plotting means for temporally arranging the results and schedules of the operation and maintenance of the equipment, each value in the basic conditions, the operation/maintenance result input means, and the operation/maintenance schedule input means. inputting the results and the schedule of operation and maintenance of the equipment, calculating a time function of the failure rate of the equipment and a time function of the maintenance cost based on the results and the schedule of operation and maintenance of the equipment; A simulation means for calculating the expected value of the restoration cost as a function of time and arranging it temporally, specifying a period for evaluating the reliability of the equipment, the maintenance cost and the failure recovery cost, and temporally by the plotting means When the arranged maintenance or operation schedule is changed, and 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 evaluation condition input means for changing the basic conditions; the results and schedules of maintenance and operation temporally arranged by the plotting means; the time function of the failure rate calculated and arranged by the simulation means; and a display section for temporally displaying at least one of the time function of the maintenance cost and the time function of the expected value of the failure recovery cost.

A device reliability and maintenance cost prediction method according to an embodiment of the present invention includes an evaluation target setting step of designating and setting a device to be evaluated for reliability, maintenance cost, and failure recovery cost in a facility; a failure rate input step of inputting failure occurrence probability and failure rate reference values for each failure type; and a maintenance characteristic input step of inputting the relationship between each of the maintenance method, maintenance method, and operation of the equipment and the failure rate. , a cost input step of inputting a maintenance standard cost for preventive maintenance of said equipment and a failure recovery standard cost required for recovery when a failure occurs in said equipment, and combining each input value input from each input step, a basic condition creation step of creating basic conditions for evaluation of the equipment; an operation and maintenance record input step of inputting operation and maintenance results of the equipment; and an operation and maintenance schedule input step of inputting operation and maintenance schedules of the equipment. , a plotting step of temporally arranging the results and the schedule of the operation and maintenance of the equipment, each value in the basic conditions, the operation and maintenance result input step, and the operation and maintenance schedule input step. inputting the results and the schedule of operation and maintenance of the equipment, calculating a time function of the failure rate of the equipment and a time function of the maintenance cost based on the results and the schedule of operation and maintenance of the equipment; A simulation step of calculating the expected value of the restoration cost as a function of time and arranging it temporally, specifying a period for evaluating the reliability of the equipment, the maintenance cost and the failure recovery cost, and temporally in the plotting step When the scheduled maintenance or operation is changed, and the simulation step 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. an evaluation condition input step for changing the basic conditions; the results and schedules of maintenance and operation temporally arranged in the plotting step; the time function of the failure rate calculated and arranged by the simulation means; and a display step of temporally displaying at least one of the time function of the maintenance cost and the time function of the expected value of the failure recovery cost.

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

FIG. 2 is a block diagram showing the configuration of the equipment reliability and maintenance cost prediction apparatus according to the first embodiment; 2 is a chart showing an example of an evaluation target device set as an evaluation target by an evaluation target setting means in FIG. 1; 2 is a chart showing an example of failure rates of initial failures, random failures, and wear-out failures of the equipment to be evaluated, which are input by the failure rate input means of FIG. 1; FIG. 2 is a chart showing an example of a failure rate for each failure mode (failure mode) of the equipment to be evaluated, which is input by the failure rate input means of FIG. 1; 2 is a chart showing an example of setting the failure rate of the device to be evaluated, which is input by the failure rate input means of FIG. 1, for each component; FIG. 2 is an explanatory diagram showing an example of the relationship between the failure rate for each failure mode of the equipment to be evaluated and the failure rates of initial failure, random failure, and wear-out failure, which are input by the failure rate input means of FIG. 1 ; 4 is a chart showing an example of the relationship between the maintenance method, the maintenance method, and the operation of the equipment to be evaluated, which are input by the maintenance characteristics input means in FIG. 1, and the failure rate; 2 is a graph showing an example of a failure rate reference value input by the failure rate input means of FIG. 1; 9 is a graph showing the relationship between the initial failure rate and maintenance method in FIG. 8 ; 9 is a graph showing the relationship between the wear-out failure rate and maintenance method in FIG. 8 ; The graph which shows that the failure rate of the initial failure of FIG. 8 falls by a maintenance method. A diagram showing an example of the equipment to be evaluated, the reference value of its failure rate (reference failure rate), the maintenance method, the influence of the maintenance method on the failure rate, the standard cost of maintenance, etc. created by the basic condition creation part in FIG. . FIG. 2 is an explanatory diagram showing an example of plotting results and schedules of operation and maintenance (contents, dates) generated by the plotting means of FIG. 1 on the basis of a time axis; FIG. 2 is an explanatory diagram showing an example of the time function of the failure rate calculated by the simulation means of FIG. 1 according to the results and schedules of maintenance and operation plotted on the basis of the time axis; FIG. 2 is an explanatory diagram showing an example of a time function of maintenance costs calculated by the simulation means in FIG. FIG. 2 is an explanatory diagram showing an example of the time function of the expected value of the failure recovery cost calculated by the simulation means of FIG. FIG. 11 is a block diagram showing the configuration of a device reliability and maintenance cost prediction device according to the second embodiment; FIG. 18 is an explanatory diagram showing an example in which the evaluation condition input means of FIG. 17 changes the scheduled period of maintenance (overhaul) and plotted by the plotting means; FIG. 18 is an explanatory diagram showing an example in which the simulation means of FIG. 17 has calculated a time function for predicting a failure rate according to changes in scheduled maintenance (overhaul) cycles. FIG. 17 is an explanatory diagram showing an example of calculation of a time function of prediction of maintenance cost and a time function of expected value of failure recovery cost in accordance with a change in the scheduled period of maintenance (overhaul) by the simulation means of FIG. 17 ; 18 is a graph showing an example of the failure rate cumulative value, the maintenance cost cumulative value, and the failure recovery cost cumulative expected value calculated by the cumulative evaluation means of FIG. FIG. 18 is an explanatory diagram showing a comparison of an example of a failure rate prediction time function calculated by the simulation means of FIG. 17 according to maintenance (condition monitoring) methods having different effects; An explanation showing an example of a comparison between the time function of prediction of maintenance cost and the time function of expected value of failure recovery cost calculated according to maintenance (condition monitoring) methods with different effects and costs by the simulation means of FIG. figure. The simulation means in FIG. 17 calculates the cumulative failure rate, cumulative maintenance cost, and failure recovery cost according to the cycle of the state monitoring on the horizontal axis, based on the difference in the effect and cost of the two state monitoring methods. 6 is a graph showing a comparison of examples of cumulative expected values; FIG. 11 is a block diagram showing the configuration of a device reliability and maintenance cost prediction device according to a third embodiment; FIG. 11 is a block diagram showing the configuration of a device 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 calculating and predicting a time function of an operation rate, which is an index of system reliability, by the cumulative evaluation means of FIG. 26 from failure rates of a plurality of devices;

EMBODIMENT OF THE INVENTION Hereinafter, the form for implementing this invention is demonstrated based on drawing.
[A] First embodiment (Figs. 1 to 16)
FIG. 1 is a block diagram showing the configuration of the equipment reliability and maintenance cost prediction apparatus according to the first embodiment. The equipment reliability and maintenance cost prediction device 10 shown in FIG. rate input means 12, maintenance characteristic input means 13, cost input means 14, basic condition creation unit 15, operation and maintenance record input means 16, operation and maintenance schedule input means 17, plot means 18, evaluation condition input means 19, simulation means 20 and It is configured to have a display unit 21 .

The evaluation target setting means 11 designates and sets evaluation target equipment, which is equipment to be evaluated for reliability, maintenance cost, and failure recovery cost (evaluation target setting step). At this time, classification information including the model of the device is also entered as necessary. These devices and models are basically information managed by a facility ledger, a facility management system, or the like in a plant or the like. An example of this is shown in FIG.

The failure rate input means 12 inputs the probability of failure occurrence and the reference value of the failure rate as a function of time according to the failure type (failure mode) of the equipment to be evaluated (failure rate input step). The reference value of the failure rate input by the failure rate input means 12 is either input by an operator by electronic means, or a time function of the failure rate for each failure type preset for each model is stored. Input from database.

Here, failure modes are classified into three categories of initial failure, accidental failure, and wear-out failure, and failure rates for each are input. An example of this is shown in FIG. Also, the parameters that define the failure rate as a function of time are the shape parameter and the scale parameter when the failure rate is given by the Weibull distribution, for example. Further, instead of using three classifications, as shown in FIG. 4, the failure mode leading to the loss of function of the equipment to be evaluated may be subdivided and input within a identifiable range. Further, for example, failures that occur in the equipment to be evaluated may be developed into component levels and events and input. An example of this is shown in FIG. The reference value of the failure rate is calculated, estimated, assumed, or the like by some means other than the present embodiment. It is calculated statistically from the actual results of maintenance.

The example of FIG. 6 is an example in which the failure mode leading to the loss of function of the equipment to be evaluated shown in FIG. 4 is subdivided within a identifiable range. As shown in FIG. 6, initial failures include the failure rate when a part is replaced in the equipment to be evaluated, and the occurrence of failures due to human error in the construction work. Accidental failures are failures caused by the influence of other equipment and failures due to operator error, and wear-out failures are deterioration due to normal use.

The maintenance characteristic input means 13 inputs the relationship between each of the maintenance method, maintenance method, and operation of the equipment to be evaluated and the failure rate of the failure mode (maintenance characteristic input step). The relationship between the maintenance method, maintenance method, and operation of the equipment to be evaluated input by the maintenance characteristics input means 13 and the failure rate of the failure mode is that the maintenance method, maintenance method, and operation each affect the failure rate of the equipment to be evaluated. The operator electronically inputs how the reference value of the failure rate changes depending on the influence on the equipment, or the data is input from a database in which the relationships are set in advance for each model.

Here, the relationship between each of the maintenance method, maintenance method, and operation and the failure rate of the failure type refers to the influence of various maintenance methods, maintenance methods, and operation on the occurrence of failures on the equipment to be evaluated, that is, the life span. This refers to elongation or shortening, prevention or induction of failure, such as the following (a) to (f). (a) Restoration by regular and appropriate replacement of deteriorated parts (initialization of wear-out failure rate), (b) Decrease in accidental failure rate due to condition monitoring, (c) Assembly error due to replacement of parts Occurrence of initial failures, (d) Occurrence of initial failures due to factory manufacturing errors associated with replacement of parts, (e) Decrease in the failure rate of accidental failures due to routine maintenance such as refueling, and (f) Operation stoppages For example, the progress of wear is stopped. In this embodiment, using the reference value of the failure rate input by the failure rate input means 12, it is expressed by predicting how the failure rate will change due to maintenance, maintenance, and operation. This is explained below.

First, FIG. 7 shows an example in which the relationship between the maintenance method, maintenance method, operation, and change in failure rate is created for each model. In this way, the effects of maintenance methods, maintenance methods, and operation on the failure rates of initial failures, random failures, and wear-out failures (deterioration over time) are discussed in terms of models and the characteristics of failures that occur in those models. Create a table of considerations. The meaning of FIG. 7 is as follows.

The reference values of the initial failure, random failure, and wear-out failure, which are input by the failure rate input means 12, are generally as shown in FIG. As shown in FIG. 8, the failure rate is determined by analyzing the causes of initial failures (initial failure failure rate B), random failures (accidental failure failure rate C), and wear-out failures (wear-out failure rate D). can be calculated separately, and the sum of these is the failure rate A of the equipment. In addition, it is known that the time change of the failure rate differs greatly for each model.

FIG. 9 is a conceptual explanation of induction of initial failure by maintenance method 1 (overhaul) illustrated in FIG. As shown in this figure, by performing maintenance method 1, the failure rate B of the initial failure returns to the initial value (the value of t=0, which is the reference value of the failure rate). FIG. 10 is a conceptual explanation of restoration of wear-out failures by maintenance method 1 illustrated in FIG. = value of 0). FIG. 11 is a conceptual explanation of the decrease in the failure rate B of the initial failure by the maintenance method 2 (monitoring of the operating state of the equipment) shown in FIG. The failure rate decreases over t (labeled F in FIG. 11). The decrease in the failure rate is the same for accidental failures and wear-out failures, and the increase in the failure rate is, of course, the opposite.

The cost input means 14 inputs a standard cost for maintenance or repair of the equipment to be evaluated (cost input step). For example, failure recovery standard costs required for restoration (repair) in the event of equipment failure, maintenance standard costs required for preventive maintenance such as equipment monitoring and periodic overhaul, and equipment failure hindering production of the entire plant. Enter the estimated costs for the cases where explanations by the government offices and correspondence to the mass media are necessary. These standard costs are entered in unit prices, such as one-time maintenance or monitoring or annual costs, respectively.

The standard maintenance cost related to preventive maintenance of the equipment to be evaluated and the standard cost to recover from the failure of the equipment to be evaluated, which are input by the cost input means 14, are input by the operator by electronic means for each equipment to be evaluated. or populated from a database.

As shown in FIG. 12, the basic condition creation unit 15, for the equipment to be evaluated, specifies the equipment name, the equipment number, and other information about the equipment, information about the model to which the equipment belongs, and the failure rate input means 12. The reference value of the failure rate input from , the relationship between each of the maintenance method, maintenance method, and operation input from the maintenance characteristic input means 13 and the failure rate, and the maintenance standard for preventive maintenance input from the cost input means 14 Combining the cost, standard failure recovery cost in the event of a failure, and estimated cost required for production inhibition and government office explanation, etc., and defining the corresponding relationship as the basic condition for evaluation of the equipment to be evaluated (basic condition creation step). This basic condition defines the basis for the relationship between technical maintenance and failures, maintenance, failures and costs, and links the maintenance performed on the equipment under evaluation with its purpose, side effects and costs. become.

Note that the reference failure rate (reference value of failure rate) in the present embodiment is calculated using statistical means for each model. In addition, the effect on the failure rate of implementing a certain maintenance method is given as knowledge for each model. Therefore, these (reference failure rate, impact on failure rate) are information related to the model. On the other hand, since the impact of failure of the equipment to be evaluated is determined by the importance of the equipment in the plant, the amount of damage caused by production disruption, the cost of dealing with government agencies, etc. are specific to the equipment. In addition, the maintenance and repair costs of the equipment to be evaluated are also information related to the unit price of parts and work man-hours specific to the equipment (for example, even if the pump is the same model, it differs depending on the manufacturer, whether it is large or small). It is the information specific to the device determined by the specification.

Furthermore, the relationship between maintenance or operation, failure rate and maintenance cost is as follows. For example, by monitoring the operating state of the equipment to be evaluated, the failure rate can be reduced by early detection of abnormalities, but monitoring costs are incurred. On the other hand, in the overhaul inspection, since the replaced parts are returned to new ones, aging deterioration can be returned to the initial value, but early failures are induced due to work errors in disassembly and assembly. In addition, disassembly inspections incur costs, and there is a risk of incurring expenses for dealing with initial failures. Furthermore, by stopping the conventional monitoring of the operating status of equipment, it becomes impossible to detect abnormalities at an early stage. Failure rate may increase.

The operation/maintenance record input means 16 inputs the results regarding the operation and maintenance of the equipment to be evaluated (operation/maintenance record input step). The operation record and maintenance record of the equipment to be evaluated, which are input by the operation and maintenance record input means 16, are the contents and the date and time of implementation, and are input by the operator by electronic means or input from a database. be. These operation results and maintenance results are basically information managed by a maintenance ledger, a maintenance management system, or the like in a plant or the like.

The operation/maintenance schedule input unit 17 inputs a schedule regarding the operation and maintenance of the equipment to be evaluated (operation/maintenance schedule input step). The operation schedule and maintenance schedule for the equipment to be evaluated, which are input by the operation and maintenance schedule input means 17, are the contents and the date and time of the scheduled implementation, and are input by the operator by electronic means or from a database. is entered. These operation schedules and maintenance schedules are basically information managed as schedules in a plant or the like using a maintenance ledger, a maintenance management system, or the like.

The plotting means 18 inputs the operation and maintenance results of the equipment to be evaluated input from the operation and maintenance record input means 16, the operation and maintenance schedule of the equipment to be evaluated input from the operation and maintenance schedule input means 17, and the evaluation conditions input. Based on the conditions (described later) input from the means 19, the results (history) and schedule of the operation and maintenance (contents, dates) of the equipment to be evaluated are plotted in a process form with reference to the time axis (plot step). An example of this is shown in FIG.

The evaluation condition input means 19 inputs an evaluation period for evaluating the reliability and maintenance costs of the equipment to be evaluated, and furthermore, inputs the contents of operation and maintenance input from the operation/maintenance schedule input means 17 and schedules for implementation timing. Change (Evaluation condition input step). That is, the evaluation condition input means 19 designates the period for evaluating the reliability, maintenance cost, and failure recovery cost of the equipment to be evaluated, and changes the maintenance or operation schedule temporally arranged by the plotting means 18. Further, the basic conditions for calculating the failure rate time function, the maintenance cost time function, and the failure recovery cost expected value time function by the simulation means 20 are changed.

Furthermore, the evaluation condition input means 19 allows the operator to change at least one of the operation and maintenance schedules of the equipment to be evaluated arranged by the plotting means 18 . In the evaluation condition input means 19, the reference value of the failure rate of the equipment to be evaluated under the basic condition input from the basic condition creation unit 15 to the simulation means 20, the maintenance method, the maintenance method, the operation, and the failure rate. The operator can change the relationship, the maintenance standard cost for preventive maintenance of the evaluation target equipment, and the failure recovery standard 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 schedules input from the operation/maintenance result input means 16 and the operation/maintenance schedule input means 17. , Calculate the time function of the failure rate of the equipment to be evaluated and the time function of the maintenance cost based on the operation and maintenance results and schedule of the equipment to be evaluated, and calculate the expected value of the failure recovery cost as a function of time. (simulation step).

In other words, the simulation means 20 first refers to the corresponding relationship between the maintenance method, the maintenance method, and the operation created by the basic condition creation unit 15, the failure rate, and the cost. The failure rate time function (including the failure rate prediction time function) of the equipment to be evaluated, which is calculated based on the failure rate reference value, in accordance with the maintenance and operation results and schedules plotted based on Calculate and place. An example is shown below.

For example, when an overhaul is carried out and major parts are replaced with new ones, as shown in FIGS. A risk of early failure failure rate B) is induced. In addition, by monitoring the state of the equipment to be evaluated while it is in operation, it is possible to reduce the failure rate B of the initial failure as shown in FIG. 11 (symbol F in FIG. 11). The extent of this decrease fluctuates depending on the frequency of monitoring and the failure finding effect. This vertical width can be set by statistical evaluation or judgment by an engineer. This effect occurs for all initial failures, random failures, and wear-out failures.

FIG. 14 shows an example of calculating and arranging the time function of the failure rate with respect to the results and schedules of maintenance and operation plotted by the plotting means 18 in this way. In FIG. 14, past results (history) regarding operation and maintenance and time functions of failure rates with respect to schedules are calculated and arranged with the evaluation implementation point as a boundary. Symbol B is the failure rate of initial failures, symbol C is the failure rate of random failures, symbol D is the failure rate of wear-out failures, and symbol A is the sum of these (failure rate of the equipment to be evaluated). Naturally, the right side of the evaluation point is the predicted value. The reason why the estimation of the past failure rate is also calculated as an object of evaluation in this embodiment is that the influence of operation and maintenance performed in the past 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 effects remain at the time of evaluation. By changing the frequency of monitoring the operating state from once a month to twice a month at the time of this evaluation, the failure rate for all failures decreased from the time of the evaluation, and the frequency of overhauls was reduced, leading to early failures. It can be expected that the chance of occurrence of B will decrease.

Here, a calculation example of the relationship between the reference value of the failure rate and operation and maintenance will be shown below. Let λ(t) be the reference value of the failure rate time function. In the above-mentioned Weibull distribution, the failure rate of initial failure is maximum at λ(0) and monotonously decreases with the passage of time t, the failure rate of random failure is a constant value regardless of time t, and the failure rate of wear-out failure The rate is minimal at λ(0) and then increases monotonically with time t.

For example, if the operating state of the equipment to be evaluated is monitored, the possibility of discovering failures at the symptom stage increases, thereby reducing the failure rate. Regarding this, if the failure rate after the operating state monitoring is "after λ", then after λ(t) = coefficient × λ(t), the coefficient can be increased or decreased depending on the effectiveness and frequency of the failure rate of the operating state monitoring. , it is possible to express the effect of operating state monitoring. Further, when maintenance such as "main unit replacement" shown in FIG. In the form of returning to the value of t=0, it becomes possible to arrange and express the reference value of the failure rate with the above-described maintenance point as a starting point.

Further, the simulation means 20 refers to the corresponding relationship between the maintenance method, the maintenance method, and the operation created by the basic condition creation unit 15, the failure rate, and the cost, and the plotting means 18 makes reference to the time axis. In accordance with the plotted maintenance and operation records and schedules, the maintenance cost time function (including the maintenance cost prediction time function) of the equipment to be evaluated is calculated and arranged. An example is shown in FIG. As shown in FIG. 15, the maintenance cost is calculated on the time axis according to the implementation date. This makes the cost of preventive maintenance predictable. This can be achieved simply by assigning the unit price for overhaul inspections, and the unit price for each implementation period for operation status monitoring and daily inspections, according to the implementation of preventive maintenance. Naturally, when the frequency of monitoring the operating state of the equipment to be evaluated is increased, it is possible to calculate the corresponding price based on the unit price.

Furthermore, the simulation means 20 refers to the correspondence relationship between the failure rate calculated as described above, the maintenance method, the maintenance method, and the operation (operation) created by the basic condition creation unit 15, and the cost. , it becomes possible to calculate (predict) the time function of the expected value of the failure recovery cost of the equipment to be evaluated. Here, what is used to calculate the expected value of the failure recovery cost of the equipment to be evaluated is the repair cost in the event of a failure of the equipment to be evaluated included in the basic conditions created by the basic condition creation unit 15, the government report etc., and losses due to production inhibition. 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 weighted by the time function of the predicted failure rate calculated by the simulation means 20. It is calculated by adding For example, the time function of the expected value of the failure recovery cost is μ(t) × (repair cost, cost of responding to government reports, etc., production sum of losses due to inhibition). An example of the time function of the expected value of the failure recovery cost is shown as the expected value G of the failure recovery cost in FIG.

The display unit 21 displays the results and schedules of maintenance and operation temporally arranged by the plotting means 18, and the time function of the failure rate calculated and arranged by the simulation means 20 (including the predicted time function of the failure rate). ), the time function of the maintenance cost (including the time function of the maintenance cost prediction), and the time function of the expected value of the failure recovery cost are temporally displayed (display step).

With the configuration as described above, according to the first embodiment, the following effect (1) can be obtained.
(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 recovery cost, thereby It is possible to calculate (predict) the expected value of the failure rate, maintenance cost, and failure recovery cost of the equipment to be evaluated by selecting the methods and their frequencies. As a result, it is possible to select the optimum maintenance method that can improve the reliability of the facility and reduce the maintenance cost.

[B] Second embodiment (Figs. 17 to 24)
FIG. 17 is a block diagram showing the configuration of the device reliability and maintenance cost prediction device according to the second embodiment. In the second embodiment, parts similar to those in the first embodiment are denoted by the same reference numerals as those in the first embodiment to simplify or omit the description.

The equipment reliability and maintenance cost prediction device 25 shown in FIG. The difference due to the period is quantitatively evaluated, and mainly the configurations of the evaluation condition input means 26, the simulation means 27 and the cumulative evaluation means 28 are different from those of the first embodiment.

The evaluation condition input unit 26 changes the value of the basic condition created by the basic condition creating unit 15 and input to the simulation unit 27 based on the specified condition. The designated condition is which value is to be changed as a parameter and the range of change. Since the specified conditions include elements in which the standard failure rate (standard value of the failure rate) created by the basic condition creation unit 15, the influence of the maintenance method on the failure rate, and the standard maintenance cost are uncertain, The purpose is to provide prediction conditions including these.

For example, the following examples are conceivable for the parameters input by the basic condition creating unit 15 shown in FIG. That is, (a) considering the statistical uncertainty of the standard failure rate, two parameters of the Weibull distribution are specified as parameters to be varied, and the upper and lower limits and the step size are specifically given. (b) In order to take into consideration the uncertainty of the effect of the maintenance method (monitoring of the operating state), α of the "standard failure rate x α" shown in Fig. 12 is specified as a parameter to be changed and specifically Give its upper and lower bounds and step size. (c) In order to take into account future changes in labor costs and repair parts purchase costs, the relevant values in the standard maintenance costs are specified as parameters to be changed, and upper and lower limits and increments are specifically given.

Although the above is only an example, the center value of the parameter to be changed may be given instead of the upper and lower limits of the parameter to be changed. Also, when there are multiple parameters to be changed, the designated condition is the method of combination. The method of this combination is to round-robin the range of variation for each of the plurality of parameters, or to perform some of them.

When the condition to be changed is related to maintenance or maintenance schedule, the evaluation condition input means 26 changes the information (period, scheduled date) related to the schedule for the designated maintenance or maintenance, and the plotting means 18 changes the maintenance schedule. The plot changes according to the information about the maintenance schedule and the maintenance schedule. For example, when changing the cycles of overhaul inspection, daily inspection, monitoring of operating conditions, and oil replenishment of the equipment to be evaluated, an upper limit, a lower limit, and a step size are given in the range of change of these cycles, and the "scheduled" in FIG. Varying these plots of parts. For example, when giving the due date of the overhaul, the plot of the "scheduled" part in FIG. 13 is changed according to the due date.

The simulation means 27 calculates a failure rate prediction time function in the same manner as in the first embodiment for each of the "plans" plotted according to the upper and lower limits, the step size, and the scheduled date. , the time function of the maintenance cost prediction is calculated, and the time function of the expected value of the failure recovery cost is calculated (predicted). 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 plotting means 18 plots the changes. FIG. 19 shows an example in which the simulation means 27 calculates the failure rate prediction time function, and FIG. 20 shows an example in which the maintenance cost prediction time function and the expected failure recovery cost time function are calculated. each shown.

The simulation means 27 comprise cumulative evaluation means 28 . When the cycles of overhaul inspection, daily inspection, monitoring of operating conditions, and oil replenishment of the equipment to be evaluated are to be changed, the cumulative evaluation means 28 is configured to: For each of the plotted "plans", the failure rate prediction time function, the maintenance cost prediction time function, and the failure recovery cost expected value time function output from the simulation means 27 are obtained during the evaluation period. The cumulative failure rate, the cumulative maintenance cost, and the expected cumulative failure recovery cost are obtained by integration, and these cumulative values and the values of the basic conditions at that time are set. As a result, basic conditions vs. cumulative failure rate, It becomes possible to obtain the accumulated maintenance cost and the expected accumulated failure recovery cost. By displaying this on the display unit 21, a failure rate cumulative value L, a maintenance cost cumulative value M, and a failure recovery cost cumulative expected value N are evaluated as shown in FIG. It becomes possible to search for a basic condition that optimizes .

In FIG. 21, three cumulative values (failure rate cumulative value L, maintenance cost cumulative value M, failure recovery cost cumulative expected value The value N) is obtained on the vertical axis. Note that the change range of the overhaul inspection period is not limited to the one that can be changed continuously by the upper limit, the lower limit, and the step size as described above, and may be discontinuous values or items.

If the basic conditions to be changed by the evaluation condition input means 26 affect the failure rate, the maintenance cost unit price, etc., the simulation means 27 predicts the failure rate, the maintenance cost, and the expected value of the failure recovery cost. The calculation method of the time function is adjusted. Based on these time functions, the cumulative evaluation means 28 calculates the failure rate cumulative value, the maintenance cost cumulative value, and the failure recovery cost cumulative expected value in the same manner as described above, and compares the changed basic conditions and each cumulative value with are set and displayed on the display unit 21, it becomes possible to evaluate each cumulative value and search for conditions that optimize them.

For example, when the operating state monitoring method is changed, as described in the first embodiment, if the failure rate after monitoring is "after λ", then after λ (t) = coefficient × λ (t). The factor can be increased or decreased depending on the monitoring method (the effectiveness of the method for anomaly detection). Also, the maintenance cost can be calculated from the unit price and the failure rate for each monitoring method, as described in the first embodiment.

22 and 23 are examples in which the simulation means 27 predicts the time function of the failure rate and the time function of the maintenance cost using two condition monitoring methods with different effects and costs. As shown in FIG. 22, the simulation means 27 expresses the effects of the two condition monitoring methods by changing the coefficients by the above-described method, calculates the time function of the failure rate prediction, and calculates the time function of the failure rate prediction. It expresses that the condition monitoring method 1 has a lower failure rate. On the other hand, as shown in FIG. 23, the simulation means 27 calculates a time function for predicting maintenance costs based on the prediction result of the failure rate in FIG. .

The cumulative evaluation means 28 changes the above-mentioned coefficients when the frequency of monitoring is changed between the state monitoring method 1 and the state monitoring method 2 (increasing the monitoring frequency makes it possible to detect failures at an early stage). (because the failure rate decreases, the coefficient is decreased), and the resulting increase in maintenance cost (which is, of course, a multiple of the unit price) is integrated by the above method, respectively, to obtain the cumulative maintenance cost. value can be calculated. An example of this is shown in FIG. This FIG. 24 shows the failure rate cumulative value L, the maintenance cost cumulative value M, and the failure recovery cost cumulative expected value for the monitoring cycle when only the monitoring cycle is changed in the state monitoring methods 1 and 2, and all other conditions are the same. It compares the value N.

With the configuration as described above, the second embodiment has the following effect (2).
(2) When the maintenance method or maintenance method is changed, the simulation means 27 calculates a failure rate prediction time function, a maintenance cost prediction time function, and an expected failure recovery cost time function, and accumulates them. The evaluation means 28 calculates a failure rate cumulative value, a maintenance cost cumulative value, and a failure recovery cost cumulative expected value. Therefore, the optimum maintenance method and maintenance method can be selected by comparing each of the above time functions according to changes in the maintenance method or maintenance method and by comparing each of the above cumulative values.

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

The equipment reliability and maintenance cost prediction device 30 shown in FIG. Quantitatively evaluate the difference due to the cycle, or compare the failure rate prediction time function, maintenance cost prediction time function, failure recovery cost expected value time function, or evaluation target It predicts the reliability of the system or system to which the equipment belongs, the reliability of each model to which the equipment to be evaluated belongs and the division in charge, and maintenance costs and failure recovery costs. The configuration of means 32 is different from that of the first embodiment.

The evaluation target setting means 31 designates and sets a plurality of devices to be evaluated. At this time, classification information including the model of the device is also entered as necessary. Here, the simulation means 20 calculates a failure rate prediction time function and a maintenance cost prediction time function for each of the plurality of designated devices to be evaluated in the same manner as in the first embodiment, Calculate (predict) the time function of the expected value of the failure recovery cost.

The simulation means 20 comprise cumulative evaluation means 32 . The cumulative evaluation means 32 superimposes the failure rate prediction time function, the maintenance cost prediction time function, and the failure recovery cost expected value time function for each of the plurality of devices to be evaluated on the basis of the time axis. to display on the display unit 21. As a result, it becomes possible to compare failure rates, maintenance costs, etc. of a plurality of devices to be evaluated, and to compare the priority of maintenance implementation for a plurality of devices to be evaluated.

In addition, the cumulative evaluation means 32 calculates the time function of the prediction of the maintenance cost and the time function of the expected value of the failure recovery cost for each of the plurality of evaluation target equipment set by the evaluation target setting means 31, with respect to the time axis. may be summed up in This makes it possible to predict the expected values of maintenance costs and failure recovery costs in the category of the entire plant and the category of the entire equipment that a certain section is in charge of.

With the configuration as described above, the third embodiment has the following effect (3).
(3) The cumulative evaluation means 32 calculates the failure rate prediction time function, the maintenance cost prediction time function, and the failure recovery cost expectation calculated for each of the plurality of evaluation target devices set by the evaluation target setting means 31. Each of the time functions of the value is superimposed on the time axis and displayed. Display the sum based on the axis. As a result, it is possible to compare and set the priority of maintenance implementation for multiple devices to be evaluated, and to reduce the maintenance cost for the entire plant including multiple devices to be evaluated and for the entirety of multiple devices to be evaluated. can be predicted.

[D] Fourth embodiment (Figs. 26 to 29)
FIG. 26 is a block diagram showing the configuration of the device reliability and maintenance cost prediction device according to the fourth embodiment. In the fourth embodiment, the same parts as in the first embodiment are denoted by the same reference numerals as those in the first embodiment, thereby simplifying or omitting the description.

The equipment reliability and maintenance cost prediction device 40 shown in FIG. 26 is a high-level concept to which the equipment to be evaluated belongs when appropriately determining equipment maintenance methods and maintenance methods in facilities such as plants and large-scale transportation systems. It evaluates the reliability of a certain system, system, equipment, plant, or the entire large-scale transportation system (hereinafter referred to as the system), and mainly includes evaluation object setting means 41, evaluation condition input means 42, and cumulative evaluation means. 43 differs from the first embodiment.

The evaluation target setting means 41 designates and sets a plurality of evaluation target devices belonging to any of the higher concept systems whose reliability is to be evaluated. At this time, classification information including the model of the device is also entered as necessary. Also, in a plant or the like, a plurality of devices are specified without omission based on, for example, an equipment ledger, an EAM system, or the like. The simulation means 20 calculates a time function for failure rate prediction for a plurality of evaluation target devices specified here by the same method as in the first embodiment.

The evaluation condition input unit 42 stores and sets a calculation formula (system reliability evaluation formula) for calculating an operating rate, which is an index of system reliability, in the cumulative evaluation unit 43 provided in the simulation unit 20 . This calculation formula is input with time functions of failure rate predictions for a plurality of devices to be evaluated, and the cumulative evaluation means 43 calculates the time functions of operating rates for each time according to the above calculation formula. When the time function of failure rate prediction for each of the multiple devices to be evaluated is λ1(t), λ2(t), λ3(t), λ4(t), . . . λn(t), the above formula is These λ1(t), λ2(t), λ3(t), λ4(t) . For example, by using reliability engineering knowledge, it becomes possible to predict the reliability (availability) of the entire system as a formula that combines time functions for predicting the failure rate of multiple devices to be evaluated. .

As shown in FIG. 27, equipment 1, equipment 2, and equipment 3 are connected in series, and when each of them is normal, the system is normal as a system. Then, R(t)=(1-λ1(t))(1-λ2(t))(1-λ3(t)). Also, as shown in FIG. 28, if the device 1, the device 2, and the device 3 are connected in parallel and the system is normal when any one of them is normal, the overall system at a certain time t is If the operating rate is R1(t), then R1(t)=1−λ1(t)λ2(t)λ3(t).

In this way, in the fourth embodiment, the knowledge of reliability engineering is easily incorporated into the actual equipment, and the reliability (operating rate) of the system is evaluated as a function of time. becomes possible. This concept is illustrated in FIG. Input is the time function of failure rate prediction for each of the devices to be evaluated, and output is the operating rate, which is an indicator of the reliability of the entire system. Changes in this operating rate can be used to evaluate the timing of inputting maintenance resources.

With the configuration as described above, the fourth embodiment has the following effect (4).
(4) The evaluation condition input unit 42 sets the calculation formula (system reliability evaluation formula) for calculating the operating rate, which is an index of system reliability, in the cumulative evaluation unit 43 . Based on the system reliability evaluation formula, the cumulative evaluation means 43 receives as input the failure rate prediction time function for each of the plurality of evaluation target equipment set by the evaluation target setting means 41, and is composed of the plurality of evaluation target equipment. The system reliability (availability) is predicted and evaluated as a function of time. For this reason, it is possible to consider the optimum maintenance, including the implementation timing, in the above system.

Although several embodiments of the invention have been described above, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be embodied in various other forms, and various omissions, replacements, changes, combinations can be made without departing from the spirit of the invention. Modifications and combinations are included in the scope and gist of the invention, as well as the invention described in the claims and the scope of equivalents thereof.

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 Result input means 17 Operation/maintenance schedule input means 18 Plot means 19 Evaluation condition input means 20 Simulation means 21 Display unit 25 Equipment reliability and maintenance cost prediction device 26 Evaluation conditions Input means 27 Simulation means 28 Cumulative evaluation means 30 Equipment reliability and maintenance cost prediction device 31 Evaluation object setting means 32 Cumulative evaluation means 40 Equipment reliability and maintenance cost prediction device , 41... Evaluation object setting means, 42... Evaluation condition input means, 43... Cumulative evaluation means

Claims (16)

an evaluation target setting means for designating and setting equipment to be evaluated for reliability, maintenance costs, and failure recovery costs in equipment;
failure rate input means for inputting a reference value of failure occurrence probability and failure rate for each failure mode of the equipment;
maintenance characteristic input means for inputting the relationship between each of the maintenance method, maintenance method, and operation of the equipment and the failure rate;
cost input means for inputting a maintenance standard cost for preventive maintenance of said equipment and a failure recovery standard cost required for recovery when a failure occurs in said equipment;
a basic condition creation unit that creates a basic condition for evaluating the device by combining the input values input from the input means;
operation and maintenance record input means for inputting the record of operation and maintenance of the equipment;
operation and maintenance schedule input means for inputting operation and maintenance schedules for the equipment;
plotting means for temporally arranging the performance and the schedule of operation and maintenance of the equipment;
Each value in the basic condition, the operation and maintenance result input means, and the operation and maintenance result and the schedule input by the operation and maintenance schedule input means are input, and the operation and maintenance result of the equipment are input. and a simulation means for calculating the time function of the failure rate of the equipment based on the schedule and the time function of the maintenance cost, and calculating the expected value of the failure recovery cost as a time function and arranging it temporally;
Designate a period for evaluating the reliability, maintenance costs, and failure recovery costs of the equipment, change the schedule of maintenance or operation temporally arranged by the plotting means, and further use the simulation means to evaluation condition input means for changing the basic conditions for calculating 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;
The results and schedules of maintenance and operation temporally arranged 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 failure recovery cost and a display for temporally displaying at least one of expected value time functions. 2. The equipment reliability and maintenance cost prediction according to claim 1, wherein when the equipment to be evaluated is set by the evaluation object setting means, the model to which the equipment belongs can be specified. Device. The reference value of the failure rate input by the failure rate input means is input by an operator by electronic means, or a time function of the failure rate for each failure type preset for each model is stored. 3. The equipment reliability and maintenance cost prediction apparatus according to claim 1, wherein the input is from a database. The relationship between each of the maintenance method, maintenance method, and operation of the equipment input by the maintenance characteristic input means and the failure rate is determined by the maintenance method, the maintenance method, and the operation, which are given to the failure rate of the equipment. It is characterized in that the operator inputs how the reference value of the failure rate changes depending on the influence by electronic means or inputs from a database in which the relationship is set in advance for each model. 4. The equipment reliability and maintenance cost prediction apparatus according to any one of claims 1 to 3. The standard maintenance cost for preventive maintenance of the equipment and the standard cost for restoration from failure in the equipment to be input by the cost input means are input by the operator by electronic means for each equipment, or 5. A device reliability and maintenance cost prediction device according to any one of claims 1 to 4, wherein the input is from a database. The basic condition created by the basic condition creation unit combines information about the equipment, such as the equipment name and equipment number that identify the equipment, and information about the model to which the equipment belongs. 6. The equipment reliability and maintenance cost prediction apparatus according to any one of claims 1 to 5, characterized in that it is constructed so as to create a basic condition by combining information related to the model to which the equipment belongs. The operation record and maintenance record of the equipment input to the operation and maintenance record input means are the content and the date and time of implementation, and the operation schedule and maintenance record of the equipment input by the operation and maintenance schedule input means. The schedule is the content and the date and time of the schedule to be implemented, and these operation results, maintenance results, and operation schedule and maintenance schedule are input by the operator by electronic means, or are input from a database. 7. The device reliability and maintenance cost prediction device according to any one of claims 1 to 6, wherein: The plotting means is characterized in that it plots the operation and maintenance results, schedule contents, and time inputted by the operation/maintenance result input means and the operation/maintenance schedule input means on the basis of the time axis. Equipment reliability and maintenance cost prediction apparatus according to any one of claims 1 to 7. The simulation means calculates the time function of the failure rate of the equipment based on the basic conditions created by the basic condition creation unit in accordance with the results and schedules of maintenance and operation plotted on the basis of the time axis by the plotting means. 9. The equipment reliability and maintenance cost prediction apparatus according to claim 8, wherein the equipment reliability and maintenance cost prediction apparatus is configured to: The simulation means calculates a time function of maintenance costs based on the basic conditions created by the basic condition creation unit in accordance with the results and schedules of maintenance and operation plotted on the basis of the time axis by the plotting means, 10. The equipment reliability and maintenance cost prediction apparatus according to claim 9, wherein the equipment reliability and maintenance cost prediction apparatus is configured to calculate a time function of an expected value of failure recovery cost based on the calculated equipment failure rate and the basic conditions. In the evaluation condition input means, the operator can change at least one of the operation and maintenance schedules of the equipment arranged in the plotting means. The reference value of the failure rate of , the relationship between each of the maintenance method, maintenance method, and operation and the failure rate, the maintenance standard cost for preventive maintenance of the equipment, and the failure recovery standard cost when the equipment fails 11. The equipment reliability and maintenance cost prediction apparatus according to any one of claims 1 to 10, wherein the operator can change the above. the simulation means comprises cumulative evaluation means;
The evaluation condition input means changes the value of the basic condition created by the basic condition creation unit based on the specified condition, the plotting means plots each of the values on the time axis, and based on the result the simulation means calculates a time function of equipment failure rate prediction, a maintenance cost prediction time function, and an expected failure recovery cost time function, and outputs each of these time functions to the cumulative evaluation means;
The cumulative evaluation means integrates the time function of the failure rate prediction, the time function of the maintenance cost prediction, and the time function of the expected value of the failure recovery cost in an evaluation period to obtain a cumulative failure rate and a cumulative maintenance cost. , the cumulative expected value of failure recovery cost is obtained, these cumulative values and the value of the basic condition at that time are set, and the value of the changed basic condition is used as an axis to calculate the cumulative failure rate value, the cumulative maintenance cost value, 12. The device reliability according to any one of claims 1 to 11, wherein at least one of the cumulative expected values of failure recovery costs is arranged in a graph and superimposed on a display unit. and maintenance cost predictor. The evaluation target setting means sets a plurality of devices, and the simulation means calculates a failure rate prediction time function, a maintenance cost prediction time function, and a failure recovery cost expected value time function for the plurality of devices. ,
The cumulative evaluation means included in the simulation means sets the time axis for each of the failure rate prediction time function, the maintenance cost prediction time function, and the failure recovery cost expected value time function for the plurality of devices. 12. The equipment reliability and maintenance cost prediction device according to claim 1, wherein the equipment reliability and maintenance cost prediction device is configured to be superimposed on the reference and displayed on the display unit. The evaluation target setting means sets a plurality of devices, and the simulation means calculates a time function of prediction of maintenance cost and a time function of expected value of failure recovery cost for the plurality of devices,
The cumulative evaluation means included in the simulation means totals the time function of the prediction of the maintenance cost and the time function of the expected value of the failure recovery cost in the plurality of devices based on the time axis, and displays them on the display unit. 12. The equipment reliability and maintenance cost prediction apparatus according to any one of claims 1 to 11, wherein the equipment reliability and maintenance cost prediction apparatus is configured to The evaluation target setting means sets a plurality of devices, and the evaluation condition input means sets a calculation formula, in which a time function for predicting failure rates of the plurality of devices is input, to the cumulative evaluation means provided in the simulation means,
According to the formula, the cumulative evaluation means calculates the time function of the operating rate, which is the result of calculation with the time function of predicting the failure rate of the equipment as input, and displays the time function of the operating rate on the display unit. 12. The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 11, wherein the equipment reliability and maintenance cost prediction device is configured as follows. an evaluation target setting step of designating and setting equipment to be evaluated for reliability, maintenance costs, and failure recovery costs in equipment;
a failure rate input step of inputting a failure occurrence probability and a reference value of a failure rate for each failure mode of the equipment;
a maintenance characteristic input step of inputting the relationship between each of the maintenance method, maintenance method, and operation of the equipment and the failure rate;
a cost inputting step of inputting a maintenance standard cost for preventive maintenance of the device and a failure recovery standard cost required for recovery when a failure occurs in the device;
a basic condition creation step of creating a basic condition for evaluating the device by combining each input value input from each of the input steps;
an operation and maintenance record input step of inputting the record of operation and maintenance of the equipment;
an operation and maintenance schedule input step of inputting a schedule for operation and maintenance of the equipment;
a plotting step of temporally arranging the performance and schedule of operation and maintenance of the equipment;
inputting each value in the basic conditions, the actual results and schedule of operation and maintenance input in the operation and maintenance result input step and the operation and maintenance schedule input step, and the operation and maintenance result of the equipment; and a simulation step of calculating the time function of the failure rate of the equipment based on the schedule and the time function of the maintenance cost, and calculating the expected value of the failure recovery cost as a time function and arranging it temporally;
Designating a period for evaluating the reliability, maintenance costs, and failure recovery costs of the equipment, changing the schedule of maintenance or operation arranged in time in the plotting step, and further, in the simulation step, an evaluation condition input step of 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;
The results and schedules of maintenance and operation temporally arranged in the plotting step, the time function of the failure rate calculated and arranged by the simulation means, the time function of the maintenance cost, and the failure recovery cost and a display step of temporally displaying at least one of the expected value time functions.

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