Equipment reliability and maintenance cost prediction device and equipment reliability and maintenance cost prediction method

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]

[0001] An embodiment of the present invention relates to an equipment reliability and maintenance cost prediction device for predicting the reliability and maintenance cost of equipment, and an equipment reliability and maintenance cost prediction method. [Background technology]

[0002] 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 by JIS and other standards, there are three types of maintenance methods for equipment maintenance: time-planned maintenance (TBM), which involves periodic overhaul inspections, condition-based maintenance (CBM), which involves observing parameters related to the deterioration and failure of the equipment and overhauling it according to its condition, and corrective maintenance (BDM), which involves repairs when a failure is found in the equipment or when a loss of function occurs. 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.

[0003] Traditionally, various attempts have been made to determine the optimal method for maintenance. For example, in the US aviation industry and military, a huge number of machine parts have been surveyed for failures and deterioration, and a time-varying failure rate curve has been obtained, and based on this, the most appropriate maintenance method is considered. As a result, it has been revealed that TBM induces so-called tinkering with most machine 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, CBM has been introduced 30 to 40 years ago, mainly in the steel and chemical industries.

[0004] However, in the current maintenance of domestic nuclear power plants, TBM is used to overhaul and inspect most of the equipment at set intervals as preventive maintenance, and most of these overhauls are carried out during regular plant inspections. With TBM, the overhaul interval must be set very short compared to the original equipment lifespan, resulting in over-maintenance and high maintenance costs. In addition, overhauls are carried out regardless of the deterioration of the equipment, which means that equipment that is not deteriorated is prone to breakage during the disassembly and assembly process. In addition, many tasks are carried out during regular inspections over a period of several months, which makes the process complicated and prone to problems. In addition, the regular inspection process cannot be shortened, making it difficult to improve the plant operation rate.

[0005] Because of this awareness, attempts are being made to optimize maintenance methods, including reliability-based 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 extensions that do not result in over-maintenance.In addition, the inspection system for nuclear power plants requires a "maintenance effectiveness evaluation" (JEAC4209, JEAG4210) that evaluates and reviews the TBM cycle and method, the applicability of CBM, etc., based on actual data.

[0006] This maintenance effectiveness evaluation evaluates whether the maintenance that maintains the function of the 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 the maintenance is being performed effectively, but if the maintenance record is deemed good and the TBM cycle such as overhaul inspection is deemed to have a margin for the deterioration rate of the equipment, the cycle can be extended. For example, the time trend of the change in the amount of wear of parts obtained from each overhaul inspection of a certain piece of equipment is evaluated, and it is determined that the current overhaul inspection cycle is short enough by the time the amount of wear reaches the failure criterion, and that various failures have not occurred for a long period of time, and the overhaul inspection cycle is extended. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Patent No. 6733004 [Patent Document 2] International Publication No. 2008 / 155982 Summary of the Invention [Problem to be solved by the invention]

[0008] On the other hand, attempts have been made 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, the maintenance status of the entire plant or multiple equipment can be judged from a statistical point of view 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, the conditions can be improved to reduce the failure rate. As a method for carrying out this evaluation with high accuracy, a method of analyzing the causes of failure by dividing them into aging deterioration (wear-out failures) and human error, etc. is proposed in Patent Document 1.

[0009] Patent Document 2 also proposes a method for examining optimal maintenance management by simulating predictions of reliability and costs based on the recovery of performance and degraded state through subsequent maintenance, based on the estimated results of performance and degraded state from the results of signal monitoring for each piece of equipment. According to this method, it becomes possible to predict the optimal maintenance method by searching for the optimal point between the increase in cost and the increase in reliability resulting from increasing the frequency of maintenance.

[0010] In the aforementioned maintenance effectiveness evaluation, the transition of data from multiple overhaul inspections over a period of several years to several decades is generally evaluated, and if it is determined that the current TBM cycle has a sufficient margin for the rate of deterioration, a decision is made to extend the cycle or transition to CBM. However, there are no quantitative evaluation criteria for clarifying this judgment, such as an evaluation of the reliability of the equipment after the change, expected maintenance costs, or expected failure recovery costs, and for this reason, the cycle has not been extended or transition to CBM has not been made. In particular, it is difficult to determine what the cycle should be after the change.

[0011] In addition, accurate evaluation of 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 the reliability of the equipment after the change, the expected maintenance costs, the expected failure recovery costs, etc., and for this reason, the extension of the cycle and the transition to CBM have not been carried out. In particular, it is similarly 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 failure recovery costs based on the overall failure rate prediction, it will not serve as a guide for selecting the optimal maintenance method and frequency.

[0012] The embodiments of the present invention have been made in consideration of the above-mentioned circumstances, and have an object to provide an equipment reliability and maintenance cost prediction device and an equipment reliability and maintenance cost prediction method that are capable of selecting a maintenance method that can improve facility reliability and reduce maintenance costs. [Means for solving the problem]

[0013] The equipment reliability and maintenance cost prediction device 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 of a failure occurrence probability and a failure rate for each failure mode of the equipment, a maintenance characteristic input means for inputting a relationship between the maintenance method, the maintenance method, and the operation of the equipment and the failure rate, a cost input means for inputting a standard maintenance cost related to preventive maintenance of the equipment and a standard failure recovery cost required for recovery when a failure occurs in the equipment, a basic condition creation unit for creating basic conditions for evaluation of the equipment by combining each input value input from each of the input means, an operation and maintenance result input means for inputting the operation and maintenance results of the equipment, an operation and maintenance schedule input means for inputting a schedule for operation and maintenance of the equipment, a plotting means for arranging the operation and maintenance results and the schedule in time, and a plotting unit for plotting each value in the basic condition and the values ​​input by the operation and maintenance result input means and the operation and maintenance schedule input means. and a simulation means for 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 the operation and maintenance of the equipment, and calculating an expected value of the failure restoration cost as a time function and arranging them over time; an evaluation condition input means for specifying a period for evaluating the reliability, maintenance cost, and failure restoration cost of the equipment, changing the maintenance or operation schedule arranged over 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 restoration cost are calculated by the simulation means; and a display unit for displaying over time at least one of the results and the schedule of maintenance and operation arranged over time by the plotting means, 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 restoration cost calculated and arranged by the simulation means.

[0014] The method for predicting reliability and maintenance costs of equipment in an embodiment of the present invention is to estimate the reliability, maintenance costs, and failure recovery costs of equipment in a facility. The evaluation target setting means isA step of specifying and setting an evaluation target, and setting a reference value of a failure occurrence probability and a failure rate for each failure mode of the equipment Failure rate input means A failure rate input step for inputting a failure rate, and a relationship between the maintenance method, maintenance method, and operation of the equipment and the failure rate Maintenance characteristic input means A maintenance characteristic input step for inputting a standard maintenance cost for preventive maintenance of the equipment and a standard failure recovery cost required for recovery when a failure occurs in the equipment are input. Cost input method is The cost input step to be entered, The basic condition creation unit: A basic condition creation step of creating basic conditions for evaluating the equipment by combining the input values ​​input from each of the input steps; Operation and maintenance performance input means An operation and maintenance record input step for inputting operation and maintenance schedules for the equipment Operation and maintenance schedule input method An operation and maintenance schedule input step for inputting the results and schedule of the operation and maintenance of the equipment. Plotting method Plot steps arranged in time; The simulation means is a simulation step of inputting each value within the basic conditions and the operation and maintenance results and plans input in the operation and maintenance result input step and the operation and maintenance plan input step, calculating a time function of the failure rate of the equipment based on the operation and maintenance results and the plan, and a time function of the maintenance cost, and calculating an expected value of a failure restoration cost as a time function and arranging them in time; The evaluation condition input means An evaluation condition input step of specifying a period for evaluating the reliability, maintenance cost, and failure recovery cost of the equipment, and changing the schedule of the maintenance or operation arranged in time in the plot step, 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 in the simulation step; Steps At least one of 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 display and a display step of displaying the information in a time sequence. Effect of the Invention

[0015] According to an embodiment of the present invention, it is possible to select a maintenance method that can improve the reliability of equipment and reduce maintenance costs. [Brief description of the drawings]

[0016] [Figure 1] 1 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a first embodiment. [Diagram 2] 2 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; [Diagram 3] 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. [Figure 4] 2 is a table showing an example of failure rates for each failure mode (failure form) of the device to be evaluated, which are inputted via the failure rate input means of FIG. 1; [Diagram 5] 2 is a table showing an example of a case where the failure rate of the evaluation target device is set for each component part by the failure rate input means of FIG. 1. [Figure 6] 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. [Figure 7] 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 in FIG. 1 and the failure rate. [Figure 8] 2 is a graph showing an example of a reference value of the failure rate inputted by the failure rate input means of FIG. 1; [Figure 9] 9 is a graph showing the relationship between the early failure rate and the maintenance method shown in FIG. 8 . [Figure 10] 9 is a graph showing the relationship between the wear-out failure rate and the maintenance method in FIG. 8. [Figure 11] 9 is a graph showing that the early failure rate of FIG. 8 is reduced by the maintenance method. [Figure 12]A chart showing an example of the equipment to be evaluated, its failure rate reference value (reference failure rate), maintenance method, the effect of the maintenance method on the failure rate, standard maintenance costs, etc., created by the basic condition creation unit in Figure 1. [Figure 13] FIG. 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. [Figure 14] 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. [Figure 15] 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. [Figure 16] 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 in accordance with the maintenance and operation results and schedule plotted on a time axis. [Figure 17] FIG. 11 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a second embodiment. [Figure 18] 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 plotting means plots the cycle. [Figure 19] FIG. 18 is an explanatory diagram showing an example in which the simulation means in FIG. 17 calculates a time function of a predicted failure rate in response to a change in a scheduled cycle of maintenance (overhaul inspection). [Figure 20] 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). [Figure 21] 18 is a graph showing an example of a cumulative failure rate value, a cumulative maintenance cost value, and an expected cumulative failure restoration cost value calculated by the cumulative evaluation means in FIG. 17, with the scheduled cycle of maintenance (disassembly and inspection) plotted on the horizontal axis. [Figure 22] FIG. 18 is an explanatory diagram showing, in comparison, an example of a time function of a predicted failure rate calculated by the simulation means of FIG. 17 according to a maintenance (condition monitoring) method having a different effect. [Figure 23] 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. [Figure 24] 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 condition monitoring cycle on the horizontal axis based on the difference in effect and cost between two condition monitoring methods, using the simulation means of FIG. 17 . [Diagram 25] FIG. 11 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a third embodiment. [Figure 26] FIG. 13 is a block diagram showing the configuration of an equipment reliability and maintenance cost prediction device according to a fourth embodiment. [Figure 27] 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. [Figure 28] FIG. 27 is a block diagram showing a case where a plurality of devices set by the evaluation target setting means in FIG. 26 are connected in parallel. [Figure 29] FIG. 27 is an explanatory diagram for explaining the improvement of maintenance by the cumulative evaluation means in FIG. 26 calculating and predicting a time function of the availability rate, which is an index of the reliability of the system, from the failure rates of a plurality of devices. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] 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 appropriately determines the maintenance method and maintenance system of equipment in facilities such as a plant or a large-scale transportation system, and includes evaluation target setting means 11, failure rate input means 12, maintenance characteristic input means 13, cost input means 14, basic condition creation unit 15, operation and maintenance performance input means 16, operation and maintenance schedule input means 17, plotting means 18, evaluation condition input means 19, simulation means 20, and display unit 21.

[0018] The evaluation target setting means 11 specifies and sets evaluation target equipment, which is equipment that is the subject of evaluation of reliability, maintenance cost, and failure recovery cost in 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 or the like, these pieces of equipment and models are basically information managed in an equipment ledger, equipment management system, or the like. An example of this is shown in FIG. 2.

[0019] The failure rate input means 12 inputs the probability of failure and the reference value of the failure rate as a time function 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 in which the time function of the failure rate for each failure type set in advance for each model is stored.

[0020] Here, the failure modes are classified into three categories, namely, initial failure, random failure, and wear-out failure, and the failure rates of each are input. An example of this is shown in FIG. 3. In addition, 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 the 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, and an example of this is 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 in a power plant, factory, etc. where the evaluation target equipment is located.

[0021] The example in Figure 6 is an example of subdividing, within an identifiable range, the failure modes that lead to loss of function of the evaluation target equipment shown in Figure 4. As shown in this 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 random failures, and deterioration during normal use is wear-out failures.

[0022] The maintenance characteristic input means 13 inputs the relationship between the maintenance method, maintenance method, operation of the evaluation target device and the failure rate of the failure type (maintenance characteristic input step). The relationship between the maintenance method, maintenance method, operation of the evaluation target device and the failure rate of the failure type input by this maintenance characteristic input means 13 is input by an operator by electronic means, indicating how the reference value of the failure rate changes depending on the influence of each of the maintenance method, maintenance method, and operation on the failure rate of the evaluation target device, or is input from a database in which the relationship is set in advance for each model.

[0023] Here, the relationship between the maintenance method, the maintenance method, the operation, and the failure rate of the failure type refers to the influence of various maintenance methods, the maintenance methods, and the operation of the evaluation target equipment 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) Recovery by periodic 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, and (f) Stopping the progress of wear by stopping operation. 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 will be explained below.

[0024] 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 (aging deterioration) are affected by each maintenance method, maintenance method, and operation. The meaning of Figure 7 is as follows.

[0025] 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.

[0026] Here, FIG. 9 is a conceptual explanation of the induction of early failures by the maintenance method 1 (disassembly and inspection) illustrated in FIG. 7. As shown in FIG. 9, the implementation of the 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 recovery of wear-out failures by the maintenance method 1 illustrated in FIG. 7, in which the failure rate D of wear-out failures returns to its initial value (the value at t=0, which is the reference value of the failure rate) by the implementation of the maintenance method 1. FIG. 11 is a conceptual explanation of the decrease in the failure rate B of early failures by the maintenance method 2 (monitoring the operating state of the equipment) illustrated in FIG. 7, in which the failure rate decreases over the entire time t with respect 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 with respect to this decrease in failure rate, and the increase in failure rate naturally changes in the opposite direction.

[0027] The cost input means 14 inputs standard costs for the maintenance or repair of the equipment to be evaluated (cost input step). For example, the standard failure recovery cost required for recovery (repair) when a failure occurs in the equipment, the standard maintenance cost required for preventive maintenance such as monitoring the equipment and regular overhaul inspection, and the expected cost in the case where an equipment failure leads to production interruptions in the entire plant or where 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.

[0028] The standard maintenance costs for preventive maintenance of the equipment being evaluated and the standard costs for recovery from a failure when a failure occurs in the equipment being evaluated, which are input by this cost input means 14, are input by an operator by electronic means for each equipment being evaluated or are input from a database.

[0029] 12, the basic condition creating unit 15 combines, for the evaluation target equipment, the equipment name, equipment number, and other equipment information that identifies the equipment, the information on the model to which the equipment belongs, the reference value of the failure rate 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, the standard cost for failure recovery when a failure occurs, and the expected cost required for production interruption and explanation to government agencies, etc. input from the cost input means 14, and defines the correspondence between them as the basic conditions for the evaluation of the evaluation target equipment (basic condition creating step). This basic condition defines the basis of the relationship between technical maintenance and failure, and the relationship between maintenance, failure, and cost, and links the maintenance performed on the evaluation target equipment with its purpose, side effects, and cost.

[0030] In this embodiment, the reference failure rate (reference value of failure rate) is calculated by using statistical means for each model. In addition, the impact on the failure rate of a certain maintenance method by implementing that 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 evaluation target device breaks down is determined by the importance of the device in the plant, so the damage amount of production interruption, the cost of dealing with government agencies, etc. are specific to the device. In addition, the maintenance cost and repair cost of the evaluation target device are information related to the part unit price and labor hours specific to the device (for example, the same model of pump differs between large and small pumps and between manufacturers), so they are information specific to the device determined by identifying the device.

[0031] Furthermore, the relationship between maintenance or operation, failure rate, and maintenance costs is as follows. For example, while monitoring the operating state of the equipment being evaluated can reduce the failure rate by detecting abnormalities early, it also incurs costs for monitoring. On the other hand, in an overhaul inspection, the replaced parts are returned to new, so deterioration over time can be restored to the initial value, but initial failures due to work errors during disassembly and assembly may be induced. 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 state, which was previously performed, it becomes impossible to detect abnormalities early, which may increase the failure rate.

[0032] 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 inputted in this operation and maintenance record input means 16 is the content, date and time of implementation, and period, and is inputted by an operator by electronic means or inputted from a database. These operation and maintenance records are basically information managed in a maintenance ledger, maintenance management system, etc. in a plant, etc.

[0033] The operation and maintenance schedule input means 17 inputs the schedule regarding the operation and maintenance of the evaluation target equipment (operation and maintenance schedule input step). The operation and maintenance schedule of the evaluation target equipment input by this operation and maintenance schedule input means 17 includes the contents and the planned date and time and period of implementation, and is input by an operator by electronic means or input from a database. These operation and maintenance schedules are basically information managed as schedules in a maintenance ledger, maintenance management system, etc. in a plant, etc.

[0034] The plotting means 18 plots (plotting step) the results (history) and schedule of the operation and maintenance (contents, dates) of the evaluation target equipment in a process 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 later) input from the evaluation condition input means 19. An example of this is shown in FIG.

[0035] The evaluation condition input means 19 inputs an evaluation period for evaluating the reliability and maintenance cost of the evaluation target device, 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 cost, and failure recovery cost of the evaluation target device, changes the maintenance or operation schedule arranged in time by the plot means 18, and further changes the basic conditions when the simulation means 20 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 recovery cost.

[0036] Furthermore, the evaluation condition input means 19 allows an operator to change at least one of the operation and maintenance schedules of the evaluation target equipment arranged by the plot means 18. Also, the evaluation condition input means 19 allows an operator to change the reference value of the failure rate of the evaluation target equipment under the basic conditions input from the basic condition creation unit 15 to the simulation means 20, the relationship between the maintenance method, the maintenance method, and the operation and the failure rate, the standard maintenance cost related to the preventive maintenance of the evaluation target equipment, and the standard failure recovery cost when a failure occurs in the evaluation target equipment.

[0037] The simulation means 20 inputs each value 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, and calculates a time function of the failure rate of the equipment to be evaluated based on the operation and maintenance results and plans of the equipment to be evaluated and a time function of the maintenance costs, and also calculates an expected value of the failure recovery costs as a time function and arranges them in time (simulation step).

[0038] That is, the simulation means 20 first 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 failure rate of the evaluation target device (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 schedule plotted on the time axis by the plotting means 18. An example is shown below.

[0039] 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 early failures (initial failure rate B) is induced. In addition, by monitoring the condition of the equipment under evaluation while it is in operation, it is possible to reduce the early 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 early failures, accidental failures, and wear-out failures.

[0040] 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 time of evaluation. By changing the monitoring frequency of the operating state from once / month to twice / 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.

[0041] Here, an example of calculating the relationship between the reference value of the failure rate and operation and maintenance is shown below. Let the reference value of the time function of the failure rate be λ(t). In the Weibull distribution mentioned 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.

[0042] For example, monitoring the operating state of the equipment being evaluated will increase the likelihood of discovering a failure at the symptom stage, thereby lowering the failure rate. Regarding this, if the failure rate after operating state monitoring is "after λ", then after λ(t) = coefficient × 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 with respect to 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 placing it from the above-mentioned maintenance point.

[0043] 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 device (including the time function of the predicted maintenance cost) in accordance with the maintenance and operation results and schedule 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, and the unit price per implementation period for operation status monitoring and daily inspection, in accordance with the implementation of preventive maintenance. Naturally, if the frequency of monitoring the operation status of the evaluation target device is increased, the price for that amount can be calculated based on the unit price.

[0044] Furthermore, the simulation means 20 can calculate (predict) the time function of the expected value of the failure restoration cost of the evaluation target device 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. Here, the repair cost at the time of failure of the evaluation target device, the cost of responding to reports to government agencies, and the loss due to production interruption, etc., included in the basic conditions created by the basic condition creation unit 15, are used to calculate the expected value of the failure restoration cost of the evaluation target device. 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 restoration 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 device is μ(t), the time function of the expected value of the failure restoration 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 the failure restoration cost as a function of time is shown in FIG.

[0045] The display unit 21 displays, over time, at least one of the results and schedules of maintenance and operation arranged over time by the plotting means 18, the time function of failure rate (including a time function of predicted failure rate) calculated and arranged by the simulation means 20, the time function of maintenance cost (including a time function of predicted maintenance cost), and the time function of expected value of failure recovery cost (display step).

[0046] 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 the optimal maintenance method that can improve the reliability of the equipment and reduce the maintenance cost.

[0047] [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.

[0048] The equipment reliability and maintenance cost prediction device 25 shown in FIG. 17 quantitatively evaluates differences due to different maintenance methods, maintenance methods, and their cycles when appropriately determining the maintenance method and maintenance method 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 condition input means 26, simulation means 27, and cumulative evaluation means 28.

[0049] 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.

[0050] 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 designated as parameters to be changed, and their upper and lower limits and intervals 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 designated as a parameter to be changed, and its upper and lower limits and intervals 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 designated as a parameter to be changed, and its upper and lower limits and intervals are specifically given.

[0051] The above are merely examples, but instead of the upper and lower limits of the parameters to be changed, the central values ​​of the parameters to be changed may be given. 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 ranges of change for each of the multiple parameters, or to only a part of them.

[0052] When the conditions to be changed relate to the schedule of maintenance or repair, the evaluation condition input means 26 changes the information (cycle, scheduled date) related to the designated maintenance or repair, and the plot means 18 changes the plot according to the information related to the schedule of maintenance or repair. For example, when changing the cycle of overhaul inspection, daily inspection, monitoring of the operating state, and oil replenishment of the evaluation target device, upper and lower limits and intervals are given within the range of change of these cycles, and these plots in the "Schedule" portion of Fig. 13 are changed. For example, when a date for overhaul inspection is given, the plots in the "Schedule" portion of Fig. 13 are changed according to that date.

[0053] 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 cost, and calculates (predicts) a time function of the expected value of the failure restoration cost. 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 change. 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 cost and a time function of the expected value of the failure restoration cost.

[0054] The simulation means 27 includes an accumulation evaluation means 28. When the cycles of the overhaul inspection, daily inspection, monitoring of the operating state, and oil supply of the evaluation target equipment are changed, the accumulation 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 accumulated failure rate value, the accumulated maintenance cost value, and the expected accumulated failure restoration cost value, and sets each of these accumulated values ​​and the value of the basic conditions at that time. This makes it possible to obtain the accumulated failure rate value, the accumulated maintenance cost value, and the expected accumulated failure restoration cost value for the basic conditions in accordance with the upper and lower limits and intervals of the change range of the cycles in accordance with the change range of the cycles of the overhaul inspection, daily inspection, monitoring of the operating state, and oil supply of the evaluation target equipment. By displaying this on the display unit 21, it becomes possible to evaluate the cumulative failure rate value L, the cumulative maintenance cost value M, and the expected cumulative failure restoration cost value N as shown in FIG. 21, and to find the basic conditions that optimize these cumulative values ​​L, M, and N.

[0055] In Fig. 21, the vertical axis represents three accumulated values ​​(accumulated failure rate L, accumulated maintenance cost M, expected accumulated failure restoration cost N) calculated by 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 one that can be changed continuously by the upper limit, lower limit, and increments as described above, but may also be discrete values ​​or items.

[0056] Furthermore, when the basic conditions changed by the evaluation condition input means 26 affect the failure rate, the unit price of maintenance cost, etc., the calculation method of each time function of the failure rate prediction, the maintenance cost prediction, and the expected value of the failure restoration 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 expected value of the accumulated failure restoration cost in the same manner as described above based on each of these time functions, 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.

[0057] For example, if the monitoring method of the operating state is changed, as described in the first embodiment, if the failure rate after monitoring is "after λ", then after λ(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, the maintenance cost can be calculated from the unit price and failure rate for each monitoring method.

[0058] 22 and 23 are examples in which the simulation means 27 predicts a time function of the failure rate and a time function of the maintenance cost using two condition monitoring methods with different effectiveness and costs. As shown in FIG. 22, the simulation means 27 calculates a time function of the predicted failure rate by expressing the effects of the two condition monitoring methods by changing the coefficients using the above-mentioned method, and expresses that the failure rate is lower in condition monitoring method 1 than in condition monitoring method 2. On the other hand, as shown in FIG. 23, the simulation means 27 calculates a time function of the predicted maintenance cost based on the failure rate prediction result in FIG. 22 and the difference in unit cost between condition monitoring method 1 and condition monitoring method 2.

[0059] The accumulation evaluation means 28 changes the above-mentioned coefficients when the monitoring frequency is changed between status monitoring method 1 and status 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 made smaller), and also 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 accumulated value of maintenance costs. An example of this is shown in Figure 24. Figure 24 compares the accumulated failure rate L, accumulated maintenance cost M, and expected accumulated failure restoration cost N for each monitoring cycle when only the monitoring cycle is changed between status monitoring methods 1 and 2 and all other conditions are kept the same.

[0060] 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.

[0061] [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 in the first embodiment are denoted by the same reference numerals as in the first embodiment, and the description thereof will be simplified or omitted.

[0062] The equipment reliability and maintenance cost prediction device 30 shown in FIG. 25 quantitatively evaluates differences due to different maintenance methods, maintenance methods, and their cycles when appropriately determining maintenance methods and maintenance methods for equipment in facilities such as plants and large-scale transportation systems, or compares time functions of predicted failure rates, time functions of predicted maintenance costs, and time functions of expected values ​​of failure recovery costs for a plurality of evaluation target equipment, or predicts the reliability of the system or bracket to which the evaluation target equipment belongs, the reliability for the model unit or responsibility category to which the evaluation target equipment belongs, and the maintenance costs and failure recovery costs, and mainly differs from the first embodiment in the configurations of the evaluation target setting means 31 and the cumulative evaluation means 32.

[0063] 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 evaluation target devices 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 restoration cost.

[0064] 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 evaluation target devices, superimposed on the time axis. This makes it possible to compare the failure rates, maintenance costs, etc. of the multiple evaluation target devices, and to compare the priority order of maintenance implementation for the multiple evaluation target devices.

[0065] Furthermore, the cumulative evaluation means 32 may take the sum, based on the time axis, of 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 set by the evaluation target setting means 31. This makes it possible to predict the expected values ​​of the maintenance cost and the failure restoration cost in categories such as the whole plant or all the devices in charge of a certain section.

[0066] 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.

[0067] [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 in the first embodiment are denoted by the same reference numerals as in the first embodiment, and the description thereof will be simplified or omitted.

[0068] The equipment reliability and maintenance cost prediction device 40 shown in Figure 26 evaluates the reliability of the system, line, facility, plant or large-scale transportation system as a whole (hereinafter 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 mainly differs from the first embodiment in the configurations of the evaluation target setting means 41, evaluation condition input means 42 and cumulative evaluation means 43.

[0069] The evaluation target setting means 41 specifies and sets multiple evaluation target devices belonging to any 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 omission based on, for example, an equipment ledger or an 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.

[0070] 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 as input a time function of the predicted failure rates of multiple evaluation target devices, 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 rates of multiple evaluation target devices are λ1(t), λ2(t), λ3(t), λ4(t), . . . λn(t), the above formula takes as input λ1(t), λ2(t), λ3(t), λ4(t), . . . λn(t) 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 formula that combines the time functions of the predicted failure rates of multiple evaluation target devices.

[0071] In the case where devices 1, 2, and 3 are connected in series as shown in Figure 27 and the system operates normally 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, in the case where devices 1, 2, and 3 are connected in parallel as shown in Figure 28 and the system operates normally 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).

[0072] In this way, in the fourth embodiment, by easily incorporating reliability engineering knowledge into an actual device and evaluating the system reliability (operation rate) as a function of time, it becomes possible to consider optimal maintenance including its implementation timing. This concept is shown in Fig. 29. The time function of the predicted failure rate for each of a plurality of 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 inputting maintenance resources can be evaluated based on changes in this operation rate.

[0073] 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.

[0074] 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 spirit of the invention. Furthermore, these substitutions, changes, and combinations are included in the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0075] 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

1. 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.

2. 2. The equipment reliability and maintenance cost prediction device according to claim 1, wherein when the equipment to be evaluated is set by the evaluation target setting means, the model to which the equipment belongs can be specified.

3. 3. The equipment reliability and maintenance cost prediction device according to claim 1, wherein the reference value of the failure rate inputted by the failure rate inputting means is inputted by an operator by electronic means, or is inputted from a database storing a time function of the failure rate for each failure type previously set for each model.

4. 4. The equipment reliability and maintenance cost prediction device according to claim 1, wherein the relationship between the failure rate and each of the maintenance methods, maintenance methods, and operations of the equipment inputted by the maintenance characteristic input means is inputted by an operator by electronic means indicating how the reference value of the failure rate changes depending on the influence of each of the maintenance methods, maintenance methods, and operations on the failure rate of the equipment, or is inputted from a database in which the relationship is preset for each model.

5. 5. The equipment reliability and maintenance cost prediction device according to claim 1, wherein 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 by electronic means for each of the equipment, or are input from a database.

6. 6. The equipment reliability and maintenance cost prediction device according to claim 1, wherein the basic conditions created by the basic condition creation unit are created as basic conditions by combining an equipment name, an equipment number, or other equipment information that identifies an equipment, and information on the model to which the equipment belongs, as well as by combining information specific to the equipment and information related to the model to which the equipment belongs.

7. 7. The equipment reliability and maintenance cost prediction device according to any one of claims 1 to 6, characterized in that the operation and maintenance record of the equipment inputted into the operation and maintenance record input means is the content thereof and the date and time when it was carried out and the period during which it was carried out, and the operation and maintenance schedule of the equipment inputted into the operation and maintenance schedule input means is the content thereof and the date and time when it is planned to be carried out and the operation and maintenance record and the operation and maintenance schedule are inputted by an operator by electronic means or inputted from a database.

8. 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 plan contents and time inputted by the operation and maintenance result input means and the operation and maintenance plan input means, based on a time axis.

9. 9. The equipment reliability and maintenance cost prediction device according to claim 8, wherein 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.

10. 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 records and plans plotted on a time axis by the plotting means, and to calculate a time function of an expected value of failure restoration costs based on the calculated equipment failure rate and the basic conditions.

11. 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 the operator can change the reference value of the failure rate of the equipment under basic conditions input from the basic condition creation unit to the simulation means, the relationship between the failure rate and each of the maintenance methods, maintenance methods, and operations, the standard maintenance cost related to preventive maintenance of the equipment, and the standard failure recovery cost when a failure occurs in the equipment.

12. 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.

13. 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.

14. 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.

15. 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.

16. 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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