Conservation improvement proposal support system and conservation improvement proposal support method

Abstract

To provide a highly convenient conservation improvement proposal support system, etc.SOLUTION: A conservation improvement proposal support system P1 comprises a processing part 3 that creates a chronological conservation plan pattern so that external conditions are satisfied based on asset knowledge information regarding failures that may occur in the asset, current conservation method information indicating a current conservation method for the asset, conservation improvement method information indicating a conservation improvement method when improving the conservation method for the asset from its current state, and external condition information including either or both of a support termination time limit of a technician who performs conservation on the asset and the a supply time limit of components as the external conditions.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a maintenance improvement proposal support system and the like. [Background technology]

[0002] As a technology for improving facility maintenance work, for example, the technology described in Patent Document 1 is known. That is, Patent Document 1 describes that "maintenance improvement measures that are in line with a maintenance improvement policy are extracted that are suited to the characteristics of an asset, and the order of their implementation is determined based on the dependencies between the technologies and data requirements between the maintenance improvement measures." [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-181230 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology described in Patent Document 1 extracts maintenance improvement measures that are suited to the characteristics of assets from among those that are in line with the user's maintenance improvement policy, but there is room for improvement in terms of convenience.

[0005] Therefore, an object of the present disclosure is to provide a highly convenient maintenance improvement proposal support system, etc. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems, the maintenance improvement proposal support system according to the present disclosure includes a processing unit that creates a time-series maintenance plan pattern based on asset knowledge information related to failures that may occur in an asset, current maintenance method information indicating the current maintenance method for the asset, maintenance improvement method information indicating a maintenance improvement method for improving the current maintenance method for the asset, and external condition information that includes, as external conditions, one or both of the support end date and parts supply deadline for the technician who maintains the asset, so that the external conditions are satisfied. [Effects of the Invention]

[0007] According to the present disclosure, a highly convenient maintenance improvement proposal support system and the like can be provided. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a configuration diagram of a maintenance improvement proposal support system according to an embodiment. [Figure 2] 1 is a diagram illustrating a hardware configuration of a maintenance improvement proposal support device included in a maintenance improvement proposal support system according to an embodiment. [Figure 3] FIG. 2 is an explanatory diagram of data stored in a storage unit of the maintenance improvement proposal support system according to the embodiment. [Figure 4] FIG. 2 is an explanatory diagram showing an example of asset knowledge information in the maintenance improvement proposal support system according to the embodiment. [Figure 5] FIG. 2 is an explanatory diagram illustrating an example of current maintenance method information of the maintenance improvement proposal support system according to the embodiment. [Figure 6] FIG. 2 is an explanatory diagram illustrating an example of maintenance improvement method information of the maintenance improvement proposal support system according to the embodiment. [Figure 7] FIG. 10 is an explanatory diagram illustrating an example of support deadline information of the maintenance improvement proposal support system according to the embodiment. [Figure 8] FIG. 10 is an explanatory diagram illustrating an example of part supply deadline information of the maintenance improvement proposal support system according to the embodiment. [Figure 9]FIG. 2 is an explanatory diagram illustrating an example of KPI information of the maintenance improvement proposal support system according to the embodiment. [Figure 10] FIG. 2 is an explanatory diagram illustrating an example of budget information of the maintenance improvement proposal support system according to the embodiment. [Figure 11] FIG. 2 is an explanatory diagram showing an example of replacement priority information of the maintenance improvement proposal support system according to the embodiment. [Figure 12] FIG. 10 is an explanatory diagram showing an example of replacement possible period information of the maintenance improvement proposal support system according to the embodiment. [Figure 13] FIG. 2 is an explanatory diagram illustrating an example of deadline response policy information of the maintenance improvement proposal support system according to the embodiment. [Figure 14] FIG. 2 is an explanatory diagram illustrating an example of maintenance plan pattern information of the maintenance improvement proposal support system according to the embodiment. [Figure 15] FIG. 2 is an explanatory diagram showing the transition of the failure probability of a predetermined asset in the maintenance improvement proposal support system according to the embodiment. [Figure 16A] 4 is a flowchart showing the processing of a processing unit of the maintenance improvement proposal support system according to the embodiment. [Figure 16B] 4 is a flowchart showing the processing of a processing unit of the maintenance improvement proposal support system according to the embodiment. [Figure 17] 10 is a display example showing the transition of the cost required for asset maintenance each year and the failure probability in the maintenance improvement proposal support system according to the embodiment. [Figure 18] 10 is a display example comparing the total costs when the current maintenance method is continued and when maintenance based on a maintenance plan pattern is performed in the maintenance improvement proposal support system according to the embodiment. [Figure 19] 10 is a display example showing a transition of parts procurement costs in preparation for the arrival of a parts supply deadline in the maintenance improvement proposal support system according to the embodiment. [Figure 20] 10 is a display example comparing the transition in the number of units to be replaced when the current maintenance method is continued and when maintenance is performed based on a maintenance plan pattern in the maintenance improvement proposal support system according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] <Embodiment> <Configuration of the maintenance improvement proposal support system> FIG. 1 is a configuration diagram of a maintenance improvement proposal support system P1 according to an embodiment. The maintenance improvement proposal support system P1 shown in FIG. 1 is a system for proposing improvements to asset maintenance work to a user, and includes a maintenance improvement proposal support device 10. The term "asset" refers to a facility. Examples of such "assets" include infrastructure such as power transmission facilities, substation facilities, communication facilities, gas facilities, water facilities, railways, and roads, as well as plants such as power plants, manufacturing plants, water treatment plants, and chemical plants. Other examples of "assets" include industrial machinery, medical facilities, air conditioning facilities, and refrigeration facilities. "Maintenance" refers to work that includes inspections of assets, as well as part replacement and repairs.

[0010] The maintenance improvement proposal support device 10 shown in Fig. 1 is a device that executes a predetermined process based on an input operation by a maintenance improvement proposer M1 and displays the results of the process on a display unit 4. Such a maintenance improvement proposal support device 10 may be configured as a single computer, or may be configured as multiple computers connected via a network. For example, the functions of the maintenance improvement proposal support device 10 may be distributed across multiple computers such as cloud servers or edge servers.

[0011] 1 is a person who proposes improvements to the maintenance work of a user who operates an asset. Such a maintenance improvement proposer M1 may be, for example, a maintenance business operator or a person belonging to the manufacturer of the asset.

[0012] As shown in Fig. 1, the maintenance improvement proposal support device 10 includes a storage unit 1, an input unit 2, a processing unit 3, and a display unit 4. Predetermined data is stored in the storage unit 1. The data stored in the storage unit 1 will be described later. The input unit 2 is used when a maintenance improvement proposer M1 performs a predetermined input operation, and is connected to the processing unit 3. For example, a keyboard or a mouse is used as the input unit 2.

[0013] The processing unit 3 executes a predetermined process based on the operation of the input unit 2. The process executed by the processing unit 3 will be described later. The display unit 4 displays the results of the process performed by the processing unit 3 in a predetermined manner. For example, a liquid crystal display is used as such a display unit 4. It is also possible to use a touch panel type mobile terminal that combines the functions of the input unit 2 and the display unit 4, such as a smartphone or tablet.

[0014] As shown in FIG. 1, the processing unit 3 includes an asset knowledge management unit 31, a current maintenance method management unit 32, a maintenance improvement method management unit 33, an external condition management unit 34, a maintenance policy management unit 35, a time-series maintenance plan pattern creation unit 36, a reliability prediction unit 37, and a pattern evaluation unit 38.

[0015] The asset knowledge management unit 31 manages asset knowledge information 11 (see FIG. 4) such as failure modes that can occur in each component of an asset, their occurrence frequency, and the impact and criticality of a failure mode when it occurs. Note that the "component" mentioned above refers to a device or part that is a constituent element of an asset (facility). Also, a "failure mode" refers to the type of failure in a component.

[0016] The current maintenance method management unit 32 manages data related to the current maintenance method of the asset. Note that the "current maintenance method" is the maintenance method of the asset currently adopted by the user. The maintenance improvement method management unit 33 manages data related to the maintenance improvement method of the asset. Note that a "maintenance improvement method" is a maintenance method when the current maintenance method is improved to a predetermined method.

[0017] The external condition management unit 34 manages external conditions when asset maintenance work is performed. Examples of such external conditions include the end of support for the technician who performs asset maintenance work and the supply deadline for parts used in the maintenance work.

[0018] The maintenance policy management unit 35 manages the maintenance policy of the user. Examples of such a maintenance policy include conditions related to the user's budget and KPIs (Key Performance Indicators) that the user values, as well as conditions related to the reliability of assets, priorities when replacing multiple assets, and conditions for the timing of replacement.

[0019] The time-series maintenance plan pattern creation unit 36 ​​creates a time-series maintenance plan pattern related to asset maintenance work. That is, the time-series maintenance plan pattern creation unit 36 ​​creates a predetermined maintenance plan pattern based on the data managed by the asset knowledge management unit 31, current maintenance method management unit 32, maintenance improvement method management unit 33, and external condition management unit 34.

[0020] The reliability prediction unit 37 predicts reliability indicators such as failure probability when asset maintenance work is carried out based on the above-mentioned maintenance plan pattern. The pattern evaluation unit 38 evaluates whether the maintenance plan pattern satisfies the conditions of the user's maintenance policy. Then, the pattern evaluation unit 38 displays, from among the multiple maintenance plan pattern candidates, the one that best suits the user's maintenance policy on the display unit 4.

[0021] FIG. 2 is a diagram showing the hardware configuration of the maintenance improvement proposal support device 10. As shown in FIG. As shown in FIG. 2, the hardware configuration of the maintenance improvement proposal support device 10 includes a processor 10a, a RAM 10b (Random Access Memory), a ROM 10c (Read Only Memory), a HDD 10d (Hard Disk Drive), a communication interface 10e, and an input / output interface 10f, which are connected in a predetermined manner via a bus 10g.

[0022] The processor 10a is hardware that constitutes the processing unit 3 (see FIG. 1) of the maintenance improvement proposal support device 10. The RAM 10b, ROM 10c, and HDD 10d are hardware that constitute the storage unit 1 (see FIG. 1) of the maintenance improvement proposal support device 10. The processor 10a reads out a predetermined program stored in the ROM 10c or HDD 10d, loads it into the RAM 10b, and executes a predetermined process.

[0023] The communication interface 10e performs predetermined communication with the user terminal 20 via the network N1. The input / output interface 10f is an interface for inputting data from the input unit 2 and outputting data to the display unit 4. Note that the hardware configuration shown in Fig. 2 is an example and is not limited to this.

[0024] FIG. 3 is an explanatory diagram of data stored in the storage unit 1 of the maintenance improvement proposal support system. 3, the storage unit 1 stores asset knowledge information 11, current maintenance method information 12, maintenance improvement method information 13, external condition information 14, maintenance policy information 15, and maintenance plan pattern information 16. Next, each of these pieces of information will be explained in order.

[0025] FIG. 4 is an explanatory diagram showing an example of the asset knowledge information 11. As shown in FIG. The asset knowledge information 11 shown in Fig. 4 is information about failures that may occur in assets, and is managed by the asset knowledge management unit 31 (see Fig. 1). Such asset knowledge information 11 is set in advance by a maintenance improvement proposer M1 (see Fig. 1) through an input unit 2 (see Fig. 1). For example, the asset knowledge information 11 is set based on a Failure Modes Effects and Criticality Analysis (FMECA).

[0026] In the asset knowledge information 11 shown in FIG. 4, "component," "ID," "failure mode," "occurrence frequency," "impact at occurrence," and "criticality" are associated with each other. Components A to C are constituent elements of a specific asset. "ID" shown in FIG. 4 is identification information assigned to the combination of a component and a failure mode. Incidentally, examples of "failure modes" include cracks and breaks in component A, bearing wear, grease deterioration, and bearing sticking in component B, and O-ring deterioration in component C.

[0027] The "occurrence frequency" shown in Figure 4 is the frequency with which a failure mode occurs, and is set based on the results of past inspections and maintenance. The occurrence frequency of a failure mode is classified into, for example, four levels. Specifically, the highest occurrence frequency of a failure mode is "Frequent," followed by "Occasional," "Infrequent," and "Improbable," in that order. Note that the cases of "Frequent" and "Improbable" are not shown in the table in Figure 4.

[0028] The "impact at the time of occurrence" shown in Figure 4 indicates the degree of impact when a specific failure mode occurs. The impact at the time of occurrence of a failure mode is classified into, for example, three levels. Specifically, the case where the impact at the time of occurrence of a failure mode is greatest is set to "Catastrophic," followed by "Degraded" and then "Incipient," in that order.

[0029] The "criticality" shown in FIG. 4 indicates the criticality when a specific failure mode occurs in a component. The criticality associated with the occurrence of a failure mode is expressed, for example, as the product of a numerical value for the frequency of occurrence and a numerical value for the impact when the failure mode occurs. Specifically, in the four-level frequency of occurrence, "Frequent" is quantified as 4, "Occasional" as 3, "Infrequent" as 2, and "Improbable" as 1. In addition, in the three-level impact when the failure mode occurs, "Catastrophic" is quantified as 3, "Degraded" as 2, and "Incipient" as 1. For example, in the failure mode (ID=1) where a crack occurs in component A, the frequency of occurrence is "Occasional" and the impact when the failure mode occurs is "Degraded," so the criticality value is 3 x 2 = 6.

[0030] The number of classifications (number of stages) for the frequency of occurrence of a failure mode and the impact when it occurs may be changed as appropriate based on the configuration and characteristics of the asset. The frequency of occurrence does not necessarily need to be classified into stages, and a predetermined value based on past cases may be used. Furthermore, the cost of maintenance or part replacement when a failure mode occurs may be used as appropriate for the impact when it occurs.

[0031] FIG. 5 is an explanatory diagram showing an example of the current maintenance method information 12. As shown in FIG. The current maintenance method information 12 shown in Figure 5 is information indicating the current maintenance method of the asset operated by the user, and is managed by the current maintenance method management unit 32 (see Figure 1). The current maintenance method information 12 is set in advance by the maintenance improvement proposer M1 (see Figure 1) through the input unit 2 (see Figure 1). For example, the current maintenance method information 12 may be set based on a prior interview with the user who owns the asset. Furthermore, the current maintenance method information 12 may be set appropriately based on the assumptions of the maintenance improvement proposer M1 (see Figure 1).

[0032] In the current maintenance method information 12 shown in Fig. 5, "component", "ID", "failure mode", "maintenance strategy", "maintenance frequency", "inspection means", "inspection cost", "treatment means", and "treatment cost" are associated with each other. Note that the "component" and "ID" are the same as those in the asset knowledge information 11 of Fig. 4, and therefore their explanation will be omitted.

[0033] The "maintenance strategy" shown in Fig. 5 is a maintenance work method for a specific failure mode of each component. Specifically, the maintenance strategy currently being used by the user is registered from among the three types of maintenance: time-based maintenance (TBM), condition-based maintenance (CBM), and breakdown maintenance (BDM).

[0034] The aforementioned time-based maintenance (TBM) is a method in which maintenance is performed when a predetermined time has passed since the end of the previous maintenance of an asset (or when a predetermined operating time has passed). Condition-based maintenance (CBM) is a method in which maintenance and other measures are performed appropriately based on the condition and operating status of assets and components. Corrective maintenance (BDM) is a method in which maintenance and other measures are performed after a failure occurs in an asset.

[0035] The "Maintenance Frequency" shown in Fig. 5 is where the maintenance frequency for each component's failure mode is registered. In the example in Fig. 5, time-based maintenance (TBM) and condition-based maintenance (CBM) are shown in days. For example, for the failure mode (ID=1) of component A, which is a crack, the maintenance strategy is to inspect the asset every 90 days as condition-based maintenance (CBM), and perform maintenance if a failure occurs. Note that for corrective maintenance (BDM), no specific maintenance is performed until a failure occurs, so the "Maintenance Frequency" column simply states "BDM."

[0036] The "inspection means" shown in Figure 5 is where the means (inspection method) used to inspect whether or not there is a failure mode in each component is registered. Note that "inspection" is a maintenance operation to discover a failure mode. The "inspection cost" shown in Figure 5 is where the cost (expense) of inspecting using a specified inspection means is registered. In the example of Figure 5, the inspection cost is registered in units of M yen (1 million yen).

[0037] The "treatment means" shown in Figure 5 is where the treatment means (treatment method) for taking a predetermined treatment for the failure mode of each component is registered. The "treatment" is a maintenance operation to eliminate or improve the predetermined failure mode. The "treatment cost" shown in Figure 5 is where the cost (expense) for taking a treatment using the predetermined treatment means is registered. In the example of Figure 5, the treatment cost is registered in units of M yen (1 million yen).

[0038] For example, for a crack in component A (ID=1), a visual inspection is performed every 90 days using condition-based maintenance (CBM). The inspection cost associated with the visual inspection is 0.005M yen (5,000 yen). If a crack is discovered in component A as a result of the visual inspection, component A will be replaced as a remedial measure. The remedial cost associated with replacing component A is 50M yen (50 million yen).

[0039] For example, for grease deterioration in component B (ID=4), an overhaul inspection is performed every 2,190 days (every six years) using time-based maintenance (TBM). The inspection cost associated with the overhaul inspection is 0.5 million yen (500,000 yen). Grease is injected as a treatment during the overhaul inspection, and the cost of this treatment is 0.1 million yen (100,000 yen).

[0040] FIG. 6 is an explanatory diagram showing an example of the maintenance improvement method information 13. As shown in FIG. The maintenance improvement method information 13 shown in Fig. 6 is information indicating a maintenance improvement method when improving the current maintenance method of an asset, and is managed by the maintenance improvement method management unit 33 (see Fig. 1). Furthermore, the maintenance improvement method information 13 is set in advance by a maintenance improvement proposer M1 (see Fig. 1) through an operation via the input unit 2 (see Fig. 1). In other words, the maintenance improvement proposer M1 (or AI: Artificial Intelligence) sets desirable measures for improving the maintenance work of an asset as the maintenance improvement method information 13.

[0041] In the maintenance improvement method information 13 shown in Fig. 6, "component", "ID", "failure mode", "maintenance strategy", "maintenance frequency", "inspection means", "inspection cost", "treatment means", "treatment cost", and "implementation cost" are associated with each other. Note that for the crack (ID=1: see Fig. 4) and break (ID=2: see Fig. 4) of component A, no particular maintenance improvement method is indicated, so the current maintenance method (see Fig. 5) will be continued.

[0042] "Online" in "Maintenance Frequency" in FIG. 6 means that online remote diagnosis is performed. "Introduction Cost" shown in FIG. 6 is the cost (expense) of newly introducing a specified inspection means. For example, the cost of purchasing a sensor used for online remote diagnosis, as well as a sensor data recording device and a diagnostic device, are registered as "Introduction Cost." Note that the items other than "Introduction Cost" are the same as those in the current maintenance method information 12 (see FIG. 5) described above, and therefore their explanation will be omitted.

[0043] For example, for bearing wear (ID=3) of component B, online remote diagnosis is performed using a vibration meter based on condition-based maintenance (CBM). The cost of implementing online remote diagnosis is 1M yen (1 million yen). Also, for O-ring deterioration (ID=6) of component C, online remote oil leak diagnosis is performed using image analysis based on condition-based maintenance (CBM). The cost of implementing online remote diagnosis is 5M yen (5 million yen).

[0044] When creating a maintenance plan pattern for an asset, it is possible to continuously apply the maintenance improvement method information 13 from the first year of the planning year. However, this may require a large amount of cost, or the timing of asset replacement may not be in line with the user's maintenance policy. Therefore, in this embodiment, when the processing unit 3 (see FIG. 1) creates a maintenance plan pattern, it selectively incorporates the current maintenance method information 12 (see FIG. 5) or the maintenance improvement method information 13 depending on the asset's component, failure mode, and planning year. The process when creating a maintenance plan pattern will be described later.

[0045] FIG. 7 is an explanatory diagram showing an example of the support expiration date information 14a. The support expiration information 14a shown in FIG. 7 is information indicating the end of support period for the technician who maintains the asset. The technician is dispatched by the asset manufacturer or the like in response to a request from the user who owns the asset. The support expiration information 14a is included in the external condition information 14 (see FIG. 3) and is managed by the external condition management unit 34 (see FIG. 1). The support expiration information 14a is set in advance by the maintenance improvement proposer M1 (see FIG. 1) through the input unit 2 (see FIG. 1).

[0046] 7, in the support expiration information 14a, assets are associated with expiration dates for technician support. In the example of FIG. 7, the expiration date for technician support for asset α is 2035. The expiration date for technician support for asset β is 2040.

[0047] FIG. 8 is an explanatory diagram showing an example of the part supply deadline information 14b. The parts supply deadline information 14b shown in Fig. 8 is information indicating the supply deadline of parts used in asset maintenance. The parts supply deadline information 14b is included in the external condition information 14 (see Fig. 3) and is managed by the external condition management unit 34 (see Fig. 1). The parts supply deadline information 14b is set in advance by the maintenance improvement proposer M1 (see Fig. 1) through the input unit 2 (see Fig. 1).

[0048] 8, in the parts supply deadline information 14b, "component," "ID," "failure mode," and "parts supply deadline" are associated with each other. For example, the parts supply deadline for a crack in component A (ID=1) is set to 2030. Also, the parts supply deadline for bearing wear in component B (ID=3) is set to 2035. No particular parts supply deadline has been set for grease deterioration in component B (ID=4).

[0049] In addition, external condition information 14 (see Figure 3), which includes the support end date of the technician who maintains the asset and the parts supply deadline as external conditions, is composed of support deadline information 14a (see Figure 7) and parts supply deadline information 14b (see Figure 8).

[0050] FIG. 9 is an explanatory diagram showing an example of the KPI information 15a. KPI information 15a shown in Fig. 9 is information indicating KPI items that a user wishes to improve. The KPI information 15a is included in the maintenance policy information 15 (see Fig. 3) and is managed by the maintenance policy management unit 35 (see Fig. 1). The KPI information 15a is set in advance by a maintenance improvement proposer M1 (see Fig. 1) through an operation via the input unit 2 (see Fig. 1) based on a prior interview with the user.

[0051] As shown in FIG. 9, the KPI information 15a associates a predetermined "ID," a "KPI," and an "improvement request" item. The "ID" shown in FIG. 9 is identification information assigned to each KPI item. In the example of FIG. 9, the "KPI" items include availability rate, total cost, cost leveling, replacement number leveling, and reliability. In the "improvement request" item, a user who operates an asset checks the KPI for which the user wishes to improve. In the example of FIG. 9, the total cost (ID=2) and reliability (ID=5) are checked, which indicates that the user wishes to improve the total cost and reliability related to asset maintenance. In this way, the maintenance policy information 15 (see FIG. 3), which indicates the user's maintenance policy when maintaining assets, includes the KPI items specified by the user.

[0052] FIG. 10 is an explanatory diagram showing an example of the budget information 15b. The budget information 15b shown in Fig. 10 is information that indicates the user's investment budget for maintenance work on a specific asset by year. The budget information 15b is included in the maintenance policy information 15 (see Fig. 3) and is managed by the maintenance policy management unit 35 (see Fig. 1). The budget information 15b is set in advance by the maintenance improvement proposer M1 (see Fig. 1) through the input unit 2 (see Fig. 1) based on a prior interview with the user.

[0053] As shown in Fig. 10, budget information 15b associates "years" such as the first and second years in the future with "investment budgets" for asset maintenance. In the example of Fig. 10, the investment budget for the maintenance work of a specific asset in the first year is 40M yen (40 million yen), but in the sixth year it is 5M yen (5 million yen).

[0054] FIG. 11 is an explanatory diagram showing an example of the replacement priority information 15c. The replacement priority information 15c shown in Fig. 11 is information indicating the priority when replacing an asset (replacing it with a new one). The replacement priority information 15c is included in the maintenance policy information 15 (see Fig. 3) and is managed by the maintenance policy management unit 35 (see Fig. 1). The replacement priority information 15c is set in advance by a maintenance improvement proposer M1 (see Fig. 1) through an operation via the input unit 2 (see Fig. 1) based on a prior interview with a user.

[0055] Each row in Figure 11 indicates an asset that is the target when comparing replacement priorities. Each column in Figure 11 indicates an asset that is the counterpart when comparing replacement priorities. If a specific asset in the row direction has a higher replacement priority than the asset it is compared to in the column direction, a check mark is placed in the box specified by that row and column. More specifically, asset α has a higher replacement priority than assets β and γ. Asset γ has a higher replacement priority than asset β. In other words, the replacement priority is asset α > asset γ > asset β.

[0056] FIG. 12 is an explanatory diagram illustrating an example of the replaceable period information 15d. The replacement period information 15d shown in Fig. 12 is information indicating the period during which each asset can be replaced (exchanged for a new asset). The replacement period information 15d is included in the maintenance policy information 15 (see Fig. 3) and is managed by the maintenance policy management unit 35 (see Fig. 1). The replacement period information 15d is set in advance by the maintenance improvement proposer M1 (see Fig. 1) through the input unit 2 (see Fig. 1).

[0057] As shown in FIG. 12, in the replacement period information 15d, an "asset," a "start year," and an "end year" are associated with each other. The "start year" is the start year of the period in which a specified asset can be replaced. The "end year" is the end year of the period in which a specified asset can be replaced. For example, for asset α, the start year of the replacement period is 2028, and the end year is 2030. This indicates that asset α should be replaced between 2028 and 2030. For asset β, the start year of the replacement period is not specifically set, and the end year is 2035. This indicates that asset β should be replaced by 2035.

[0058] In this way, the maintenance policy information 15 (see Figure 3) indicating the user's maintenance policy when maintaining assets includes the replacement timing (see Figure 12) when replacing an asset with a new one, or the priority of replacement relative to other assets (see Figure 11).

[0059] Incidentally, in the above-mentioned replacement priority information 15c (see FIG. 11), the priority of replacement is asset α > asset γ > asset β. Considering such priority of replacement, the replaceable period information 15d in FIG. 12 shows that asset β needs to be replaced by 2035, and therefore asset γ, which has a higher priority of replacement than asset β, also needs to be replaced by 2035.

[0060] FIG. 13 is an explanatory diagram showing an example of the deadline response policy information 15e. Deadline response policy information 15e shown in Fig. 13 is information indicating a user's response policy regarding the support end deadline (see Fig. 7) and the parts supply deadline (see Fig. 8) of the technician who maintains the asset. The deadline response policy information 15e is included in the maintenance policy information 15 (see Fig. 3) and is managed by the maintenance policy management unit 35 (see Fig. 1). Furthermore, the deadline response policy information 15e is set in advance by a maintenance improvement proposer M1 (see Fig. 1) through an operation via the input unit 2 (see Fig. 1) based on a prior interview with the user.

[0061] As shown in FIG. 13, in the deadline response policy information 15e, "asset," "technician support," and "parts supply" are associated with each other. The "technician support" column registers the user's response policy in preparation for the end of technician support. The "parts supply" column registers the user's response policy in preparation for the end of supply of parts used in maintenance work. The example of FIG. 13 shows a policy that the user will provide in-house training on the maintenance work of asset α in preparation for the end of technician support for asset α. Also, a policy that the user will procure a predetermined amount of parts for asset α by the parts supply deadline in preparation for the end of parts supply for asset α is shown.

[0062] Furthermore, for asset β, a policy has been indicated in which the user will provide in-house training in preparation for the end of technician support. Furthermore, a policy has been indicated in which the parts used in the maintenance work for asset β will be manufactured within the user's company (in-house production) in preparation for the end of parts supply. For asset γ, no policy has been indicated regarding the end of technician support or parts supply. This means that no particular maintenance work for asset γ will be carried out after the expiration of each deadline.

[0063] FIG. 14 is an explanatory diagram showing an example of the maintenance plan pattern information 16. As shown in FIG. The maintenance plan pattern information 16 shown in Fig. 14 is information indicating a time-series maintenance plan pattern related to maintenance work for a specified asset, and is created by the time-series maintenance plan pattern creation unit 36 ​​(see Fig. 1). As shown in Fig. 14, the maintenance plan pattern based on the maintenance plan pattern information 16 is created as a time-series maintenance plan that includes whether or not to replace the asset, whether or not to inspect and take measures for a failure mode of the asset, whether or not to switch the maintenance method, and the quantity of parts to be procured for the asset.

[0064] An "asset" shown in FIG. 14 is a piece of equipment that is the target of maintenance work. A "failure mode" is a type of failure in an asset. Note that in FIG. 14, a failure mode is set for each asset, but this is not limited to this. For example, a failure mode may be set for each component that constitutes an asset.

[0065] The "maintenance items" shown in Figure 14 indicate the maintenance work items for each asset. Such maintenance items include asset replacement, inspection and treatment (maintenance, etc.), parts procurement, and maintenance switchover. Note that a "maintenance switchover" refers to switching the method of maintenance work. Examples of such a "maintenance switchover" include switching from on-site asset inspection to online remote diagnosis, changing the inspection cycle, and changing the maintenance strategy (for example, from time-based maintenance (TBM) to condition-based maintenance (CDM)).

[0066] In the "Planned Year" shown in FIG. 14, for example, the next year is set as the 1st year, 2nd year, ..., 20th year, etc., with the time when the maintenance plan pattern information 16 was generated (present) as the base year. A predetermined number is set in the column for each planned year in association with the content of the maintenance work (maintenance item). In the example of FIG. 14, asset α is replaced in the 18th year, so the value "1" is set in the corresponding column. Furthermore, asset α is not replaced in the 1st to 17th years or the 19th and 20th years, so the value "0" is set in the corresponding columns.

[0067] Furthermore, for failure mode FM1 of asset α, a maintenance switchover (for example, online remote diagnosis through the introduction of IoT) will be performed in the first year, so a value of "1" is set in the corresponding field. Note that in each year after the planned year in which the maintenance switchover was performed (first year in the example of FIG. 14), specified maintenance will be performed based on the maintenance improvement method information 13 (see FIG. 6). Incidentally, from the second year onwards, the value of "maintenance switchover" is "0," but because the maintenance switchover was already performed in the first year, maintenance will also be performed in each year after the second year based on the maintenance improvement method information 13 (see FIG. 6).

[0068] For "parts procurement," the amount of parts required for n maintenance operations (n ​​is a natural number) is set as the value of "n." For example, for failure mode FM1 of asset α, a predetermined inspection and treatment will be performed in the sixth year, so in preparation for this, the maintenance plan pattern is set so that parts for one maintenance operation will be procured in the fourth year, and parts for two maintenance operations will be procured in the fifth year.

[0069] Note that the maintenance schedule pattern may be displayed in a table format as shown in Fig. 14 on the display unit 4 (see Fig. 1). The maintenance schedule pattern may also be displayed in other formats such as a graph. A specific method for creating a maintenance schedule pattern will be described later.

[0070] FIG. 15 is an explanatory diagram showing an example of the transition of the failure probability of a predetermined asset. The horizontal axis of FIG. 15 represents the planned fiscal year (year) based on the time when the maintenance plan pattern information 16 was created. The vertical axis of FIG. 15 represents the failure probability of a specified asset. The failure probability for each planned fiscal year is calculated by the reliability prediction unit 37 (see FIG. 1). The solid line graph in FIG. 15 shows the transition of the failure probability when part replacement is performed. The dashed line graph shows the transition of the failure probability when part replacement is not performed.

[0071] Assets generally deteriorate over time, and the failure probability also increases with age. However, when parts are replaced or assets are replaced (with new ones), the replacement parts or assets become new, and the failure risk of the entire asset decreases. In the example of Figure 15, the failure probability decreases in the seventh year after the parts were replaced.

[0072] For example, the reliability prediction unit 37 (see FIG. 1) may calculate a predetermined health score based on the number of years since the asset was introduced, and then calculate the failure probability of the asset based on this health score. When an asset is replaced, the number of years since the asset was introduced is also reset to zero. When some parts of an asset are replaced, the failure probability of the entire asset is calculated appropriately based on the failure probability of each part. The failure probability value is used as a reliability index when predicting the reliability of the asset.

[0073] 16A and 16B are flowcharts showing the processing of the processing unit of the maintenance improvement proposal support system (see also FIG. 1 as appropriate). 16A, it is assumed that a maintenance plan pattern is generated for a certain asset as a target for maintenance work. It is also assumed that asset knowledge information 11 and current maintenance method information 12 shown in FIG. 3 as well as maintenance improvement method information 13, external condition information 14, and maintenance policy information 15 have already been set and stored in the storage unit 1.

[0074] In step S101, the processing unit 3 creates a maintenance plan pattern using the time-series maintenance plan pattern creation unit 36. The maintenance plan pattern information 16 created initially may be a maintenance plan in which no particular maintenance work is performed each year, or may be a maintenance plan in which the current maintenance method is continued as is. In addition, for example, a predetermined maintenance plan pattern assumed by the maintenance improvement proposer M1 (or AI) may be set initially.

[0075] The components and failure modes included as items in the maintenance plan pattern are set based on the asset knowledge information 11 (see FIG. 4). Regarding asset replacement, an initial maintenance plan pattern may be created so that an asset is replaced with a new one when the expected lifespan is reached. As will be described later, the provisional maintenance plan pattern created in step S101 is updated successively.

[0076] In step S102 of Fig. 16A, the processing unit 3 sets the value of the planned year t in the maintenance plan pattern to 1 (t = 1). For example, if a maintenance plan pattern such as that shown in Fig. 14 is created in step S101, in step S102 the processing unit 3 selects the first year from among the planned years 1 to 20.

[0077] In step S103, the processing unit 3 selects a component. That is, for a predetermined asset that is the target of the maintenance work, the processing unit 3 selects one of a plurality of components that are constituent elements of the asset. In step S104, the processing unit 3 selects a failure mode, that is, the processing unit 3 selects one of a plurality of failure modes that may occur in the component selected in step S103.

[0078] In step S105, the processing unit 3 determines whether or not the maintenance has been switched over. That is, the processing unit 3 determines whether or not the maintenance work method for the failure mode (selected in S104) of a predetermined component (selected in S103) has been switched over in the first year of the planning year (t=1 in S102) in the maintenance plan pattern created in step S101.

[0079] For example, assume that a maintenance plan pattern is created in step S101 to continue the current maintenance method. In this case, no maintenance switchover has been performed in the first year of the planning year (t=1). If no maintenance switchover has been performed in step S105 (S105: No), the processing unit 3 proceeds to step S106.

[0080] In step S106, the processing unit 3 performs current maintenance judgment. Here, "current maintenance judgment" means that for the planning year, component, and failure mode selected in steps S102 to S104, the appropriateness of the maintenance plan pattern should be judged based on the current maintenance method information 12 (see FIG. 5).

[0081] 14, it is possible that a maintenance plan pattern is created so that a predetermined maintenance switchover (for example, online remote diagnosis) is performed in the first year (t=1) of the planning fiscal year. In this case, the maintenance switchover will have already been performed from the first year onwards, and the determination result in step S105 will be "maintenance switchover completed."

[0082] If maintenance has been switched in step S105 (S105: Yes), the processing of the processing unit 3 proceeds to step S107. In step S107, the processing unit 3 performs an improvement maintenance judgment. Here, "improvement maintenance judgment" means that for the planned year, component, and failure mode selected in steps S102 to S104, the appropriateness of the maintenance plan pattern should be judged based on the maintenance improvement method information 13 (see FIG. 6).

[0083] After performing the processing of step S106 or S107, the processing of the processing unit 3 proceeds to step S108. In step S108, the processing unit 3 determines whether the maintenance strategy of the maintenance method that was the subject of the determination in step S106 or S107 is time-based maintenance (TBM). As described above, time-based maintenance (TBM) is a maintenance strategy in which inspections and treatments are performed at a predetermined maintenance frequency (maintenance cycle). If the maintenance strategy is time-based maintenance (TBM) in step S108 (S108: Yes), the processing of the processing unit 3 proceeds to step S109.

[0084] In step S109, the processing unit 3 performs inspection and treatment in accordance with a predetermined maintenance frequency. For example, assume that a failure mode of grease deterioration of component B (see ID=5 in FIG. 5) is selected in steps S103 and S104, and a maintenance planning pattern is created so that the current maintenance method is continued in the first year of the planning fiscal year. In this case, as shown in the current maintenance method information 12 in FIG. 5, an overhaul inspection of component B is performed every 2190 days. Therefore, in step S109, the maintenance planning pattern is appropriately set so that the cycle of overhaul inspection for grease deterioration of component B is 2190 days.

[0085] If the maintenance frequency or the like in the maintenance schedule pattern is inappropriate, the process may return to step S101 and a new maintenance schedule pattern may be created. The same applies to the processes in steps S112, S113, and S114 described below.

[0086] Furthermore, if the maintenance strategy is not time-based maintenance (TBM) in step S108 (S108: No), the processing of the processing unit 3 proceeds to step S110. In step S110, the processing unit 3 determines whether the maintenance strategy of the maintenance method that was the subject of determination in step S106 or S107 is condition-based maintenance (CBM). As described above, condition-based maintenance (CBM) is a maintenance strategy in which maintenance is performed appropriately based on the state and operating status of assets and components. If the maintenance strategy is condition-based maintenance (CBM) in step S110 (S110: Yes), the processing of the processing unit 3 proceeds to step S111.

[0087] In step S111, the processing unit 3 determines whether the maintenance frequency in condition-based maintenance (CBM) is "Online." That is, the processing unit 3 determines whether the maintenance strategy is condition-based maintenance (CBM) with online remote diagnosis. If the maintenance frequency is "Online" in step S111 (S111: Yes), the processing of the processing unit 3 proceeds to step S112.

[0088] In step S112, the processing unit 3 sets an inspection in accordance with a predetermined procedure. That is, the inspection is performed when performing a procedure such as maintenance in accordance with condition-based maintenance (CBM). For example, assume that a failure mode of bearing wear of component B (see ID=3 in FIG. 6) is selected in steps S103 and S104, and a maintenance plan pattern is created so that a maintenance improvement method is performed in the first year of the planned fiscal year. In this case, as shown in the maintenance improvement method information 13 in FIG. 6, online remote diagnosis is performed using a vibrometer. Therefore, the processing unit 3 sets a maintenance plan pattern so that online remote diagnosis is performed for bearing wear of component B.

[0089] If the maintenance frequency is not "Online" in step S111 (S111: No), the processing unit 3 proceeds to step S113. In step S113, the processing unit 3 sets an inspection in accordance with a predetermined maintenance frequency (inspection cycle) and performs measures such as maintenance based on the results of the inspection.

[0090] Furthermore, if the maintenance strategy is not condition-based maintenance (CBM) in step S110 (S110: No), the processing of the processing unit 3 proceeds to step S114. In step S114, the processing unit 3 determines not to perform preventive maintenance. In this case, BDM (corrective maintenance) is set, in which maintenance, etc. is performed after an asset failure occurs. In other words, it is set so that inspection and treatment will not be performed in the planned fiscal year (t=1) set in step S102.

[0091] After performing any one of steps S109 and S112 to S114, the processing of the processing unit 3 proceeds to step S115. In step S115, the processing unit 3 determines whether or not another failure mode exists. That is, the processing unit 3 determines whether or not another failure mode exists for a predetermined component in the first year of the planning year (t=1 in S102) that is different from the one selected in the first step S104. If another failure mode exists in step S115 (S115: Yes), the processing of the processing unit 3 returns to step S104. Then, in step S104, the processing unit 3 appropriately selects another predetermined failure mode based on the asset knowledge information 11 (see FIG. 4).

[0092] Furthermore, if no other failure modes exist in step S115 (S115: No), the processing of the processing unit 3 proceeds to step S116. In step S116, the processing unit 3 determines whether or not other components exist. That is, the processing unit 3 determines whether or not other components exist that are different from the one selected in the first step S103 for the first year of the planning fiscal year (t=1 in S102). If other components exist in step S116 (S116: Yes), the processing of the processing unit 3 returns to step S103. Then, in step S103, the processing unit 3 appropriately selects other predetermined components based on the asset knowledge information 11 (see FIG. 4).

[0093] Furthermore, if there are no other components in step S116 (S116: No), the processing by the processing unit 3 proceeds to step S117. In step S117, the processing unit 3 determines whether or not t has reached a predetermined number of planned years. The predetermined number of planned years is a preset upper limit value of the planned year when the processing unit 3 creates the maintenance plan pattern information 16. If t has not reached the predetermined number of planned years in step S117 (S117: No), the processing by the processing unit 3 proceeds to step S118.

[0094] In step S118, the processing unit 3 increments the value of t for the planned year, and returns to the processing of step S103. Also, if t has reached the predetermined number of planned years in step S117 (S117: Yes), the processing by the processing unit 3 proceeds to step S119 in FIG. 16B. In step S119, the processing unit 3 predicts the reliability of the asset using the reliability prediction unit 37. That is, the processing unit 3 calculates reliability indexes such as the future failure probability (see FIG. 15) when maintenance work is performed in accordance with the maintenance plan pattern, based on the asset knowledge information 11 (see FIG. 4), current maintenance method information 12 (see FIG. 5), and maintenance improvement method information 13 (see FIG. 6).

[0095] Next, in step S120, the processing unit 3 calculates predetermined evaluation indexes using the pattern evaluation unit 38. That is, the processing unit 3 calculates evaluation indexes such as KPIs based on the maintenance plan pattern and the prediction results of the reliability index. For example, if the total cost of maintenance work is specified as an item of KPI that the user wishes to improve, the processing unit 3 calculates the evaluation indexes as follows. First, the processing unit 3 calculates the corrective maintenance cost when corrective maintenance (BDM) is performed on the asset based on the future failure probability of the asset. Then, the processing unit 3 includes the corrective maintenance cost in the total cost required for maintaining the asset. Specifically, the processing unit 3 calculates the total cost by adding the replacement cost, inspection cost, treatment cost, parts procurement cost, maintenance changeover cost, and the corrective maintenance cost.

[0096] Next, in step S121, the processing unit 3 determines whether or not the maintenance schedule pattern satisfies predetermined constraint conditions. The constraint conditions are set in advance based on external condition information 14 (see FIG. 3) including support deadline information 14a (see FIG. 7) and parts supply deadline information 14b (see FIG. 8), as well as on user-side maintenance policy information 15 (see FIG. 3).

[0097] Note that by introducing the condition inventory quantity (t) ≧ 0 as one of the constraints, maintenance planning patterns that perform maintenance above the inventory quantity may be discarded. In a maintenance planning pattern, if parts are procured by the year T when parts supply is stopped, the inventory quantity (t) of parts in year t is calculated based on the following formula (1). Note that the procurement quantity (t) included in formula (1) is the amount of parts procured in year t. Furthermore, inventory quantity (t-1) is the amount of parts in stock in year (t-1). Furthermore, usage quantity (t) is the amount of parts used in year t.

[0098] Inventory amount (t) = Procurement amount (t) + Inventory amount (t-1) - Usage amount (t) ···(1)

[0099] Incidentally, for usage (t), when t≦T, usage (t) = 0, and when t>T, usage (t) = treatment (t). In other words, when a specified treatment is carried out using a part in year t, the procured part is consumed only once. Also, since the procurement of parts has stopped when t>T, procurement amount (t) = 0.

[0100] If the maintenance plan pattern does not satisfy the predetermined constraint conditions such as external conditions in step S121 of Fig. 16B (S121: No), the processing by the processing unit 3 returns to step S101 of Fig. 16A. In this case, a new maintenance plan pattern is created based on a predetermined algorithm such as mathematical optimization (S101). Also, if the maintenance plan pattern satisfies the predetermined constraint conditions such as external conditions in step S121 (S121: Yes), the processing by the processing unit 3 proceeds to step S122.

[0101] In this way, the processing unit 3 creates a time-series maintenance plan pattern based on the asset knowledge information 11, the current maintenance method information 12, the maintenance improvement method information 13, and the external condition information 14 so that the specified external conditions identified in the external condition information 14 are satisfied.

[0102] In step S122, the processing unit 3 determines, by the pattern evaluation unit 38, whether or not the maintenance plan pattern satisfies the conditions of a predetermined evaluation index. For example, the processing unit 3 identifies the maintenance plan pattern with the best KPI evaluation index from among the multiple maintenance plan patterns that satisfy the constraint conditions in step S121. That is, the processing unit 3 creates a maintenance plan pattern such that the conditions of the KPI item specified by the user are satisfied. For example, if the KPI that the user places importance on is total cost, the processing unit 3 selects, as the best maintenance plan pattern, a maintenance plan pattern that minimizes total cost. This makes it possible to create a maintenance plan pattern that meets the user's wishes regarding KPI.

[0103] Furthermore, it is preferable that the processing unit 3 creates a maintenance plan pattern so that the conditions for replacement timing when replacing an asset with a new one or the priority of replacement relative to other assets are satisfied. This makes it possible to create a maintenance plan pattern that meets the user's wishes regarding replacement timing and priority of replacement.

[0104] The maintenance policy information 15 (see FIG. 3) includes a user's policy regarding parts supply deadlines (see FIG. 13). If this policy is to procure parts to be used for maintenance until their supply deadlines, the processing unit 3 first identifies the parts supply deadlines by referring to the external condition information 14 (see FIG. 3), although this is omitted in FIGS. 16A and 16B. Then, the processing unit 3 creates a maintenance plan pattern so that a predetermined amount of parts are procured by the parts supply deadlines.

[0105] The maintenance policy information 15 (see FIG. 3) also includes the user's response policy regarding the end of support period for technicians (see FIG. 13). If this response policy is a policy for the user to provide in-house training regarding asset maintenance, the processing unit 3 includes the training cost required for the in-house training in the total cost required for asset maintenance. This allows the total cost required for asset maintenance to be calculated accurately.

[0106] Next, in step S123, the processing unit 3 displays the results on the display unit 4. That is, the processing unit 3 displays the maintenance plan patterns that satisfy the conditions of step S122 on the display unit 4. Note that it is preferable that the processing unit 3 compares and displays on the display unit 4 the values ​​of the KPI items specified by the user, the total cost required for asset maintenance, the trend in the future asset failure probability, or the trend in the number of asset replacement units in the future, between the case where the current maintenance method is continued and the case where maintenance based on the maintenance plan pattern is performed. This makes it easier for the user to understand what benefits there are to be gained by performing maintenance in accordance with the maintenance plan pattern.

[0107] Furthermore, information such as maintenance plan patterns may be transmitted from the maintenance improvement proposal support device (see FIG. 2) to the user terminal 20 (see FIG. 2) via the network N1 (see FIG. 2). This allows the information such as maintenance plan patterns to be provided to the user. After performing the process of step S123, the processing unit 3 ends the series of processes (END).

[0108] 16A and 16B, the processing unit 3 determines whether or not a maintenance switch has been made in step S105, but this is not limiting. For example, by setting the value indicating whether or not a maintenance switch has been made to 0 for each year (setting to no maintenance switch), predicted values ​​of future costs and reliability indexes in the case where the current maintenance method is continued may be calculated.

[0109] FIG. 17 is a display example showing the transition of the cost required for asset maintenance each year and the failure probability. The horizontal axis in Figure 17 is the planned year when the maintenance plan pattern is created. The vertical axis (solid line) on the left side of Figure 17 is the cost required for maintenance each year when a specified maintenance plan pattern is adopted. The vertical axis (dashed line) on the right side of Figure 17 is the asset failure probability each year when a specified maintenance plan pattern is adopted.

[0110] In the example of Figure 17, the cost trends for each planning year are shown in a bar graph, and the asset failure probability trends are shown in a curve (dashed line). As mentioned above, assets deteriorate over time, so the failure probability increases with each passing year. However, if prescribed maintenance or other procedures are performed on the asset, the failure probability temporarily decreases. By displaying a graph such as that shown in Figure 17, the user can grasp at a glance the trends in maintenance costs and failure probability. It is also possible to display a comparison of the trends in maintenance costs and failure probability when the user continues using their current maintenance method and when the maintenance method is improved (including when the maintenance method is selectively improved in some planning years).

[0111] FIG. 18 is a display example comparing the total costs when the current maintenance method is continued and when maintenance is performed based on the maintenance plan pattern. In Fig. 18, it is assumed that the KPI that the user places importance on is the total cost required to maintain the asset. Of the two bar graphs in Fig. 18, the bar graph on the left side of the page shows the breakdown of the total cost if the user continues with their current maintenance method. In addition, the bar graph on the right side of the page shows the breakdown of the total cost if a predetermined maintenance plan pattern based on a maintenance improvement method is adopted.

[0112] This comparative display allows the user to understand, for example, that the maintenance plan pattern significantly reduces the costs of inspection, treatment, and corrective maintenance. The user can also understand that the maintenance plan pattern requires the introduction and procurement costs of IoT (Internet of Things).

[0113] FIG. 19 is a display example showing the transition of parts procurement costs in preparation for the arrival of parts supply deadlines. The horizontal axis in FIG. 19 represents the planned year in the maintenance planning pattern (see FIG. 14). The vertical axis in FIG. 19 represents the parts procurement cost for each planned year based on the maintenance planning pattern. The example in FIG. 19 shows that a predetermined amount of parts is procured by the parts supply deadline. By procuring parts in advance in this way, assets can be maintained using parts in stock even after parts supply has been stopped.

[0114] FIG. 20 is a display example comparing the transition in the number of replacement units when the current maintenance method is continued and when maintenance is performed based on the maintenance plan pattern. In FIG. 20, the KPI that the user places importance on is the leveling of the number of replacement units. The horizontal axis of FIG. 20 is the planned year in the maintenance plan pattern (see FIG. 14). The vertical axis of FIG. 20 is the number of replacement units of assets. The number of replacement units is the number of units when an asset is replaced with a new one. In the example of FIG. 20, the solid bar graph shows the transition of the number of replacement units in each planned year in the current maintenance method. The dashed bar graph shows the transition of the number of replacement units in each planned year when a predetermined maintenance plan pattern based on the maintenance improvement method is adopted.

[0115] In the maintenance plan pattern based on the maintenance improvement method, asset life is extended and replacement timing is postponed, thereby leveling out the number of replacement units. By displaying this comparison, the user can see at a glance that the maintenance plan pattern aims to level out the number of replacement units.

[0116] <Effects> According to this embodiment, it is possible to propose a maintenance plan pattern that is in line with the user's maintenance policy, taking into consideration the end of support deadlines for technicians and parts procurement deadlines while maintaining asset reliability. Furthermore, even in situations where the user owns many aging assets, it is possible to propose a maintenance plan pattern that reduces maintenance costs and evens out asset replacement while maintaining asset reliability. Thus, according to this embodiment, it is possible to provide a highly convenient maintenance improvement proposal support system P1 and maintenance improvement proposal support method.

[0117] <<Variations>> The maintenance improvement proposal support system P1 and the maintenance improvement proposal support method according to the present disclosure have been described above in the embodiments, but the present disclosure is not limited to these descriptions and various modifications can be made. For example, in the embodiment, a case has been described in which the probability of future failure is used as the reliability index for an asset, but this is not limiting. That is, the mean time between failures of an asset may be used as the reliability index. The mean time between failures is the average time interval when an asset is assumed to fail.

[0118] In the embodiment, both the support end date and the parts supply deadline are used as external conditions, but this is not limiting. In other words, either the support end date or the parts supply deadline may be used as the external condition. In this case, the same effects as those of the embodiment are achieved. Furthermore, a failure probability may be used as a constraint condition used in creating a maintenance schedule pattern. Specifically, a maintenance schedule pattern may be created so that the future failure probability is equal to or less than a predetermined threshold value.

[0119] The process described in the embodiment can also be solved using mixed integer programming, for example, with each element of the maintenance plan pattern as a decision variable. Furthermore, AI may be used as appropriate when generating a maintenance plan pattern. For example, a maintenance improvement proposer M1 may provide information such as asset knowledge, maintenance methods, external conditions, and maintenance policies to the generating AI, and obtain a solution from the generating AI via chat.

[0120] Furthermore, the process (maintenance improvement proposal support method) executed by the maintenance improvement proposal support system P1 may be executed as a predetermined program on a computer. The program may be provided via a communication line or may be written to a predetermined recording medium and distributed.

[0121] Furthermore, the present disclosure is not limited to the embodiments and includes various modifications. For example, the embodiments have been described in detail to clearly explain the present disclosure, and the present disclosure is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to add, delete, or replace part of the configuration of the embodiments with other configurations.

[0122] Furthermore, the above-mentioned configurations, functions, processing units, processing means, etc. may be partly or entirely implemented in hardware, for example, by designing them as integrated circuits. Furthermore, the above-mentioned configurations, functions, etc. may be implemented in software, with a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0123] In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected. [Explanation of symbols]

[0124] 1 Storage section 2 Input section 3 Processing section 4 Display 10 Maintenance improvement proposal support device 11 Asset Knowledge Information 12 Current maintenance method information 13 Maintenance improvement method information 14 External Condition Information 15. Maintenance Policy Information 16 Maintenance plan pattern information 31 Asset Knowledge Management Department 32 Current Maintenance Method Management Department 33 Maintenance Improvement Method Management Department 34 External Condition Management Department 35 Maintenance Policy Management Department 36 Time-series maintenance plan pattern creation section 37 Reliability Prediction Department 38 Pattern Evaluation Unit P1 Maintenance improvement proposal support system

Claims

1. 1. A maintenance improvement proposal support system comprising: a processing unit that creates a time-series maintenance plan pattern based on asset knowledge information related to failures that may occur in an asset; current maintenance method information indicating a current maintenance method for the asset; maintenance improvement method information indicating a maintenance improvement method for improving the current maintenance method for the asset; and external condition information including, as external conditions, one or both of a support end date for a technician who maintains the asset and a parts supply deadline, so that the external conditions are satisfied.

2. The maintenance policy information indicating the user's maintenance policy when maintaining the asset includes a KPI (Key Performance Indicator) item designated by the user, The processing unit creates the maintenance plan pattern so that the conditions of the items of the KPI designated by the user are satisfied.

2. The maintenance improvement proposal support system according to claim 1,

3. The maintenance policy information indicating the user's maintenance policy when maintaining the asset includes a replacement timing when the asset is replaced with a new one, or a priority of replacement with respect to other assets; the processing unit creates the maintenance plan pattern so that the conditions of the replacement time or the priority are satisfied.

2. The maintenance improvement proposal support system according to claim 1,

4. the external condition information includes a supply deadline for the part; maintenance policy information indicating a user's maintenance policy when maintaining the asset includes a user's policy regarding a supply deadline for the part; When the response policy is a policy to procure the part by the supply deadline of the part, the processing unit refers to the external condition information to identify the supply deadline of the part, and creates the maintenance plan pattern so that a predetermined amount of the part is procured by the supply deadline of the part.

2. The maintenance improvement proposal support system according to claim 1,

5. the external condition information includes a support end date for the technician; maintenance policy information indicating a user's maintenance policy when maintaining the asset includes a user's response policy regarding the end of support period for the technician; If the response policy is a policy that the user will conduct in-house training regarding the preservation of the asset, the processing unit includes the training cost required for the in-house training in the total cost required for the preservation of the asset.

2. The maintenance improvement proposal support system according to claim 1,

6. The processing unit calculates a corrective maintenance cost when corrective maintenance is performed on the asset based on a future failure probability of the asset, and includes the corrective maintenance cost in a total cost required for maintaining the asset.

2. The maintenance improvement proposal support system according to claim 1,

7. The maintenance plan pattern is a time-series maintenance plan that includes whether or not to replace the asset, whether or not to inspect and take measures for a failure mode of the asset, whether or not to switch the maintenance method, and the quantity of parts to be procured for the asset.

2. The maintenance improvement proposal support system according to claim 1,

8. The processing unit causes the display unit to compare and display the value of a KPI item designated by a user, the total cost required for maintaining the asset, the transition in the probability of failure of the asset in the future, or the transition in the number of replacement units of the asset in the future, between a case where the current maintenance method is continued and a case where maintenance based on the maintenance plan pattern is performed.

2. The maintenance improvement proposal support system according to claim 1,

9. 1. A maintenance improvement proposal support method comprising: a process for creating a time-series maintenance plan pattern based on asset knowledge information relating to failures that may occur in an asset; current maintenance method information indicating a current maintenance method for the asset; maintenance improvement method information indicating a maintenance improvement method for improving the current maintenance method for the asset; and external condition information including, as external conditions, one or both of a support end date for a technician who maintains the asset and a parts supply deadline, so that the external conditions are satisfied.

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