Facility maintenance system and facility maintenance method

Abstract

To prevent an increase in site visit costs due to another site visit in response to occurrence of another failure mode after a failure has been dealt with.SOLUTION: A facility maintenance system 1 includes an asset knowledge database 41 in which failure information relating to a facility failure, a failure cause, whether or not a site visit to the facility by a maintenance person is required when the failure occurs, and a cost for dealing with the failure are managed in association with each other. The facility maintenance system 1 includes a failure cause presentation unit 33 configured to calculate, for a failure cause requiring a site visit among a plurality of failure causes estimated by a failure cause estimation unit 31, a ratio of a first cost for a case in which the maintenance person deals with the failure on the current site visit to a second cost for a case in which the maintenance person makes another site visit for dealing with the failure in a subsequent occurrence. Based on the ratio calculated by the failure cause presentation unit 33, the facility maintenance system 1 outputs failure causes that should be addressed preferentially, among the failure causes requiring a site visit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an equipment maintenance system and an equipment maintenance method. [Background technology]

[0002] When equipment breaks down (for example, a multifunction printer cannot print), the maintenance department listens to the symptoms from the user, visits the user's site, deduces several possible causes of the failure, and maintenance staff then repairs the cause of the failure and takes action such as replacing parts.

[0003] For example, Patent Document 1 discloses a technology that generates repair items based on the risk of failure, the frequency of failure, and the impact of failure, and supports the creation of a repair plan for equipment. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-11327 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the maintenance support system disclosed in the above-mentioned Patent Document 1 does not take into consideration the number of business trips, travel time required for business trips, and costs related to transportation expenses when providing maintenance services.

[0006] When maintenance personnel respond to a failure at a user site, there are multiple failure modes that can occur. Due to response time limitations, it is common to only respond to failure modes that are likely to occur. However, in this case, other failure modes may occur at a later date, which creates the problem of increased travel costs due to additional visits.

[0007] The present invention has been made in consideration of the above circumstances, and aims to suppress an increase in travel costs due to another travel to respond to a failure when another failure mode occurs after responding to the failure. [Means for solving the problem]

[0008] In one aspect of the present invention, an equipment maintenance system for maintaining and managing equipment includes an asset knowledge database in which failure information regarding failures of the equipment, the causes of the failures, whether or not a maintenance worker will be dispatched to the equipment in the event of the failure, and the cost of responding to the failure are managed in a corresponding manner; an input unit that accepts input of the failure information related to the equipment; a failure cause estimation unit that refers to the asset knowledge database based on the failure information accepted by the input unit and estimates multiple causes of the failure; a failure cause presentation unit that calculates, for a failure cause that requires a dispatch among the multiple failure causes estimated by the failure cause estimation unit, a ratio between a first cost in the case where the maintenance worker will respond to the failure on the current dispatch and a second cost in the case where the failure cause recurs in the next or subsequent cases and the maintenance worker will make another dispatch to respond; and an output unit that outputs to a terminal, the failure causes that require a dispatch based on the ratio calculated by the failure cause presentation unit. [Effects of the Invention]

[0009] According to the present invention, it is possible to suppress an increase in travel costs due to another travel to deal with a failure after another failure mode occurs after the failure has been dealt with. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing the configuration of an equipment maintenance system according to a first embodiment. [Figure 2] FIG. 2 is a diagram showing the configuration of maintenance knowledge data according to the first embodiment. [Figure 3] FIG. 4 is a diagram showing failure probability data according to the first embodiment. [Figure 4]FIG. 10 is a diagram showing the probability of a child node malfunction occurring when a parent node malfunctions according to the first embodiment. [Figure 5] FIG. 10 is a diagram showing the probability of a child node malfunction occurring when a parent node is normal according to the first embodiment. [Figure 6] FIG. 3 is a diagram showing the configuration of a failure cause response method table according to the first embodiment. [Figure 7] FIG. 4 is a diagram showing the configuration of a business trip expense table according to the first embodiment. [Figure 8] FIG. 1 is a diagram showing a maintenance knowledge Bayesian network according to the first embodiment. [Figure 9] 4 is a flowchart showing a maintenance knowledge Bayesian network generation process according to the first embodiment. [Figure 10] 4 is a flowchart showing a fault cause estimation process according to the first embodiment. [Figure 11] FIG. 4 is a diagram showing a failure cause estimation result according to the first embodiment. [Figure 12] FIG. 4 is a diagram showing an outline of a check item search process according to the first embodiment. [Figure 13] FIG. 10 is a flowchart showing a process of searching for check items to be investigated according to the first embodiment. [Figure 14] FIG. 2 is a diagram showing check items to be surveyed according to the first embodiment. [Figure 15] 4 is a flowchart showing a fault cause presentation process according to the first embodiment. [Figure 16] FIG. 10 is a diagram showing the cost ratio calculation results according to the first embodiment. [Figure 17] FIG. 2 is a diagram showing an input screen according to the first embodiment. [Figure 18] FIG. 10 is a diagram showing a result screen according to the first embodiment. [Figure 19] FIG. 10 is a diagram showing the configuration of an equipment maintenance system according to a second embodiment. [Figure 20] FIG. 10 is a diagram showing a failure cause response history according to the second embodiment. [Figure 21] 10 is a flowchart showing a fault cause presentation update process according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] In the following description, a "CPU (Central Processing Unit)" is an example of one or more processor devices. The at least one processor device is typically not limited to a CPU, but may be another type of processor device such as a GPU (Graphics Processing Unit). The at least one processor device may be a single-core or multi-core. The at least one processor device may be a processor core.

[0012] At least one processor device may be a circuit that is a collection of gate arrays written in a hardware description language that performs some or all of the processing. The circuit is a processor device in the broad sense, such as a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), or an application-specific integrated circuit (ASIC).

[0013] In the following explanation, the processing may be mainly explained using the "yyy program." In this case, the program is executed by a CPU to realize a processing function called the "yyy functional unit," and is the main executing entity of the processing. The processing function may be realized by one or more computer programs being executed by a processor, or may be realized by one or more hardware circuits (e.g., FPGA or ASIC), or a combination thereof.

[0014] When a function is realized by executing a program by a processor, the specified processing is performed using a storage device and / or an interface device, etc., so the function may be considered to be at least a part of the processor. Processing described using a functional unit as the subject may also be processing performed by a processor or a device having that processor.

[0015] The program may be installed from a program source. The program source may be, for example, a program distribution computer or a computer-readable recording medium (e.g., a non-transitory recording medium). The description of each function is an example, and multiple functions may be combined into one function, or one function may be divided into multiple functions. A "yyy function unit" may be called a "yyy unit."

[0016] In the following description, various information may be described in table format, but the data format of the information may be a format other than a table format (for example, CSV (Comma Separated Values) format, etc.) Furthermore, various information may be stored in a storage unit as a table, or may be embedded as logic in a program.

[0017] In addition, in the following description, when describing elements of the same type without distinguishing between them, common reference symbols will be used, and when describing elements of the same type with distinction between them, reference symbols will be used.

[0018] [Embodiment 1] (Configuration of equipment maintenance system 1 according to embodiment 1) FIG. 1 is a diagram showing the configuration of an equipment maintenance system 1 according to a first embodiment. The equipment maintenance system 1 has a CPU (Central Processing Unit) 2, a memory 3, an external storage device 4, and an input / output unit 5. The input / output unit 5 includes an input unit that accepts information input via a maintenance worker's terminal 6, and an output unit that outputs information to the display screen of the maintenance worker's terminal 6. In this embodiment, the equipment maintenance system 1 is described as being configured using a standalone computer, but it may also be realized by a server on the cloud, or each function may be divided and realized by multiple computers.

[0019] The memory 3 includes a fault cause estimation unit 31, a check item search unit 32, and a fault cause presentation unit 33.

[0020] The failure cause estimation unit 31 estimates the cause of a failure based on the input equipment status and alarms. When an abnormality occurs in the equipment, the failure cause estimation unit 31 generates a maintenance knowledge Bayesian network BN (FIG. 8) described below for cause estimation. The failure cause estimation unit 31 inputs check items into the maintenance knowledge Bayesian network BN according to information on the symptoms of the failure input by the maintenance staff or user, and calculates the occurrence probability of each failure mode.

[0021] The check item search unit 32 identifies and outputs items that maintenance personnel should check from the failure causes estimated by the failure cause estimation unit 31. The failure cause presentation unit 33 calculates and outputs a ranking of failure causes that should be addressed with priority during on-site maintenance from the check items identified by the check item search unit 32, in accordance with a specification of whether financial cost or time cost is to be prioritized.

[0022] The external storage device 4 stores an asset knowledge database 41 and a failure mode response method database 42 .

[0023] The asset knowledge database 41 is a database that accumulates maintenance knowledge. Maintenance knowledge is information extracted from, for example, a maintenance manual, a Failure Mode and Effects Analysis (FMEA), etc. Specifically, the asset knowledge database 41 stores maintenance knowledge data T1, failure probability data T2, a child node abnormality occurrence probability T3 when a parent node is abnormal, and a child node abnormality occurrence probability T4 when the parent node is normal.

[0024] The maintenance knowledge data T1 is information that associates functional failures and alarms with the failure modes that are the causes of the failures. The failure probability data T2 is data that stores the probability that the cause of the failure will occur.

[0025] The failure mode response method database 42 stores a failure cause response method table T5 that determines whether a failure can be handled remotely or whether an on-site response is required, a travel expense table T6 that lists the time and expense required for a travel, and failure cause estimation results T7. The failure cause estimation results T7 are a list of failure causes (failure modes) estimated based on the input failure information and the maintenance knowledge Bayesian network BN, associated with their respective occurrence probabilities, and listed in order of occurrence probability.

[0026] (Maintenance knowledge data T1 according to embodiment 1) FIG. 2 is a diagram showing the configuration of maintenance knowledge data T1 according to the first embodiment. Functional failure T11 indicates a failure phenomenon such as cooling water not circulating or component 2 not being able to be stored. Failure mode T12 indicates the cause of the failure. Check item T13 is a column for storing items to be checked, such as equipment sensor data, environment, equipment, components, etc. Check item T13 is used to identify phenomena that can occur when a failure mode occurs and to check whether the phenomenon has occurred. There is not necessarily one check item corresponding to one failure mode. Alarm T14 includes information about alarms that frequently occur when a failure corresponding to functional failure T11 occurs.

[0027] (Failure probability data T2 according to embodiment 1) 3 is a diagram showing failure probability data T2 according to the first embodiment. The failure probability data T2 is data for setting a probability that is set when creating a Bayesian network. The failure probability data T2 includes a failure mode T21 in which the name of the failure mode is stored, a state T22, and a probability T23. The occurrence probability of each failure mode can be known based on the failure probability data T2.

[0028] The state T22 stores Y or N. "Y" in the state T22 means that the failure mode has occurred, and "N" means that the failure mode has not occurred. These states are set so that the sum of the respective probabilities T23 of Y and N related to the same failure mode is 1.

[0029] Probability T23 stores the probability of the failure mode state. Here, the failure mode probability may be set to a fixed value such as 50% as the probability corresponding to the failure mode states Y and N. However, this is not limited to this, and calculations can also be made from past history, etc. The probability of the failure mode occurrence state is, for example, the value obtained by dividing the number of occurrences of the failure mode in the failure history by the total number of occurrences.

[0030] (Child Node Abnormality Occurrence Probability T3 When Parent Node Abnormality Occurs According to Embodiment 1) 4 is a diagram showing the child node abnormality occurrence probability T3 when the parent node is abnormal according to embodiment 1. The child node abnormality occurrence probability T3 when the parent node is abnormal includes a parent node T31, a state T32, a child node T33, a child node state T34, and a probability T35. The child node abnormality occurrence probability T3 when the parent node is abnormal indicates the probability of abnormality or normality of the check item of the child node when a failure mode in the parent node occurs.

[0031] The parent node T31 stores the name of the failure mode. The state T32 stores Y, which indicates the occurrence state of the failure mode.

[0032] A check item is stored in child node T33. Child node status T34 stores the status of the check item, and stores the status of the part corresponding to child node T33. Probability T35 stores the probability of the status of the check item stored in child node T33. The sum of the abnormal and normal probabilities related to the status of the same check item is set to 1.0 (100%). Note that fixed values such as abnormal: 100% and normal: 0% may also be set. The fixed values can be calculated from past failure history.

[0033] (Child Node Abnormality Occurrence Probability T4 When Parent Node is Normal According to Embodiment 1) 5 is a diagram showing the child node abnormality occurrence probability T4 when the parent node is normal according to embodiment 1. The child node abnormality occurrence probability T4 when the parent node is normal includes a child node T41, a child node state T42, and a probability T43.

[0034] A check item is stored in child node T41. A child node status T42 stores the status of the check item, and stores the status of the part corresponding to child node T41. A probability T43 stores the probability of the status of the check item stored in child node status T42. The sum of the abnormal and normal probabilities related to the status of the same check item is set to 1.0 (100%). Note that fixed values such as abnormal: 100% and normal: 0% may also be set. The fixed values can be calculated from past failure history.

[0035] (Fault Cause Response Method Table T5 according to the First Embodiment) 6 is a diagram showing the configuration of a failure cause response method table T5 according to embodiment 1. The failure cause response method table T5 contains information used in the check item search process (FIG. 14) described later. The failure cause response method table T5 includes a failure mode T51, a response method T52, and a response time T53.

[0036] The response method T52 is information indicating whether the repair can be performed by on-site or remotely for the failure mode T51. The response time T53 is the work time required to perform the action for each failure mode T51.

[0037] (Travel Expense Table T6 According to First Embodiment) 7 is a diagram showing the configuration of a travel expense table T6 according to the first embodiment. The travel expense table T6 contains information used in the failure cause presentation process (FIG. 16) described below. The travel expense table T6 includes customer names T61, travel time T62 required to travel to the customer's site, transportation costs T63 required to travel to the customer's site, and labor costs T64. The labor costs T64 are the labor costs per hour per worker for each customer name T61.

[0038] (Maintenance Knowledge Bayesian Network BN According to Embodiment 1) 8 is a diagram showing a maintenance knowledge Bayesian network BN according to embodiment 1. The maintenance knowledge Bayesian network BN is a Bayesian network with a four-layer structure of alarms BN1, functional failures BN2, failure modes BN3, and check items BN4. In the maintenance knowledge Bayesian network BN, arrows represent causal relationships, with the base of the arrow being a parent node and representing a cause, and the tip of the arrow being a child node and representing a result.

[0039] (Maintenance Knowledge Bayesian Network Generation Process According to First Embodiment) 9 is a flowchart showing the maintenance knowledge Bayesian network generation process according to embodiment 1. The maintenance knowledge Bayesian network generation process is executed by the failure cause estimation unit 31 using the maintenance knowledge data T1 stored in the asset knowledge database 41.

[0040] First, in step S11, the failure cause estimation unit 31 acquires maintenance knowledge data T1 from the asset knowledge database 41. Next, in step S12, the failure cause estimation unit 31 creates nodes of the maintenance knowledge Bayesian network BN from each cell of the maintenance knowledge data T1. At this time, the failure cause estimation unit 31 generates cells with the same content as one node.

[0041] Next, in step S13, the failure cause estimation unit 31 establishes parent-child relationship links for each node of the maintenance knowledge Bayesian network BN generated in step S12, in accordance with the causal relationships described in the maintenance knowledge data 18. Specifically, the causal relationships (parent-child relationships) are such as "failure mode" → "functional failure," "failure mode" → "check item," and "functional failure" → "alarm," and arrows representing the causal relationships are set for each node.

[0042] Next, in step S14, the failure cause estimation unit 31 sets the probability of the failure probability data T2 as a priori probability for the arrow set in step S13. Next, in step S15, the failure cause estimation unit 31 sets a posterior probability for the arrow indicating the parent-child relationship using the child node abnormality occurrence probability T3 when the parent node is abnormal and the child node abnormality occurrence probability T4 when the parent node is normal.

[0043] (Flowchart showing a fault cause estimation process according to the first embodiment) FIG. 10 is a flowchart showing the failure cause estimation process according to the first embodiment.

[0044] First, in step S21, the failure cause estimation unit 31 receives information on the symptoms of the failure from a maintenance worker operating the maintenance worker terminal 6 via the input / output unit 5. The maintenance worker operates the input screen D1 (Fig. 17) to input "abnormal" or "normal" in the check items on the screen, thereby inputting information on the equipment failure. "Abnormal" means that an abnormality has occurred, and "normal" means that an abnormality has not occurred. If it is unclear whether an abnormality has occurred, do not check "Abnormal". For example, if there is information that "oil is leaking," the maintenance worker checks "Abnormal" in the check item "oil is leaking."

[0045] Next, in step S22, the failure cause estimation unit 31 generates a maintenance knowledge Bayesian network BN based on the information input in step S21. Next, in step S23, the failure cause estimation unit 31 calculates the occurrence probability of each failure mode using the maintenance knowledge Bayesian network BN, and outputs the failure cause estimation result T7 to the failure cause presentation unit 33.

[0046] (Results of failure cause estimation according to the first embodiment) 11 is a diagram showing a failure cause estimation result T7 according to embodiment 1. In step S23, an occurrence probability T72 corresponding to each failure mode T71 is calculated, as in the failure cause estimation result T7 shown in FIG.

[0047] (Check Item Search Process According to the First Embodiment) 12 is a diagram showing an outline of the check item search process according to embodiment 1. The check item search process extracts failure modes whose response method is "on-site visit" from the failure cause estimation results, and extracts check items that should be checked by maintenance personnel who have visited the site to investigate whether or not these failure modes have occurred.

[0048] As an example of the check item search process, as shown in Figure 12, suppose a symptom of "oil leaking" occurs and a maintenance worker checks "oil leaking." In this case, the failure mode "sticking of part 3" is linked only to "oil leaking" (the link shown by the dashed line), so there is no need to check other check items to investigate the occurrence of the failure mode "sticking of part 3." For other failure modes, it would be better to check the check item "abnormal noise" (shown in hatching) for the failure mode "poor installation of part 1," and "oil dripping" and "high internal temperature" (shown in hatching) for the failure mode "damage to part 4." For this reason, such check items are extracted. The check item search process can obtain information on the check items that maintenance workers should check, and this information is used in the failure cause presentation process (Figure 15).

[0049] (Check item search process for survey target according to the first embodiment) 13 is a diagram showing a flowchart of a check item search process for an investigation target according to embodiment 1. The check item search process processes the failure cause estimation results T7 one by one using the maintenance knowledge data T1 and the failure cause response method table T5.

[0050] First, in step S31, the check item search unit 32 reads the maintenance knowledge data T1, the failure cause response method table T5, and one unprocessed record of the failure cause estimation result T7. Then, the check item search unit 32 searches the failure cause response method table T5 based on the failure mode included in the read failure cause estimation result T7, and obtains the response method that corresponds to either on-site or remote work for the failure mode.

[0051] Next, in step S32, the check item search unit 32 determines whether the response method for the failure mode read in step S31 is a business trip. If it is a business trip (step S32: Yes), the check item search unit 32 proceeds to step S33, and if it is remote (step S32: No), the check item search unit 32 returns to step S31.

[0052] Next, in step S33, the check item search unit 32 refers to the maintenance knowledge data T1 and acquires check items corresponding to the failure mode determined to be a business trip in step S32. However, in step S33, check items that have already been acquired are excluded so as not to be acquired redundantly.

[0053] Next, in step S34, the check item search unit 32 outputs the failure mode determined to be a business trip in step S32, the check items to be investigated acquired in step S33, and the response method and response time acquired from the failure cause response method table T5. This information is output to the check items to be investigated T8 (FIG. 14).

[0054] Next, in step S37, the check item search unit 32 determines whether all records of the failure cause estimation results T7 have been processed. If all records of the failure cause estimation results T7 have been processed (Yes in step S35), the check item search unit 32 ends the check item search process. On the other hand, if there are any records of the failure cause estimation results T7 that have not been processed (No in step S35), the check item search unit 32 returns the process to step S31.

[0055] (Survey target check item T8 according to embodiment 1) FIG. 14 is a diagram showing check items T8 to be investigated according to the first embodiment. The check items T8 to be investigated include a failure mode T81, a check item T82, a response method T83, and a probability T84. The check item T82 is a check item that should be checked to investigate whether or not a failure mode in the failure cause estimation result T7 has occurred, in addition to the check items already entered by the maintenance personnel. The response method T83 is a response method of on-site or remote work corresponding to the failure mode T71 in the failure cause estimation result T7, and after the check item search process (FIG. 13) is performed, only the on-site failure mode is included. The probability T84 is the occurrence probability of the failure mode in the failure cause estimation result T7.

[0056] (Fault cause presentation process according to the first embodiment) 15 is a flowchart showing the failure cause presentation process according to the first embodiment. The failure cause presentation process is a process for generating a ranking of the priority order of which failure mode the maintenance personnel will deal with first during the current visit. The failure cause presentation process reads the check items T8 to be investigated that were generated in the check item search process (FIG. 13).

[0057] First, in step S41, the failure cause presenting unit 33 searches for K (a predetermined number) check items from the check items T8 to be investigated.

[0058] Next, in step S42, the failure cause presentation unit 33 obtains the travel time T62, transportation costs T63, and labor costs T64 corresponding to the customer name entered by the maintenance worker via the input / output unit 5 from the travel expense table T6.

[0059] Next, in step S43, the failure cause presentation unit 33 calculates the expected cost C of a future business trip according to formula (1-1) if the priority cost is a financial cost, or according to formula (1-2) if the priority cost is a time cost. 後日 P (failure cause) is the probability of occurrence of the failure mode during the processing of the failure cause estimation result T7. The priority cost is set from the input screen (Fig. 7) described later. Cost C 後日 is an example of the second cost. The cost C based on the formula (1-1) 後日 is the expected value of the cost in monetary terms. The cost C based on formula (1-2) 後日 is the expected time-based cost. C 後日 =P(Failure cause)Business trip×(T 交通 ×M 人件費 / H +M 交通費 +T 対応時間 ×M 人件費 / H ) (1-1) C 後日 =P(Failure cause)Business trip×(T 交通 +T 対応時間 ) (1-2)

[0060] Next, in step S44, the failure cause presentation unit 33 calculates the cost C of the investigation time expected for this business trip according to formula (2-1) if the priority cost is the financial cost, or according to formula (2-2) if the priority cost is the time cost. 本日 Calculate the cost C 本日 is an example of the first cost. The cost C based on the formula (2-1) 本日 is the expected value of the cost in monetary terms. The cost C based on formula (2-2) 本日 is the expected time-based cost. C 本日 = [Number of check items K × T 点検時間 +P(failure cause)×T 対応時間 ]×M 人件費 / H (2-1) C 本日 = [Number of check items K × T 点検時間 +P(failure cause)×T 対応時間 ] (2-2)

[0061] Next, in step S45, the fault cause presentation unit 33 後日 and C 本日 Ratio C 後日 / C 本日 =C 優先度 Calculate the ratio C 優先度 Based on this, the failure modes are ranked in the form of cost ratio calculation result T9 (FIG. 16).

[0062] (Cost Ratio Calculation Result T9 According to Embodiment 1) 16 is a diagram showing a cost ratio calculation result T9 according to the first embodiment. The cost ratio calculation result T9 includes a failure mode T91, a cost ratio T92, a check item T93, and a probability T94. The cost ratio T92 is calculated by multiplying the ratio C calculated in the failure cause presentation process (FIG. 15). 優先度 is.

[0063] (Input screen D1 according to embodiment 1) Fig. 17 is a diagram showing an input screen D1 according to the first embodiment. The input screen D1 has an input form for inputting a customer name, an alarm, check boxes for inputting check items, and a check box for inputting a priority cost (a type of cost that takes priority between financial cost and time cost). After inputting the input information, when the failure cause presentation button is clicked, the failure cause estimation process (Fig. 10), the check item search process for the investigation target (Fig. 13), and the failure cause presentation process (Fig. 15) are executed in sequence, and the screen transitions to the display of the result screen D2 shown in Fig. 18.

[0064] (Result screen D2 according to embodiment 1) 18 is a diagram showing a result screen D2 according to the first embodiment. The result screen D2 displays a cost ratio calculation result T9. By referring to the result screen D2, a maintenance technician can determine high-priority failure modes and check items that should be checked. The cost ratio calculation result T9 is not limited to being presented on the result screen D2, and may be presented in an interactive format using an interface such as a generation AI (Artificial Intelligence).

[0065] (Effects of the First Embodiment) In the first embodiment, a failure cause that should be dealt with as a priority among failure causes that require a visit is output to a terminal based on the ratio of a first cost in the case where a maintenance worker responds on the current visit to a second cost in the case where the failure cause recurs and the maintenance worker makes another visit to deal with the cause next time onward. Therefore, when a maintenance worker is on a visit, the maintenance worker can recognize a failure mode that should be dealt with as a priority within a limited time and can deal with the failure efficiently.

[0066] In the first embodiment, the cause of a failure that should be addressed with priority is output to the terminal based on the expected value of the monetary cost based on the response time of the maintenance personnel to respond to the failure, the travel time of the maintenance personnel to travel to the customer's site, and the labor cost of the maintenance personnel as the first cost and the second cost. This makes it possible to efficiently respond to failures while reducing wasteful monetary costs.

[0067] In the first embodiment, the cause of the failure to be dealt with on a priority basis is output to the terminal based on the expected value of the time-based cost based on the response time of the maintenance personnel to deal with the failure and the travel time of the maintenance personnel to travel to the customer's site as the first cost and the second cost, thereby making it possible to efficiently deal with the failure while reducing time wastage.

[0068] Furthermore, in the first embodiment, a maintenance knowledge Bayesian network is generated based on the input failure information and maintenance knowledge data, including parent-child relationships that represent the causal relationships from failure modes to functional failures and alarms, and parent-child relationships that represent the causal relationships from failure modes to check items. Furthermore, the occurrence probability of each failure mode in the maintenance knowledge Bayesian network is calculated using the child node abnormality occurrence probability data when the parent node is abnormal and the child node abnormality occurrence probability data when the parent node is normal. Therefore, it is possible to determine the occurrence probability of a failure mode with a high likelihood based on the Bayesian network, and to present failure modes that should be addressed with priority based on this occurrence probability.

[0069] [Embodiment 2] In the second embodiment, a history of past failure cause presentations is used to improve the accuracy of the failure cause presentation unit 33. In the following, in each drawing for explaining this embodiment, differences from the first embodiment will be mainly explained, and the same components as those in the first embodiment will be given the same names and symbols, and repeated explanations will be omitted.

[0070] (Equipment maintenance system 1B according to embodiment 2) 19 is a diagram showing the configuration of an equipment maintenance system 1B according to embodiment 2. Compared with the equipment maintenance system 1 according to embodiment 1, the equipment maintenance system 1B further includes a failure cause presentation and update unit 34 and a failure cause response history database 43.

[0071] (Fault Cause Response History T10 According to the Second Embodiment) 20 is a diagram showing a failure cause response history T10 according to the second embodiment. The failure cause response history T10 is stored in the failure cause response history database 43. The failure cause response history T10 includes information on the work date T101 on which the work was performed, the failure mode T102 which is the investigation result of the work target, and the check item T103 which was entered when the failure mode T102 was identified. The failure cause response history T10 manages the failure mode and check items that were actually handled by the maintenance personnel by referring to the failure cause estimation result T7.

[0072] (Fault cause presentation update process according to the second embodiment) FIG. 21 is a flowchart showing the fault cause presentation update process according to the second embodiment.

[0073] The failure cause presentation update process is executed after the failure cause presentation process (FIG. 15) of the first embodiment is executed. In the failure cause presentation update process, a history of the past failure cause response history T10 is searched for the same check item as the check item input by the maintenance worker this time, and the ratio C of the corresponding failure mode included in the processing result by the failure cause presentation unit 33 is calculated. 後日 / C 本日 is multiplied by a positive parameter α. As a result, the ranking of the corresponding failure mode is raised in the current failure cause presentation result, and the priority of the corresponding failure mode is made higher for maintenance personnel. The parameter α is a fixed or variable parameter greater than 1, for example.

[0074] First, in step S51, the failure cause presentation unit 33 reads in the cost ratio calculation result T9 (FIG. 16) one record at a time. Next, in step S52, the failure cause presentation unit 33 refers to the failure cause response history T10 (FIG. 20) and searches for a check item T103 that is the same as the check item T93 included in the record read in step S51.

[0075] Next, in step S53, the failure cause presentation unit 33 determines whether or not the failure cause response history T10 (FIG. 20) contains a check item T103 that is the same as the check item T93 included in the record of the cost ratio calculation result T9 read in step S51. If the same check item T103 exists (step S53: Yes), the failure cause presentation unit 33 proceeds to step S54. On the other hand, if the same check item T103 does not exist (step S53: No), the failure cause presentation unit 33 returns the process to step S51.

[0076] In step S54, the failure cause presentation unit 33 determines whether the failure mode T102 corresponding to the check item T103 determined to be identical to the check item T93 in the failure cause response history T10 is identical to the failure mode T91 corresponding to the cost ratio calculation result T9. If the failure mode T102 and the failure mode T91 are identical (step S54: Yes), the failure cause presentation unit 33 proceeds to step S55. On the other hand, if the failure mode T102 and the failure mode T91 are different (step S54: No), the failure cause presentation unit 33 returns the process to step S51.

[0077] In step S55, the failure cause presentation unit 33 multiplies the cost ratio T92 of the cost ratio calculation result T9 for which it was determined in steps S53 and S54 that a record with the same check item and failure mode exists in the failure cause response history T10 by the parameter α.

[0078] (Effects of the second embodiment) In the second embodiment, when the failure cause response history contains data with the same failure mode and check item as the cost ratio calculation result, the ratio corresponding to the failure mode and check item in the cost ratio calculation result is multiplied by a predetermined parameter to update the ratio. Therefore, by multiplying by a parameter the ratio of the cost ratio calculation result having the same failure mode and check item as the past failure response history and emphasizing it, the accuracy of the failure cause presentation function can be improved using the history of past failure cause presentations.

[0079] Although the embodiments of the present disclosure have been described above in detail, the present disclosure is not limited to the above-described embodiments and can be modified in various ways without departing from the spirit of the present disclosure. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present disclosure is not necessarily limited to those having all of the described configurations. Furthermore, some of the configurations of the above-described embodiments can be added to, deleted from, or replaced with other configurations.

[0080] Furthermore, the above-described configurations, functional units, processing units, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software by 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 memory, storage devices such as HDDs and SSDs, or recording media such as IC cards, SD cards, and DVDs.

[0081] In addition, in the above-mentioned drawings, the control lines and information lines shown are those that are considered necessary for explanation, and do not necessarily show all the control lines and information lines that are actually implemented. For example, it may be considered that almost all components are actually connected to each other.

[0082] The above-described arrangement of the processing functions and data is merely an example, and the arrangement of the processing functions and data can be changed to an optimal arrangement in terms of the performance of the hardware and software, processing efficiency, communication efficiency, etc. [Explanation of symbols]

[0083] 1, 1B: Equipment maintenance system, 5: Input / output section, 6: Maintenance worker terminal, 18: Maintenance knowledge data, 31: Failure cause estimation section, 32: Check item search section, 33: Failure cause presentation section, 34: Failure cause presentation update section, 41: Asset knowledge database, 42: Failure mode response method database, 43: Failure cause response history database, BN: Maintenance knowledge Bayesian network, T1: Maintenance knowledge data, T2: Failure probability data, T3: Child node abnormality occurrence probability when parent node is abnormal, T4: Child node abnormality occurrence probability when parent node is normal, T5: Failure cause response method table, T6: Travel cost table, T7: Failure cause estimation result, T8: Check items to be investigated, T9: Cost ratio calculation result, T10: Failure cause response history.

Claims

1. An equipment maintenance system for maintaining and managing equipment, an asset knowledge database in which failure information regarding a failure of the equipment, the cause of the failure, whether or not a maintenance technician needs to visit the equipment in the event of the failure, and the cost required to respond to the failure are managed in association with each other; an input unit that accepts input of the failure information related to the facility; a failure cause estimation unit that refers to the asset knowledge database based on the failure information input and accepted by the input unit, and estimates a plurality of failure causes of the failure; a failure cause presentation unit that calculates a ratio of a first cost in the case where the maintenance staff responds to a failure cause requiring a visit among the plurality of failure causes estimated by the failure cause estimation unit on the current visit to a second cost in the case where the failure cause occurs again in the next or subsequent visits and the maintenance staff responds by making the visit again; an output unit that outputs to a terminal the failure cause that should be dealt with with priority among the failure causes that require a business trip based on the ratio calculated by the failure cause presentation unit; and An equipment maintenance system comprising:

2. 2. The equipment maintenance system according to claim 1, a failure mode response method database in which the response time required for each failure cause, the travel time required for the business trip for each customer who installs the equipment, the transportation costs required for the business trip, and the labor costs of the maintenance personnel are managed; The failure cause presentation unit Calculating expected values of monetary costs based on the response time, the travel time, and the labor costs as the first cost and the second cost. A facility maintenance system characterized by:

3. 2. The equipment maintenance system according to claim 1, a failure mode response method database in which the response time required for response to each failure cause and the travel time required for the business trip to each customer who installs the equipment are managed; The failure cause presentation unit Calculating expected values of time-based costs based on the response time and the travel time as the first cost and the second cost. A facility maintenance system characterized by:

4. 2. The equipment maintenance system according to claim 1, The asset knowledge database comprises: maintenance knowledge data for managing, in association with one another, functional failures that represent the failures as phenomena, failure modes that represent classifications of the functional failures, check items that the maintenance personnel should check in the event of the failure modes, and types of alarms that are issued in the event of the functional failures; Failure probability data for managing the occurrence probability of each of the failure modes; child node abnormality occurrence probability data when a parent node is abnormal, which manages the probability that the check item corresponding to the failure mode in the maintenance knowledge data becomes abnormal or normal when the failure mode occurs; and child node abnormality occurrence probability data when the parent node is normal, which manages the probability that the check item corresponding to the failure mode in the maintenance knowledge data becomes abnormal or normal when the failure mode does not occur, The failure cause estimation unit generating a maintenance knowledge Bayesian network based on the failure information and the maintenance knowledge data input by the input unit, the maintenance knowledge network including a parent-child relationship representing a causal relationship from the failure mode to the functional failure and the alarm, and a parent-child relationship representing a causal relationship from the failure mode to the check item; Using the data on the probability of abnormality occurrence of the child node when the parent node is abnormal and the data on the probability of abnormality occurrence of the child node when the parent node is normal, the probability of occurrence of each of the failure modes in the maintenance knowledge Bayesian network is calculated and output. A facility maintenance system characterized by:

5. 5. The equipment maintenance system according to claim 4, The failure cause presentation unit generating a cost ratio calculation result by associating the failure mode, the ratio, the check item, and the occurrence probability; The output unit The cost ratio calculation result is output to the terminal. A facility maintenance system characterized by:

6. 6. The equipment maintenance system according to claim 5, a failure cause presentation and update unit that stores the failure mode and the check items dealt with by the maintenance engineer as a failure cause handling history; The failure cause presentation update unit If the failure cause response history contains data in which the failure mode and check item are identical to the cost ratio calculation result, the ratio corresponding to the failure mode and check item in the cost ratio calculation result is multiplied by a predetermined parameter to update the ratio. A facility maintenance system characterized by:

7. An equipment maintenance method executed by an equipment maintenance system for maintaining and managing equipment, comprising: The equipment maintenance system includes: a processor; an asset knowledge database in which failure information regarding a failure of the equipment, the cause of the failure, whether or not a maintenance technician needs to visit the equipment in the event of the failure, and the cost required to respond to the failure are managed in association with each other; The processor: Accepting input of the failure information related to the equipment; referencing the asset knowledge database based on the received input of the failure information, and estimating a plurality of causes of the failure; For a failure cause that requires a business trip among the estimated plurality of failure causes, a ratio is calculated between a first cost in the case where the maintenance staff responds to the failure cause on the current business trip and a second cost in the case where the failure cause occurs again in the next or subsequent cases and the maintenance staff responds by making the business trip again; Based on the ratio, the failure cause that should be dealt with with priority among the failure causes that require a business trip is output. An equipment maintenance method characterized by comprising each process.

8. The equipment maintenance method according to claim 7, The equipment maintenance system includes: a failure mode response method database in which the response time required for each failure cause, the travel time required for the business trip for each customer who installs the equipment, the transportation costs required for the business trip, and the labor costs of the maintenance personnel are managed; The processor: Calculating expected values of monetary costs based on the response time, the travel time, and the labor costs as the first cost and the second cost.

1. A facility maintenance method comprising:

9. The equipment maintenance method according to claim 7, a failure mode response method database in which the response time required for response to each failure cause and the travel time required for the business trip to each customer who installs the equipment are managed; The processor: Calculating expected values of time-based costs based on the response time and the travel time as the first cost and the second cost.

1. A facility maintenance method comprising:

10. The equipment maintenance method according to claim 7, The asset knowledge database comprises: maintenance knowledge data for managing, in association with one another, functional failures that represent the failures as phenomena, failure modes that represent classifications of the functional failures, check items that the maintenance personnel should check in the event of the failure modes, and types of alarms that are issued in the event of the functional failures; Failure probability data for managing the occurrence probability of each of the failure modes; child node abnormality occurrence probability data when a parent node is abnormal, which manages the probability that the check item corresponding to the failure mode in the maintenance knowledge data becomes abnormal or normal when the failure mode occurs; and child node abnormality occurrence probability data when the parent node is normal, which manages the probability that the check item corresponding to the failure mode in the maintenance knowledge data becomes abnormal or normal when the failure mode does not occur, The processor: generating a maintenance knowledge Bayesian network based on the failure information and maintenance knowledge data whose inputs have been accepted, the maintenance knowledge network including a parent-child relationship representing a causal relationship from the failure mode to the functional failure and the alarm, and a parent-child relationship representing a causal relationship from the failure mode to the check item; Using the data on the probability of abnormality occurrence of the child node when the parent node is abnormal and the data on the probability of abnormality occurrence of the child node when the parent node is normal, the probability of occurrence of each of the failure modes in the maintenance knowledge Bayesian network is calculated and output.

1. A facility maintenance method comprising:

11. The equipment maintenance method according to claim 10, The processor: generating a cost ratio calculation result by associating the failure mode, the ratio, the check item, and the occurrence probability; Output the cost ratio calculation results 1. A facility maintenance method comprising:

12. The equipment maintenance method according to claim 11, The processor: The failure mode and the check items dealt with by the maintenance personnel are stored as a failure cause dealt with history, If the failure cause response history contains data in which the failure mode and check item are identical to the cost ratio calculation result, the ratio corresponding to the failure mode and check item in the cost ratio calculation result is multiplied by a predetermined parameter to update the ratio.

1. A facility maintenance method comprising:

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