JP6766982B2 - Elevator maintenance work support device - Google Patents

Description

The present invention relates to an elevator maintenance work support device.

Patent Document 1 describes an example of a maintenance work support device. The maintenance work support device stores information on the occurrence of an abnormality and information on measures for the abnormality as past cases. The maintenance work support device prioritizes past cases based on the correlation with the input data.

Japanese Patent No. 5820072

However, the maintenance work support device described in Patent Document 1 does not consider the accuracy of treatment. Therefore, high priority can be set for actions that are likely to recur after a temporary recovery.

The present invention has been made to solve such a problem. An object of the present invention is to provide an elevator maintenance work support device capable of setting the priority of treatment in consideration of the accuracy of treatment.

The maintenance work support device for an elevator according to the present invention has a history storage unit that stores failure information and information on measures for the failure, and a search unit that searches the history storage unit for a failure similar to the failure represented by the input data. A calculation unit that calculates the recurrence rate, which represents the rate of occurrence of failures similar to the failure within a predetermined period after the failure, for each failure searched by the search unit. And a priority setting unit for setting the priority of the treatment for the failure represented by the data based on the recurrence rate calculated by the calculation unit for each treatment.

According to the present invention, the priority setting unit sets the priority of treatment based on the recurrence rate for each treatment. As a result, the priority of the treatment can be set in consideration of the accuracy of the treatment.

It is a block diagram of the maintenance work support apparatus which concerns on Embodiment 1. FIG. It is a figure which shows the example of the failure history database which concerns on Embodiment 1. FIG. It is a figure which shows the example of the elevator attribute database which concerns on Embodiment 1. FIG. It is a figure which shows the example of the similar failure data table which concerns on Embodiment 1. FIG. It is a figure which shows the example of the join data table which concerns on Embodiment 1. FIG. It is a figure which shows the example of data processing in maintenance work support apparatus which concerns on Embodiment 1. FIG. It is a flowchart which shows the example of the operation of the maintenance work support apparatus which concerns on Embodiment 1. FIG. It is a flowchart which shows the example of the operation of the determination part which concerns on Embodiment 1. FIG. It is a flowchart which shows the example of the operation of the classification part which concerns on Embodiment 1. FIG. It is a figure which shows the hardware composition of the main part of the maintenance work support apparatus which concerns on Embodiment 1. FIG. It is a block diagram of the maintenance work support apparatus which concerns on Embodiment 2. FIG. It is a figure which shows the example of the recurrence rate database which concerns on Embodiment 2. It is a figure which shows the example of the recurrence rate calculated by the calculation part which concerns on Embodiment 3.

A mode for carrying out the present invention will be described with reference to the accompanying drawings. In each figure, the same or corresponding parts are designated by the same reference numerals, and duplicate description will be appropriately simplified or omitted.

Embodiment 1.
FIG. 1 is a configuration diagram of a maintenance work support device according to the first embodiment.

The maintenance work support device 1 is applied to the elevator 2.

The elevator 2 is provided in the building 3.

Building 3 has a plurality of floors. The hoistway 4 runs through each floor of the building 3. Each of the plurality of landings 5 is provided on each floor of the building 3. Each of the plurality of landings 5 faces the hoistway 4. Each of the plurality of landings 5 includes a landing door 6.

The elevator 2 includes a basket 7, a balance weight 8, a hoisting machine 9, and a main rope 10.

The car 7 is provided inside the hoistway 4 so as to be able to move up and down along a guide rail (not shown). The car 7 includes a car door 11. The car door 11 is configured so that when the car 7 is stopped on any of a plurality of floors, the landing door 6 can be interlocked to open and close. The balancing weight 8 is provided inside the hoistway 4 so as to be able to move up and down along a guide rail (not shown). The hoisting machine 9 is provided above the hoistway 4. The main rope 10 is wound around the hoisting machine 9. Both ends of the main rope 10 are held by the basket 7 and the balance weight 8, respectively.

The terminal device 12 is possessed by the maintenance staff 13.

The maintenance work support device 1 includes an input unit 101, a history storage unit 102, a search unit 103, a determination unit 104, an attribute storage unit 105, a classification unit 106, a calculation unit 107, and a priority setting unit 108. , And an output unit 109.

The input unit 101 is connected to the terminal device 12 through the communication line 14 so that failure data can be input. The communication line 14 is, for example, an internet line. The failure data is data representing a failure that occurs in the elevator 2. The failure data includes information such as the type and status of the failure. The failure data is input from the terminal device 12 by, for example, the maintenance staff 13. The failure data includes, for example, a failure code or free-form text set for each type of failure.

The history storage unit 102 is configured to store the failure history database. The failure history database is a database that stores failure history data. The failure history data is data including information on failures that have occurred in the past and information on measures for the failure.

The search unit 103 is connected to the input unit 101 so that failure data can be acquired. The search unit 103 is connected to the history storage unit 102 so that the failure history database can be accessed. The search unit 103 is configured to be able to obtain a similar failure data table corresponding to the failure data from the failure history database by searching. The similar failure data table is a data table including a plurality of similar failure data of the corresponding failure data. The similar failure data is data including information on a failure similar to the failure represented by the failure data and information on measures for the similar failure.

The determination unit 104 is connected to the search unit 103 so that a similar failure data table can be acquired. The determination unit 104 is configured to be able to determine the presence or absence of recurrence for each of the plurality of similar failure data included in the similar failure data table. The presence or absence of recurrence is a value indicating whether or not a failure similar to the failure has occurred within the recurrence determination period after the treatment for the failure. Similar failure data includes values for the presence or absence of recurrence. The recurrence determination period is a period predetermined for the determination unit 104.

The attribute storage unit 105 is configured to store the elevator attribute database. The elevator attribute database is a database that stores elevator attribute data. The elevator attribute data is data including information on the attributes of the elevator 2.

The classification unit 106 is connected to the determination unit 104 so that a similar failure data table in which the presence or absence of recurrence is determined for each of the similar failure data can be acquired. The classification unit 106 is connected to the attribute storage unit 105 so that the elevator attribute database can be accessed. The classification unit 106 is configured to be able to generate a join data table from a similar failure data table and an elevator attribute database. The joined data table is a data table containing a plurality of joined data. The combined data is data in which the similar failure data and the elevator attribute data of the elevator 2 in which the failure has occurred included in the similar failure data are combined. The classification unit 106 is configured so that each of the plurality of similar failure data included in the similar failure data table can be classified into a group corresponding to the attribute of the elevator 2 by the combined data table.

The calculation unit 107 is connected to the classification unit 106 so that each of a plurality of similar failure data classified into groups can be acquired. The calculation unit 107 is configured to be able to calculate the recurrence rate for each treatment based on the value of the presence or absence of recurrence included in the similar failure data.

The priority setting unit 108 is connected to the calculation unit 107 so that data representing the recurrence rate calculated for each treatment can be acquired. The priority setting unit 108 is configured so that the priority of treatment can be set based on the recurrence rate.

The output unit 109 is connected to the priority setting unit 108 so that data representing the priority of the set action can be acquired. The output unit 109 is connected to the terminal device 12 through the communication line 14 so that the treatment and the data representing the priority set for the treatment can be transmitted.

In the normal operation of the elevator 2, the main rope 10 is driven by the hoisting machine 9 to move. The car 7 and the balance weight 8 move up and down following the movement of the main rope 10. The car 7 responds to a call from the user by ascending and descending in the hoistway 4. The car 7 stops on the floor where the landing 5 is provided. The landing door 6 opens in conjunction with the car door 11. The user of the elevator 2 gets on or off the car 7 from the landing 5.

When a failure occurs in the elevator 2, the maintenance staff 13 inputs the failure data to the maintenance work support device 1 through the terminal device 12. The maintenance work support device 1 sets a priority for treatment based on the recurrence rate of a failure similar to the failure represented by the failure data. The maintenance work support device 1 outputs data representing the action and the priority set for the action to the terminal device 12. The terminal device 12 presents the action to the maintenance person 13 according to the set priority.

Subsequently, the failure history data will be described with reference to FIG.
FIG. 2 is a diagram showing an example of a failure history database according to the first embodiment.

The failure history data includes, for example, information for identifying the elevator 2 in which the failure has occurred, a failure occurrence date and time, a failure code, and a failure status as failure information. The information that identifies the elevator 2 is, for example, a building number and a unit number. The building number is a number that identifies each of the one or more buildings 3. The unit number is a number that identifies each of the one or more elevators 2 provided in the building 3. The failure occurrence date and time is the date and time when the failure occurred. The failure code is a code set for each type of failure. The failure status is a free text that describes the failure status. In addition, the failure history data may include recurrence data indicating that the same failure has occurred in the same elevator during a predetermined period. Recurrence data is code or free text data that represents the status of recurrence.

The failure history data includes, for example, a treatment code and a treatment content as treatment information. The action code is a code set for each type of action. The action content is a free text that describes the action content.

Subsequently, the elevator attribute data will be described with reference to FIG.
FIG. 3 is a diagram showing an example of an elevator attribute database according to the first embodiment.

The elevator attribute data includes, for example, a building number and a unit number as information for identifying the elevator 2. The elevator attribute data includes, for example, a model, a door closing method, and the number of years of completion as attribute information.

Subsequently, similar failure data will be described with reference to FIG.
FIG. 4 is a diagram showing an example of a similar failure data table according to the first embodiment.

FIG. 4 shows, as an example, a similar failure data table acquired from the failure history database of FIG. In this example, the failure data corresponding to the similar failure data table represents a failure similar to the failure of the failure status "door open / close failure".

The similar failure data table includes similar failure data of the failure of the failure status "door opening / closing failure" as a failure similar to the failure represented by the corresponding failure data. Similar failure data includes information included in the failure history data and a value of presence / absence of recurrence.

Subsequently, the combined data will be described with reference to FIG.
FIG. 5 is a diagram showing an example of a join data table according to the first embodiment.

FIG. 5 shows, as an example, a join data table generated from the similar failure data table of FIG. 4 and the elevator attribute database of FIG.

The combined data is data in which the elevator attribute data acquired from the elevator attribute database is combined with similar failure data using the information for identifying the elevator 2 as a key.

For example, in the similar failure data of the failure that occurred in the elevator 2 identified by the building number "1234567" and the machine number "001", the model "A", the door closing method "CO", and the number of years of completion " 10 ”is added. When there are a plurality of similar failure data of the failure generated in the elevator 2, attribute information is added to each of the plurality of similar failure data. Similarly, in the similar failure data of the failure that occurred in the elevator 2 identified by the building number "23456778" and the unit number "001", the model "B", the door closing method "2S", and the number of years of completion are used as the attributes of the elevator 2. "6" is added.

Subsequently, the function of the maintenance work support device 1 will be described with reference to FIG.
FIG. 6 is a diagram showing an example of data processing in the maintenance work support device according to the first embodiment.

The maintenance staff 13 inputs failure data to the input unit 101 through the terminal device 12. In this example, a failure with a failure code "F001" and a failure status "door opening / closing failure" has occurred in an elevator having a model "A", a door closing method "CO", and a completion age of "4".

The search unit 103 acquires failure data from the input unit 101. The search unit 103 acquires a similar failure data table corresponding to the failure data from the failure history database by searching. For example, when the failure codes of a plurality of failures match, the search unit 103 searches for similar failure data assuming that the plurality of failures are similar.

The determination unit 104 acquires a similar failure data table from the search unit 103. The determination unit 104 determines the presence or absence of recurrence for each of the plurality of similar failure data included in the acquired similar failure data table.

The determination unit 104 determines the presence or absence of recurrence as follows, for example. The determination unit 104 initializes the value of the presence / absence of recurrence by setting the value of the presence / absence of recurrence of all the similar failure data included in the similar failure data table to “none”. The determination unit 104 searches the similar failure data table for a pair of similar failure data in which the interval between the failure occurrence dates and times does not exceed the recurrence determination period. When the failure represented by each of the searched pair of similar failure data is a failure that occurred in the same elevator, the determination unit 104 determines whether or not there is a recurrence of the pair of similar failure data with the earlier failure occurrence date and time. Is "Yes". Here, the determination unit 104 calculates the interval of the failure occurrence date and time as a daily unit by truncating the unit below the hour. The recurrence determination period is k days with k as an integer. When the failure history data includes recurrence data, the determination unit 104 determines the presence or absence of recurrence by searching for the presence or absence of a code or text indicating recurrence.

The classification unit 106 acquires a similar failure data table for which the presence or absence of recurrence has been determined from the determination unit 104. The classification unit 106 generates a join data table from the acquired similar failure data table and the elevator attribute database. The classification unit 106 classifies each of the plurality of similar failure data included in the similar failure data table into groups corresponding to the attributes of the elevator 2 by the join data table.

The classification unit 106 classifies each of the plurality of similar failure data as follows, for example.

The classification unit 106 has a group list. The group list is a list that stores groups. The group list is a list whose initial state is empty. The group has a list of used attributes. The used attribute list is a list of the attributes of the elevator 2 that has already been used to classify the group having the list.

The classification unit 106 stores the entire plurality of similar failure data included in the similar failure data table in the group list as one unclassified group. The group has an empty list of used attributes.

The classification unit 106 repeats the following processing until the group list does not include unclassified groups. The classification unit 106 extracts one unclassified group from the group list. The classification unit 106 searches for one classification attribute from the attributes not included in the used attribute list of the extracted group. The classification attribute is an attribute in which there is a significant difference in the recurrence rate among the plurality of subgroups when the extracted group is classified into a plurality of subgroups according to the classification attribute. Here, the recurrence rate is calculated based on the value of the presence or absence of recurrence of similar failure data included in each of the plurality of subgroups. The classification unit 106 sets the usage attribute list of each of the plurality of subgroups as a list in which classification attributes are added to the usage attribute list of the extracted group. The classification unit 106 adds each of the plurality of subgroups to the group list as an unclassified group. On the other hand, when the classification attribute is not searched, the classification unit 106 returns the extracted group as a classified group to the group list.

Here, the classification unit 106 has a significant difference in the recurrence rate among the subgroups depending on the p value which is the significant probability of the null hypothesis that "there is no significant difference between the recurrence rates of the subgroups". Is determined. The classification unit 106 calculates a p-value for each of the attributes not included in the used attribute list of the extracted group. The classification unit 106 sets the attribute having the lowest p value as the classification attribute from the attributes having the p value lower than the significance level. If there is no attribute whose p value is lower than the significance level, the classification unit 106 determines that the classification attribute has not been searched. The classification unit 106 integrates the subgroups having no significant difference in recurrence rate among the plurality of subgroups classified by the classification attribute.

In this example, the classification by the classification unit 106 will be described more specifically. The classification unit 106 acquires 500 similar failure data tables. The classification unit 106 generates a join data table. The classification unit 106 stores an unclassified group including 500 combined data as a parent group in the group list. The used attribute list of the parent group is empty.

The classification unit 106 retrieves the parent group from the group list. The classification unit 106 searches for classification attributes from the attributes that are not included in the used attribute list of the parent group. When the p-value for the door-closing method is lower than the significance level and the p-value for other attributes, the classification unit 106 determines that the door-closing method is a classification attribute. The classification unit 106 classifies the parent group into subgroups such as "CO" and "2S" by the door closing method. When there is no statistically significant difference in the recurrence rate of the subgroups other than "CO" and "2S" in the door closing method, the classification unit 106 refers to the subgroups other than "CO" and "2S" as "other". Integrate as a subgroup of. The classification unit 106 stores in the group list a subgroup containing 200 combined data whose door closing method is “CO” as an unclassified group. The classification unit 106 stores in the group list a subgroup containing 200 combined data whose door closing method is “2S” as an unclassified group. The classification unit 106 stores in the group list a subgroup containing 100 combined data whose door closing method is “other” as an unclassified group. The list of attributes used by these groups includes the door closing method.

The classification unit 106 extracts a group whose door closing method is "CO" from the group list. The classification unit 106 determines the model as a classification attribute from the attributes excluding the door closing method included in the used attribute list. The classification unit 106 classifies the extracted group into subgroups of "A", "B", "C" and "Other" according to the model. The classification unit 106 stores in the group list a subgroup containing 50 combined data whose door closing method is “CO” and whose model is “A” as an unclassified group. The used attribute list of the group includes the door closing method and the model. Similarly, the classification unit 106 stores subgroups of models "B", "C", and "others" as unclassified groups in the group list.

The classification unit 106 extracts a group whose door closing method is "2S" from the group list. The classification unit 106 determines the number of years of completion as a classification attribute from the attributes excluding the door closing method included in the used attribute list. The classification unit 106 classifies the extracted groups into subgroups of "5 years or less" and "6 years or more" according to the number of years of completion. The classification unit 106 stores in the group list a subgroup containing 120 combined data having a door closing method of “CO” and a completion period of “5 years or less” as an unclassified group. The list of attributes used by the group includes the door closing method and the number of years of completion. Similarly, the classification unit 106 stores the subgroups whose completion years are “6 years or more” as unclassified groups in the group list.

The classification unit 106 extracts a group whose door closing method is “other” from the group list. The classification unit 106 searches for a classification attribute from the attributes excluding the door closing method included in the used attribute list. If there is no attribute whose p value for classification by the attribute is lower than the significance level among the attributes excluding the door closing method included in the used attribute list, the classification unit 106 determines that the classification attribute has not been searched. The classification unit 106 returns the subgroup containing 100 combined data whose door closing method is “other” to the group list as a classified group.

The classification unit 106 repeats the hierarchical classification of the groups according to the attributes of the elevator 2 until the group list does not include the unclassified list.

The calculation unit 107 acquires each of the plurality of similar failure data classified into the groups from the classification unit 106. The calculation unit 107 searches for a group corresponding to the attribute of the elevator 2 in which the failure has occurred. The calculation unit 107 calculates the recurrence rate for each treatment for the searched group. The recurrence rate is the ratio of the number of recurrences to the number of failures. The number of failures is the number of data included in the group. The number of recurrences is the number of data in which the value of presence / absence of recurrence is "Yes" among the data included in the group. The calculation unit 107 calculates the recurrence rate for each treatment even when there is no significant difference in the recurrence rate.

In this example, a group whose door closing method is "CO" and whose model is "A" is searched. The calculation unit 107 calculates the number of recurrences as 50% for 20 failures for which the treatment "inspection" was performed in the searched group. Similarly, the calculation unit 107 calculates the number of recurrences as 0% for 10 failures for which the treatment "board replacement" has been performed in the searched group.

The priority setting unit 108 acquires data representing the recurrence rate calculated for each treatment from the calculation unit 107. The priority setting unit 108 sets the highest priority in order from the treatment with the smallest recurrence rate. The priority setting unit 108 integrates lower-priority treatments as “others”.

In this example, the priority setting unit 108 sets the highest priority for the treatment "board replacement". The priority setting unit 108 sets the next highest priority for the treatment “inspection”.

The output unit 109 acquires data representing the priority of the set action from the priority setting unit 108. The output unit 109 transmits the treatment and data representing the priority set for the treatment to the terminal device 12.

The terminal device 12 presents the high-priority measures to the maintenance personnel 13 by displaying the actions in the order of priority.

Subsequently, the operation of the maintenance work support device 1 will be described with reference to FIGS. 7 to 9.
FIG. 7 is a flowchart showing an example of the operation of the maintenance work support device according to the first embodiment. FIG. 8 is a flowchart showing an example of the operation of the determination unit according to the first embodiment. FIG. 9 is a flowchart showing an example of the operation of the classification unit according to the first embodiment.

FIG. 7 shows the overall operation of the maintenance work support device 1.

In step S101, the input unit 101 acquires failure data. After that, the operation of the maintenance work support device 1 proceeds to step S102.

In step S102, the search unit 103 acquires a similar failure data table corresponding to the failure data by searching. After that, the operation of the maintenance work support device 1 proceeds to step S103.

In step S103, the determination unit 104 determines the presence or absence of recurrence for each of the similar failure data in the similar failure data table. After that, the operation of the maintenance work support device 1 proceeds to step S104.

In step S104, the classification unit 106 generates a join data table from the similar failure data table and the elevator attribute database. After that, the operation of the maintenance work support device 1 proceeds to step S105.

In step S105, the classification unit 106 classifies each of the plurality of similar failure data into groups corresponding to the attributes of the elevator 2 by the join data table. After that, the operation of the maintenance work support device 1 proceeds to step S106.

In step S106, the calculation unit 107 calculates the recurrence rate for each treatment for similar failures included in the group corresponding to the attribute of the elevator 2 in which the failure has occurred. After that, the operation of the maintenance work support device 1 proceeds to step S107.

In step S107, the priority setting unit 108 sets the priority of the action for the failure based on the calculated recurrence rate. After that, the output unit 109 transmits data representing the action and the priority set for the action. After that, the operation of the maintenance work support device 1 ends.

FIG. 8 shows the operation of the determination unit 104 in step S103 of FIG.

In step S201, the determination unit 104 acquires a similar failure data table including m similar failure data. After that, the determination unit 104 initializes the value of the presence / absence of recurrence in the similar failure data table. After that, the operation of the determination unit 104 proceeds to step S202.

In step S202, the determination unit 104 sorts the similar failure data table in ascending order according to the failure occurrence date and time. After that, the operation of the determination unit 104 proceeds to step S203.

In step S203, the determination unit 104 substitutes 0 for the loop variable i. After that, the operation of the determination unit 104 proceeds to step S204.

In step S204, the determination unit 104 determines whether i <m. If the determination result is Yes, the operation of the determination unit 104 proceeds to step S205. When the determination result is No, the operation of the determination unit 104 ends.

In step S205, the determination unit 104 substitutes i + 1 for the loop variable j. After that, the operation of the determination unit 104 proceeds to step S206.

In step S206, the determination unit 104 determines whether j ≦ m. When the determination result is No, the operation of the determination unit 104 proceeds to step S207. If the determination result is Yes, the operation of the determination unit 104 proceeds to step S208.

In step S207, the determination unit 104 adds 1 to the loop variable i. After that, the operation of the determination unit 104 proceeds to step S204.

In step S208, the determination unit 104 calculates the interval of the failure occurrence date and time for the i-th and j-th similar failure data. After that, the determination unit 104 determines whether the calculated interval is k days or less of the recurrence determination period. When the determination result is No, the operation of the determination unit 104 proceeds to step S207. If the determination result is Yes, the operation of the determination unit 104 proceeds to step S209.

In step S209, the determination unit 104 determines whether the failure represented by each of the i-th and j-th similar failure data is a failure that occurred in the same elevator. If the determination result is Yes, the operation of the determination unit 104 proceeds to step S210. When the determination result is No, the operation of the determination unit 104 proceeds to step S211.

In step S210, the determination unit 104 sets the value of the presence / absence of recurrence of the i-th similar failure data to “Yes”. After that, the operation of the determination unit 104 proceeds to step S211.

In step S211 the determination unit 104 adds 1 to the loop variable j. After that, the operation of the determination unit 104 proceeds to step S206.

FIG. 9 shows the operation of the classification unit 106 in step S105 of FIG.

In step S301, the classification unit 106 adds the entire plurality of similar failure data included in the similar failure data table to the group list initialized as one unclassified group. After that, the operation of the classification unit 106 proceeds to step S302.

In step S302, the classification unit 106 determines whether the group list includes an unclassified group. If the determination result is Yes, the operation of the classification unit 106 proceeds to step S303. When the determination result is No, the operation of the classification unit 106 ends.

In step S303, the classification unit 106 selects and retrieves one unclassified group from the group list. After that, the operation of the classification unit 106 proceeds to step S304.

In step S304, the classification unit 106 selects one attribute of the elevator 2 that has not yet been selected for the retrieved group. After that, the operation of the classification unit 106 proceeds to step S305.

In step S305, the classification unit 106 determines whether the selected attribute is included in the used attribute list of the extracted group. When the determination result is No, the operation of the classification unit 106 proceeds to step S306. If the determination result is Yes, the operation of the classification unit 106 proceeds to step S310.

In step S306, the classification unit 106 classifies the extracted group into a plurality of subgroups according to the selected attribute. After that, the operation of the classification unit 106 proceeds to step S307.

In step S307, the classification unit 106 calculates the recurrence rate for each of the plurality of subgroups. The classification unit 106 then calculates the p-value, which is the significance probability of the null hypothesis that "there is no significant difference between the recurrence rates of the subgroups classified by the selected attribute." After that, the operation of the classification unit 106 proceeds to step S308.

In step S308, the classification unit 106 determines whether the calculated p value is lower than the significance level. If the determination result is Yes, the operation of the classification unit 106 proceeds to step S309. When the determination result is No, the operation of the classification unit 106 proceeds to step S310.

In step S309, the classification unit 106 stores the selected attribute and the p-value for the attribute in the temporary list for the retrieved group. After that, the operation of the classification unit 106 proceeds to step S310.

In step S310, the classification unit 106 determines whether all the attributes of the elevator 2 have been selected for the group taken out. When the determination result is No, the operation of the classification unit 106 proceeds to step S304. If the determination result is Yes, the operation of the classification unit 106 proceeds to step S311.

In step S311 the classification unit 106 determines whether or not one or more attributes and one or more p-values for the attributes are stored in the temporary list for the retrieved group. When the determination result is No, the operation of the classification unit 106 proceeds to step S312. If the determination result is Yes, the operation of the classification unit 106 proceeds to step S313.

In step S312, the classification unit 106 determines that the classification attribute has not been searched. After that, the classification unit 106 adds the extracted group as a classified group to the group list. After that, the operation of the classification unit 106 proceeds to step S302.

In step S313, the classification unit 106 sets the attribute having the lowest p-value stored in the temporary list for the retrieved group as the classification attribute. After that, the classification unit 106 adds the attributes stored in the used attribute list of the extracted group to the used attribute list of the subgroup classified by the classification attribute. After that, the classification unit 106 adds the classification attribute to the used attribute list of the subgroup classified by the classification attribute. After that, the operation of the classification unit 106 proceeds to step S314.

In step S314, the classification unit 106 integrates a plurality of subgroups classified by the classification attribute with no significant difference in recurrence rate as one of the subgroups classified by the classification attribute. After that, the operation of the classification unit 106 proceeds to step S315.

In step S315, the classification unit 106 adds each of the plurality of subgroups classified by the classification attribute to the group list as an unclassified group. After that, the operation of the classification unit 106 proceeds to step S302.

As described above, the maintenance work support device 1 according to the first embodiment includes a history storage unit 102, a search unit 103, a calculation unit 107, and a priority setting unit 108. The history storage unit 102 stores failure information and information on measures for the failure. The search unit 103 searches the history storage unit 102 for a failure similar to the failure represented by the input failure data. Calculation unit 107, the failure to be searched to the search section 103 calculates a recurrence rate per treatment for that failure. The recurrence rate represents the rate at which a failure similar to the failure occurs within a predetermined period after the failure. The priority setting unit 108 sets the priority of the treatment for the failure represented by the failure data based on the recurrence rate calculated by the calculation unit 107 for each treatment.

The maintenance work support device 1 can determine a treatment with a high possibility of recurrence of a similar failure after a temporary recovery based on the recurrence rate calculated for each treatment. As a result, the maintenance work support device 1 can set the priority of the treatment in consideration of the accuracy of the treatment. The maintenance work support device 1 can present an appropriate treatment in consideration of the accuracy of the treatment to the maintenance staff 13 through the terminal device 12.

Further, the maintenance work support device 1 includes a determination unit 104. The determination unit 104 determines whether or not there is a recurrence of the failure searched by the search unit 103. The presence or absence of recurrence indicates whether or not a failure similar to the failure has occurred within a predetermined period after the failure. The calculation unit 107 calculates the recurrence rate for each treatment based on the presence or absence of recurrence determined by the determination unit 104.

The maintenance staff 13 or the administrator of the elevator 2 does not need to add information indicating the presence or absence of recurrence to the failure history database. As a result, the maintenance staff 13 or the manager of the elevator 2 can more easily use the maintenance work support device 1. The history storage unit 102 does not need to store information indicating the presence or absence of recurrence. As a result, the storage capacity required for the history storage unit 102 is reduced.

Further, the maintenance work support device 1 includes a classification unit 106. The classification unit 106 classifies the failure searched by the search unit 103 into a group corresponding to the attribute of the elevator 2 in which the failure has occurred. The calculation unit 107 calculates the recurrence rate for each treatment for the failures classified into the group corresponding to the attribute of the elevator 2 in which the failure represented by the failure data has occurred.

The calculation unit 107 calculates the recurrence rate in consideration of the attribute of the elevator 2 in which the failure has occurred. As a result, the priority setting unit 108 can set the priority of the treatment with higher accuracy.

Further, when there is a significant difference in the recurrence rate between the failures that occurred in the elevators 2 having different attributes, the classification unit 106 classifies them into groups according to the attributes.

The classification unit 106 and the calculation unit 107 divide the groups having a significant difference in the recurrence rate and calculate the recurrence rate. As a result, the priority setting unit 108 can set the priority of the treatment with higher accuracy.

The failure data may be input from the monitoring center outside the building 3 without relying on the maintenance staff 13. The failure data may be signal values of one or more sensors provided in the elevator 2. Failure data may be automatically entered when the signal values of one or more sensors are in the range of values representing the failure.

When the failure situations of a plurality of failures are similar, the search unit 103 may search for similar failure data assuming that the plurality of failures are similar. At this time, the search unit 103 calculates the degree of similarity between the failure situations by, for example, natural language processing.

The search unit 103 may search for similar failures by using a preset similarity determination table. The similarity determination table is a table showing whether or not a set of failures represented by a set of failure codes are similar.

The search unit 103 may search for similar failures according to the code system of the failure code. At this time, the code system of the failure code is set so that, for example, failures with similar failure codes are similar to each other.

When the failure data is the signal value of one or more sensors, the search unit 103 may search for a similar failure by the difference between the signal values. The search unit 103 calculates the difference between the signal values by, for example, the Euclidean distance.

The classification unit 106 may search for a numerical value that causes a significant difference in the recurrence rate when classifying into subgroups according to the attribute represented by the numerical value. For example, the classification unit 106 classifies into subgroups of "n or less" or "n + 1 or more" while changing the numerical value n of the attribute, and searches for the numerical value n that causes a significant difference in the recurrence rate of the subgroup. The attribute represented by a numerical value is, for example, the number of years of completion.

When a group containing a number of combined data less than a predetermined threshold value is obtained, the classification unit 106 does not have to perform the classification. For example, when the number of combined data included in the unclassified group extracted from the group list is less than the threshold value, the classification unit 106 may return the extracted group as a classified group to the group list as it is. When a subgroup containing a number of combined data less than the threshold value is obtained by classifying by the selected attribute, the classification unit 106 does not have to classify into the subgroup according to the attribute. Here, the threshold is predetermined as the lower limit of the number of combined data for which a reliable recurrence rate is calculated for the classified group. This prevents, for example, when a group of 100 cases is divided into 95 cases and 5 cases by classification, the reliability of the recurrence probability cannot be ensured because the number of cases divided is as small as 5 cases. Is done.

The terminal device 12 may present the high-priority treatment to the maintenance personnel 13 by displaying the treatment in different sizes or colors depending on the priority. The terminal device 12 may display the recurrence rate together with the treatment. The terminal device 12 may present the high-priority action to the maintenance personnel 13 by not displaying the low-priority action.

The terminal device 12 may accept the input of the treatment data by the maintenance staff after presenting the treatment to the maintenance staff 13. At this time, the terminal device 12 may add the failure data and the treatment data as failure history data to the failure history database stored in the history storage unit 102.

Subsequently, an example of the hardware configuration of the maintenance work support device 1 will be described with reference to FIG.
FIG. 10 is a diagram showing a hardware configuration of a main part of the maintenance work support device according to the first embodiment.

Each function of the maintenance work support device 1 can be realized by a processing circuit. The processing circuit includes at least one processor 1b and at least one memory 1c. The processing circuit may include at least one dedicated hardware 1a with or as a substitute for the processor 1b and the memory 1c.

When the processing circuit includes the processor 1b and the memory 1c, each function of the maintenance work support device 1 is realized by software, firmware, or a combination of software and firmware. At least one of the software and firmware is written as a program. The program is stored in the memory 1c. The processor 1b realizes each function of the maintenance work support device 1 by reading and executing the program stored in the memory 1c.

The processor 1b is also referred to as a CPU (Central Processing Unit), a processing device, an arithmetic unit, a microprocessor, a microcomputer, and a DSP. The memory 1c is composed of, for example, a non-volatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, EEPROM, a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a DVD, or the like.

When the processing circuit includes dedicated hardware 1a, the processing circuit is realized by, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof.

Each function of the maintenance work support device 1 can be realized by a processing circuit. Alternatively, each function of the maintenance work support device 1 can be collectively realized by a processing circuit. For each function of the maintenance work support device 1, a part may be realized by the dedicated hardware 1a, and the other part may be realized by software or firmware. As described above, the processing circuit realizes each function of the maintenance work support device 1 by the hardware 1a, the software, the firmware, or a combination thereof.

Embodiment 2.
In the second embodiment, the differences from the examples disclosed in the first embodiment will be described in detail. As for the features not described in the second embodiment, any of the features of the examples disclosed in the first embodiment may be adopted.

The configuration of the maintenance work support device 1 according to the second embodiment will be described.
FIG. 11 is a configuration diagram of the maintenance work support device according to the second embodiment.

The maintenance work support device 1 includes a generation unit 110 and a recurrence rate storage unit 111.

The generation unit 110 is configured to be able to comprehensively generate failure data, for example, regarding a failure code and a failure situation. The generation unit 110 is connected to the search unit 103 so as to be able to provide the failure data to be generated.

The recurrence rate storage unit 111 is configured to store the recurrence rate database. The recurrence rate database is a database that stores recurrence rate data. The recurrence rate data is data including information on the recurrence rate calculated by the calculation unit 107 for each treatment.

The search unit 103 is connected to the generation unit 110 so that failure data can be acquired.

The calculation unit 107 is connected to the recurrence rate storage unit 111 so that the recurrence rate database can be accessed.

The priority setting unit 108 is connected to the input unit 101 so that failure data can be acquired. The priority setting unit 108 is connected to the recurrence rate storage unit 111 so that the recurrence rate data can be acquired. The priority setting unit 108 is configured so that the priority of treatment can be set based on the recurrence rate.

The output unit 109 is connected to the priority setting unit 108 so that data representing the priority of the set action can be acquired. The output unit 109 is connected to the terminal device 12 through the communication line 14 so that the treatment and the data representing the priority set for the treatment can be transmitted.

Subsequently, the recurrence rate data according to the second embodiment will be described.
FIG. 12 is a diagram showing an example of a recurrence rate database according to the second embodiment.

The recurrence rate data includes, for example, a failure code and a failure status as failure information. The recurrence rate data includes the first attribute, the first item, the second attribute, and the second item as the information of the attributes used for the classification. The recurrence rate data includes a treatment code and a treatment content as treatment information. The recurrence rate data includes the number of failures, the number of recurrences, and the recurrence rate as information on the recurrence rate.

The first attribute is an attribute that classifies the entire similar failure data table into groups. The first item is the value of the first attribute. The second attribute is an attribute that classifies the group classified by the first attribute into a lower group. The second item is the value of the second attribute. The data of the second attribute and the second item is empty when it is not classified into a group lower than the group classified by the first attribute. The recurrence rate data includes information on the attribute that classifies the group classified by the second attribute into a lower group.

The number of failures is the number of similar failure data searched for each treatment. The number of recurrences is the number of similar failure data for which the presence or absence of recurrence was determined to be “presence” among the searched similar failure data. The recurrence rate is the ratio of the number of recurrences to the number of failures.

Recurrence rate data is generated, for example, as follows. For example, when the calculation load of the maintenance work support device 1 is low, the generation unit 110 transmits the generated failure data to the search unit 103. The search unit 103 acquires a similar failure data table corresponding to the failure data from the failure history database by searching. The determination unit 104 determines the presence or absence of recurrence for each of the plurality of similar failure data included in the similar failure data table. The classification unit 106 generates a join data table from the similar failure data table and the elevator attribute database. The classification unit 106 classifies each of the plurality of similar failure data included in the similar failure data table into groups corresponding to the attributes of the elevator 2 by the join data table. The calculation unit 107 calculates the recurrence rate for each treatment based on the value of the presence or absence of recurrence included in the similar failure data. The calculation unit 107 generates failure information, attribute information used for classification, treatment information, and recurrence rate information as recurrence rate data.

The recurrence rate data is used, for example, as follows. The input unit 101 receives input of failure data from the terminal device 12 by, for example, a maintenance worker 13. The priority setting unit 108 acquires failure data from the input unit 101. The priority setting unit 108 acquires recurrence rate data for each treatment for the group of attributes corresponding to the elevator 2 in which the failure has occurred with respect to the failure represented by the acquired failure data. The priority setting unit 108 sets the priority of the treatment for the failure represented by the failure data based on the recurrence rate data.

As described above, the maintenance work support device 1 according to the second embodiment includes a recurrence rate storage unit 111. The recurrence rate storage unit 111 stores the recurrence rate calculated by the calculation unit 107 for each treatment. The priority setting unit 108 sets the priority of the treatment for the failure represented by the failure data based on the recurrence rate stored in the recurrence rate storage unit 111.

The maintenance work support device 1 can perform processing such as determination or classification of recurrence before inputting failure data. Therefore, the maintenance work support device 1 reduces the calculation load from the input of the failure data to the setting of the priority. As a result, the maintenance work support device 1 can set a priority for the action immediately after the failure data is input.

The generation unit 110 may transmit the failure data to the search unit 103 at predetermined time intervals. That is, the recurrence rate database is updated at predetermined time intervals. Alternatively, the recurrence rate database may be updated when data is added to the history storage unit 102.

Embodiment 3.
In the third embodiment, the differences from the examples disclosed in the first embodiment or the second embodiment will be described in detail. As for the features not described in the third embodiment, any of the features of the examples disclosed in the first embodiment or the second embodiment may be adopted.

FIG. 13 is a diagram showing an example of the recurrence rate calculated by the calculation unit according to the third embodiment.

In FIG. 13, the horizontal axis represents the number of days elapsed after the failure treatment. The vertical axis represents the recurrence rate for the failure after treatment. Treatment α and treatment β represent different treatments for failures classified in the same group. In this example, the scheduled maintenance date for the elevator 2 in which the failure has occurred is 20 days after the input of the failure data representing the failure. The recurrence rate after 20 days is higher in treatment α than in treatment β. The recurrence rate after 50 days is higher in treatment β than in treatment α.

The determination unit 104 determines the interval until the failure recurs as a value for the presence or absence of recurrence. The determination unit 104 initializes the value of the presence / absence of recurrence by setting the value of the presence / absence of recurrence of all the similar failure data included in the similar failure data table to an integer value 0 representing “none”. When the interval between the failure occurrence dates and times of the pair of similar failure data is d days of k days or less, the determination unit 104 determines the value of the presence or absence of recurrence as an integer value d.

The calculation unit 107 calculates the recurrence rate every day after the failure. The recurrence rate for each day after the failure is an example of the recurrence rate for each elapsed time after the failure. The calculation unit 107 determines the ratio of the number of failures in which similar failures have recurred by d days after the treatment to the number of failures in which the treatment was performed for each treatment in the group classified by the classification unit 106, and the recurrence rate after d days. Calculate as.

The priority setting unit 108 sets a high priority for a treatment having a low recurrence rate on the next maintenance day. That is, the priority setting unit 108 sets the priority of the treatment β having a low recurrence rate after 20 days higher than that of the treatment α.

As described above, the calculation unit 107 of the maintenance work support device 1 according to the third embodiment calculates the recurrence rate for each elapsed time after the failure.

If the failure does not recur by the maintenance date, the maintenance staff 13 takes fundamental measures on the maintenance day to suppress the recurrence of the failure. If the recurrence rate by the maintenance date is low, the priority setting unit 108 can set a high priority even for emergency measures in which the recurrence rate becomes high after a long period of time. Therefore, the priority setting unit 108 can set a priority suitable for the treatment for the failure according to the interval until the scheduled maintenance date for the elevator 2 in which the failure has occurred.

The calculation unit 107 may calculate, for example, the recurrence rate every three days after the failure as the recurrence rate for each elapsed time after the failure.

When the recurrence rate on the next maintenance day is lower than the predetermined rate, the priority setting unit 108 may set the priority of the remote possible treatment high regardless of the maintenance staff 13. A remote possible procedure is, for example, a procedure of transmitting a maintenance control signal to the elevator 2.

The terminal device 12 may present the change in the recurrence rate for each treatment with respect to the elapsed days to the maintenance staff 13 by displaying it, for example, by a graph.

The maintenance work support device according to the present invention can be applied to an elevator.

1 Maintenance work support device, 101 input unit, 102 history storage unit, 103 search unit, 104 judgment unit, 105 attribute storage unit, 106 classification unit, 107 calculation unit, 108 priority setting unit, 109 output unit, 110 generation unit, 111 Recurrence rate storage, 1a hardware, 1b processor, 1c memory, 2 elevator, 3 building, 4 hoistway, 5 landing, 6 landing door, 7 car, 8 balanced weight, 9 hoist, 10 main rope 11 car doors, 12 terminal devices, 13 maintenance personnel, 14 communication lines

Claims (6)

A history storage unit that stores failure information and action information for the failure,
A search unit that searches the history storage unit for failures similar to the failures represented by the input data, and
With respect to the failure searched by the search unit, a calculation unit that calculates a recurrence rate representing the rate of occurrence of a failure similar to the failure within a predetermined period after the failure for each treatment for the failure. ,
A priority setting unit that sets the priority of the treatment for the failure represented by the data based on the recurrence rate calculated by the calculation unit for each treatment.
Elevator maintenance work support device equipped with. The search unit is provided with a determination unit for determining whether or not a failure similar to the failure has occurred within a predetermined period after the failure.
The elevator maintenance work support device according to claim 1, wherein the calculation unit calculates the recurrence rate for each treatment based on the presence or absence of the recurrence determined by the determination unit. A classification unit that classifies failures searched by the search unit into groups corresponding to the attributes of the elevator in which the failure occurred, and a classification unit.
With
The elevator maintenance work according to claim 1 or 2, wherein the calculation unit calculates the recurrence rate for each treatment for a failure classified into a group corresponding to the attribute of the elevator in which the failure represented by the data has occurred. Support device. The elevator maintenance work support device according to claim 3, wherein the classification unit classifies the elevators having different attributes into the group according to the attributes when there is a significant difference in the recurrence rate between the failures. A recurrence rate storage unit that stores the recurrence rate calculated by the calculation unit for each treatment is provided.
The priority setting unit according to any one of claims 1 to 4, which sets the priority of treatment for the failure represented by the data based on the recurrence rate stored in the recurrence rate storage unit. Elevator maintenance work support device described. The elevator maintenance work support device according to any one of claims 1 to 5, wherein the calculation unit calculates the recurrence rate for each elapsed time after the failure.

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