KR20210006466A - Elevator maintenance work support device - Google Patents

Abstract

An object of the present invention is to provide a maintenance work support apparatus 1 for an elevator 2 capable of setting the priority of treatment in consideration of the accuracy of treatment. The maintenance work support apparatus 1 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 information on a failure and information on treatment for the failure. The search unit 103 searches the history storage unit 102 for a failure similar to a failure indicated by the input failure data. For a failure searched by the calculation unit 107 and the search unit 103, a recurrence rate is calculated for each treatment for the failure. The recurrence rate represents the rate of occurrence of a failure similar to the failure within a predetermined period after the failure. The priority setting unit 108 sets the priority of treatment for a failure indicated by the failure data based on the recurrence rate calculated by the calculation unit 107 for each treatment.

Description

Elevator maintenance work support device

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

Patent document 1 describes an example of a maintenance work support device. The maintenance work support device stores information on an abnormality that has occurred and information on treatment for the abnormality as a past case. The maintenance work support apparatus sets priorities in past cases based on the correlation with input data.

Japanese Patent No. 5820072

However, the maintenance work support apparatus described in Patent Document 1 does not take into account the accuracy of treatment. For this reason, it is possible to set a high priority to a treatment in which a similar failure is likely to recur after a temporary restoration.

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

An elevator maintenance work support apparatus according to the present invention includes a history storage unit for storing information of a failure and information on treatment for the failure, a search unit for searching a failure similar to a failure indicated by input data from the history storage unit, and , For failures searched by the search unit, the recurrence rate indicating the rate of occurrence of a failure similar to the failure within a predetermined period after the failure is based on a calculation unit that calculates each treatment for the failure, and a recurrence rate that the calculation unit calculates for each treatment. Thus, there is provided a priority setting unit for setting the priority of treatment for a failure indicated by the data.

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

1 is a configuration diagram of a maintenance work support device according to a first embodiment.
2 is a diagram showing an example of a failure history database according to the first embodiment.
3 is a diagram showing an example of an elevator attribute database according to the first embodiment.
4 is a diagram showing an example of a pseudo-failure data table according to the first embodiment.
5 is a diagram illustrating an example of a combined data table according to the first embodiment.
6 is a diagram showing an example of data processing in the maintenance work support device according to the first embodiment.
7 is a flowchart showing an example of the operation of the maintenance work support device according to the first embodiment.
8 is a flowchart showing an example of the operation of the determination unit according to the first embodiment.
9 is a flowchart showing an example of the operation of the classification unit according to the first embodiment.
10 is a diagram showing a hardware configuration of a main part of the maintenance work support apparatus according to the first embodiment.
11 is a configuration diagram of a maintenance work support device according to a second embodiment.
12 is a diagram showing an example of a recurrence rate database according to the second embodiment.
13 is a diagram illustrating an example of a recurrence rate calculated by a calculation unit according to the third embodiment.

EMBODIMENT OF THE INVENTION An embodiment for carrying out this invention is demonstrated, referring accompanying drawings. In each drawing, the same reference numerals are assigned to the same or corresponding parts, and overlapping descriptions are appropriately simplified or omitted.

Embodiment 1.

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

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

The elevator 2 is provided in the building 3.

The building 3 has multiple floors. The hoistway (4) passes through each floor of the building (3). Each of the plurality of platforms 5 is provided on each floor of the building 3. Each of the plurality of platforms 5 faces the hoistway 4. Each of the plurality of platforms 5 is provided with a platform door 6.

The elevator 2 is provided with a car 7, a counterweight 8, a hoisting machine 9, and a main rope 10.

The car 7 is provided so as to be able to move up and down along a guide rail not shown in the interior of the hoistway 4. The car 7 is provided with a car door 11. The car door 11 is configured so that it can be opened and closed by interlocking the landing door 6 when the car 7 is stopped on any of a plurality of floors. The counterweight 8 is provided so as to be able to move up and down along a guide rail not shown in the interior of the hoistway 4. The hoisting machine 9 is provided above the hoistway 4. The main rope 10 is wound around the hoisting machine 9 and hung. Both ends of the main rope 10 are held in a car 7 and a counterweight 8, respectively.

The terminal device 12 is carried by the maintenance person 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, and , A calculation unit 107, a priority setting unit 108, and an output unit 109 are provided.

The input unit 101 is connected to the terminal device 12 via a 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 indicating a failure occurring in the elevator 2. The fault data includes information such as the type and situation of the fault. The failure data is input from the terminal device 12 by the maintenance person 13, for example. Fault data includes, for example, fault codes or freely written text that are set for each fault type.

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

The search unit 103 is connected to the input unit 101 so as to obtain failure data. The search section 103 is connected to the history storage section 102 so that it can access the failure history database. The search unit 103 is configured to be able to acquire a similar failure data table corresponding to the failure data from the failure history database by searching. The pseudo-failure data table is a data table including a plurality of pseudo-failure data of corresponding failure data. The pseudo-failure data is data including information on a failure similar to a failure indicated by the failure data and information on treatment for the similar failure.

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

The attribute storage unit 105 is configured to be able to store an 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 attribute of the elevator 2.

The classification unit 106 is connected to the determination unit 104 so as to obtain a similar failure data table in which the presence or absence of recurrence is determined for each of the similar failure data. The classification unit 106 is connected to the attribute storage unit 105 so as to be able to access the elevator attribute database. The classification unit 106 is configured to generate a combined data table from the similar failure data table and the elevator attribute database. The combined data table is a data table including a plurality of combined data. The combined data is data in which pseudo-failure data and elevator attribute data of the elevator 2 in which a failure occurred, included in the pseudo-failure data, are combined. The classification unit 106 is configured to be able to classify each of a plurality of pseudo-failure data included in the pseudo-failure data table into groups corresponding to the attributes of the elevator 2 by the combined data table.

The calculation unit 107 is connected to the classification unit 106 so as to obtain each of a plurality of pseudo-failure data classified into groups. 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 pseudo-failure data.

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

The output unit 109 is connected to the priority setting unit 108 so that data indicating the priority of the set treatment can be obtained. The output unit 109 is connected to the terminal device 12 via the communication line 14 so that data indicating the treatment and 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 counterweight 8 follow the movement of the main rope 10 and move up and down. The car 7 responds to a call from a user by moving up and down in the hoistway 4. The car 7 stops on the floor where the platform 5 is provided. The landing door 6 is opened in conjunction with the car door 11. The user of the elevator 2 gets on or off the car 7 from the platform 5.

When a failure occurs in the elevator 2, the maintenance person 13 inputs the failure data to the maintenance work support device 1 via the terminal device 12. The maintenance work support apparatus 1 sets priority on treatment based on a recurrence rate of a failure similar to a failure indicated by the failure data. The maintenance work support device 1 outputs to the terminal device 12 data indicating a treatment and a priority set for the treatment. The terminal device 12 presents the treatment to the maintenance worker according to the set priority.

Next, failure history data will be described using FIG. 2.

2 is a diagram showing an example of a failure history database according to the first embodiment.

The failure history data, as information on a failure, includes, for example, information identifying the elevator 2 in which the failure occurred, the time of occurrence of the failure, a failure code, and a failure situation. The information identifying 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 date and time when the failure occurred is the date and time when the failure occurred. The fault code is a code set for each type of fault. A fault condition is a freely written text indicating the condition of the fault. Further, the failure history data may include recurrence data indicating that the same failure has occurred in the same elevator during a predetermined period. The recurrence data is data of a code or freely written text indicating a situation of recurrence.

The failure history data is information on treatment, and includes, for example, a treatment code and treatment contents. The treatment code is a code set for each treatment type. The treatment content is a freely written text indicating the content of the treatment.

Next, elevator attribute data will be described with reference to FIG. 3.

3 is a diagram showing an example of an elevator attribute database according to the first embodiment.

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

Next, pseudo-failure data will be described using FIG. 4.

4 is a diagram showing an example of a pseudo-failure data table according to the first embodiment.

In Fig. 4, a table of similar failure data acquired from the failure history database of Fig. 2 is shown as an example. In this example, the failure data corresponding to the similar failure data table indicates a failure similar to the failure of the failure situation "door opening/closing failure".

The pseudo-failure data table contains pseudo-failure data of a failure of a failure situation "door opening/closing failure" as a failure similar to a failure indicated by the corresponding failure data. The pseudo-failure data includes information included in the failure history data and a value of recurrence.

Next, the combined data will be described using FIG. 5.

5 is a diagram illustrating an example of a combined data table according to the first embodiment.

In Fig. 5, a combined data table generated from the pseudo-failure data table of Fig. 4 and the elevator attribute database of Fig. 3 is shown as an example.

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

For example, in the pseudo-failure data of the failure occurring in the elevator 2 identified by the building number "1234567" and the unit number "001", model "A" and door closing method "CO" as attributes of the elevator 2 , Completion training "10" is added. When there are a plurality of pseudo-failure data of a failure occurring in the elevator 2, attribute information is added to each of the plurality of pseudo-failure data. Similarly, in the pseudo-failure data of the failure that occurred in the elevator 2 identified by the building number "2345678" and the unit number "001", the model "B", the door closing method "2S", as the attributes of the elevator 2, were completed. Training "6" is added.

Next, the function of the maintenance work support device 1 will be described using FIG. 6.

6 is a diagram showing an example of data processing in the maintenance work support device according to the first embodiment.

The maintenance person 13 inputs failure data into the input unit 101 via the terminal device 12. In this example, a failure with a failure code "F001" and a failure condition "door opening/closing failure" occurs in an elevator with a model "A", a door closing method "CO", and a completion number of years "4".

The search unit 103 acquires failure data from the input unit 101. The search unit 103 obtains a pseudo-failure data table corresponding to the failure data from the failure history database by searching. When the fault codes of a plurality of faults match, for example, the search unit 103 makes the plurality of faults similar, and searches for similar fault data.

The determination unit 104 acquires a pseudo-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 pseudo-failure data included in the acquired pseudo-failure data table.

The determination unit 104 determines whether there is a recurrence, for example, as follows. The determination unit 104 initializes the value of the presence or absence of recurrence by setting the value of the recurrence or absence of all the similar failure data included in the pseudo-failure data table to "None". The determination unit 104 searches for a pair of pseudo-failure data in the pseudo-failure data table in which the interval between the occurrence date and time of the failure does not exceed the recurrence determination period. In the case where the failure indicated by each of the searched pair of similar failure data is a failure occurring in the same elevator, the determination unit 104 determines the value of the recurrence of the one with the earlier failure occurrence date among the pair of similar failure data. Yes”. Here, the determination unit 104 calculates the interval at the time of occurrence of the failure as a unit by discarding units less than the hour. The recurrence determination period is k days with k as an integer. In addition, when the failure history data contains recurrence data, the determination unit 104 determines the presence or absence of a recurrence by searching for the presence or absence of a code or text indicating the recurrence.

The classification unit 106 acquires, from the determination unit 104, a pseudo-failure data table in which the presence or absence of recurrence is determined. The classification unit 106 generates a combined data table from the acquired pseudo-failure data table and elevator attribute database. The classification unit 106 classifies each of the plurality of pseudo-failure data included in the pseudo-failure data table into groups corresponding to the attributes of the elevator 2 by the combined data table.

The classification unit 106 classifies each of a plurality of pseudo-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. Groups have a list of properties used. The used attribute list is a list of attributes of the elevator 2 previously used for classification of the group having the list.

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

The classification unit 106 repeats the following processing until the group list does not contain unclassified groups. The classification unit 106 extracts one unclassified group from the group list. The classification unit 106 searches for a classification attribute among attributes not included in the retrieved group's use attribute list. The classification attribute is an attribute in which there is a significant difference in the recurrence rate between 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 recurrence of similar failure data included in each of the plurality of subgroups. The classification unit 106 makes a list of usage attributes included in each of the plurality of subgroups into a list obtained by adding classification attributes to the retrieved group's usage attribute list. The classification unit 106 adds each of the plurality of subgroups as unclassified groups to the group list. On the other hand, when the classification attribute is not searched, the classification unit 106 returns the retrieved group to the group list as a classified group.

Here, the classification unit 106 determines whether there is a significant difference in the recurrence rate between the subgroups based on 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". The classification unit 106 calculates a p value for each attribute not included in the retrieved group's use attribute list. The classification unit 106 sets the attribute having the lowest p value among attributes having a p value lower than the significance level as a classification attribute. When 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 unifies subgroups having no significant difference in the recurrence rate among a plurality of subgroups classified according to classification attributes.

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

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

The sorting unit 106 extracts a group whose door closing method is "CO" from the group list. The classification unit 106 determines a model as a classification attribute among attributes other than the door closing method included in the use attribute list. The classification unit 106 classifies the taken out groups into subgroups of "A", "B", "C" and "Others" according to the model. The classification unit 106 stores, as an unclassified group, a subgroup containing 50 pieces of combined data with a door closing method of "CO" and a model of "A" in the group list. The list of usage attributes of the group includes the door closing method and model. Similarly, the classification unit 106 stores subgroups of "B", "C" and "Others" of the model types as unclassified groups in the group list.

The sorting 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 among attributes other than the door closing method included in the use attribute list. The classification unit 106 classifies the group taken out into subgroups of "5 years or less" and "6 years or more" according to the number of years completed. The classification unit 106 stores, as an unclassified group, a subgroup including 120 pieces of combined data with a door closing method of "CO" and a completion year of "5 years or less" in the group list. The list of usage attributes of the group includes the door closing method and the number of years of completion. Similarly, the classification unit 106 stores subgroups whose completion years are "6 years or more" as unclassified groups in the group list.

The sorting unit 106 extracts a group whose door closing method is "other" from the group list. The classification unit 106 searches for a classification attribute among attributes other than the door closing method included in the use attribute list. When there is no attribute whose p value for classification by the attribute is lower than the significance level among attributes other than the door closing method included in the use attribute list, the classification unit 106 determines that the classification attribute has not been searched. The classification unit 106 returns a subgroup containing 100 pieces of 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 groups according to the attributes of the elevator 2 until the group list does not include an unclassified list.

The calculation unit 107 acquires each of a plurality of pseudo-failure data classified into 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 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 recurrence is "yes" among 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 in which the door closing method is "CO" and the model is "A" is searched. The calculation unit 107 calculates the number of recurrences as 50% for 20 failures for which treatment "check" was performed in the searched group. Similarly, the calculation unit 107 calculates the number of recurrences as 0% for 10 failures in which the treatment "substrate exchange" was performed in the searched group.

The priority setting unit 108 acquires data indicating the recurrence rate calculated for each treatment from the calculation unit 107. The priority setting unit 108 sets a high priority in order from treatments with a low recurrence rate. The priority setting unit 108 integrates a lower-order treatment with a low priority as "other".

In this example, the priority setting unit 108 sets the highest priority to the treatment "substrate exchange". The priority setting unit 108 sets the next highest priority to the treatment "check".

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

The terminal device 12 presents the treatment with a high priority to the maintenance worker 13 by displaying treatments in order of priority.

Next, the operation of the maintenance work support apparatus 1 will be described with reference to FIGS. 7 to 9.

7 is a flowchart showing an example of the operation of the maintenance work support device according to the first embodiment. 8 is a flowchart showing an example of the operation of the determination unit according to the first embodiment. 9 is a flowchart showing an example of the operation of the classification unit according to the first embodiment.

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 pseudo-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 whether there is a recurrence of each of the pseudo-failure data in the pseudo-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 combined data table from the pseudo-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 pseudo-failure data into groups corresponding to the attributes of the elevator 2 by the combined 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 a recurrence rate for each treatment for a similar failure included in the group corresponding to the attribute of the elevator 2 in which the failure 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 treatment for a failure based on the calculated recurrence rate. After that, the output unit 109 transmits data indicating the treatment and the priority set for the treatment. After that, the operation of the maintenance work support device 1 ends.

In Fig. 8, the operation of the determination unit 104 in step S103 of Fig. 7 is shown.

In step S201, the determination unit 104 acquires a pseudo-failure data table containing m pseudo-failure data. After that, the determination unit 104 initializes the value of the recurrence of the pseudo-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 pseudo-failure data table in ascending order by the date and time of the failure. 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. When 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. When 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 an interval between the occurrence date and time of the failure with respect to the i-th and j-th pseudo-failure data. After that, the determination unit 104 determines whether the calculated interval is equal to or less than k days, which is the recurrence determination period. When the determination result is No, the operation of the determination unit 104 proceeds to step S207. When 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 a failure indicated by each of the i-th and j-th pseudo-failure data is a failure occurring in the same elevator. When 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 recurrence or absence of the i-th pseudo-failure data as "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.

In FIG. 9, the operation of the classification unit 106 in step S105 of FIG. 7 is shown.

In step S301, the classification unit 106 adds all of the plurality of pseudo-failure data included in the pseudo-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 an unclassified group is included in the group list. When 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 group taken out. After that, the operation of the classification unit 106 proceeds to step S305.

In step S305, the classification unit 106 determines whether or not the selected attribute is included in the used attribute list of the retrieved group. When the determination result is No, the operation of the classification unit 106 proceeds to step S306. When 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. After that, the classification unit 106 calculates a p-value, which is a 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. When 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 a 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 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. When 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 at least one attribute and a p value for the attribute 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. When 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 attribute stored in the retrieved group use attribute list to the subgroup use attribute list classified by the classification attribute. After that, the classification unit 106 adds the classification attribute to the use 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 combines a plurality of subgroups that do not have a significant difference in the recurrence rate among the plurality of subgroups classified according to the classification attribute as one of the subgroups classified according to 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 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. Equipped. The history storage unit 102 stores information on a failure and information on treatment for the failure. The search unit 103 searches the history storage unit 102 for a failure similar to a failure indicated by the input failure data. For a failure searched by the calculation unit 107 and the search unit 103, a recurrence rate is calculated for each treatment for the failure. The recurrence rate represents the rate of occurrence of a failure similar to the failure within a predetermined period after the failure. The priority setting unit 108 sets the priority of treatment for a failure indicated by the failure data based on the recurrence rate calculated by the calculation unit 107 for each treatment.

The maintenance work support apparatus 1 can determine a treatment with a high probability of recurrence of a similar failure after temporarily recovering from the recurrence rate calculated for each treatment. Thereby, the maintenance work support apparatus 1 can set the priority of treatment in consideration of the accuracy of treatment. The maintenance work support device 1 can present to the maintenance worker 13 an appropriate treatment in consideration of the accuracy of treatment through the terminal device 12.

Further, the maintenance work support apparatus 1 includes a determination unit 104. The determination unit 104 determines the presence or absence of a recurrence of a failure searched by the search unit 103. The presence or absence of a recurrence indicates whether a failure similar to the failure 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 personnel 13 or the manager of the elevator 2 need not add information indicating the presence or absence of recurrence to the failure history database. Thereby, the maintenance worker 13, the manager, etc. of the elevator 2 can use the maintenance work support apparatus 1 more easily. 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.

In addition, the maintenance work support apparatus 1 includes a sorting unit 106. The classification unit 106 classifies the failures searched by the search unit 103 into groups corresponding to the attributes of the elevator 2 in which the failure occurs. The calculation unit 107 calculates a recurrence rate for each treatment for a failure classified into a group corresponding to the attribute of the elevator 2 in which the failure indicated by the failure data occurred.

The calculation unit 107 calculates the recurrence rate in consideration of the properties of the elevator 2 in which the failure occurred. Thereby, the priority setting unit 108 can set the priority of treatment with higher precision.

In addition, when there is a significant difference in the recurrence rate between failures occurring in the elevators 2 with different attributes, the classification unit 106 classifies them into groups according to the attributes.

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

Further, the failure data may be input from a monitoring center outside the building 3, not by the maintenance person 13. The failure data may be a signal value of one or more sensors provided in the elevator 2. Fault data may be entered automatically when the signal values of one or more sensors are within a range of values representing faults.

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

The search unit 103 may search for similar failures based on a similarity determination table set in advance. The similarity determination table is a table indicating whether or not a set of failures indicated by a set of failure codes are similar.

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

The search unit 103 may search for similar failures based on a difference in signal values when the failure data are signal values of one or more sensors. The search unit 103 calculates the difference between the signal values, for example, by the Euclidean distance.

The classification unit 106 may search for a numerical value at which a significant difference in the recurrence rate occurs when classifying into subgroups by the attribute indicated 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 attribute value n, and searches for a numerical value n at which a significant difference in the recurrence rate of the subgroup occurs. The attribute represented by a numerical value is, for example, the number of years of completion.

When a group including the number of combined data less than a predetermined threshold is obtained, the classification unit 106 does not need to perform classification. For example, when the number of combined data included in the unclassified group retrieved from the group list is less than the threshold value, the classification unit 106 may return the retrieved group as it is to the group list as a classified group. When a subgroup including the number of combined data less than the threshold value is obtained by classifying by the selected attribute, the classification unit 106 does not need to classify into subgroups based on the attribute. Here, the threshold is predetermined as a lower limit of the number of combined data for which a reliable recurrence rate is calculated for the classified group. This prevents a case where reliability of the recurrence probability cannot be secured because, for example, when 100 groups are divided into 95 cases and 5 cases according to classification, the number of cases in one divided case is as small as 5 cases.

The terminal device 12 may present the treatment with a high priority to the maintenance person 13 by displaying treatments 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 treatment with a high priority to the maintenance person 13 by not displaying the treatment with a low priority.

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

Next, an example of the hardware configuration of the maintenance work support device 1 will be described with reference to FIG. 10.

10 is a diagram showing a hardware configuration of a main part of the maintenance work support apparatus 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 be provided with at least one dedicated hardware 1a together 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 software and firmware is described as a program. The program is stored in the memory 1c. The processor 1b reads and executes the program stored in the memory 1c, thereby realizing each function of the maintenance work support device 1.

The processor 1b is also referred to as a CPU (Central Processing Unit), a processing unit, a computing unit, a microprocessor, a microcomputer, and a DSP. The memory 1c is constituted by, for example, a nonvolatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, EEPROM, magnetic disk, flexible disk, optical disk, compact disk, mini disk, DVD, etc. do.

When the processing circuit includes the dedicated hardware 1a, the processing circuit is realized by, for example, a single circuit, a complex 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, respectively. Alternatively, each function of the maintenance work support device 1 can be integrated and implemented by a processing circuit. For each function of the maintenance work support device 1, a part may be realized by dedicated hardware 1a, and another part may be realized by software or firmware. In this way, the processing circuit realizes each function of the maintenance work support apparatus 1 by means of hardware 1a, software, firmware, or a combination thereof.

Embodiment 2.

In Embodiment 2, differences from the example disclosed in Embodiment 1 will be described in detail. For features not described in the second embodiment, any feature of the example disclosed in the first embodiment may be employed.

The configuration of the maintenance work support device 1 according to the second embodiment will be described.

11 is a configuration diagram of a maintenance work support device according to a second embodiment.

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

The generation unit 110 is configured to generate fault data comprehensively about fault codes and fault conditions, for example. The generation unit 110 is connected to the search unit 103 so as to provide the generated failure data.

The recurrence rate storage unit 111 is configured to store a 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 as to obtain failure data.

The calculation unit 107 is connected to the recurrence rate storage unit 111 so as to access the recurrence rate database.

The priority setting unit 108 is connected to the input unit 101 so as to obtain failure data. 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 to be able to set the priority of treatment based on the recurrence rate.

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

Next, the recurrence rate data according to the second embodiment will be described.

12 is a diagram showing an example of a recurrence rate database according to the second embodiment.

The recurrence rate data is information on a failure and includes, for example, a failure code and a failure situation. The recurrence rate data is information on an attribute used for classification and includes a first attribute, a first item, a second attribute, and a second item. The recurrence rate data is treatment information and includes a treatment code and treatment contents. The recurrence rate data is information on the recurrence rate, and includes the number of failures, the number of recurrences, and the recurrence rate.

The first attribute is an attribute for classifying the entire pseudo-failure data table into groups. The first item is the value of the first attribute. The second attribute is an attribute for further classifying a group classified by the first attribute into a lower group. The second item is the value of the second attribute. When not classified into a lower group than the group classified by the first attribute, the data of the second attribute and the second item are empty. The recurrence rate data includes information on an attribute that further classifies the group classified by the second attribute into a lower group.

The number of failures is the number of similar failure data retrieved for each treatment. The number of recurrences is the number of pseudo-failure data for which the presence or absence of recurrence is determined as &quot;yes&quot; among the searched for similar failure data. The recurrence rate is the ratio of the number of recurrences to the number of failures.

The recurrence rate data is generated, for example, as follows. When the calculation load of the maintenance work support apparatus 1 is low, for example, the generation unit 110 transmits the generated failure data to the search unit 103. The search unit 103 obtains a pseudo-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 pseudo-failure data included in the pseudo-failure data table. The classification unit 106 generates a combined data table from the pseudo-failure data table and the elevator attribute database. The classification unit 106 classifies each of the plurality of pseudo-failure data included in the pseudo-failure data table into groups corresponding to the attributes of the elevator 2 by the combined 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 pseudo-failure data. The calculation unit 107 generates information on a failure, information on an attribute used for classification, information on treatment, and information on a recurrence rate as recurrence rate data.

Recurrence rate data is used as follows, for example. The input unit 101 accepts input of failure data from the terminal device 12 by the maintenance person 13, for example. 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 a group of attributes corresponding to the elevator 2 in which the failure occurred for a failure indicated by the acquired failure data. The priority setting unit 108 sets the priority of treatment for a failure indicated 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 the 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 treatment for a failure indicated by the failure data based on the recurrence rate stored in the recurrence rate storage unit 111.

The maintenance work support apparatus 1 can perform processing, such as determination or classification of recurrence, before inputting failure data. For this reason, the maintenance work support apparatus 1 reduces the computational load from inputting the failure data until the priority is set. Thereby, the maintenance work support apparatus 1 can set priority to the treatment quickly after failure data is input.

Further, the generation unit 110 may transmit 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 Embodiment 3, differences from the examples disclosed in Embodiment 1 or Embodiment 2 will be described in detail. For features not described in the third embodiment, any of the features disclosed in the first embodiment or the second embodiment may be employed.

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

In Fig. 13, the horizontal axis represents the number of days elapsed after treatment for a failure. 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 occurred is 20 days after input of failure data indicating the failure. The recurrence rate after 20 days was higher for treatment α than for treatment β. The recurrence rate after 50 days was higher for treatment β than for treatment α.

The determination unit 104 determines, as a value of the presence or absence of recurrence, an interval until the failure recurs. The determination unit 104 initializes the recurrence presence/absence value by setting the value of the recurrence presence/absence value of all the pseudo-failure data included in the pseudo-failure data table to an integer value 0 indicating "no". When the interval between the occurrence date and time of the failure of the pair of pseudo-failure data is d days of k days or less, the determination unit 104 determines a recurrence or not as an integer value d.

The calculation unit 107 calculates the recurrence rate every time one day elapses from the failure. The recurrence rate every 1 day from the failure is an example of the recurrence rate every elapsed time after the failure. For each group classified by the classification unit 106, the calculation unit 107 calculates the ratio of the number of recurrences of similar failures until d days after the treatment to the number of failures for which the treatment was performed for each treatment. It is calculated as the recurrence rate.

The priority setting unit 108 sets a high priority to a treatment with a low recurrence rate on the next maintenance day. That is, the priority setting unit 108 sets the priority of the treatment β with a low recurrence rate 20 days later than 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 repair day, the repair worker 13 takes a fundamental action on the repair day, thereby suppressing recurrence of the failure. The priority setting unit 108 can also set a high priority for emergency treatment in which the recurrence rate increases after a long period of time, if the recurrence rate until the maintenance day is low. For this reason, the priority setting unit 108 can set the 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 occurred.

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

The priority setting unit 108 may set a higher priority of treatment possible remotely without the maintenance person 13 when the recurrence rate on the next maintenance day is lower than a predetermined ratio. The treatment possible remotely is, for example, a treatment in which a control signal for maintenance is transmitted to the elevator 2.

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

Industrial availability

The maintenance work support apparatus 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 unit
1a: hardware 1b: processor
1c: memory 2: elevator
3: building 4: hoistway
5: platform 6: platform door
7: car 8: counterweight
9: hoisting machine 10: main rope
11: car door 12: terminal device
13: maintenance worker 14: communication line

Claims (6)

A history storage unit that stores information of a failure and information of treatment for the failure,
A search unit that searches for a failure similar to a failure indicated by input data from the history storage unit,
For a failure searched by the search unit, a calculation unit that calculates a recurrence rate indicating a rate of occurrence of a failure similar to that of the failure within a predetermined period after the failure for each treatment for the failure,
An elevator maintenance work support apparatus comprising a priority setting unit that sets a priority of treatment for a failure indicated by the data based on the recurrence rate calculated by the calculation unit for each treatment. The method according to claim 1,
With respect to the failure searched by the search unit, a determination unit for determining the presence or absence of a recurrence indicating whether a failure similar to the failure has occurred within a predetermined period after the failure,
The elevator maintenance work support device, 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. The method according to claim 1 or 2,
A classification unit for classifying a failure searched by the search unit into a group corresponding to an attribute of an elevator in which the failure occurs,
The calculation unit is an elevator maintenance work support device that calculates the recurrence rate for each treatment for a failure classified into a group corresponding to an attribute of an elevator in which the failure indicated by the data occurred. The method of claim 3,
The classification unit, when there is a significant difference in the recurrence rate between failures occurring in elevators having different attributes, classifies them into the group according to the attribute. The method according to any one of claims 1 to 4,
The calculation unit includes a recurrence rate storage unit for storing the recurrence rate calculated for each treatment,
The priority setting unit sets the priority of treatment for a failure indicated by the data based on the relapse rate stored in the recurrence rate storage unit. The method according to any one of claims 1 to 5,
The elevator maintenance work support device, wherein the calculation unit calculates the recurrence rate for each elapsed time after a failure.

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