JP5822788B2 - Work plan support device, work plan support method, and work plan support program - Google Patents

Description

  The present invention relates to, for example, a work plan support apparatus, a work plan support method, and a work plan support program that support creation of a work plan for equipment maintenance work.

In order to stably operate facilities such as public facilities, transportation facilities, manufacturing industries, and building facilities, workers are dispatched to the site where the facilities are provided, and maintenance work is performed by the dispatched workers. For example, maintenance work is regularly performed by a contract with a customer.
For maintenance work that is performed regularly, a maintenance work plan that defines when and to whom equipment is dispatched and maintenance work is created in advance, and workers are dispatched according to the plan.
Therefore, it is important to create a plan with higher expected maintenance quality at the stage of creating a maintenance work plan. As an index indicating maintenance quality, the number of failures that occur after maintenance work is performed under the maintenance work plan is used.

  Patent Document 1 discloses a method for selecting a worker who can be dispatched to the site and can recover the equipment from the failure, for the equipment that has suddenly failed. The method disclosed in Patent Document 1 is to evaluate the degree of failure and recovery and the presence / absence of the worker's ability at several levels, and select the optimum worker based on the evaluation result. .

  Patent Literature 2 discloses a method for drafting a maintenance plan for parts constituting equipment. The method disclosed in Patent Document 2 calculates the reliability with which each facility achieves its function based on the list of components necessary to achieve a specific function for each facility and the reliability data of the component. The maintenance parts are selected so that the reliability is maintained at a predetermined value or more.

In order to develop a maintenance work plan with high expected maintenance quality, it is necessary to quantitatively calculate and evaluate the expected maintenance quality for each maintenance work in a specific maintenance work plan.
In general, the maintenance quality is evaluated by estimating the failure frequency expected to occur under similar conditions using history information such as past failures of each facility.
At this time, if examples of facilities that are affected variously are included in the history information for estimating the failure frequency, the range in which the estimated value can be taken is widened, and a highly accurate appropriate estimated value cannot be obtained.
For example, this is an example of equipment in which the installation environment changes irregularly or equipment in which another maintenance worker performs maintenance work each time.
In planning a maintenance work plan that focuses on workers, cases are limited for equipment that has been continuously maintained for a certain period of time by the same worker in order to reduce the factors affected. Yes.
However, the equipment that completely satisfies this condition is low in terms of the overall ratio. Therefore, in the conventional method, the amount of data that can be used for learning is reduced. Furthermore, facilities that can perform plan optimization based on the obtained estimation results are also limited to those that satisfy this condition.

JP 2011-57308 A JP 2011-60088 A

Introduction to Statistics-Basic Statistics I, Department of Statistics, Faculty of Liberal Arts, The University of Tokyo, Appendix 4 F Distribution Table

  For example, an object of the present invention is to support a work plan for assigning an appropriate worker for each work.

The work plan support apparatus of the present invention comprises:
For each worker who performs work, a worker data storage unit that stores worker data in which a worker identifier that identifies a worker and a worker attribute value indicating an attribute related to the worker are associated with each other;
A past work data storage unit that stores past work data in which a past work identifier that identifies a past work and a past worker identifier that identifies a worker who has performed the past work are associated with each other in the past; ,
For each defect that occurred in the past work, a defect data storage unit that stores defect data including a defect work identifier that identifies the defect work in which the defect has occurred;
For each past work data stored in the past work data storage unit, the number of fault data including the same fault work identifier as the past work identifier of the past work data among the fault data stored in the fault data storage unit is faulty. A defect number calculation unit to calculate as a number;
For each past work data stored in the past work data storage unit, a worker attribute value associated with the same worker identifier as the past worker identifier of the past work data is used as a past attribute value from the worker data storage unit. A past attribute value acquisition unit to be acquired;
For each past attribute value acquired by the past attribute value acquisition unit, the total number of defects of past work data having the same past attribute value out of the number of defects calculated by the number of defects calculation unit is calculated. An attribute-specific defect count calculation unit for calculating
For each past attribute value acquired by the past attribute value acquisition unit, the past work number calculation unit by attribute that calculates the number of past work identifiers having the same past attribute value as the past work number by attribute,
Based on the past number of tasks by attribute calculated for each past attribute value by the past number of tasks by attribute and the number of defects by attribute calculated for each past attribute value by the number of defects by attribute A defect index value calculation unit that calculates a value related to the ratio of the number of defects by attribute to the past number of tasks by attribute for each value as a defect index value;
A worker candidate selection unit that selects a worker attribute value of a worker candidate to perform a new work based on the defect index value calculated for each past attribute value by the defect index value calculation unit.

  The present invention can support, for example, a work plan for assigning an appropriate worker for each work.

2 is a functional configuration diagram of a work plan support apparatus 100 according to Embodiment 1. FIG. The figure which shows the format of the worker table 200 in Embodiment 1. FIG. The figure which shows the format of the equipment table 210 in Embodiment 1. FIG. FIG. 4 is a diagram showing a format of a maintenance work table 220 in the first embodiment. FIG. 4 is a diagram showing a format of a failure table 230 in the first embodiment. The figure which shows the format of the long-term equipment table 240 in Embodiment 1. FIG. The figure which shows the format of the semi-long-term equipment table 250 in Embodiment 1. FIG. The figure which shows the format of the long-term equipment failure number table 260 in Embodiment 1. FIG. The figure which shows the format of the quasi-long-term equipment failure number table 270 in Embodiment 1. FIG. The figure which shows the format of the long-term equipment failure rate table 280 in Embodiment 1. FIG. FIG. 6 is a diagram showing a format of a work quality table 290 in the first embodiment. FIG. 3 is a diagram showing a format of a maintenance schedule table 300 in the first embodiment. FIG. 4 is a diagram showing a format of maintenance work plan data 310 in the first embodiment. FIG. 3 is a data flow diagram of the work plan support apparatus 100 according to the first embodiment. 5 is a flowchart showing a work plan support method of the work plan support apparatus 100 according to the first embodiment. FIG. 3 is a schematic diagram showing an example of equipment classification processing (S110) in the first embodiment. FIG. 3 is a schematic diagram illustrating an example of a failure number evaluation process (S120) in the first embodiment. FIG. 3 is a schematic diagram showing an example of long-term equipment failure rate evaluation processing (S130) in the first embodiment. The figure which shows the magnitude relationship of the long-term confidence interval and semi-long-term confidence interval in Embodiment 1. FIG. FIG. 3 is a schematic diagram showing an example of a semi-long-term facility failure rate evaluation process (S140) in the first embodiment. FIG. 3 is a diagram illustrating an example of hardware resources of the work plan support apparatus 100 according to the first embodiment.

Embodiment 1 FIG.
A work plan support apparatus that supports the creation of a work plan for maintenance work or other work of equipment (for example, building elevators and other building equipment) will be described.

FIG. 1 is a functional configuration diagram of a work plan support apparatus 100 according to the first embodiment.
A functional configuration of the work plan support apparatus 100 according to the first embodiment will be described with reference to FIG.

The work plan support apparatus 100 is an apparatus that supports the creation of a work plan for maintenance work of equipment.
However, the work plan support apparatus 100 may be used to support the creation of a work plan for work other than equipment maintenance work.

The work plan support apparatus 100 includes an equipment classification unit 110 and a failure number evaluation unit 120 (an example of a defect number calculation unit).
The work plan support apparatus 100 includes a long-term equipment failure rate evaluation unit 130 (an example of a reference attribute value acquisition unit, an attribute-specific defect reference number calculation unit, and an attribute-specific reference work number calculation unit), and a quasi-long-term equipment failure rate evaluation unit 140 ( An example of a past attribute value acquisition unit, an attribute-specific defect number calculation unit, an attribute-specific past work number calculation unit, a defect index value calculation unit, and a past work type acquisition unit).
The work plan support apparatus 100 includes a work plan creation unit 150, a work plan evaluation unit 160, a work plan update unit 170 (an example of a worker candidate selection unit and a new work selection unit), and a device storage unit 190 (worker data). An example of a storage unit, a past work data storage unit, a defect data storage unit, a reference work data storage unit, a work type data storage unit, and a scheduled work data storage unit).

The device storage unit 190 stores data used by the work plan support device 100. For example, the device storage unit 190 stores the following data.
The device storage unit 190 includes a worker table 200 (an example of worker data), an equipment table 210 (an example of work type data), a maintenance work table 220, a failure table 230 (an example of defect data), and a maintenance schedule table 300 (schedule). An example of work data) is stored in advance.
The device storage unit 190 stores a long-term equipment table 240 (an example of reference work data) and a semi-long-term equipment table 250 (an example of past work data) generated by the equipment classification unit 110.
The device storage unit 190 stores a long-term facility failure number table 260 and a semi-long-term facility failure number table 270 generated by the failure number evaluation unit 120.
The device storage unit 190 stores a long-term equipment failure rate table 280 generated by the long-term equipment failure rate evaluation unit 130.
The device storage unit 190 stores a work quality table 290 generated by the semi-long-term facility failure rate evaluation unit 140.
The device storage unit 190 stores maintenance work plan data 310 generated by the work plan creation unit 150 and updated by the work plan update unit 170.

  The functional configuration other than the device storage unit 190 of the work plan support apparatus 100 and the data stored in the device storage unit 190 will be described later.

FIG. 2 is a diagram showing a format of the worker table 200 in the first embodiment.
The worker table 200 according to Embodiment 1 will be described with reference to FIG.

  The worker table 200 is data regarding workers who perform maintenance work.

The worker table 200 associates “worker ID” and “worker attribute” as data items.
“Worker ID” indicates a worker identifier for identifying a worker.
“Worker attribute” indicates an attribute related to the worker (for example, the department to which the worker belongs).

FIG. 3 is a diagram showing a format of the equipment table 210 in the first embodiment.
The equipment table 210 in Embodiment 1 is demonstrated based on FIG.

  The equipment table 210 is data regarding equipment.

The equipment table 210 associates “equipment ID” and “equipment type” as data items.
“Equipment ID” indicates an equipment identifier for identifying the equipment.
“Equipment type” indicates the type of equipment (for example, model, installation year, contract, application, installation environment). An example of a facility contract is a contract for regular maintenance or a contract for irregular maintenance if necessary. As an example of the installation environment of equipment, indoor or outdoor can be cited.

FIG. 4 is a diagram showing a format of the maintenance work table 220 in the first embodiment.
The maintenance work table 220 in the first embodiment will be described with reference to FIG.

  The maintenance work table 220 is data relating to maintenance work performed in the past.

The maintenance work table 220 associates “date and time”, “equipment ID”, “worker ID”, and “maintenance work” as data items.
“Date and time” indicates the date and time when the maintenance work was performed.
“Equipment ID” indicates an equipment identifier for identifying equipment for which maintenance work has been performed.
“Worker ID” indicates a worker identifier for identifying a worker who has performed maintenance work.
“Maintenance work” indicates the content of the maintenance work.

FIG. 5 is a diagram showing a format of the failure table 230 in the first embodiment.
The failure table 230 in the first embodiment will be described with reference to FIG.

  The failure table 230 is data regarding equipment failures that have occurred in the past.

The failure table 230 associates “date and time”, “facility ID”, and “failure type” as data items.
“Date and time” indicates the date and time when the failure occurred.
“Equipment ID” indicates an equipment identifier for identifying an equipment in which a failure has occurred.
“Failure type” indicates the content of the failure.

FIG. 6 is a diagram showing a format of the long-term equipment table 240 in the first embodiment.
The long-term equipment table 240 in Embodiment 1 is demonstrated based on FIG.

The long-term equipment table 240 is equipment in which maintenance work for a predetermined period is performed by a worker who is scheduled to perform maintenance work (hereinafter referred to as “charge worker”), that is, a worker other than the charge worker performs the maintenance work. It is data about equipment that did not exist.
Hereinafter, a facility in which maintenance work for a predetermined period is performed by a worker in charge is referred to as “long-term facility” or “long-term maintenance facility”. Also, long-term facility maintenance work is referred to as “long-term work” or “long-term maintenance work”.

The long-term equipment table 240 associates “equipment ID”, “responsible worker ID”, “continuation work period”, and “start date / time” as data items.
“Equipment ID” indicates a long-term equipment identifier for identifying a long-term equipment.
“Responsible worker ID” indicates a responsible worker identifier for identifying a responsible worker.
“Continuous work period” indicates a work period in which long-term work is performed.
The “start date / time” indicates the start date / time when the long-term work is started.

FIG. 7 is a diagram showing a format of the semi-long-term equipment table 250 in the first embodiment.
The semi-long-term equipment table 250 in the first embodiment will be described with reference to FIG.

The semi-long-term equipment table 250 is data relating to equipment (hereinafter referred to as “semi-long-term equipment” or “quasi-long-term maintenance equipment”) temporarily performed on behalf of the responsible worker by a worker other than the responsible worker. is there.
Hereinafter, a worker who has temporarily performed maintenance work in place of the worker in charge is referred to as a “temporary worker”. In addition, maintenance work for a semi-long-term facility is called “semi-long-term work” or “semi-long-term maintenance work”.

The semi-long-term equipment table 250 associates “equipment ID”, “responsible worker ID”, “continuous work period”, “start date / time”, “temporary worker ID”, and “temporary work date / time” as data items.
“Equipment ID” indicates a semi-long-term equipment identifier for identifying a semi-long-term equipment.
“Responsible worker ID” indicates a responsible worker identifier for identifying a responsible worker.
“Continuous work period” indicates a work period during which a semi-long-term work is performed.
The “start date / time” indicates the start date / time when the semi-long-term work is started.
“Temporary worker ID” indicates a temporary worker identifier for identifying a temporary worker.
“Temporary work date and time” indicates the start date and time of the maintenance work performed by the temporary worker.

FIG. 8 is a diagram showing a format of the long-term equipment failure number table 260 in the first embodiment.
The long-term equipment failure number table 260 in the first embodiment will be described with reference to FIG.

  The long-term equipment failure count table 260 is data regarding the number of long-term equipment failures.

The long-term equipment failure count table 260 associates “equipment ID”, “evaluation start date / time”, “evaluation end date / time”, and “number of failures” as data items.
“Equipment ID” indicates a long-term equipment identifier for identifying a long-term equipment.
“Evaluation start date and time” indicates the start date and time of a target period (hereinafter referred to as “evaluation period”) for counting the number of failures.
“Evaluation end date and time” indicates the end date and time of the evaluation period.
“Number of failures” indicates the number of failures that occurred during the evaluation period.

FIG. 9 is a diagram showing a format of the quasi long-term equipment failure number table 270 in the first embodiment.
The quasi long-term equipment failure count table 270 in the first embodiment will be described with reference to FIG.

  The semi-long-term equipment failure number table 270 is data relating to the number of troubles of the semi-long-term equipment.

The semi-long-term equipment failure count table 270 associates “equipment ID”, “evaluation start date / time”, “evaluation end date / time”, and “number of failures” as data items.
“Equipment ID” indicates a semi-long-term equipment identifier for identifying a semi-long-term equipment.
“Evaluation start date” indicates the start date of the evaluation period.
“Evaluation end date and time” indicates the end date and time of the evaluation period.
“Number of failures” indicates the number of failures that occurred during the evaluation period.

FIG. 10 is a diagram showing a format of the long-term equipment failure rate table 280 in the first embodiment.
The long-term equipment failure rate table 280 in the first embodiment will be described with reference to FIG.

  The long-term equipment failure rate table 280 is data relating to the failure rate for each combination of the type of long-term equipment and the attribute of the worker in charge.

The long-term equipment failure rate table 280 associates “equipment type”, “worker attribute”, and “failure rate confidence interval” as data items.
“Equipment type” indicates the type of long-term equipment.
“Worker attribute” indicates an attribute of the worker in charge.
The “failure rate confidence interval” indicates a confidence interval of the failure rate.

FIG. 11 is a diagram showing a format of the work quality table 290 in the first embodiment.
The work quality table 290 in the first embodiment will be described with reference to FIG.

  The work quality table 290 is data relating to the failure rate for each combination of the type of semi-long term equipment and the attribute of the temporary worker.

The work quality table 290 associates “equipment type”, “responsible worker attribute”, “temporary worker attribute”, “failure rate confidence interval”, and “failure increment index” as data items.
“Equipment type” indicates the type of semi-long-term equipment.
The “in-charge worker attribute” indicates an attribute of the in-charge worker.
“Temporary worker attribute” indicates an attribute of a temporary worker.
The “failure rate confidence interval” indicates a confidence interval of the failure rate.
The “failure increment index” indicates an index value representing the magnitude of the failure rate (reliability interval) of the semi-long-term facility with respect to the failure rate (reliability interval) of the long-term facility.

FIG. 12 is a diagram illustrating a format of the maintenance schedule table 300 according to the first embodiment.
The maintenance schedule table 300 according to the first embodiment will be described with reference to FIG.

  The maintenance schedule table 300 is data regarding future maintenance work.

The maintenance schedule table 300 associates “schedule date”, “equipment ID”, and “maintenance work” as data items.
“Scheduled date” indicates a scheduled date on which maintenance work is performed.
“Equipment ID” indicates an equipment identifier for identifying equipment for which maintenance work is to be performed.
“Maintenance work” indicates the contents of the planned maintenance work.

FIG. 13 is a diagram showing a format of the maintenance work plan data 310 in the first embodiment.
The maintenance work plan data 310 according to the first embodiment will be described with reference to FIG.

  The maintenance work plan data 310 is data related to a worker who is scheduled to perform maintenance work.

The maintenance work plan data 310 associates “planned work date”, “facility ID”, “worker ID”, and “maintenance work” as data items.
“Planned work date” indicates a scheduled date for performing maintenance work.
“Equipment ID” indicates an equipment identifier for identifying equipment for which maintenance work is to be performed.
“Worker ID” indicates a worker identifier for identifying a worker who is scheduled to perform maintenance work.
“Maintenance work” indicates the contents of the planned maintenance work.

FIG. 14 is a data flow diagram of the work plan support apparatus 100 according to the first embodiment.
A data flow of the work plan support apparatus 100 according to the first embodiment will be described with reference to FIG.

  The equipment classification unit 110 generates a long-term equipment table 240 (see FIG. 6) and a semi-long-term equipment table 250 (see FIG. 7) based on the maintenance work table 220 (see FIG. 4).

The failure number evaluation unit 120 generates a long-term facility failure number table 260 (see FIG. 8) based on the long-term facility table 240 and the failure table 230 (see FIG. 5).
The failure number evaluation unit 120 generates a semi-long-term equipment failure number table 270 (see FIG. 9) based on the semi-long-term equipment table 250 and the failure table 230.

  The long-term equipment failure rate evaluation unit 130 creates a long-term equipment failure rate table 280 (see FIG. 10) based on the long-term equipment failure number table 260, the worker table 200 (see FIG. 2), and the equipment table 210 (see FIG. 3). Generate.

  The semi-long-term equipment failure rate evaluation unit 140 generates a work quality table 290 (see FIG. 11) based on the long-term equipment failure rate table 280, the semi-long-term equipment failure number table 270, the worker table 200, and the equipment table 210.

  The work plan creation unit 150 generates maintenance work plan data 310 (see FIG. 13) based on the maintenance schedule table 300 (see FIG. 12).

  The work plan evaluation unit 160 evaluates the maintenance work plan data 310 based on the long-term equipment failure rate table 280.

  The work plan update unit 170 updates the maintenance work plan data 310 based on the work quality table 290.

FIG. 15 is a flowchart showing the work plan support method of the work plan support apparatus 100 according to the first embodiment.
A work plan support method of the work plan support apparatus 100 according to Embodiment 1 will be described with reference to FIG.

  In S110, the equipment classification unit 110 generates a long-term equipment table 240 (see FIG. 6) and a semi-long-term equipment table 250 (see FIG. 7) based on the maintenance work table 220 (see FIG. 4).

The equipment classification unit 110 generates the long-term equipment table 240 as follows.
For each equipment ID in the maintenance work table 220, the equipment classification unit 110 aggregates the date and time and the worker ID, and sets the maximum period during which the maintenance work is performed by the same worker (the worker in charge) as the continuous work period. calculate.
The equipment classification unit 110 selects, as a long-term equipment identifier, an equipment ID whose calculated continuous work period is a predetermined period threshold (for example, one month) or more. That is, the maintenance work table 220 selects, as a long-term equipment identifier, the equipment ID of equipment for which the worker has not been changed even once during a period equal to or greater than the predetermined period threshold.
For each selected long-term equipment identifier, the equipment classification unit 110 sets the long-term equipment identifier (equipment ID), the worker ID of the worker in charge (charged worker ID), the continuous work period, and the start date and time of the continuous work period. Set in table 240.

The equipment classification unit 110 generates the semi-long term equipment table 250 as follows.
The equipment classification unit 110 counts the date and time and the worker ID for each equipment ID in the maintenance work table 220, except for one maintenance work by another worker (temporary worker). The maximum period during which the maintenance work is performed by the worker) is calculated as the continuous work period.
The equipment classification unit 110 selects, as a semi-long-term equipment identifier, an equipment ID whose calculated continuous work period is a predetermined period threshold (for example, one month) or more. That is, the maintenance work table 220 selects, as a semi-long-term equipment identifier, the equipment ID of equipment whose worker has been changed only once during a period equal to or greater than a predetermined period threshold.
For each selected semi-long-term equipment identifier, the equipment classification unit 110 obtains a semi-long-term equipment identifier (equipment ID), a worker ID of the worker in charge (worker worker ID), a continuous work period, and a start date and time of the continuous work period Set in the semi-long-term equipment table 250. Furthermore, the equipment classification unit 110 sets the worker ID (temporary worker ID) of the temporary worker and the date and time (temporary work date and time) when the temporary worker performed the maintenance work.

FIG. 16 is a schematic diagram showing an example of the equipment classification process (S110) in the first embodiment.
In the case of the maintenance work table 220 shown in FIG. 16, the maintenance work for the equipment 0001 is performed by the same worker 001, and the continuous work period is one month or longer. Therefore, the equipment classification unit 110 sets the equipment 0001 in the long-term equipment table 240.
Further, the maintenance work of the facility 0002 is performed by the same worker 002 except for one maintenance work by the worker 902, and the continuous work period is one month or more. Therefore, the equipment classification unit 110 sets a record in the semi-long-term equipment table 250 using the equipment 0002 as a semi-long-term equipment identifier.
On the other hand, the maintenance work of the facility 0003 is performed by a plurality of workers, and even if one maintenance work by the worker 803 or the worker 703 is excluded, the continuous work period is less than one month. Therefore, the equipment classification unit 110 does not set the equipment 0003 in either the long-term equipment table 240 or the semi-long-term equipment table 250.

Returning to FIG. 15, the description of the work plan support method will be continued.
It progresses to S120 after S110.

In S120, the failure number evaluation unit 120 generates a long-term equipment failure number table 260 (see FIG. 8) based on the long-term equipment table 240 (see FIG. 6) and the failure table 230 (see FIG. 5).
Furthermore, the failure number evaluation unit 120 generates a quasi-long-term equipment failure number table 270 (see FIG. 9) based on the quasi-long-term equipment table 250 (see FIG. 7) and the failure table 230.

The failure number evaluation unit 120 generates the long-term equipment failure number table 260 as follows.
The failure number evaluation unit 120 searches the failure table 230 using the facility ID as a search key for each facility ID in the long-term facility table 240, and hits a search among the records in the failure table 230 including the date and time within a predetermined evaluation period. The number of recorded records is calculated as the number of failures.
The failure number evaluation unit 120 sets the facility ID, the start date / time of the evaluation period (evaluation start date / time), the end date / time of the evaluation period (evaluation end date / time), and the number of failures for each facility ID in the long-term equipment failure number table 260.

  The failure number evaluation unit 120 generates a quasi-long-term facility failure number table 270 in the same manner as the long-term facility failure number table 260.

FIG. 17 is a schematic diagram showing an example of the failure number evaluation process (S120) in the first embodiment.
An example of the failure number evaluation process (S120) in the first embodiment will be described with reference to FIG.

In the long-term equipment table 240, equipment 0001 is set, and in the semi-long-term equipment table 250, equipment 0002 is set.
Here, it is assumed that the evaluation period is from 0:00 on February 1 to 0:00 on March 1.
The number of failures of the equipment 0001 within the evaluation period set in the failure table 230 is four. Therefore, the failure number evaluation unit 120 sets “4” as the failure number of the equipment 0001 in the long-term equipment failure number table 260.
Further, the number of failures of the equipment 0002 within the evaluation period set in the failure table 230 is five. Therefore, the failure number evaluation unit 120 sets “5” as the number of failure of the facility 0002 in the near-long-term facility failure number table 270.

Returning to FIG. 15, the description of the work plan support method will be continued.
It progresses to S130 after S120.

  In S130, the long-term equipment failure rate evaluation unit 130 determines the long-term equipment failure number table 260 (see FIG. 8), the worker table 200 (see FIG. 2), the equipment table 210 (see FIG. 3), and the long-term equipment table 240 (FIG. 6). And a long-term equipment failure rate table 280 (see FIG. 10).

The long-term equipment failure rate evaluation unit 130 generates the long-term equipment failure rate table 280 as follows.
The long-term equipment failure rate evaluation unit 130 acquires, for each equipment ID set in the long-term equipment table 240, the equipment type associated with the same equipment ID as the equipment ID from the equipment table 210.
The long-term equipment failure rate evaluation unit 130 acquires a worker ID associated with each equipment ID from the long-term equipment table 240.
The long-term equipment failure rate evaluation unit 130 acquires, for each acquired worker ID, a worker attribute associated with the same worker ID as the worker ID from the worker table 200.
The long-term facility failure rate evaluation unit 130 acquires the number of failures associated with each facility ID from the long-term facility failure number table 260.
For each combination of equipment type and worker attribute, the long-term equipment failure rate evaluation unit 130 calculates the total number of failures for each equipment ID corresponding to the combination, and based on the calculated total number of failures Calculate confidence intervals for rates.
The long-term equipment failure rate evaluation unit 130 sets the equipment type, worker attribute, and failure rate confidence interval in the long-term equipment failure rate table 280 for each combination of equipment type and worker attribute.

For example, the long-term equipment failure rate evaluation unit 130 calculates the following equation (1) to calculate a 95% confidence interval for the failure rate. The 95% confidence interval is a range of failure rates that can be taken with a probability of 95%.
The meanings of the symbols used in the following formula (1) are as follows.
r _L ^min is the lower limit of the 95% confidence interval.
r _L ^max is the upper limit value of the 95% confidence interval.
E _L is the total value of the failure number.
N _L is the number of facility IDs associated with the facility type (hereinafter referred to as “the number of facilities”).
r _L is a failure rate (= total number of failures E _L ÷ number of facilities N _L ).
F _α [a, b] is an F distribution critical value corresponding to the upper probability α for the values a and b. For example, Non-Patent Document 1 discloses the F distribution critical value.

FIG. 18 is a schematic diagram showing an example of the long-term equipment failure rate evaluation process (S130) in the first embodiment.
An example of the long-term equipment failure rate evaluation process (S130) in the first embodiment will be described with reference to FIG.

The equipment list 001 lists equipment IDs corresponding to combinations of equipment type “equipment type 001” and worker attribute “worker attribute 01” among equipment IDs set in the long-term equipment table 240 (not shown). Is. It is assumed that 150 equipment IDs including equipment 0001 and equipment 0004 are set in the equipment list 001.
In the long-term equipment failure number table 260, the number of troubles of each equipment ID in the equipment list 001 is set, and the total value is “15”.
In this case, the failure rate confidence interval calculated using the above equation (1) is “0.057 (5.7%) to 0.160 (16.0%)”.
Therefore, the long-term equipment failure rate evaluation unit 130 associates the failure rate confidence interval “0.057 to 0.160” with the long-term equipment failure in association with the equipment type “equipment type 001” and the worker attribute “worker attribute 01”. Set in the rate table 280.

The equipment list 002 is a list of equipment IDs corresponding to combinations of equipment type “equipment type 002” and worker attribute “worker attribute 02” among equipment IDs set in the long-term equipment table 240 (not shown). . It is assumed that 80 equipment IDs including equipment 0006 are set in the equipment list 002.
In the long-term equipment failure number table 260, the number of troubles of each equipment ID in the equipment list 002 is set, and the total value is “8”.
In this case, the failure rate confidence interval calculated using the above equation (1) is “0.044 (4.4%) to 0.188 (18.8%)”.
Therefore, the long-term equipment failure rate evaluation unit 130 associates the failure rate confidence interval “0.044 to 0.188” with the long-term equipment failure in association with the equipment type “equipment type 002” and the worker attribute “worker attribute 02”. Set in the rate table 280.

Returning to FIG. 15, the description of the work plan support method will be continued.
It progresses to S140 after S130.

  In S140, the semi-long-term equipment failure rate evaluation unit 140 performs a long-term equipment failure rate table 280 (see FIG. 10), a semi-long-term equipment failure number table 270 (see FIG. 9), an operator table 200 (see FIG. 2), and an equipment table. A work quality table 290 (see FIG. 11) is generated based on 210 (see FIG. 3) and the semi-long-term equipment table 250 (see FIG. 7).

The semi-long-term facility failure rate evaluation unit 140 generates the work quality table 290 as follows.
The semi-long-term equipment failure rate evaluation unit 140 acquires, for each equipment ID set in the semi-long-term equipment table 250, the equipment type associated with the same equipment ID as the equipment ID from the equipment table 210.
The semi-long-term equipment failure rate evaluation unit 140 acquires the worker ID and temporary worker ID associated with each equipment ID from the semi-long-term equipment table 250 from the semi-long-term equipment table 250.
The quasi-long-term equipment failure rate evaluation unit 140 acquires, for each acquired worker ID, a worker attribute (charge worker attribute) associated with the same worker ID as the worker ID from the worker table 200. . Further, the semi-long-term equipment failure rate evaluation unit 140 obtains, for each acquired temporary worker ID, a worker attribute (temporary worker attribute) associated with the same worker ID as the temporary worker ID from the worker table 200. get.
The semi-long-term facility failure rate evaluation unit 140 acquires the number of failures associated with each facility ID from the semi-long-term facility failure number table 270.
The semi-long-term equipment failure rate evaluation unit 140 calculates, for each combination of equipment type and responsible worker attribute (and temporary worker attribute), the total number of failures for each equipment ID corresponding to the combination. A confidence interval for the failure rate is calculated based on the total number of failures. Hereinafter, the confidence interval of the failure rate calculated by the quasi-long-term equipment failure rate evaluation unit 140 is referred to as a “quasi-long-term confidence interval”.
The quasi-long-term equipment failure rate evaluation unit 140 determines the failure rate confidence interval (hereinafter referred to as “long-term reliability”) set in the long-term equipment failure rate table 280 for each combination of the equipment type and the assigned worker attribute (and temporary worker attribute). A failure increment index representing the increment of the semi-long-term confidence interval for the “interval” is calculated.
The quasi-long-term equipment failure rate evaluation unit 140 sets the equipment type, the responsible worker attribute, the temporary worker attribute, and the long-term confidence interval (failure rate confidence) for each combination of the equipment type and the responsible worker attribute (and the temporary worker attribute). Section) and the failure increment index are set in the work quality table 290.

For example, the semi-long-term equipment failure rate evaluation unit 140 calculates the following equation (2) to calculate a 95% confidence interval for the failure rate.
The meanings of the symbols used in the following formula (2) are as follows.
r _S ^min is the lower limit of the 95% confidence interval.
r _S ^max is the upper limit value of the 95% confidence interval.
E _S is the total value of the failure number.
N _S is the number of equipment ID associated with the equipment type (hereinafter, referred to as "the number of facilities") is.
r _S is the failure rate (= total value E _S / number of facilities N _S ).

  For example, the semi-long-term equipment failure rate evaluation unit 140 determines the magnitude relationship between the long-term confidence interval and the semi-long-term confidence interval, and calculates a failure increment index based on the determination result as follows.

FIG. 19 is a diagram illustrating a magnitude relationship between the long-term confidence interval and the quasi-long-term confidence interval in the first embodiment. A method for calculating the failure increment index in the first embodiment will be described with reference to FIG.
<CASE 1> When the lower limit value r _S ^min of the semi-long-term confidence interval r _s is larger than the upper limit value r _L ^max of the long-term confidence interval r _L , the semi-long-term equipment failure rate evaluation unit 140 calculates the following equation (3) Thus, the failure increment index is calculated.
<CASE 2> upper limit value _r ^{S max} of subchronic confidence interval _{r s} is greater than the upper limit value _r ^{L max} long-term confidence interval _{r L,} the lower limit value _r ^{S min} of subchronic confidence interval _{r s} is long confidence interval _{r L} When the lower limit value r _L ^{min is} equal to or greater than the upper limit value r _L ^max , the semi-long-term facility failure rate evaluation unit 140 calculates the failure increment index by calculating the following equation (4).
<CASE 3> In other cases (when the upper limit value r _S ^max of the quasi-long-term confidence interval r _s is less than or equal to the upper limit value r _L ^max of the long-term confidence interval r _L ), the quasi-long-term equipment failure rate evaluation unit 140 (5) is calculated to calculate a failure increment index (= 0).

FIG. 20 is a schematic diagram illustrating an example of a semi-long-term facility failure rate evaluation process (S140) in the first embodiment.
An example of the semi-long-term facility failure rate evaluation process (S140) in the first embodiment will be described with reference to FIG.

The equipment list 001 is a list of equipment IDs corresponding to combinations of equipment type “equipment type 001” and worker attribute “worker attribute 01” among equipment IDs set in the semi-long term equipment table 250 (not shown). It is a thing. It is assumed that 100 equipment IDs including the equipment 0005 are set in the equipment list 001. It is assumed that the temporary worker attribute is “worker attribute 02”.
The number of failures is set in the semi-long-term facility failure count table 270 in association with each facility ID, and the total number of failures for each facility ID in the facility list 001 is “13”.
In this case, the quasi-long-term confidence interval (failure rate confidence interval) calculated by calculating Equation (2) above is “0.071 (7.1%) to 0.212 (21.2%)”. .
The long-term confidence interval (failure rate confidence interval) set in the long-term equipment failure rate table 280 in association with the equipment type “equipment type 001” and the worker attribute “worker attribute 01” is “0.057 to 0.160. It is.
According to the magnitude relationship between the long-term confidence interval “0.057 to 0.160” and the quasi-long-term confidence interval “0.071 to 0.212”, the quasi-long-term equipment failure rate evaluation unit 140 calculates the above equation (4). Thus, the failure increment index “0.045” is calculated.
The semi-long-term equipment failure rate evaluation unit 140 associates the equipment type “equipment type 001” and the worker attribute “worker attribute 01” with the temporary worker attribute “worker attribute 02” and the long-term confidence interval “0.057”. ˜0.160 ”(failure rate confidence interval) and failure increment index“ 0.045 ”are set in the work quality table 290.

The equipment list 002 is a list of equipment IDs corresponding to combinations of equipment type “equipment type 002” and worker attribute “worker attribute 02” among equipment IDs set in the semi-long term equipment table 250 (not shown). It is a thing. It is assumed that 45 equipment IDs including the equipment 0002 are set in the equipment list 002. It is assumed that the temporary worker attribute is “worker attribute 01”.
In the near-long-term equipment failure number table 270, the number of troubles is set in association with each equipment ID, and the total number of troubles for each equipment ID in the equipment list 002 is “21”.
In this case, the quasi-long-term confidence interval (failure rate confidence interval) calculated by calculating Equation (2) is “0.317 (31.7%) to 0.621 (62.1%)”. .
The long-term confidence interval (failure rate confidence interval) set in association with the equipment type “equipment type 002” and the worker attribute “worker attribute 02” in the long-term equipment failure rate table 280 is “0.041 to 0.075. It is.
According to the magnitude relationship between the long-term confidence interval “0.041 to 0.075” and the quasi-long-term confidence interval “0.317 to 0.621”, the quasi-long-term equipment failure rate evaluation unit 140 calculates the above equation (3). Then, the failure increment index “0.353” is calculated.
The semi-long-term equipment failure rate evaluation unit 140 associates the equipment type “equipment type 002” with the worker attribute “worker attribute 02” and associates the temporary worker attribute “worker attribute 01” with the long-term confidence interval “0.041”. ˜0.075 ”(failure rate confidence interval) and failure increment index“ 0.353 ”are set in the work quality table 290.

Returning to FIG. 15, the description of the work plan support method will be continued.
After S140, the process proceeds to S150.

In S150, the work plan creation unit 150 generates maintenance work plan data 310 (see FIG. 13) based on the maintenance schedule table 300 (see FIG. 12).
At this time, the work plan creation unit 150 acquires the scheduled date, the equipment ID, and the maintenance work from the record for each record of the maintenance schedule table 300, and acquires the scheduled date (planned work date), the equipment ID, and the maintenance work. Is set in the record of the maintenance work plan data 310. In addition, the work plan creation unit 150 selects a worker ID satisfying a predetermined selection condition for each record of the maintenance work plan data 310 from the worker table 200 or the maintenance work table 220, and sets the selected worker ID in the record. Set.
For example, the work plan creation unit 150 obtains a worker ID associated with the same equipment ID as the equipment ID set in the record of the maintenance work plan data 310 from the maintenance work table 220, and the obtained worker ID is Set to record.
After S150, the process proceeds to S160.

  In S160, the work plan evaluation unit 160 calculates the work quality value (evaluation value) of the maintenance work plan data 310 based on the long-term equipment failure rate table 280 (see FIG. 10), and the work of the calculated maintenance work plan data 310 is calculated. Output quality values.

For example, the work plan evaluation unit 160 calculates the work quality value of the maintenance work plan data 310 as follows.
The work plan evaluation unit 160 acquires, for each record of the maintenance work plan data 310, the equipment type associated with the same equipment ID as the equipment ID set in the record from the equipment table 210, and the work set in the record The worker attribute associated with the same worker ID as the worker ID is acquired from the worker table 200.
The work plan evaluation unit 160 acquires, from the long-term equipment failure rate table 280, the failure rate confidence interval associated with the same equipment type and worker attribute as the record for each record of the maintenance work plan data 310, and acquires the acquired failure. An intermediate value of the rate confidence interval (hereinafter referred to as “estimated failure rate”) is calculated.
The work plan evaluation unit 160 calculates the total value of the estimated failure rate for each record of the maintenance work plan data 310 and performs a maintenance work by dividing the calculated total value of the estimated failure rate by the number of records in the maintenance work plan data 310. The work quality value of the plan data 310 is calculated. The smaller the work quality value, the smaller the estimated failure rate.
After S160, the process proceeds to S170.

In S170, the work plan update unit 170 performs maintenance work plan data in which the combination of the planned work date and the worker ID is the same for each combination of the planned work date and the worker ID set in the maintenance work plan data 310. The number of records of 310 is calculated as the workload number. The number of workloads means the number of maintenance work performed by the worker identified by the worker ID on the planned work day.
The work plan update unit 170 compares the number of workloads of the combination with a predetermined load number threshold for each combination of the planned work date and the worker ID set in the maintenance work plan data 310.
Then, the work plan update unit 170 determines whether there is a combination in which the number of workloads is greater than a predetermined load number threshold among the combinations of the planned work date and the worker ID set in the maintenance work plan data 310. .
When there is a combination in which the number of workloads is greater than a predetermined load number threshold among the combinations of the planned work date and the worker ID (YES), the process proceeds to S171.
If there is no combination in which the number of workloads is greater than the predetermined load number threshold among the combinations of the planned work date and the worker ID (NO), the process of the work plan support method ends.

Hereinafter, a combination in which the number of workloads is greater than a predetermined load number threshold among combinations of planned work dates and worker IDs is referred to as “overload combination”.
A value obtained by subtracting a predetermined load number threshold value from the number of work loads is referred to as a “number of overloads”.

In S <b> 171, the work plan update unit 170 selects the record of the number of overloads as the update target record from the records in which the overload combination is set from the maintenance work plan data 310. When the number of records for which the overload combination is set is “5” and the number of overload is “2”, the work plan update unit 170 selects two records among the five records for which the overload combination is set. Select a record for update.
The work plan update unit 170 selects a new worker ID based on the work quality table 290 for each update target record, and sets the selected new worker ID in the update target record of the maintenance work plan data 310. For example, when the worker ID of the update target record is “worker 001” and the new worker ID is “worker 002”, the work plan update unit 170 sets the worker ID of the update target record to “work”. From "person 001" to "worker 002".

For example, the work plan update unit 170 selects a new worker ID as follows.
The work plan update unit 170 acquires the equipment type associated with the same equipment ID as the update target record from the equipment table 210 and sets the worker attribute associated with the same worker ID as the update target record. Get from. Hereinafter, the combination of the acquired equipment type and the worker attribute is referred to as “target combination”.
The work plan update unit 170 selects each record in the work quality table 290 in which the same equipment type and worker attribute (responsible worker attribute) as the target combination are set. Furthermore, the work plan update unit 170 selects the record with the smallest failure increment index (hereinafter referred to as “minimum failure increment record”) among the selected records.
The work plan update unit 170 acquires a temporary worker attribute from the minimum failure increment record, and acquires each worker ID associated with the same worker attribute as the acquired temporary worker attribute from the worker table 200.
The work plan update unit 170 selects a new worker ID from each worker ID acquired from the worker table 200. For example, the work plan update unit 170 selects worker IDs as new worker IDs in ascending order of the number of workloads on the planned work day set in the update target record.

  By S171, the process of the work plan support method ends.

The processing of the work plan support method of FIG. 15 may be the following processing.
In S110, the equipment classification unit 110 may select, as a long-term equipment identifier, the equipment ID of the equipment that has not been changed by the operator, regardless of the length of the period. Further, the facility classification unit 110 may select the facility ID of the facility whose number of changes of the worker is equal to or less than the first number threshold (for example, once or less) as the long-term facility identifier.
In S110, the equipment classification unit 110 may select the equipment ID of the equipment that has been changed only once by the operator as the semi-long-term equipment identifier regardless of the length of the period. In addition, the equipment classification unit 110 selects the equipment ID of equipment whose number of operator changes is greater than the first frequency threshold and is equal to or less than the second frequency threshold (for example, 3 times or less) as the semi-long-term equipment identifier. It doesn't matter.
When updating the maintenance schedule table 300 (S170, S171), the user designates an update target record in the work plan support apparatus 100, and the work plan update unit 170 updates the worker ID of the designated update target record. It doesn't matter.

The work plan support method of FIG. 15 has the following effects.
Maintenance is not limited to equipment (long-term equipment) that has been maintained by a single worker for a certain period of time or longer, but also equipment (semi-long-term equipment) that has been maintained by another worker within a certain period of time. It is possible to learn and optimize a work plan, and to support the creation of a maintenance work plan with higher expected maintenance quality.

FIG. 21 is a diagram illustrating an example of hardware resources of the work plan support apparatus 100 according to the first embodiment.
In FIG. 21, the work plan support apparatus 100 (an example of a computer) includes a CPU 901 (Central Processing Unit). The CPU 901 is connected to hardware devices such as a ROM 903, a RAM 904, a communication board 905 (communication device), a display 911 (display device), a keyboard 912, a mouse 913, a drive 914, and a magnetic disk device 920 via a bus 902. Control hardware devices. The drive 914 is a device that reads and writes a storage medium such as an FD (Flexible Disk Drive), a CD (Compact Disc), and a DVD (Digital Versatile Disc).
The ROM 903, the RAM 904, the magnetic disk device 920, and the drive 914 are examples of storage devices. A keyboard 912, a mouse 913, and a communication board 905 are examples of input devices. The display 911 and the communication board 905 are examples of output devices.

  The communication board 905 is wired or wirelessly connected to a communication network such as a LAN (Local Area Network), the Internet, or a telephone line.

  The magnetic disk device 920 stores an OS 921 (operating system), a program group 922, and a file group 923.

  The program group 922 includes programs that execute the functions described as “units” in the embodiments. A program (for example, a work plan support program) is read and executed by the CPU 901. That is, the program causes the computer to function as “to part”, and causes the computer to execute the procedures and methods of “to part”.

  The file group 923 includes various data (input, output, determination result, calculation result, processing result, etc.) used in “˜part” described in the embodiment.

In the embodiment, arrows included in the configuration diagrams and flowcharts mainly indicate input and output of data and signals.
The processing of the embodiment described based on the flowchart and the like is executed using hardware such as the CPU 901, a storage device, an input device, and an output device.

  In the embodiment, what is described as “to part” may be “to circuit”, “to apparatus”, and “to device”, and “to step”, “to procedure”, and “to processing”. May be. That is, what is described as “to part” may be implemented by any of firmware, software, hardware, or a combination thereof.

  In the first embodiment, for example, the following work plan support apparatus 100 has been described. The name of the functional configuration or the item used in the first embodiment is shown in parentheses.

The work plan support apparatus 100 includes an operator data storage unit, a past work data storage unit, and a defect data storage unit (hereinafter, device storage unit 190).
The work plan support apparatus 100 includes a defect number calculation unit (failure number evaluation unit 120).
The work plan support apparatus 100 includes a past attribute value acquisition unit, an attribute-specific defect number calculation unit, an attribute-specific past work number calculation unit, and a defect index value calculation unit (hereinafter referred to as a semi-long-term facility failure rate evaluation unit 140). Prepare.
The work plan support apparatus 100 includes a worker candidate selection unit (work plan update unit 170).
The worker data storage unit associates a worker identifier (worker ID) for identifying a worker with a worker attribute value (worker attribute) indicating an attribute related to the worker for each worker who performs the work. Worker data (records in the worker table 200) is stored.
The past work data storage unit stores a past work identifier (equipment ID) for identifying a past work and a past worker identifier for identifying a worker who has performed the past work for each past work (semi-long term work) performed in the past. The past work data (record of the semi-long term equipment table 250) associated with the person in charge ID) is stored.
The failure data storage unit stores failure data (record of the failure table 230) including a failure work identifier (equipment ID) for identifying a failure work in which a failure has occurred for each failure that has occurred in the past work.
The defect number calculation unit includes, for each past work data stored in the past work data storage unit, the same defect work identifier as the past work identifier of the past work data among the defect data stored in the defect data storage unit. The number of defect data (number of failures) is calculated as the number of defects.
The past attribute value acquisition unit, for each past work data stored in the past work data storage unit, sets the worker attribute value associated with the same worker identifier as the past worker identifier of the past work data. Obtained as a past attribute value from the storage unit.
The number of defects by attribute is the number of defects of past work data in which the past attribute value is the same among the number of defects calculated by the number of defects calculated for each past attribute value acquired by the past attribute value acquisition unit. To calculate the number of defects by attribute (total number of failures).
The attribute-based past work number calculation unit calculates the number of past work identifiers (equipment number) having the same past attribute value as the past work number by attribute for each past attribute value acquired by the past attribute value acquisition unit. .
The defect index value calculation unit includes an attribute-based past work number calculated for each past attribute value by the attribute-based past work number calculation unit and an attribute-specific defect number calculated for each past attribute value by the attribute Based on the above, for each past attribute value, a value (failure increment index) related to the ratio (failure rate) of the number of defects by attribute to the number of past tasks by attribute is calculated as a defect index value.
The worker candidate selection unit is configured to perform a new operation (maintenance operation for the record to be updated) based on the defect index value calculated for each past attribute value by the defect index value calculation unit. (Worker ID) is selected.

The work plan support apparatus 100 includes a reference work data storage unit (device storage unit 190).
The work plan support apparatus 100 includes a reference attribute value acquisition unit, an attribute-specific defect reference number calculation unit, and an attribute-specific reference work number calculation unit (hereinafter, long-term equipment failure rate evaluation unit 130).
The reference work data storage unit includes a reference work identifier (equipment ID) for identifying a reference work and a work for which the reference work is performed for each reference work (long-term work) that satisfies a predetermined work condition among the work performed in the past. Reference work data (a record in the long-term equipment table 240) that associates a reference worker identifier (in-charge worker ID) for identifying a worker is stored.
The past work data storage unit stores past work data for each past work (semi-long term work) that does not satisfy the predetermined work condition among the work performed in the past.
The defect number calculation unit includes, for each reference work data stored in the reference work data storage unit, the same defect work identifier as the reference work identifier of the reference work data among the defect data stored in the defect data storage unit. The number of failure data (number of failures) is calculated as the failure reference number.
For each reference work data stored in the reference work data storage unit, the reference attribute value acquisition unit obtains a worker attribute value associated with the same worker identifier as the reference worker identifier of the reference work data. Obtained as a reference attribute value from the data storage unit.
The attribute-specific defect reference number calculation unit includes, for each reference attribute value acquired by the reference attribute value acquisition unit, reference work data having the same reference attribute value among the defect reference numbers calculated by the defect number calculation unit. The number of defect standards is totaled to calculate the number of defect standards by attribute (total number of malfunctions).
The attribute-specific reference work number calculation unit calculates the number of reference work identifiers (equipment number) having the same reference attribute value as the reference work number by attribute for each reference attribute value acquired by the reference attribute value acquisition unit. To do.
The defect index value calculation unit calculates, for each reference attribute value, a statistical value (long-term confidence interval) representing a ratio of the defect reference number by attribute to the reference work number by attribute of the reference attribute value as a defect reference rate. The defect index value calculation unit calculates, for each past attribute value, a statistical value (quasi-long-term confidence interval) representing a ratio of the number of defects by attribute to the number of past tasks by attribute of the past attribute value as a defect rate. The defect index value calculation unit calculates, for each past attribute value, the magnitude of the defect rate of the past attribute value (increment of the failure rate confidence interval) with respect to the defect reference rate of the same reference attribute value as the past attribute value as the defect index value To do.

  DESCRIPTION OF SYMBOLS 100 Work plan support apparatus, 110 Equipment classification part, 120 Failure number evaluation part, 130 Long-term equipment failure rate evaluation part, 140 Semi-long-term equipment failure rate evaluation part, 150 Work plan preparation part, 160 Work plan evaluation part, 170 Work plan update , 190 device storage unit, 200 worker table, 210 equipment table, 220 maintenance work table, 230 failure table, 240 long-term equipment table, 250 semi-long-term equipment table, 260 long-term equipment failure count table, 270 semi-long-term equipment failure count table 280 Long-term equipment failure rate table, 290 Work quality table, 300 Maintenance schedule table, 310 Maintenance work plan data, 901 CPU, 902 bus, 903 ROM, 904 RAM, 905 Communication board, 911 Display, 912 Keyboard, 913 Mouse, 914 drive, 920 magnetic disk device, 921 OS, 922 program group, 923 file group.

Claims (10)

For each worker who performs work, a worker data storage unit that stores worker data in which a worker identifier that identifies a worker and a worker attribute value indicating an attribute related to the worker are associated with each other;
A past work data storage unit that stores past work data in which a past work identifier that identifies a past work and a past worker identifier that identifies a worker who has performed the past work are associated with each other in the past; ,
For each defect that occurred in the past work, a defect data storage unit that stores defect data including a defect work identifier that identifies the defect work in which the defect has occurred;
For each past work data stored in the past work data storage unit, the number of fault data including the same fault work identifier as the past work identifier of the past work data among the fault data stored in the fault data storage unit is faulty. A defect number calculation unit to calculate as a number;
For each past work data stored in the past work data storage unit, a worker attribute value associated with the same worker identifier as the past worker identifier of the past work data is used as a past attribute value from the worker data storage unit. A past attribute value acquisition unit to be acquired;
For each past attribute value acquired by the past attribute value acquisition unit, the total number of defects of past work data having the same past attribute value out of the number of defects calculated by the number of defects calculation unit is calculated. An attribute-specific defect count calculation unit for calculating
For each past attribute value acquired by the past attribute value acquisition unit, the past work number calculation unit by attribute that calculates the number of past work identifiers having the same past attribute value as the past work number by attribute,
Based on the past number of tasks by attribute calculated for each past attribute value by the past number of tasks by attribute and the number of defects by attribute calculated for each past attribute value by the number of defects by attribute A defect index value calculation unit that calculates a value related to the ratio of the number of defects by attribute to the past number of tasks by attribute for each value as a defect index value;
A worker candidate selection unit that selects a worker attribute value of a worker candidate to perform a new work based on the defect index value calculated for each past attribute value by the defect index value calculation unit. Work plan support device to do. The work plan support device further includes a reference work data storage unit, a reference attribute value acquisition unit, an attribute-specific defect reference number calculation unit, and an attribute-specific reference work number calculation unit,
The reference work data storage unit includes a reference work identifier for identifying a reference work and a reference worker identifier for identifying a worker who has performed the reference work for each reference work that satisfies a predetermined work condition among works performed in the past. And memorize the reference work data
The past work data storage unit stores past work data for each past work that does not satisfy the predetermined work condition among works performed in the past,
The defect number calculation unit includes, for each reference work data stored in the reference work data storage unit, the same defect work identifier as the reference work identifier of the reference work data among the defect data stored in the defect data storage unit. The number of defect data is calculated as the defect reference number,
For each reference work data stored in the reference work data storage unit, the reference attribute value acquisition unit obtains a worker attribute value associated with the same worker identifier as the reference worker identifier of the reference work data. Obtained as a reference attribute value from the data storage unit,
The attribute-specific defect reference number calculation unit includes, for each reference attribute value acquired by the reference attribute value acquisition unit, reference work data having the same reference attribute value among the defect reference numbers calculated by the defect number calculation unit. The total defect standard number is calculated to calculate the defect standard number by attribute.
The attribute-specific reference work number calculation unit calculates, for each reference attribute value acquired by the reference attribute value acquisition unit, the number of reference work identifiers having the same reference attribute value as the attribute-specific reference work number,
The defect index value calculation unit calculates, as a defect reference rate, a statistical value representing a ratio of the defect reference number by attribute to the reference work number by attribute of the reference attribute value for each reference attribute value, and the past attribute value for each past attribute value The statistical value indicating the ratio of the number of defects by attribute to the past number of tasks by attribute is calculated as the defect rate, and the defect rate of the past attribute value is larger than the defect reference rate of the same reference attribute value as the past attribute value for each past attribute value The work plan support apparatus according to claim 1, wherein the work index is calculated as the defect index value. The work plan support apparatus according to claim 2, wherein the defect index value calculation unit calculates a confidence interval as the statistical value. The reference work is a work in which the number of times the worker has changed is less than a predetermined number of times threshold,
4. The work plan support apparatus according to claim 2, wherein the past work is a work in which the number of times the worker has changed is greater than the predetermined threshold value. The worker candidate selection unit acquires a worker identifier associated with the same worker attribute value as the selected worker attribute value from the worker data storage unit, and outputs the acquired worker identifier. The work plan support apparatus according to any one of claims 1 to 4. The work plan support device further includes:
A work type data storage unit that stores work type data including a work identifier for identifying a work and a work type for identifying the type of work for each work;
For each past work data, a past work type acquisition unit that acquires a work type associated with the same work identifier as the past work identifier of the past work data as a past work type from the work type data storage unit,
The attribute-specific defect count calculation unit calculates the attribute-specific defect count for each combination of the past work type and the past attribute value,
The attribute-based past work number calculation unit calculates the attribute-based past work number for each combination of the past work type and the past attribute value,
The defect index value calculation unit calculates a defect index value for each combination of a past work type and a past attribute value. The worker candidate selection unit calculates a defect for each combination of a past work type and a past attribute value. 6. The work plan support apparatus according to claim 1, wherein a worker attribute value of the worker candidate is selected based on an index value. The work plan support device further includes:
A scheduled work data storage unit for storing scheduled work data including a scheduled work identifier for identifying a scheduled work for each scheduled scheduled work;
A new work selection unit that selects a specific scheduled work identifier from the scheduled work data storage unit as a new work identifier for identifying the new work;
The worker candidate selection unit
The work type associated with the same work identifier as the new work identifier selected by the new work selection unit is acquired as a new work type from the work type data storage unit, and includes the same past work type as the acquired new work type. 7. The work plan support according to claim 6, wherein a worker attribute value of the worker candidate is selected from past attribute values of a combination including the same past work type as the new work type based on a combination defect index value. apparatus. Each scheduled work data includes a scheduled date on which the scheduled work will be performed and a scheduled worker identifier that identifies the worker scheduled to perform the scheduled work.
The new work selection unit calculates, as the scheduled work number, the number of scheduled work data in which the combination of the scheduled date and the scheduled worker identifier is the same for each combination of the scheduled date and the scheduled worker identifier. Select at least one scheduled work data including a scheduled date and a scheduled worker identifier whose number is greater than a predetermined number of tasks threshold, and select a scheduled task identifier included in the selected scheduled task data as the new task identifier. The work plan support apparatus according to claim 7. Worker data storage unit, past work data storage unit, defect data storage unit, defect number calculation unit, past attribute value acquisition unit, attribute-specific defect number calculation unit, attribute-specific past work number calculation unit, A work plan support method using a work plan support device comprising a defect index value calculation unit and a worker candidate selection unit,
The worker data storage unit is a storage unit that stores worker data in which a worker identifier for identifying a worker and a worker attribute value indicating an attribute related to the worker are associated with each other for each worker who performs the work. ,
The past work data storage unit stores past work data in which a past work identifier for identifying a past work and a past worker identifier for identifying a worker who has performed the past work are associated with each past work performed in the past. A storage unit for storing,
The defect data storage unit is a storage unit that stores defect data including a defect work identifier for identifying a defect work in which a defect has occurred for each defect that has occurred in a past work,
The defect number calculation unit includes, for each past work data stored in the past work data storage unit, the same defective work identifier as the past work identifier of the past work data among the defect data stored in the defect data storage unit. The number of defect data is calculated as the number of defects,
For each past work data stored in the past work data storage unit, the past attribute value acquisition unit obtains a worker attribute value associated with the same worker identifier as the past worker identifier of the past work data. Obtained as past attribute values from the data storage unit,
For each past attribute value acquired by the past attribute value acquisition unit, the defect number calculation unit for each attribute has a defect of past work data in which the past attribute value is the same among the number of defects calculated by the defect number calculation unit. Calculate the number of defects by attribute by summing the numbers,
For each past attribute value acquired by the past attribute value acquisition unit, the past work number calculation unit by attribute calculates the number of past work identifiers having the same past attribute value as the past work number by attribute,
The defect index value calculation unit calculates the past work number by attribute calculated for each past attribute value by the past work number calculation unit by attribute and the defect by attribute calculated for each past attribute value by the defect number calculation unit by attribute. Based on the number, a value related to the ratio of the number of defects by attribute to the number of past tasks by attribute for each past attribute value is calculated as a defect index value,
The worker candidate selection unit selects a worker attribute value of a candidate worker to perform a new work based on the defect index value calculated for each past attribute value by the defect index value calculation unit. Work plan support method to do.   A work plan support program for causing a computer to execute the work plan support method according to claim 9.

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