WO2014061080A1 - Système, procédé et programme d'aide à l'élaboration d'un plan de maintenance - Google Patents

Système, procédé et programme d'aide à l'élaboration d'un plan de maintenance Download PDF

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Publication number
WO2014061080A1
WO2014061080A1 PCT/JP2012/076610 JP2012076610W WO2014061080A1 WO 2014061080 A1 WO2014061080 A1 WO 2014061080A1 JP 2012076610 W JP2012076610 W JP 2012076610W WO 2014061080 A1 WO2014061080 A1 WO 2014061080A1
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WIPO (PCT)
Prior art keywords
maintenance
information
database
parts
work
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PCT/JP2012/076610
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English (en)
Japanese (ja)
Inventor
峻行 羽渕
裕 吉川
荒井　正人
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株式会社日立製作所
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Application filed by 株式会社日立製作所 filed Critical 株式会社日立製作所
Priority to PCT/JP2012/076610 priority Critical patent/WO2014061080A1/fr
Priority to PCT/JP2013/077813 priority patent/WO2014061604A1/fr
Priority to CA2888334A priority patent/CA2888334C/fr
Priority to AU2013332924A priority patent/AU2013332924B2/en
Priority to JP2014542114A priority patent/JP5938481B6/ja
Publication of WO2014061080A1 publication Critical patent/WO2014061080A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance

Definitions

  • the present invention relates to a maintenance planning support system, a maintenance planning support method, and a maintenance planning support program.
  • failure diagnosis is to provide a failure diagnosis system that effectively utilizes maintenance case information including data ambiguity and some missing parts.
  • a system see Patent Document 1 has been proposed.
  • an object of the present invention is to provide a technique that enables an effective maintenance plan to be efficiently formulated without depending on the skills of maintenance personnel.
  • the maintenance planning support system of the present invention that solves the above problems includes information on a phenomenon that has occurred in the work machine, information on a failure that has occurred in the work machine after the occurrence of the phenomenon, and maintenance work that has been performed for the failure.
  • a first database that holds information in association with each other
  • a second database that holds information on standard maintenance work defined for each work machine, and information on the availability of each person and equipment for maintenance work
  • the third database to be held, each stock and price of parts used for maintenance work or its old version parts or remanufactured parts, and delivery date and transportation cost information for each transportation destination and transportation means are retained for each warehouse.
  • the first database is used to collate the information on the phenomenon, the failure that may occur after the occurrence of the corresponding phenomenon is estimated, and the information on the maintenance work performed on the work machine at the time of the failure is identified in the first database.
  • the maintenance work information is collated with the second database, the standard maintenance work information expected to be carried out on the work machine is specified, and the maintenance work personnel and equipment availability specified by the maintenance work information Is identified in the third database as the maintenance implementation candidate date, and the parts specified by the maintenance work information or its old version parts or remanufactured parts are in stock, and the parts or their old version parts or regenerated parts are transported to the location of the work machine
  • the delivery date for delivery by means is within the grace period from the current time to the maintenance candidate date
  • the transportation means corresponding to the delivery date and its transportation cost Generate and output information on delivery dates, warehouses, transportation means, transportation costs and maintenance candidate dates as maintenance plan information for the parts to be used for maintenance work or the old version parts or recycled parts specified in the database.
  • a processing device that executes processing to be output to the device.
  • FIG. 1 is a diagram showing a network configuration example including a maintenance plan planning system 100 according to the present embodiment.
  • a maintenance plan planning system 100 shown in FIG. 1 is a computer system that enables an effective maintenance plan to be efficiently planned without depending on the skills of maintenance personnel.
  • a large mining machine will be described as an example of a work machine.
  • the market for this mining machine has expanded rapidly due to the increase in global demand for resources, while the parts supply capacity on the machine manufacturer side has not caught up with the market demand.
  • new parts that are the latest version, old version parts that have not been retroactively implemented, and refurbished parts that have repaired and refurbished faulty parts can be used in common.
  • Skilled maintenance staff used various parts with the same functions but different states and origins. However, parts with such various attributes are stored in warehouses scattered around the world, and unskilled maintenance personnel accurately recognize attributes, locations, inventory, etc., and appropriately incorporate them into the mining equipment maintenance plan. Has been difficult in the past.
  • the maintenance plan planning support system 100 according to the present embodiment enables even an inexperienced maintenance staff to appropriately adopt the above-described components having various attributes and appropriately plan a complicated maintenance plan.
  • the maintenance planning support system 100 is connected to the network 180 and can communicate data with the monitoring system 170 and the client terminal 190.
  • the monitoring system 170 monitors the measurement value of the sensor 11 installed in the mining machine 10, that is, sensor data, or monitors the parameter calculated by applying the sensor data to an appropriate algorithm, and 10 is a computer system for detecting an abnormality in 10.
  • the monitoring system 170 detects an abnormality when the sensor data or the calculated parameter exceeds a predetermined threshold, and transmits a notification of the abnormality detection to the maintenance planning support system 100.
  • the sensor 11 described above can be assumed to be a sensor that measures, for example, the motor rotation speed of the mining machine 10, the pump internal pressure, and the temperature and vibration of each place.
  • the sensor 11 installed in the mining machine 10 transmits sensor data to the monitoring system 170 by using a communication device provided in the mining machine 10 or a communication device provided in the sensor 11 itself.
  • the client terminal 190 accesses the maintenance plan planning support system 100, receives data input from maintenance personnel using a keyboard, a mouse, and the like, or displays data obtained from the maintenance plan planning support system 100 on a display or the like. It is responsible for each processing.
  • the hardware configuration of the maintenance planning system 100 is as follows.
  • the maintenance planning system 100 reads out to the memory 113 a storage device 115 composed of a suitable non-volatile storage device such as a hard disk drive, a memory 113 composed of a volatile storage device such as RAM, and a program held in the storage device 115.
  • the CPU 114 (arithmetic unit) for performing overall control of the system itself and performing various determinations, computations and control processes, and the communication device 112 connected to the network 180 and responsible for communication processing with other devices.
  • Functions implemented by executing the above-described programs include a phenomenon diagnosis function 121, a failure diagnosis function 122, a countermeasure extraction function 131, a plan creation function 141, a periodic maintenance plan adjustment function 142, a life calculation function 151, and a downtime calculation function 152.
  • a functional unit in which each of these function groups and a database group storing data used by each function is illustrated.
  • the functional units include an abnormality diagnosis unit 120, a countermeasure extraction unit 130, a plan creation unit 140, a performance prediction unit 150, and an output management unit 160. Data transmission between the functional units is managed by the I / O 111 via the BUS.
  • the database of each functional unit will be described later.
  • the maintenance planning support system 100 may have an input / output function and a device (display, keyboard, etc.). .
  • the maintenance planning support system 100 receives information on a phenomenon that has occurred in the mining machine 10 at a certain location from the monitoring system 170 via the network 180, and uses the phenomenon history database 123 and the failure history database as information on the received phenomenon. 124 (both are the first database), a failure that may occur after the occurrence of the corresponding phenomenon is estimated, and information on the maintenance work performed on the mining machine 10 at the time of the corresponding failure is stored in the work history database 132 (first database). Specific functions.
  • the maintenance planning support system 100 collates the maintenance work information specified above with the maintenance work database 133 (second database), and standard maintenance work expected to be performed on the mining machine 10 described above. And the maintenance work candidate specified by the maintenance work information and the time when the equipment can be operated are specified in the schedule database 143 (third database) as the maintenance execution candidate date.
  • the maintenance planning support system 100 stocks the parts specified by the above-described maintenance work information or the old version parts or the recycled parts thereof, and transports the corresponding parts or the old version parts or the recycled parts to the location of the corresponding mining machine 10.
  • the maintenance planning support system 100 uses the customer knowledge database 145 (No. 1) as the load factor information of the mining machine 10 or the part where the phenomenon occurs, which is included in the information on the phenomenon related to the mining machine 10 (from the monitoring system 170). 5 database), estimated the remaining life of the mining machine 10 or the part where the phenomenon occurred, and reduced the load factor according to the extent that the remaining life is less than the grace period from the current time to the maintenance candidate date. Is the load factor in the corresponding mining machine 10, the economic loss at the load factor is specified in the customer knowledge database 145 (fifth database), and the reduced load factor and the information on the economic loss at the load factor are described above. It is included in the maintenance plan information included in the maintenance plan database 161 or output to the client terminal 190.
  • the maintenance planning support system 100 relates to a part used for maintenance work or an old version part or a reproduced part indicated by the above-described maintenance plan information, in the part history database 153 (sixth database), the same type of part or an old version thereof.
  • the history of the attachment and removal of the part or the remanufactured part is specified, the time between the specified attachment and removal is calculated as the life, and the life information is included in the maintenance plan information and stored in the maintenance plan database 161 Or a function of outputting to the client terminal 190.
  • the maintenance planning support system 100 relates to a part used for maintenance work or an old version part or a reproduction part thereof indicated by the above-described maintenance plan information, and the same type of part or an old version thereof in the failure history database 124 (first database).
  • the presence or absence of failure information on the part or the remanufactured part is specified, and when the failure information exists, the maintenance work information performed for the failure is specified in the work history database 132 (first database).
  • the time from the start of work to the end of work indicated by the information of the corresponding maintenance work is calculated as downtime, and the downtime information is included in the maintenance plan information described above and stored in the maintenance plan database 161, Alternatively, it has a function of outputting to the client terminal 190.
  • the maintenance planning support system 100 relates to a part used for maintenance work or an old version part or a recycled part indicated by the maintenance plan information described above, in the operation result table 1010 (seventh database) of the part operation database 154.
  • Information on the measured value of the part or its old version part or recycled part is specified, and the information on the specified measured value is collated with the operation determination table 1000 (eighth database) of the part operation database 154, It has the function of calculating the downtime of the old version parts or the recycled parts as downtime and storing the downtime information in the maintenance plan database 161 included in the above-mentioned maintenance plan information or outputting it to the client terminal 190 .
  • the maintenance plan formulation support system 100 determines whether the regular maintenance schedule is included in the regular maintenance database 146 (the ninth database) within the period from the present time to the maintenance execution candidate date indicated by the above-described maintenance plan information. If the scheduled maintenance schedule is included in the period until the maintenance execution candidate date indicated by the maintenance plan information, replace the maintenance execution candidate date with the corresponding scheduled maintenance date, and generate maintenance plan information again. It has the function to do.
  • the abnormality diagnosis unit 120 included in the maintenance planning support system 100 includes a phenomenon history database 122 that stores phenomenon histories that have occurred in the mining machine 10 and the like, and sensor data or parameters received from the monitoring system 170 by the phenomenon diagnosis function 121. By referring to and comparing, it is diagnosed what kind of phenomenon the abnormality detected by the monitoring system 170 for the mining machine 10 is.
  • the abnormality diagnosis unit 120 included in the maintenance planning support system 100 includes a failure history database 124 that stores failure histories that have occurred in the mining machine 10 and the like using the failure diagnosis function 122, and the phenomenon that the phenomenon diagnosis function 121 identifies. By referring to and comparing the above, it is diagnosed what kind of failure the phenomenon specified by the phenomenon diagnosis function 121 is.
  • the abnormality diagnosis unit 120 of the maintenance planning support system 100 identifies what kind of failure the abnormality detected by the monitoring system 170 is associated with using the above-described function group.
  • the phenomenon diagnosis function 121 and the failure diagnosis function 122 of the abnormality diagnosis unit 120 transmit the specified phenomenon and failure to the output management unit 160.
  • the output management unit 160 stores and manages this in the maintenance plan database 161.
  • the countermeasure extraction unit 130 included in the maintenance planning support system 100 uses the countermeasure extraction function 131 to identify the work history database 132 in which maintenance work histories for past failures of the mining machine 10 and the like and the failure diagnosis function 122 have identified. By comparing the failure with the reference, a countermeasure to be taken is extracted for the abnormality detected by the monitoring system 170. Further, the countermeasure extracting function 131 refers to the maintenance work database 133 and extracts maintenance staff skills, equipment, work costs, and work time necessary for performing the maintenance work extracted from the work history database 132. In addition, the measure extraction function 131 transmits information on measures to be taken, extracted as described above, to the output management unit 160. The output management unit 160 stores and manages this in the maintenance plan database 161.
  • the plan creation unit 140 included in the maintenance plan planning support system 100 extracts a schedule of maintenance personnel and equipment corresponding to the measures extracted by the above-described measure extraction unit 130 from the schedule database 143 by the plan creation function 141. Extract maintenance candidate dates.
  • the plan creation function 141 refers to the parts procurement database 144 and drafts a procurement plan for procurement. Details of this planning procedure will be described later. Further, the plan creation function 141 drafts an operation plan from the operation loss information and the remaining life information in the customer knowledge database 145. Details of this planning procedure will be described later.
  • the regular maintenance plan adjustment function 142 in the plan creation unit 140 adjusts the maintenance schedule by adjusting the regular maintenance schedule in the regular maintenance database 146 and the schedule of the above-described procurement plan and operation plan. Details of this adjustment procedure will be described later.
  • the information related to the maintenance plan composed of the operation plan and the procurement plan prepared by the plan creation function 141 and the regular maintenance plan adjustment function 142 is transmitted to the output management unit 160 by the plan creation unit 140.
  • the output management unit 160 stores and manages this in the maintenance plan database 161.
  • the life calculation function 151 in the performance prediction unit 150 is Referring to the work history for each component recorded in the component history database 153, the life history of the used component is calculated. In addition, the life calculation function 151 transmits information on the calculated life record to the output management unit 160. The output management unit 160 stores and manages this in the prediction result database 162. At this time, the downtime calculation function 152 of the performance prediction unit 150 identifies a part whose status has been exchanged in the part history database 153, that is, a part that has already reached the end of its life.
  • the downtime calculation function 152 is recorded from the load factor of each mining machine 10 (sensor data obtained from various sensors 11 attached to the mining machine 10) held in the part operation database 154. Calculate the downtime of the parts used. Details of this calculation method will be described later.
  • the downtime calculation function 152 determines whether there is a difference between the downtime based on the failure history thus obtained and the downtime based on the sensor data, and transmits the determination result to the client terminal 190 to present to the user.
  • the user may be allowed to select any downtime.
  • the downtime calculation function 152 may accept any downtime correction from the user via the client terminal 190.
  • the performance prediction unit 150 transmits the downtime uniquely determined in this way to the output management unit 160.
  • the output management unit 160 stores and manages this in the prediction result database 162.
  • the down time calculation function 152 may be executed in response to an instruction from the user not only when an abnormality occurs in the mining machine 10 but also during normal times.
  • the output management unit 160 included in the maintenance plan planning support system 100 also outputs the results output from the above-described abnormality diagnosis unit 120, countermeasure extraction unit 130, and plan creation unit 140 to the maintenance plan database 161 and the performance prediction unit 150.
  • the output results are held and managed in the prediction result database 162, respectively.
  • the data of the maintenance plan database 161 and the prediction result database 162 is output to the client terminal 190 accessed via the network 180. In this output, the content output to the client terminal 190 may be changed in response to a user request from the client terminal 190.
  • FIG. 2A shows an example of the phenomenon history database 123 in the present embodiment.
  • the phenomenon history database 123 is a database in which the history of phenomena observed for the mining machine 10 in the past is accumulated.
  • the data structure includes an occurrence date and time 202, a site ID 203, a machine ID 204, a model name 205, a phenomenon code 206, a phenomenon content 207, a part code 208, a part name 209, n, using the phenomenon ID 201 as a key.
  • This is a set of records composed of sensor data 210.
  • the phenomenon ID 201 an ID for uniquely identifying a phenomenon observed in the past for the mining machine 10 is stored.
  • the occurrence date 202 stores the date when the corresponding phenomenon occurred.
  • the site ID 203 stores the ID of the site where the mining machine 10 where the corresponding phenomenon is observed, that is, the mine.
  • the machine ID 204 stores the ID of the mining machine 10 in which the corresponding phenomenon is observed.
  • the model name 205 stores the model name of the mining machine 10.
  • the phenomenon code 206 stores a code indicating the corresponding phenomenon, and the phenomenon content corresponding to the code is stored in the phenomenon content 207.
  • the part code 208 stores a code indicating the part of the mining machine 10 where the phenomenon is observed, and the part name 209 stores the name of the part.
  • n sensor data 210 stores information observed by each sensor 11.
  • the information stored in the sensor data 210 may indicate the presence or absence of an abnormality, or may be a value itself observed by the sensor 11.
  • an abnormality detection parameter calculated by the monitoring system 170 from one or a plurality of sensor data may be stored.
  • FIG. 2B shows an example of the failure history database 124.
  • the failure history database 124 is a database in which a history of failures that have occurred in the past in the mining machine 10 is accumulated.
  • This failure history database 124 uses a failure ID 211 as a key, a phenomenon ID 212, an occurrence date and time 213, a machine ID 214, a model name 215, a part serial number 216, a part code 217, a part name 218, and a cause part number. 219, a cause component recycled product determination 220, an hour meter 221, a failure code 222, and a failure content 223.
  • the phenomenon ID 212 stores an ID for identifying a phenomenon observed in the mining machine 10 prior to the failure. This phenomenon ID 212 is common to the phenomenon ID 201 in the phenomenon history database 123 described above.
  • the occurrence date and time 213 stores the date and time when the corresponding failure occurred.
  • the machine ID 214 stores an ID for identifying the mining machine 10 in which the corresponding failure has occurred, and the model name 215 stores the model name of the corresponding mining machine 10.
  • the part serial number 216 stores a number for uniquely identifying a failed part in the mining machine 10.
  • the part code 217 and the part name 218 store a code indicating the part of the failed mining machine 10 and its name.
  • the cause part number 219 stores the product number of the failed part.
  • the cause component recycled product determination 220 stores a flag for determining whether the failed component is a recycled component or a new one.
  • the hour meter 221 stores an instruction value of an hour meter for operating time measurement provided in the mining machine 10. The indication value of this hour meter becomes the indication value at the time when the corresponding part fails.
  • the failure code 222 stores a code indicating the content of the failure that has occurred, and the failure content 223 stores the content of the failure that has occurred. Note that the relationship between each code and content in the failure history database 124 described above can also be managed by creating a separate master table in the same manner as the phenomenon and location in the phenomenon history database 123 described above.
  • FIG. 3 shows an example of the work history database 132 of the present embodiment.
  • the work history database 132 is a database that accumulates a history of maintenance work performed for failures that have occurred in the past in the mining machine 10.
  • the work history database 132 uses the work ID 301 as a key, a failure ID 302, a corresponding start date / time 303, a corresponding end date / time 304, a machine ID 305, a fault code 306, a fault content 307, a part code 308, and a part name. 309, cause part serial number 310, cause part number 311, work code 312, work content 313, replacement part serial number 314, replacement part number 315, and replacement part recycled product determination 316. It is an aggregate of. Of these, the failure ID 302 is common to the failure history database 124.
  • an ID for identifying the work performed for the failure corresponding to the failure ID 302 is stored.
  • the corresponding start date and time 303 and the corresponding end date and time 304 store the time when the corresponding work was started and the time when the corresponding work was completed.
  • the machine ID 305 stores an ID for identifying the mining machine 10 in which a failure has occurred and the maintenance work has been performed.
  • the failure code 306 and the failure content 307 store a code indicating the failure that has occurred and its content.
  • a code indicating the part where the failure has occurred and its name are stored.
  • the cause part serial number 310 stores a number that uniquely identifies the failed part, and the cause part number 311 stores the product number.
  • the work code 312 stores a code corresponding to the content of the maintenance work performed, and the work content 313 stores the content of the maintenance work. If the corresponding maintenance work involves parts replacement, the ID of the part to be newly attached to the mining machine 10 instead of the failed part is stored in the replacement part serial number 314.
  • the replacement part number 315 stores the product number of the replaced part, and the replacement part recycled product determination 316 stores a flag indicating whether or not the part is a recycled part.
  • each history database shown in FIG. 2A and FIG. 3 is the first database in the present invention, and is created and managed by a maintenance business operator, and is continued by performing the maintenance business. Expanded.
  • FIG. 4 shows an example of the maintenance work database 133 in this embodiment.
  • the maintenance work database 133 corresponds to the second database in the present invention that holds information on standard maintenance work defined for each work machine.
  • This maintenance work database 133 is a database that stores information on necessary resources and costs of standard maintenance work to be performed for each type of mining machine 10.
  • the maintenance work database 133 uses the model name 401 as a key, the work code 402, the work content 403, the part code 404, the part name 405, the part number 406, the replacement part number 407, the work cost 408, and the standard. This is a set of records composed of a work time 409, necessary equipment 410, and necessary maintenance staff skills 411.
  • the model name 401 described above stores the model name of the mining machine 10 to be subjected to maintenance work.
  • the work code 402 and the work content 403 respectively store a code for specifying the work content and the content thereof.
  • the part code 404, the part name 405, and the part number 406 respectively store a code indicating a target part where maintenance work is performed in the mining machine 10, a name thereof, and a product number of the target part. Even if the work code 402 has the same work content, the work code 402 is a different code when the cost, work time, and required resources differ depending on the type, part, and part of the mining machine 10.
  • the replacement part number 407 stores the product number of a part to be newly attached when the part is replaced in the corresponding maintenance work.
  • the replacement part number 407 is blank or a predetermined determination symbol is stored.
  • the work cost 408, the standard work time 409, the necessary equipment 410, and the necessary maintenance staff skill 411 include the cost required for the maintenance work, the time required for the maintenance work, the name of the equipment required for the maintenance work, and the maintenance. Stores the skill names of maintenance personnel required for the work.
  • FIG. 5 shows an example of the schedule database 143 in the present embodiment.
  • the schedule database 143 corresponds to a third database in the present invention that holds information on the availability of each person for maintenance work and each equipment.
  • the schedule database 143 is a collection of records including a date 500, a maintenance staff schedule 501, and an equipment schedule 502.
  • the schedule database 143 can be said to be a database that stores equipment owned by a maintenance company and a schedule of maintenance personnel employed.
  • the period in which the equipment and the maintenance staff can handle the maintenance work is represented by “1”, and the period in which the equipment and maintenance staff cannot handle is represented by “0”.
  • the date 500 is expressed in units of one day.
  • the maintenance manager or the like arbitrarily sets such as every hour, every eight hours, or every week. It's okay.
  • FIG. 6A shows an example of a parts inventory table 600 included in the parts procurement database 144 of this embodiment.
  • the parts procurement database 144 is composed of a parts inventory table 600, a transport means table 610, and a compatible parts table 620, and each stock and price of parts used for maintenance work or old version parts or recycled parts, and transportation.
  • the parts inventory table 600 is an aggregate of records including a part code 601, a part name 602, a part number 603, a recycled product determination 604, a warehouse 605, a stock 606, and a price 607. Each record shows how many parts are stocked in which warehouse and how much the price is.
  • the part code 601, the part name 602, the part number 603, and the recycled product determination 604 are information on the corresponding attribute of the inventory part.
  • the replacement parts used for the maintenance of the mining machine 10 are repaired and refurbished as new parts that are the latest version, old version parts that have not been retroactively implemented, and failed parts. There are recycled parts. Among these, the recycled parts are ranked according to the degree of wear.
  • N indicates a new article
  • Re-A”, “Re-B”, and “Re-C” indicate that a recycled part has a low level of wear, that is, a high-ranked one. Since the old version part is an old new article with only an old model number, it is “N” in the example of FIG. 6A. Of course, a notation for identifying the old version part may be used.
  • the warehouse 605 stores the name of the warehouse where the stock parts are stored, the stock 606 stores the number of stock parts, and the price 607 stores the unit price of the stock parts.
  • the stock 606 and the price 607 are variables that change with time, but here, it is assumed that the latest values are always stored.
  • FIG. 6B shows an example of the transportation means table 610 included in the parts procurement database 144 of this embodiment.
  • the transportation means table 610 included in the parts procurement database 144 is a collection of records including a warehouse 611, a transportation destination 612, a transportation means 613, a delivery date 614, and a transportation cost 615.
  • This record shows what kind of transportation is available from the warehouse as the transportation source to the site as the transportation destination, and how much time and cost it takes.
  • the warehouse 611 stores the name of the warehouse that is the transportation source of the parts.
  • a site name that is a transportation destination of the parts is stored in the transportation destination 612.
  • the transportation means 613 stores names of means used for parts transportation.
  • the delivery date and the cost in each case are stored in the delivery date 614 and the transportation cost 615, respectively.
  • FIG. 6C shows an example of the compatible component table 620 included in the component procurement database 144 of this embodiment.
  • the compatible parts table 620 included in the parts procurement database 144 is a collection of records including a model name 621, a part code 622, a part name 623, a part number 624, and a regular replacement interval 625.
  • This record shows a list of compatible parts that can be used in a certain part of a certain mining machine 10 and its regular replacement interval.
  • the model name 621 includes information indicating the model name of the target mining machine 10
  • the part code 622 includes information specifying the target part of the mining machine 10
  • the part name 623 includes the part code.
  • the names of the parts indicated by 622 are respectively stored.
  • the target mining machine 10 and its part can be specified by each information of the model name 621, the part code 622, and the part name 623.
  • the part number 624 stores a product number of a part that can be used by being attached to the target mining machine 10.
  • the parts that are specified by the information of the type name 621, the part code 622, and the part name 623 and that can be applied to a predetermined part of a certain mining machine 10 have the same specifications and functions, and are new parts with the latest model numbers. 3 parts of the old version parts and the recycled parts are included.
  • the periodic replacement interval 625 stores a component replacement interval recommended by a component manufacturer.
  • FIG. 7A shows an example of the operation loss table 700 included in the customer knowledge database 145 of this embodiment.
  • the customer knowledge database 145 stores the remaining life of each mining machine 10 according to the load factor at the time of failure and information on the economic loss in the user of the mining machine 10 due to the load factor reduction in association with each other. Corresponds to 5 databases.
  • the customer knowledge database 145 includes an operation loss table 700, a remaining life table 710, and a customer table 730.
  • the customer is a user of the mining machine 10 and a customer of the maintenance service of the mining machine 10.
  • the operation loss table 700 is a collection of records including a customer ID 701, a site ID 702, a model name 703, a part code 704, a part name 705, a load factor 706, and an operation loss 707.
  • the operation loss table 700 shows the customer's economic loss that occurs when the load factor of a certain part of the mining machine 10 is limited at a certain customer's site.
  • the customer ID 701 stores an ID for identifying a customer
  • the site ID 702 stores an ID for identifying a site where the corresponding mining machine 10 is operated.
  • the type name 703, the part code 704, and the part name 705, the type name of the mining machine 10, the code indicating the part, and the name of the part are stored.
  • the load factor 706 stores a load limiting rate when the load at the normal rated operation in the mining machine 10 is 100.
  • the “load” corresponds to the number of rotations and torque when the “part” is a motor, for example.
  • the operation loss 707 stores information on economic loss per unit time of a customer who operates the mining machine 10 that occurs when a load is limited. This operation loss 707 is characterized by the customer's operation policy, the type of resource mined at the site, and the part that limits the load.
  • FIG. 7B shows an example of the remaining life table 710 included in the customer knowledge database 145 of this embodiment.
  • the remaining life table 710 includes customer ID 711, site ID 712, model name 713, part code 714, part name 715, phenomenon code 716, phenomenon content 717, failure code 718, failure content 719, load This is a set of records composed of a rate 720 and a remaining life 721.
  • the customer ID 711 stores an ID for specifying a customer
  • the site ID stores an ID for specifying a site.
  • the model name 713, the part code 714, and the part name 715 store the model name of the target mining machine 10, the code indicating the part, and the name of the corresponding part.
  • the phenomenon code 716 and the phenomenon content 717 store a code indicating a phenomenon that has occurred in the corresponding part and the content of the corresponding phenomenon.
  • the failure code 718 and the failure content 719 store a code indicating the failure corresponding to the phenomenon and the content of the failure.
  • the load factor 720 stores the load factor at the corresponding part of the mining machine 10 that can be specified by the model name 713, the part code 714, and the part name 715.
  • the remaining life 721 stores a time from when an abnormality is detected at a corresponding part until a failure occurs.
  • the remaining life 721 is the phenomenon code at the site specified by the site code 714 and the site name 715 of the mining machine 10 of the model name 713 operated by the customer specified by the customer ID 711 at the site specified by the site ID 712. 716 and the phenomenon content 717, when the corresponding part is operated at the load factor of 720, it means how long the failure is stored in the failure code 718 and the failure content 719. .
  • FIG. 7C shows an example of the customer table 730 included in the customer knowledge database 145 of this embodiment.
  • the customer table 730 is an aggregate of records including a customer ID 731, a customer name 732, a site ID 733, a site name 734, a site type 735, and a country name code 736.
  • the customer ID 731 has an ID for identifying the customer
  • the customer name 732 has the name of the customer
  • the site ID 733 has an ID for identifying the site operated by the customer
  • the site name 734 has the ID of the site.
  • the name of the site type 735 stores the type of resource mined at the site
  • the country name code 736 stores a country name code representing the country in which the site exists.
  • the operation loss table 700, the remaining life table 710, and the customer table 730 described above are associated with each other using the customer ID and the site ID as keys.
  • FIG. 8 shows an example of the regular maintenance database 146 of this embodiment.
  • the regular maintenance database 146 corresponds to the ninth database of the present invention that stores a schedule of regular maintenance planned by the maintenance company for the mining machine 10.
  • the date on which the scheduled maintenance is planned is represented by “1”
  • the date on which the scheduled maintenance is not scheduled to be performed is represented by “0”.
  • the schedule unit may be arbitrarily set by the user.
  • FIG. 9 shows an example of the component history database 153 of this embodiment.
  • the parts history database 153 corresponds to a sixth database of the present invention that stores information on the attachment and removal of individual parts or their old version parts or recycled parts from the mining machine 10.
  • the component history database 153 includes a component serial number 901, a part code 902, a part name 903, a part number 904, a remanufactured product determination 905, a customer ID 906, a site ID 907, an attachment machine ID 908, and a status flag 909. And a collection of records composed of an attachment date 910 and a removal date 911.
  • the part serial number 901 stores a number that uniquely identifies the part that the maintenance company performs maintenance on.
  • the part code 902 and the part name 903 store a code indicating the part to which the corresponding part is attached and its name.
  • the part number 904 and the recycled product determination 905 store the product number of the component specified by the component serial number 901 and the recycled product determination flag, respectively.
  • Parts are put on the market as recycled parts through a cycle of mounting ⁇ removal ⁇ recycling ⁇ mounting. In this process, the recycled parts are ranked according to the degree of wear as described above. Recycled parts tend to lower the rank of the recycled product determination 905 as the reproduction is repeated.
  • the life from the attachment to the removal of the parts is called the life.
  • the lifespan is managed by assigning different parts serial numbers 901 in order to distinguish the parts of the same individual for each reproduction opportunity.
  • the mounting machine ID 909 stores the ID of the mining machine 10 to which the corresponding part is attached.
  • the customer ID 907 and the site ID 908 respectively store the ID of the customer who operates the mining machine 10 and the ID of the site where the mining machine 10 operates.
  • the status flag 910 stores the current status of the part.
  • the installation date / time 911 and the removal date / time 912 store the date / time when the corresponding part was attached to the mining machine 10 and the date / time when the part was removed from the mining machine 10.
  • FIG. 10A shows an example of an operation determination table 1000 included in the component operation database 154 of this embodiment.
  • the part operation database 154 stores information for determining whether to operate / stop a part using a value acquired from the sensor 11 attached to the part.
  • a part attached to a certain part of the mining machine 10 is stored in the part operation database 154.
  • An operation determination table 1000 that stores a determination formula for determining whether or not it is operating, and an operation result table 1010 that stores sensor data related to the mining machine 10 during a period specified by the user.
  • the operation determination table 1000 shown in FIG. 10A includes information of a model name 1001, a part code 1002, a part name 1003, a determination item 1004, a determination value 1005, and a determination condition 1006.
  • the determination item 1004 is a value such as the rotation speed or torque.
  • a condition in which “period” of the determination item 1004 is “2000” or more as the determination value 1005 is a condition for determining “operation”.
  • FIG. 10B shows an example of an operation result table 1010 included in the component operation database 154 of the present embodiment.
  • the operation result table 1010 is a collection of records including a component serial number 1011, an item 1012, a period 1013, and an average value 1014.
  • the part serial number 1011 stores a part number that uniquely identifies the part that the sensor 11 is measuring.
  • the item 1012 stores the type of sensor data stored for the corresponding part.
  • a period 1013 information on a period during which the sensor 11 has measured the corresponding part indicated by the part serial number 1011 is stored.
  • the average value 1014 stores an average value of the sensor data measured by the sensor 11 for the corresponding component indicated by the component serial number 1011 in the period 1013.
  • the period 1013 is set to one hour as a unit time, but may be appropriately changed by a user operation.
  • FIG. 11A shows an example of the abnormality diagnosis result table 1100 included in the maintenance plan database 161 of this embodiment.
  • the maintenance plan database 161 includes an abnormality diagnosis result table 1100, a countermeasure extraction result table 1120, an execution candidate table 1130, and a procurement / operation plan table 1140. These tables 1100 to 1140 are created as outputs of the abnormality diagnosis unit 120, the countermeasure extraction unit 130, the plan creation unit 140, and the performance prediction unit 150.
  • the abnormality diagnosis result table 1100 is a table output by the abnormality diagnosis unit 120, and includes an abnormality ID 1101, an occurrence date and time 1102, an hour meter 1103, a customer ID 1104, a site ID 1105, a machine ID 1106, a part serial number 1107, and a phenomenon.
  • This is a set of records including a code 1108, a phenomenon content 1109, a failure code 1110, and a failure content 1111.
  • the anomaly ID 1101 is an anomaly identified by the anomaly diagnosis unit 120 described above, and stores an ID that uniquely identifies an anomaly that is considered to be a sign of failure.
  • the occurrence date and time 1102 and the hour meter 1103 store the date and time and hour value when the corresponding abnormality is detected.
  • the customer ID 1104, the site ID 1105, the machine ID 1106, and the part serial number 1107 are respectively an ID that identifies a customer who owns the mining machine 10 that has detected an abnormality, and an ID that identifies a site where the mining machine 10 is operating.
  • the ID for identifying the mining machine 10 and the ID for identifying the component in which the abnormality is detected are stored.
  • the result of diagnosis by the phenomenon diagnosis function 121 described above is stored in the phenomenon code 1108 and the phenomenon content 1109
  • the result of diagnosis by the failure diagnosis function 122 is stored in the failure code 1110 and the failure content 1111.
  • FIG. 11B shows an example of the measure extraction result table 1120 included in the maintenance plan database 161 of this embodiment.
  • the countermeasure extraction result table 1120 includes a countermeasure ID 1121, an abnormality ID 1122, a work code 1123, a work content 1124, a standard work time 1125, a work cost 1126, and necessary equipment 1127 output from the above-described countermeasure extraction unit 130. , A set of records composed of necessary maintenance personnel skills 1128.
  • the countermeasure ID 1121 stores an ID that uniquely identifies a countermeasure, that is, maintenance work planned for the abnormality corresponding to the abnormality ID 1101 in the abnormality diagnosis result table 1100 described above.
  • the abnormality ID 1122 stores an abnormality ID 1122 that is common to the abnormality ID 1101 in the abnormality diagnosis result table 1100 described above.
  • the work code 1123 and the work content 1124 store the maintenance work code extracted from the work history database 132 and its content.
  • the standard work time 1125, work cost 1126, necessary equipment 1127, and necessary maintenance staff skill 1128 include the time, cost, and equipment required for the maintenance work extracted from the maintenance work database 133 for the relevant maintenance work. And maintenance staff skill information are stored.
  • FIG. 11C shows an example of the implementation candidate table 1130 included in the maintenance plan database 161 of this embodiment.
  • the implementation candidate table 1130 is a table that the plan function 141 of the plan creation unit 140 extracts and outputs from the measure extraction result table 1120 and the schedule database 143 that are the outputs of the measure extraction unit 130.
  • This execution candidate table 1130 is an aggregate of records including schedule ID 1131, countermeasure ID 1132, execution candidate 1133, possible date 1134, corresponding maintenance staff 1135, corresponding equipment 1136, and tx1137.
  • the schedule ID 1131 stores an ID for identifying a candidate period for performing maintenance work.
  • the countermeasure ID 1132 stores an ID that identifies the countermeasure to be implemented, in common with the countermeasure ID 1121 in the countermeasure extraction result table 1120 described above.
  • the execution candidate 1133 stores a value that matches the schedule ID 1131.
  • the execution date 1134 stores a schedule that allows the maintenance work to be extracted, which is extracted by the plan creation function 141 described above.
  • the maintenance staff 1135 and the equipment 1136 store the maintenance staff name and the equipment name corresponding to the correspondence, respectively.
  • a grace time from the current time to the execution candidate date of maintenance work is stored.
  • FIG. 11D shows an example of the procurement / operation table 1140 included in the maintenance plan database 161 of this embodiment.
  • the procurement / operation table 1140 stores the results output by the plan creation function 141 of the plan creation unit 140 described above with reference to the inventory parts database 145 and the customer knowledge database 145.
  • a procurement / operation table 1140 shown in FIG. 11D is a table configuration example showing the contents planned for maintenance work including parts replacement work.
  • the procurement / operation table 1140 includes a plan ID 1141, a schedule ID 1142, a part number 1143, a recycled product determination 1144, a warehouse 1145, a transportation means 1146, a delivery date 1147, a part price 1148, a transportation cost 1149, a load
  • plan ID 1141 stores an ID for uniquely identifying the procurement / operation plan. Note that if the maintenance work does not include parts replacement and therefore does not require parts procurement, the plan ID 1141 is an ID for specifying the operation plan.
  • the schedule ID 1142 stores an ID corresponding to the schedule ID 1131 of the execution candidate table 1130 described above.
  • the part number 1143 and the recycled product determination 1144 store the component number of the component to be newly installed in the replacement operation of the component and the recycled product determination flag of the corresponding component.
  • these part number 1143 and remanufactured product judgment 1144 are blank or some judgment symbols are stored.
  • the warehouse 1145, the transportation means 1146, the delivery date 1147, the part price 1148, and the transportation cost 1149 respectively include the name of the warehouse for procuring replacement parts, the transportation means, the delivery date, the price of the corresponding part, and the transportation cost. Stored.
  • the warehouse 1145, the transportation means 1146, the delivery date 1147, the part price 1148, and the transportation cost 1149 are blank or Some kind of judgment symbol is stored.
  • the load factor 1150 stores the upper limit of the load factor of the corresponding part (part replacement target part) in the mining machine 10 when the maintenance plan is executed.
  • the operation loss 1151 stores the customer's economic loss caused by limiting the load on the mining machine 10 to the value indicated by the load factor 1150.
  • the work loss 1152 stores the economic loss of the customer due to the stoppage of the operation of the mining machine 10 when the maintenance work is performed.
  • the procurement / operation table 1140 may be managed separately as a procurement table for parts procurement and an operation table for operations such as load factor and operation loss.
  • FIG. 12 shows an example of the prediction result database 162 in this embodiment.
  • the prediction result database 162 includes an object 1201, a part code 1202, a part name 1203, a part number 1204, a recycled product determination 1205, a regular replacement interval 1206, an average life 1207, and a history-based average DT (downtime). 1208, an operation base average DT 1209, and a set of records composed of 1210 samples.
  • This record is the output of the life calculation function 151 and the downtime calculation function 152 of the performance prediction unit 150.
  • the target 1201 specifies the range of the mining machine 10 for which the lifetime calculation function 151 and the downtime calculation function 152 described above are targets of performance prediction, and the country code and customer ID indicating the corresponding mining machine 10 and the like. Specified by the site ID.
  • the value of the site ID is set as the target 1201.
  • the part code 1202 and the part name 1203 store a code indicating the part targeted for performance prediction and its name.
  • the part number 1204 and the recycled product determination 1205 store the product number of the component subjected to performance prediction and the recycled product determination flag.
  • the periodic replacement interval 1206 stores the periodic replacement interval of the part whose performance is to be predicted, that is, the part indicated by the part number 1204.
  • the value of the regular replacement interval 1206 is, for example, a design replacement interval value defined by a component manufacturer.
  • the average life 1207 stores a value of the average life calculated by the above-described life calculation function 151 based on the component history database 153. The value of the average life 1207 is to be compared with the value of the regular replacement interval 1206 described above.
  • the history-based average DT 1208 stores the average downtime value calculated by the above-described downtime calculation function 152 based on the component history database 153 and the failure history database 124.
  • the operation base average DT 1209 stores the average downtime value calculated by the downtime calculation function 152 described above based on the component history database 153 and the component operation database 154.
  • the number of samples 1210 stores the number of parts processed by the life calculation function 151 and the downtime calculation function 152.
  • FIG. 13 is a flowchart showing a processing procedure example 1 of the maintenance plan planning method in the present embodiment. This flow is executed when the maintenance planning support system 100 receives a notification from the monitoring system 170 that the value of the sensor data of the sensor 11 exceeds a predetermined threshold.
  • the process S1301 is executed by the phenomenon diagnosis function 121 of the abnormality diagnosis unit 120.
  • the phenomenon diagnosis function 121 identifies and responds to a phenomenon detected by the monitoring system 170 by comparing the sensor data abnormality detected by the monitoring system 170 with the sensor data 210 of the phenomenon history database 123. Information on the corresponding phenomenon such as the phenomenon ID 201, the phenomenon code 206, and the phenomenon content 207 is extracted from the phenomenon history database 123.
  • the phenomenon diagnosis function 121 includes information related to the phenomenon identified by itself, information related to a part for which the monitoring system 170 detects an abnormality in sensor data (eg, customer ID, site ID, machine ID, part serial number, etc.) Is output to the abnormality diagnosis result table 1100 in the maintenance plan database 161.
  • information related to a part for which the monitoring system 170 detects an abnormality in sensor data eg, customer ID, site ID, machine ID, part serial number, etc.
  • the failure diagnosis function 122 refers to the failure history database 124 using the value of the phenomenon ID 201 extracted in the above-described process S1301 as a key, identifies a failure corresponding to the phenomenon detected by the monitoring system 170, and sets the failure ID 211 and the failure code. 222 is extracted.
  • the failure diagnosis function 122 outputs information on the failure thus extracted to the abnormality diagnosis result table 1100 in the maintenance plan database 161.
  • step S1303 is executed by the measure extracting function 131 of the measure extracting unit 130.
  • the countermeasure extracting function 131 refers to the work history database 132 by using the value of the failure ID 211 extracted by the failure diagnosis function 122 in the process S1302 described above as a key, and performs maintenance work that has been performed for the same failure in the past. Then, the work code 312 is extracted. The measure extraction function 131 outputs the extracted result to the measure extraction result table 1120.
  • step S1304 is executed by the measure extraction function 131 of the measure extraction unit 130.
  • the countermeasure extracting function 131 refers to the maintenance work database 133 using the work code 312 extracted in the processing S1303 as a key, and the work cost 408, the standard work time 409, the necessary equipment 410, the maintenance staff skill required for the corresponding maintenance work. The value of 411 is extracted.
  • the measure extraction function 131 outputs the result extracted here to the measure extraction result table 1120.
  • step S1305 is executed by the plan creation function 141 of the plan creation unit 140.
  • the plan creation function 141 reads, from the schedule database 143, the schedule of the maintenance staff who possesses the equipment corresponding to the necessary equipment 410 extracted in the above-described processing S1304 and the skills indicated by the maintenance staff skills 411. From the schedule read here, the plan creation function 141 identifies a “vacant day” that can be handled by the relevant equipment and maintenance personnel, that is, no other work schedules, as the implementation candidate date, and implements from the present time. The period tx until the candidate date is calculated. The plan creation function 141 outputs information on the identified implementation candidate date (corresponding to “execution date” in the implementation candidate table 1130) and the period tx to the implementation candidate table 1130.
  • step S1306 is executed by the plan creation function 141.
  • the plan creation function 141 determines whether the maintenance work specified by the measure extraction function 131 in the above-described process S1303 includes a parts replacement work. When the maintenance work does not include the part replacement work (S1306: No), the plan creation function 141 executes the process S1307. On the other hand, when the maintenance work includes parts replacement work (S1306: Yes), the plan creation function 141 executes the process S1308.
  • plan creation function 141 creates an operation plan with reference to the implementation candidate table 1130 and the customer knowledge database 145, and outputs the operation plan to the procurement / operation table 1140.
  • the detailed procedure for creating the operation plan will be described later with reference to FIG.
  • the process S1308 is executed by the plan creation function 141 of the plan creation unit 140.
  • the plan creation function 141 creates a procurement / operation plan by referring to the execution candidate table 1130, the parts procurement database 144, and the customer knowledge database 145, and outputs the procurement / operation plan to the procurement / operation plan table 1140. Details of the procurement / operation plan creation will be described later with reference to FIG.
  • step S1309 is executed by the performance prediction unit 150.
  • the life calculation function 151 of the performance prediction unit 150 calculates the average life of the corresponding part based on the part history database 153 for the replacement part indicated in the procurement / operation plan created in the above-described process S1308.
  • the downtime calculation function 152 of the performance prediction unit 150 calculates the downtime of the corresponding part based on the part history database 153, the failure history database 124, and the part operation database 154.
  • the average lifetime value calculated by the lifetime calculation function 151 and the downtime value calculated by the downtime calculation function 152 are output to the prediction result database 162 by each function.
  • Each process in the life calculation function 151 and the downtime calculation function 152 will be described later with reference to FIGS.
  • step S1310 is executed by the regular maintenance plan adjustment function 142 of the plan creation unit 140.
  • the regular maintenance plan adjustment function 142 refers to the operation / procurement plan table 1140 created by the above-described plan creation function 141 and the regular maintenance database 146, and performs the implementation candidate date and the scheduled maintenance execution schedule indicated by the operation / procurement plan. It is determined whether or not the date matches. If the execution candidate date matches the scheduled scheduled maintenance date (S1310: Yes), the scheduled maintenance plan adjustment function 142 executes step S1311. On the other hand, when the execution candidate date does not match the scheduled scheduled maintenance date (S1310: No), the scheduled maintenance plan adjustment function 142 executes step S1312.
  • the process S1311 is executed by the plan creation function 141 of the plan creation unit 140.
  • the plan creation function 141 sets the scheduled maintenance execution date as the only execution candidate date, and executes the processing S1307 to create an operation plan when the above-described operation / procurement plan does not include parts replacement work.
  • the plan creation function 141 creates a procurement / operation plan by executing step S1308 when the above-described operation / procurement plan includes parts replacement work.
  • the plan creation function 141 outputs the operation / procurement plan and operation plan thus created to the procurement / operation plan table 1140.
  • the output management unit 160 outputs the maintenance plan and the prediction result stored in the maintenance plan database 161 and the prediction result database 162 of the output management unit 160 in the procedure so far to the client terminal 190.
  • the client terminal 190 outputs the maintenance plan and the prediction result on the display, and is used for evaluation and examination of the maintenance plan by the corresponding user.
  • FIG. 14 is an example of an operation plan creation procedure (processing S1307) in the present embodiment.
  • the process S1307 is executed by the plan creation function 141 of the plan creation unit 140.
  • the plan creation function 141 can refer to the abnormality diagnosis result table 1100, the countermeasure extraction result table 1120, and the implementation candidate table 1130 of the maintenance plan database 161 output in the processing S1301 to S1305 described above. To do.
  • the plan creation function 141 extracts, for example, the one related to the implementation candidate with the earliest implementation date 1134 among the records in the implementation candidate table 1130 (execution candidate x). From time to date 1134 is acquired and stored in the memory 113.
  • the plan creation function 141 specifies the abnormality ID 1122 in the countermeasure extraction result table 1120 using the value of the countermeasure ID 1132 indicated by the record extracted above as a key, and uses the abnormality ID 1122 as a key to diagnose the abnormality diagnosis result table 1100. Then, information such as a customer ID, a site ID, a phenomenon code, a phenomenon content, a failure code, and a failure content relating to a part to be maintained is specified. Further, the plan creation function 141 collates the information specified here with the remaining life table 710 of the customer knowledge database 145, and acquires the value of the remaining life 721 of the corresponding part. The plan creation function 141 compares the remaining life value acquired in this way with the time tx from the current time to the execution date 1134, and determines whether or not a failure occurs before the maintenance work is performed.
  • the plan creation function 141 estimates that the corresponding part will fail by the execution date 1134 of the execution candidate x, and the next process S1403 is executed.
  • FIG. 19A shows the relationship between the remaining life and the time tx from the present time to the implementation date 1134.
  • the execution candidate 1 has a relationship of t1 ⁇ remaining life, and it is predicted that no component failure will occur by the execution date 1134 of the maintenance work.
  • the execution candidate 2 has a relationship of t2> remaining life, and it is expected that a component will fail by the execution date 1134 of the maintenance work.
  • the plan creation function 141 refers to the remaining life table 710 of the customer knowledge database 145, and determines the load factor at which the corresponding part does not fail by the date of the maintenance work, that is, the maximum load factor that satisfies the remaining life> tx. Identify. For example, when the remaining life is 2 days shorter than tx, the remaining life table 710 may specify the load factor “90” that is 3 days longer than the case where the load factor is “100”.
  • step S1405 the plan creation function 141 calculates an operation loss and a work loss.
  • the mining machine 10 is not fully operated during that period, and the customer's profit is reduced, resulting in economic loss. Will result.
  • this economic loss be an operational loss.
  • the plan creation function 141 collates the load factor acquired in step S1402 or step S1403 and step S1404 with the operation loss table 700 of the customer knowledge database 145, and specifies the value of the corresponding operation loss 707.
  • the plan creation function 141 calculates the operation loss by multiplying the value of the specified operation loss 707 by the above-described value of tx (the grace time from the current time to the maintenance work implementation date 1134).
  • the plan creation function 141 multiplies the standard work time 1125 extracted from the measure extraction result table 1120 by the value of the operation loss 707 in the case of the load factor “0” in the operation loss table 700 of the customer knowledge database 145 to calculate the work loss. calculate.
  • the plan creation function 141 outputs the load factor, operation loss, and work loss corresponding to the execution candidate x to the procurement / operation plan table 1140 of the maintenance plan database 161.
  • step S1307 maintenance work that does not include parts replacement work is targeted.
  • the plan creation function 141 uses the part number 1143, the recycled product determination 1144, the warehouse 1145, and the like in the procurement / operation plan table 1140.
  • the values of the transportation means 1146, the delivery date 1147, the part price 1148, and the transportation cost 1149 are blank, or some judgment symbol is output.
  • the plan creation function 141 refers to the execution candidate table 1130 of the maintenance plan database 161, and determines whether there are other execution candidates that have not yet been processed in the above-described processes S1401 to S1406. . If there are other execution candidates (S1407: Yes), the plan creation function 141 executes the process S1401 again. On the other hand, when there is no other implementation candidate (S1407: No), the plan creation function 141 ends the flow, that is, the process S1307.
  • FIG. 15 is an example of a procurement / operation plan creation procedure (processing S1308) in the present embodiment.
  • the process S1308 is executed by the plan creation function 141 of the plan creation unit 140.
  • the plan creation function 141 can refer to the abnormality diagnosis result table 1100, the countermeasure extraction result table 1120, and the execution candidate table 1130 of the maintenance plan database 161 output in the processing S1301 to S1305 described above.
  • the plan creation function 141 extracts, for example, the implementation candidate whose implementation date 1134 is the latest from the implementation candidate table 1130 (execution candidate x), and the time tx from the current time to the implementation date 1134. Are extracted from the corresponding record and stored in the memory 113.
  • the plan creation function 141 extracts the value of the part serial number 1107, which is the ID of the part in which the abnormality is detected, from the phenomenon diagnosis result table 1100 of the maintenance plan database 161.
  • the plan creation function 141 uses the value of the part serial number 1107 extracted here as a key to refer to the part history database 153 and extracts the part number and each value of the recycled product determination. Further, the plan creation function 141 reads the parts inventory table 600 of the parts procurement database 144 using the extracted part number and each value of the remanufactured product as a key, acquires the value of the inventory 606 of the corresponding part, and stores it in the memory 113. Store.
  • the plan creation function 141 selects a warehouse 605 having one or more stocks from the value of the stock 606 in the parts procurement database 144 read in S1502.
  • the plan creation function 141 specifies the corresponding record in the abnormality diagnosis result table 1100 using the abnormality ID of the execution candidate x described above as a key, and the mining machine 10 in which the abnormality is detected from this record.
  • the value of the site ID 1105 of the site where is operating is extracted.
  • the plan creation function 141 collates the value of the site ID 1105 with the customer table 730 in the customer knowledge database 145 and specifies the value of the site name 734 such as “siteA”.
  • site name the transportation means 613 in which the value of the warehouse 611 in the transportation means table 610 is the value of the warehouse 605 described above is selected.
  • the plan creation function 141 maintains the values of the parts extracted in process S1502, the transport means selected in process S1504, the transport costs corresponding to the transport means, and the delivery date values. Stored in the corresponding column of the procurement / operation plan table 1140 of the plan database 161.
  • step S1506 the plan creation function 141 determines whether or not replacement parts used for the maintenance work are delivered from the warehouse by the maintenance work execution date 1134.
  • the plan creation function 141 compares the value of the delivery date 1147 stored in the procurement / operation plan table 1140 with the above-described time tx from the current time to the implementation date 1134, and if delivery date> tx (S1506: Yes), it is estimated that the corresponding part is scheduled to be delivered by the maintenance work implementation date 1134, and the process S1507 is executed.
  • the plan creation function 141 estimates that the relevant part will not be delivered by the maintenance work implementation date 1134, and executes the process S1515.
  • the plan creation function 141 compares the remaining life with tx in the same manner as in process S1402 described above, and determines whether or not a failure occurs in the part to be replaced by the maintenance work implementation date 1134. judge.
  • the plan creation function 141 determines that there is no problem until the date of maintenance work even if the corresponding part is fully operated as usual, and the procurement / operation plan table 1140
  • the load factor of the corresponding part is set to “100”.
  • the plan creation function 141 refers to the remaining life table 710 of the customer knowledge database 145 in the same manner as in the above-described process S1403.
  • the maximum load factor that satisfies> tx is specified. For example, when the remaining life is 2 days shorter than tx, the remaining life table 710 may specify the load factor “90” that is 3 days longer than the case where the load factor is “100”.
  • step S1510 the plan creation function 141 calculates operation loss and work loss in the same manner as in step S1405 described above.
  • the plan creation function 141 collates the load factor acquired in step S1507, step S1508, or step S1509 with the operation loss table 700 of the customer knowledge database 145, and specifies the value of the corresponding operation loss 707.
  • the plan creation function 141 calculates the operation loss by multiplying the value of the specified operation loss 707 by the above-described value of tx (the grace time from the current time to the maintenance work implementation date 1134). Moreover, since the mining machine 10 is stopped during the maintenance work, the load factor of the corresponding part during the maintenance work becomes “0”. In that case, during that period, the mining machine 10 is stopped, and the profit of the customer is reduced, resulting in an economic loss. This economic loss is defined as work loss.
  • the plan creation function 141 multiplies the standard work time 1125 extracted from the measure extraction result table 1120 by the value of the operation loss 707 in the case of the load factor “0” in the operation loss table 700 of the customer knowledge database 145 to calculate the work loss. calculate.
  • the plan creation function 141 outputs the procurement / operation plan to the procurement / operation table 1140 of the maintenance plan database 161 in the same manner as the above-described process S1406.
  • the plan creation function 141 includes a part number 1143 in the procurement / operation plan table 1140 and a remanufactured product determination 1144.
  • the value of the part serial number 1107 of the corresponding part extracted in the above-described processing S1502 and a remanufactured product determination flag. Is stored respectively.
  • the plan creation function 141 stores the value of the warehouse 605 selected in the above-described processing S1503 in the warehouse 1145 in the procurement / operation plan table 1140.
  • plan creation function 141 stores the transportation means selected in the above-described processing S1504 in the transportation means 1146 in the procurement / operation plan table 1140, and similarly, the delivery date 1147, the part price 1148, and the transportation cost 1149 are stored. Stores the delivery date, price, and transportation cost stored in step S1505.
  • the plan creation function 141 refers to the part inventory table 600 of the part procurement database 144 by the same method as in the above-described process S1503, and determines whether the inventory of the target part is in another warehouse.
  • the plan creation function 141 executes the process S1503.
  • the plan creation function 141 executes the process S1514.
  • the plan creation function 141 refers to the compatible part table 620 of the part procurement database 144 and determines whether there is a compatible part of the part whose inventory has been confirmed in the above-described process S1502.
  • the plan creation function 141 uses values such as the site ID 1105, machine ID 1106, and fault code 1110 (extracted from the abnormality diagnosis result table 1100) related to the parts whose inventory has been confirmed in step S1502 as keys.
  • the record is searched in the failure history database 124, and the model name 215, the part code 217, and the part name 218 of the mining machine 10 are specified from the corresponding record.
  • the plan creation function 141 executes a search in the compatible part table 620 using the values of the type name 215, the part code 217, and the part name 218 specified here as keys, and the type name 621, the part code 622, and the part name 623 are searched. Although each value is common, it is determined whether there is a part that is different from the part number of the part whose inventory has been confirmed in the above-described processing S1502, that is, a compatible part. In the process S1514, when it is determined that there is a compatible part (S1514: Yes), the plan creation function 141 executes the process S1502 again. On the other hand, when it is determined that there is no compatible part (S1514: No), the plan creation function 141 executes the process S1515.
  • step S1515 the plan creation function 141 refers to the execution candidate table 1130 of the maintenance plan database 161 as in the above-described step S1406, and determines whether there are other unprocessed execution candidates. If there is another unprocessed execution candidate in this determination (S1515: Yes), the plan creation function 141 executes the process S1501 again. On the other hand, when there is no other unprocessed execution candidate (S1515: No), the plan creation function 141 ends this flow, that is, the process S1308.
  • FIG. 16 to FIG. 18 show an example of a life / downtime simulation execution procedure (processing S1309) in the present embodiment.
  • the life / downtime simulation process includes a life simulation S1309 (a) shown in FIG. 16, a downtime simulation S1309 (b) shown in FIG. 17, and a downtime simulation S1309 (c) shown in FIG. These are independent of each other and may be executed from any processing.
  • the life prediction simulation shown in FIG. 16 is executed by the life calculation function 151 of the performance prediction unit 150, and the downtime simulation shown in FIGS. 17 and 18 is executed by the downtime calculation function 152.
  • the life calculation function 151 and the downtime calculation function 152 can refer to the maintenance plan database 161 output from the above-described processing S1301 to processing S1308.
  • FIG. 16 is an example of a procedure for performing a life simulation in the present embodiment.
  • the life calculation function 151 refers to the part history database 153 and calculates the life of parts used and replaced in the past.
  • the life calculation function 151 reads the component history database 153.
  • the life calculation function 151 extracts the part number 1143 of the replacement part used for the maintenance work and each value of the recycled product determination 1144 from the procurement / operation plan table 1140 of the maintenance plan database 161, Using these values as keys, the parts history database 153 is searched, and records relating to the corresponding parts in which the values of the part number 1143 and the recycled product determination 1144 and the values of the part number 9043 and the recycled product determination 905 match are specified. Further, the life calculation function 151 reads the value of the status flag 910 from each record extracted here, specifies the record of the component whose value is “replaced”, and stores the data in the memory 113, for example. To do.
  • the life calculation function 151 calculates the difference between the values of the attachment date / time 911 and the removal date / time 912 in the data of each part obtained in the above-described process S1602, as the service life of the corresponding part.
  • the lifetime calculation function 151 executes the determination in step S1604 to determine whether the lifetime calculation process, that is, the process S1603 has been executed for all the data extracted in the process S1602, and thereby to all the data extracted in the process S1602. The above-described life calculation is executed.
  • the life calculation function 151 calculates an average value of the life values calculated for each data in process S1603, and outputs this as the value of the average life 1208 in the prediction result database 162. Further, the life calculation function 151 outputs the number of data specified in the process S1603 to the prediction result database 162 as the number of samples 1211.
  • the life calculation function 151 uses the part number 1143 of the replacement part used for maintenance work extracted in the above-described process S1602 and the part specified by the set of each value of the recycled product determination 1144. It is determined whether or not a plan using other different parts is stored in the procurement / operation table 1140 of the maintenance plan database 161. When there is a plan using another part (S1606: Yes), the life calculation function 151 executes the process from step S1602 again with the part as a processing target. On the other hand, when there is no plan using other parts (S1606: No), the life calculation function 151 ends this flow, that is, the process S1309 (a).
  • FIG. 17 is an example of a procedure for performing a downtime simulation based on the failure history database 124 and the component history database 153 in the present embodiment.
  • the downtime calculation function 152 refers to the failure history database 124 and the component history database 153 to calculate the downtime of the parts that have been used and replaced in the past.
  • the downtime calculation function 152 reads the parts history database 153 and performs maintenance work from the procurement / operation plan table 1140 of the maintenance plan database 161 in the same manner as the above-described processes S1601 and S1602.
  • the part number 1143 of the replacement part to be used and each value of the recycled product judgment 1144 are extracted, and the parts history database 153 is searched using these values as keys, and the part number 1143 and each value of the recycled product judgment 1144, A record relating to the corresponding part in which the values of the part number 9043 and the recycled product determination 905 match is specified.
  • the downtime calculation function 152 reads the value of the status flag 910 from each record extracted here, identifies the record of the part whose value is “replaced”, and stores the data in the memory 113, for example. Store.
  • step S1703 the downtime calculation function 152 acquires a part serial number from the data obtained in step S1702.
  • step S1704 the downtime calculation function 152 refers to the failure history database 124 using the acquired component serial number as a key.
  • the downtime calculation function 152 referring to the failure history database 124 determines whether or not the component indicated by the above-described component serial number has a failure history in the process S1705. When there is a failure history in the corresponding part (s1705: Yes), the downtime calculation function 152 executes the process S1706. On the other hand, when there is no failure history in the corresponding part (s1705: No), the downtime calculation function 152 executes step S1708.
  • step S1706 the downtime calculation function 152 refers to the work history database 132 using the failure ID 211 in the failure history database 124 as a key, and sets the difference between the corresponding start date 303 and the corresponding end date 304 of the corresponding task as the failure ID 211. Calculate as the corresponding downtime.
  • step S1707 the downtime calculation function 152 determines whether or not the downtime has been calculated for all the parts determined to have a failure in the above-described step S1705. When there is a failure whose downtime is not determined (S1707: No), the downtime calculation function 152 repeatedly executes the process S1706, and when the downtime is calculated for all failures (S1707: Yes), the process S1707 is performed. Execute.
  • step S1708 the downtime calculation function 152 determines whether the last line of the data extracted from the part history database 153 in step S1702 has been reached. If the last line has been reached (S1708: Yes), the downtime calculation function 152 executes step S1709. On the other hand, when there is still data (S1708: No), the downtime calculation function 152 executes the processing after the processing S1703 again to calculate the downtime of the corresponding part.
  • the downtime calculation function 152 calculates the average value of the downtime calculated in the above-described process S1706, and stores this as the value of the history base average DT1209 of the performance prediction database 162.
  • step S1710 the downtime calculation function 152 determines whether there is a plan using other parts in the procurement / operation table 1140 of the maintenance plan database 161 in the same manner as in step S1606.
  • the downtime calculation function 152 executes the process after the above-described process S1702 again with the part as a processing target part.
  • the downtime calculation function 152 ends this flow, that is, the process S1309 (b).
  • FIG. 18 is an example of a downtime simulation execution procedure in the present embodiment.
  • the downtime calculation function 152 refers to the failure history database 124, the component history database 153, and the component operation database 154, and calculates the downtime of the parts that have been used and replaced in the past.
  • the basic procedure of the implementation procedure (S1309 (c)) shown here is the same as the above-described processing S1309 (b). Therefore, here, the procedure from the processing S1804 to the processing S1807 for calculating the downtime and the processing S1809 for the output, which are different procedures from the processing S1309 (b), will be described.
  • step S1804 the downtime calculation function 152 narrows down the data in the component operation database 154 using the component serial numbers acquired in the same manner as in steps S1701 to S1703.
  • the downtime calculation function 152 refers to the value of the period 1013 in the operation result table 1010 of the component operation database 154 captured as described above, and calculates a determination unit time (example in FIG. 10B). (The unit time is 1 hour).
  • the downtime calculation function 152 refers to the determination value 1005 and the determination condition 1006 in the operation determination table 1000 of the component operation database 154, and the average value 1014 of the operation result table 1010 is smaller than the determination value 1005.
  • the record is identified as having the corresponding part “stopped”. Further, the downtime calculation function 152 adds the above unit time values for the number of records specified as “stopped”, and adds up the time determined to be “stopped”.
  • the downtime calculation function 152 displays the removal date and time 912 of the part history database 153 and the period 1013 of the corresponding record (record of the operation result table 1010) that is the target of the integration process in the process S1805 described above.
  • the date indicated by this period 1013 reaches the date indicated by the removal date and time 912 (S1806: Yes)
  • the integration process of the above-described process S1805 is terminated, and the process S1807 is executed.
  • the downtime calculation function 152 returns the process to the above-described process S1805.
  • step S1807 the downtime calculation function 152 stores the time accumulated so far, that is, the downtime, in the memory 113 as the operation base downtime of the corresponding part. Further, the downtime calculation function 152 repeats the process up to the process S1807 until it is executed for all the data obtained in the process S1802 (s1808).
  • the downtime calculation function 152 calculates the average of the downtime obtained for each data extracted in process S1802, and stores this in the prediction result database 162 as the operation base average DT1209.
  • the output management unit 160 extracts necessary data for each screen type from the data stored in the maintenance plan database 161 and the prediction result database 162 in response to a request from the client terminal 190, for example. This data is generated by setting the corresponding screen format (held by the output management unit 160) and outputting it to the client terminal 190.
  • the output management unit 160 may output screen format data to the client terminal 190 to accept a screen configuration customization operation from the user.
  • FIG. 20 shows a screen 2000 displaying a maintenance plan candidate list.
  • each record is listed in ascending or descending order of total cost, average life, history base average DT, and operation base average DT.
  • a radio button 2001 for designating any one of the total cost, the average life, the history base average DT, and the operation base average DT as the sort criterion so that the user can sort the records based on the enumeration criteria.
  • the screen 2000 is included.
  • the user can press the radio button 2001 to perform evaluation between maintenance plan candidates.
  • FIG. 21 shows an example of the procurement / operation plan details and operation display screen 2100 regarding the maintenance plan candidates displayed on the screen 2000 shown in FIG.
  • This screen 2100 is obtained from the data stored in the maintenance plan database 161 and the prediction result database 162 when the output management unit 160 receives a request for detailed display from the client terminal 190 for a certain candidate in the screen 2000 described above.
  • the data necessary for the corresponding screen is extracted, the data is set in the format of the corresponding screen, generated, and output to the client terminal 190.
  • This screen 2100 shows a replacement part used for maintenance work in addition to the plan ID, execution date, machine ID, part number, warehouse, transportation means, delivery date, part price, and transportation cost regarding the target procurement / operation plan.
  • FIG. 22 shows a screen 2200 showing the allocation of expenses related to the maintenance work.
  • This screen 2200 may be used, for example, when a maintenance cost share is determined between a maintenance company and a customer who operates the mining machine 10 in a maintenance contract.
  • the part price can be compared with the other total costs excluding the part price. Good. Therefore, the total cost, the part price, the transportation cost, the operation loss, the operation cost, the work loss, the total cost, the part price, the transportation cost
  • the screen 2200 includes a radio button 2201 for designating any one of the operation loss, work cost, work loss, and user definition as a sorting criterion.
  • the user can press the radio button 2201 to compare the maintenance plan candidates with each other in terms of cost.
  • replacement parts are not handled unambiguously, and even parts having similar functions are considered for multiple types of parts such as old edition parts and recycled parts, and these various parts are prepared as maintenance plans for work machines. Can be reflected.
  • abnormalities and failures can be estimated from phenomena occurring in work machines, and maintenance operations can be identified accordingly. Therefore, it is possible to estimate failures that may occur in accordance with various situations and identify appropriate maintenance measures. It is possible.
  • parts procurement which is an important consideration in terms of cost and time required for maintenance work in large machines such as mining equipment, taking into account old version parts and remanufactured parts, delivery date, transportation cost, load factor, It is possible to support the planning of multiple patterns of maintenance plans based on the total economic loss according to the load factor.
  • the maintenance planning support technology of this embodiment when an abnormality or failure is detected in the work machine, the old version parts, the refurbished parts, and the procurement plan thereof are also taken into consideration, and what is to be evaluated. Along with this, it can be provided to users to support maintenance planning work.
  • the storage device corresponds to the remaining life of each work machine according to the load factor at the time of failure and the information on the economic loss of the work machine user accompanying the load factor decrease.
  • the arithmetic device collates information on a load factor of a work machine or a part where the phenomenon occurs, included in the information on the phenomenon related to the work machine, with the fifth database.
  • the remaining life of the work machine or the part where the phenomenon occurs is estimated, and the load factor which is reduced according to the extent that the remaining life is less than the grace period from the current time to the maintenance execution candidate date ,
  • the economic loss at the load factor is specified in the fifth database, and the reduced load factor and the economic loss information at the load factor are specified.
  • the maintenance plan in which information further executes a process of outputting to the output device, including a may be. According to this, the load factor that should be reduced to the extent that the failed part can continue to operate until the date of maintenance is identified, and the economic loss on the customer side when the component is operated at this load factor is reported to the user. This makes it possible for the user side to easily consider the customer side in terms of business continuity and economy, which is important when determining a maintenance plan.
  • the storage device stores a sixth database that stores information related to attachment to and removal from the work machine of individual parts or old version parts or regenerated parts thereof.
  • the computing device relates to a part used for the maintenance work or an old version part or a reproduction part thereof indicated by the maintenance plan information, and the same type of part or the old version part or the reproduction thereof in the sixth database.
  • a process of identifying the history of component attachment and removal, calculating the time between the identified attachment and removal as a lifetime, and including the information on the lifetime in the maintenance plan information and outputting to the output device It may be executed. According to this, by presenting to the user how long the replacement parts used in the maintenance plan will have, the user can create a maintenance plan that takes into account, for example, the balance between parts cost and life. It has the effect of making it easier to do
  • the arithmetic unit is related to a part used for the maintenance work indicated by the maintenance plan information or an old version part or a recycled part thereof, and the same type of parts in the first database. Also, the presence or absence of failure information of the old version parts or remanufactured parts is specified, and when the failure information exists, the information on the maintenance work performed for the corresponding failure is specified in the first database, and the corresponding The time between the work start and work end indicated by the maintenance work information is calculated as downtime, and the process of including the downtime information in the maintenance plan information and outputting it to the output device is further executed. There may be.
  • the storage device includes a seventh database storing measured values related to the behavior of the corresponding part by a sensor installed on the part of the work machine, and whether or not the work machine part is in operation. And an eighth database storing conditions of measurement values by the sensor for determining the sensor, and the arithmetic unit relates to a part used for the maintenance work indicated by the maintenance plan information or an old version part or a recycled part thereof
  • the seventh database information on measured values for the same type of part or its old version parts or remanufactured parts is specified, and the information on the specified measured values is collated with the eighth database, and the corresponding part or its old version
  • the downtime of parts or remanufactured parts is calculated as downtime, and the downtime information is stored in the maintenance In which further executes a process of outputting to the output device included in the image information may be.
  • the replacement part adopted in the maintenance plan is shown to the user how much downtime is expected, so on the user side, For example, there is an effect that a maintenance plan considering the balance between parts cost and downtime can be easily made.
  • the storage device further includes a ninth database that stores a schedule of scheduled maintenance scheduled to be performed on the work machine.
  • a ninth database that stores a schedule of scheduled maintenance scheduled to be performed on the work machine.

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Abstract

L'invention a pour objectif de permettre l'élaboration d'un plan de maintenance efficace sans dépendre des compétences ou éléments analogues d'un technicien de maintenance. Pour ce faire, un système informatique (100) utilise un système de suivi (170) pour une machine de travail (10) afin d'exécuter les processus suivants : un processus permettant de recevoir des informations concernant un phénomène survenu dans la machine de travail (10) à un emplacement donné, de collecter ces informations avec une première base de données, de prédire une défaillance susceptible de se produire, et d'identifier des informations dans la première base de données concernant le travail de maintenance effectué lors de l'occurrence de ladite défaillance ; un processus permettant de collecter les informations identifiées sur le travail de maintenance avec la seconde base de données, d'identifier des informations sur le travail de maintenance standard prévu, et d'identifier, dans une troisième base de données, une période pendant laquelle il est possible d'envoyer un technicien et un équipement pour le travail de maintenance, en tant que date candidate pour l'exécution de la maintenance ; et un processus permettant de stocker un composant, une version antérieure de celui-ci ou un composant réutilisable spécifié par les informations sur le travail de maintenance, d'identifier, dans une quatrième base de données, un entrepôt de stockage pendant la période allant jusqu'à la date candidate d'exécution de maintenance, ainsi que le moyen de transport et les coûts de transport lors de la livraison à l'emplacement donné de la machine de travail, de générer, en tant qu'informations de plan de maintenance, des informations concernant la date candidate d'exécution de maintenance et des informations concernant le délai, l'entrepôt, le moyen de transport et les coûts de transport relatifs au composant, à la version antérieure de celui-ci ou au composant réutilisable à utiliser pour le travail de maintenance, et de générer celles-ci vers un dispositif de sortie (111).
PCT/JP2012/076610 2012-10-15 2012-10-15 Système, procédé et programme d'aide à l'élaboration d'un plan de maintenance WO2014061080A1 (fr)

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Application Number Priority Date Filing Date Title
PCT/JP2012/076610 WO2014061080A1 (fr) 2012-10-15 2012-10-15 Système, procédé et programme d'aide à l'élaboration d'un plan de maintenance
PCT/JP2013/077813 WO2014061604A1 (fr) 2012-10-15 2013-10-11 Système d'aide à l'ébauche d'un plan de maintenance, procédé d'aide à l'ébauche d'un plan de maintenance et programme d'aide à l'ébauche d'un plan de maintenance
CA2888334A CA2888334C (fr) 2012-10-15 2013-10-11 Systeme d'aide a l'ebauche d'un plan de maintenance, procede d'aide a l'ebauche d'un plan de maintenance et programme d'aide a l'ebauche d'un plan de maintenance
AU2013332924A AU2013332924B2 (en) 2012-10-15 2013-10-11 Maintenance-plan-drafting support system, maintenance-plan-drafting support method, and maintenance-plan-drafting support program
JP2014542114A JP5938481B6 (ja) 2012-10-15 2013-10-11 保守計画立案支援システム、保守計画立案支援方法、保守計画立案支援プログラム

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KR101996070B1 (ko) * 2017-12-06 2019-07-04 주식회사 블루비즈 부품을 효율적으로 관리하는 장치 및 방법
JP6649416B2 (ja) 2018-02-02 2020-02-19 ファナック株式会社 障害分類装置、障害分類方法及び障害分類プログラム
JP6705845B2 (ja) 2018-02-08 2020-06-03 ファナック株式会社 障害部位特定装置、障害部位特定方法及び障害部位特定プログラム
CA3099659A1 (fr) * 2018-05-07 2019-11-14 Strong Force Iot Portfolio 2016, Llc Procedes et systemes de collecte, d'apprentissage et de diffusion en continu de signaux de machine a des fins d'analyse et de maintenance a l'aide de l'internet des objets industriel
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JP5938481B2 (ja) 2016-06-22
WO2014061604A1 (fr) 2014-04-24
JP5938481B6 (ja) 2018-06-27
AU2013332924B2 (en) 2016-12-22

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