Information processing method, estimation model generation method, information processing device, and program

Abstract

This information processing method determines the assignment of workers in charge of production equipment in a production process in which any one of a plurality of workers is in charge of recovery work for a plurality of pieces of production equipment, wherein an information processing device: acquires stopped equipment information indicating stopped equipment, which is production equipment that has stopped; acquires stoppage factor information indicating the factors of the stoppage of the stopped equipment; acquires worker-specific list information indicating production equipment currently assigned to each worker and stoppage factors thereof; and determines a worker to be assigned in charge of the stopped equipment, on the basis of the stopped equipment information, the stoppage factor information, and the list information.

Description

Information processing method, estimation model generation method, information processing device, and program

[0001] The present disclosure relates to an information processing method, an estimation model generation method, an information processing device, and a program.

[0002] A work notification method according to the background art is disclosed in Patent Document 1. In this work notification method, when a production facility (a facility to be worked on) is newly stopped, a worker among a plurality of workers who can complete the restoration work for the facility to be worked on in the shortest time is assigned to work on the facility to be worked on.

[0003] The work notification method according to the background art may, depending on the circumstances, result in a decrease in productivity throughout the entire production process.

[0004] International Publication No. 2022 / 039080

[0005] The present disclosure aims to provide an information processing method, an estimation model generation method, an information processing device, and a program that can appropriately determine the worker to be assigned to be in charge of stopped equipment, thereby improving productivity throughout the entire production process.

[0006] An information processing method according to one aspect of the present disclosure is an information processing method for determining the allocation of production equipment to workers in a production process in which one of multiple workers is responsible for recovery work on multiple pieces of production equipment, in which an information processing device acquires stopped equipment information indicating stopped equipment, which is production equipment that has been stopped, acquires stop cause information indicating the cause of the stoppage of the stopped equipment, acquires list information by worker indicating the production equipment currently assigned to each worker and the cause of the stoppage, and determines the worker to be assigned to the stopped equipment based on the stopped equipment information, the stop cause information, and the list information.

[0007] FIG. 1 is a simplified diagram showing the overall configuration of a production system according to a first embodiment. FIG. 2 is a simplified diagram showing an example of operation history information. FIG. 3 is a flowchart showing processing executed by a processing unit of a learning device according to a first embodiment. FIG. 4 is a simplified diagram showing an example of list information. FIG. 5 is a flowchart showing processing executed by a processing unit of a determination device according to a first embodiment. FIG. 6 is a diagram showing a processing for estimating a working time. FIG. 7 is a simplified diagram showing an example of list information after updating. FIG. 8 is a flowchart showing processing executed by a processing unit of a learning device according to a second embodiment. FIG. 9 is a flowchart showing processing executed by a processing unit of a determination device according to a second embodiment. FIG. 10 is a diagram showing a processing for estimating a productivity index value. FIG. 11 is a flowchart showing processing executed by a processing unit of a determination device according to a third embodiment.

[0008] (Knowledge forming the basis of the present disclosure) In a production process in which products are produced by operating multiple pieces of production equipment, multiple workers are on standby in the factory to perform recovery work when a production piece of equipment stops, and one of the workers is responsible for the recovery work for each piece of production equipment. Therefore, it is necessary to determine the allocation of production equipment responsibilities to each worker, and traditionally, the production site manager has determined this allocation based on experience and intuition. However, there are differences in the work abilities of each worker depending on the level of proficiency in the work, and even the same worker has strengths and weaknesses in tasks depending on the cause of the stoppage. In other words, the work time for recovery work varies depending on the combination of worker and cause of the stoppage. Therefore, it is difficult to determine the optimal allocation of responsibilities that can maximize productivity throughout the entire production process based solely on the manager's experience and intuition.

[0009] In the work notification method according to the background art, when a production facility (a facility to be worked on) is newly stopped, the worker who can complete the restoration work to restore the facility to the shortest time is assigned to be in charge of the facility to be worked on.

[0010] According to the work notification method of the background art, if a worker is notified of instructions for the equipment to be worked on while he or she is performing recovery work on another production equipment, the recovery work on the other production equipment will be suspended or the equipment to be worked on will be left in a stopped state until the recovery work on the other production equipment is completed. This situation can occur even if there are other workers available, which may result in a decrease in productivity throughout the entire production process.

[0011] In order to solve this problem, the present inventors have come up with the idea of ​​managing list information showing the production equipment currently assigned to each worker and the reasons for its shutdown for each worker, and determining the assignment of responsibilities based on the shutdown equipment information, shutdown cause information, and list information, thereby making it possible to appropriately determine the worker in charge of the shutdown equipment, thereby improving productivity throughout the entire production process, and have come up with the present disclosure.

[0012] Next, each aspect of the present disclosure will be described.

[0013] An information processing method according to a first aspect of the present disclosure is an information processing method for determining the allocation of production equipment to workers in a production process in which one of a plurality of workers is responsible for recovery work on a plurality of pieces of production equipment, in which an information processing device acquires stopped equipment information indicating stopped equipment, which is production equipment that has been stopped, acquires stop cause information indicating the cause of the stoppage of the stopped equipment, acquires list information by worker indicating the production equipment currently assigned to each worker and the cause of the stoppage, and determines the worker to be in charge of the stopped equipment based on the stopped equipment information, the stop cause information, and the list information.

[0014] According to the first aspect, the list information for each worker indicates the production equipment currently assigned to each worker and the cause of its shutdown. By determining the assignment of responsibilities based on the shutdown equipment information, shutdown cause information, and list information, it is possible to appropriately determine the worker in charge of the shutdown equipment. As a result, it is possible to improve productivity throughout the entire production process.

[0015] In the information processing method according to the second aspect of the present disclosure, in the first aspect, when determining the workers, the outage cause information and the list information may be input into a work time model that represents the required time for recovery work for each worker and each cause of outage, thereby calculating a recovery score when each worker is assigned to be in charge of the stopped equipment.

[0016] According to the second aspect, by calculating the restoration score by inputting the stoppage cause information and the list information into the operation time model, it is possible to appropriately determine the worker to be put in charge of the stopped equipment based on the restoration score.

[0017] In the information processing method according to the third aspect of the present disclosure, in the second aspect, the recovery score may indicate the elapsed time from the present time to the scheduled time when recovery work for the stopped equipment is completed, when each worker is assigned to be in charge of the stopped equipment.

[0018] According to the third aspect, it is possible to appropriately determine the worker to be in charge of the stopped equipment based on the elapsed time from the current time until the scheduled time when the restoration work for the stopped equipment is completed.

[0019] In the information processing method according to a fourth aspect of the present disclosure, in the third aspect, in determining the worker, the worker with the smallest restoration score may be assigned to be in charge of the stopped equipment.

[0020] According to the fourth aspect, the worker who will be in charge of the stopped equipment in the shortest time from the current time until the scheduled completion of the recovery work for the stopped equipment can be assigned to the stopped equipment, thereby further improving productivity throughout the entire production process.

[0021] In the information processing method according to a fifth aspect of the present disclosure, in any one of the second to fourth aspects, when determining the worker, the shutdown frequency of the stopped equipment is calculated, and a productivity index value when each worker is assigned to be in charge of the stopped equipment is calculated based on at least one of the recovery score and the shutdown frequency, and the worker with the best productivity index value is assigned to be in charge of the stopped equipment.

[0022] According to the fifth aspect, by assigning the worker with the best productivity index value to be in charge of the stopped equipment, productivity in the entire production process can be further improved.

[0023] An information processing method according to a sixth aspect of the present disclosure is, in the fifth aspect, when the stopped equipment includes multiple pieces of stopped equipment, in determining the workers, the sum of the productivity index values ​​is calculated for each of multiple combinations of the multiple workers and the multiple pieces of stopped equipment, and one or more workers to be in charge of the multiple pieces of stopped equipment are determined corresponding to the combination that results in the best sum of the productivity index values.

[0024] According to the sixth aspect, even when a plurality of pieces of production equipment are stopped at the same time, it is possible to appropriately determine one or more workers to be in charge of the plurality of pieces of stopped equipment.

[0025] In the information processing method according to the seventh aspect of the present disclosure, in any one of the first to sixth aspects, it is preferable that, after determining the worker who will be in charge of the stopped equipment, the list information corresponding to the worker is updated, thereby adding the stopped equipment and the cause of its stoppage to the list information.

[0026] According to the seventh aspect, by updating the list information, it is possible to appropriately determine the worker who will be in charge of a piece of equipment that has been stopped after the update, based on the updated list information.

[0027] In the information processing method according to the eighth aspect of the present disclosure, in the seventh aspect, the updated list information may further be sent to a mobile device carried by the worker in charge of the stopped equipment.

[0028] According to the eighth aspect, by sending the updated list information to a mobile terminal, workers can easily refer to the updated list information, thereby enabling them to properly carry out recovery work on the stopped equipment for which they are responsible.

[0029] An information processing method according to a ninth aspect of the present disclosure, in any one of the first to eighth aspects, may further acquire progress information indicating the work progress of each worker, and if a deviation of a predetermined value or more occurs between the work plan indicated in the list information corresponding to a certain worker and the work progress indicated in the progress information related to that worker, redetermine the allocation of responsibilities of the plurality of production equipment to the plurality of workers.

[0030] According to the ninth aspect, if a deviation of a predetermined value or more occurs between the work plan and the work progress for a certain worker, the work assignment is redetermined, thereby further improving productivity throughout the entire production process.

[0031] An information processing method according to a tenth aspect of the present disclosure is, in the ninth aspect, when redetermining the work assignment, if the work progress for the certain worker is more advanced than the work plan, the certain worker may be assigned to work on production equipment that has not yet been assigned to another worker.

[0032] According to the tenth aspect, by assigning production equipment that has not yet been worked on and that has been assigned to another worker to a worker whose work progress is more advanced than the work plan, productivity throughout the entire production process can be further improved.

[0033] An information processing method according to an eleventh aspect of the present disclosure is, in the ninth aspect, when redetermining the work assignment, if the work progress for a certain worker is behind the work plan, the production equipment that was assigned to the certain worker but that has not yet been worked on may be assigned to another worker.

[0034] According to the eleventh aspect, productivity throughout the entire production process can be further improved by having another worker take charge of the unworked production equipment that was assigned to a worker whose work progress is behind the work plan.

[0035] A method for generating an estimation model according to a twelfth aspect of the present disclosure is a method for generating an estimation model for determining the allocation of production equipment to workers in a production process in which any one of a plurality of workers is in charge of recovery work for a plurality of pieces of production equipment, in which an information processing device acquires operation history information for the plurality of pieces of production equipment, including stopped equipment information indicating stopped equipment that is stopped production equipment, stop cause information indicating the cause of the stoppage of the stopped equipment, work start time information indicating the start time of recovery work for the stopped equipment, recovery time information indicating the time the stopped equipment was recovered, and identification information of the worker in charge of the recovery work for the stopped equipment, and generates an estimation model by machine learning using the operation history information as learning data, based on the stopped equipment information, the stop cause information, and list information for each worker that indicates the production equipment currently assigned to each worker and the cause of the stoppage.

[0036] According to the twelfth aspect, an estimation model for determining a worker to be in charge of a stopped piece of equipment can be appropriately generated by machine learning using operation history information as learning data.

[0037] An information processing device according to a thirteenth aspect of the present disclosure is an information processing device that determines the allocation of production equipment to workers in a production process in which one of multiple workers is responsible for recovery work on multiple pieces of production equipment, and obtains stopped equipment information that indicates stopped production equipment, which is production equipment that has been stopped, obtains stop cause information that indicates the cause of the stoppage of the stopped equipment, obtains list information by worker that indicates the production equipment currently assigned to each worker and the cause of the stoppage, and determines the worker to be in charge of the stopped equipment based on the stopped equipment information, the stop cause information, and the list information.

[0038] According to the thirteenth aspect, the list information for each worker indicates the production equipment currently assigned to each worker and the cause of its shutdown. By determining the assignment based on the shutdown equipment information, shutdown cause information, and list information, it is possible to appropriately determine the worker in charge of the shutdown equipment. As a result, it is possible to improve productivity throughout the entire production process.

[0039] A program according to a fourteenth aspect of the present disclosure is a program for causing an information processing device to execute processing to determine the allocation of production equipment to workers in a production process in which any one of a plurality of workers is responsible for recovery work on a plurality of pieces of production equipment, the processing acquiring stopped equipment information indicating stopped production equipment that is stopped, acquiring stop cause information indicating the cause of the stop of the stopped equipment, acquiring list information by worker indicating the production equipment currently assigned to each worker and the cause of the stop, and determining the worker to be in charge of the stopped equipment based on the stopped equipment information, the stop cause information, and the list information.

[0040] According to the fourteenth aspect, the list information for each worker indicates the production equipment currently assigned to each worker and the cause of its shutdown. By determining the assignment based on the shutdown equipment information, shutdown cause information, and list information, it is possible to appropriately determine the worker in charge of the shutdown equipment. As a result, it is possible to improve productivity throughout the entire production process.

[0041] The present disclosure can also be realized as a program that causes a computer to execute each characteristic configuration included in such a method or apparatus, or as a system operated by this program. Needless to say, such a computer program can be distributed on a computer-readable non-transitory recording medium such as a CD-ROM or via a communication network such as the Internet.

[0042] (Embodiments of the Present Disclosure) Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Elements with the same reference numerals in different drawings indicate the same or corresponding elements. Furthermore, the components, the arrangement positions of the components, the connection forms, the order of operations, etc. shown in the following embodiments are merely examples and are not intended to limit the present disclosure. The present disclosure is limited only by the claims. Therefore, among the components in the following embodiments, components that are not described in the independent claims that represent the highest concept of the present disclosure are not necessarily required to achieve the objectives of the present disclosure, but are described as constituting more preferred forms.

[0043] First Embodiment FIG. 1 is a simplified diagram showing the overall configuration of a production system according to a first embodiment. The production system is constructed in a factory where products are produced. The production system includes a learning device 1, a determination device 2, a communication network 3, and a plurality of m pieces of production equipment 4 (4 １ ~4 ｍ ), and multiple n workers 5 (5 １ ~5 ｎ ) possesses n mobile terminals 6 (6 １ ~6 ｎ The mobile terminal 6 may be a dedicated terminal, or may be a general-purpose smartphone, tablet terminal, or the like.

[0044] The learning device 1 and the determination device 2 may be a computer terminal, an edge server, or an on-premise server in a factory, or may be a cloud server outside a factory. The learning device 1 and the determination device 2 may be configured as a single terminal that shares hardware. The learning device 1 and the determination device 2 can communicate with production equipment 4 and a mobile terminal 6 via a communication network 3. The learning device 1 and the determination device 2 can also communicate with each other via the communication network 3. The communication network 3 may be a dedicated line network or a public line network.

[0045] Within a factory, m pieces of production equipment 4 are arranged in a predetermined layout. The products produced by the production equipment 4 may be final products or work-in-progress products. The production performed by the production equipment 4 may be manufacturing such as processing or assembly, or product inspection. Each of the multiple production equipment 4 is assigned an equipment ID as identification information for identifying each production equipment 4.

[0046] There are n workers 5 on standby in the factory. Operation of each production facility 4 may stop due to various reasons. When a certain production facility 4 stops, recovery work for that production facility 4 is performed by a worker 5 on standby in the factory. The recovery work for each production facility 4 is performed by one of the multiple workers 5. The determination device 2 determines the allocation of production facilities 4 to each worker 5. In other words, the determination device 2 determines the allocation of production facilities 4 to workers 5 in a production process in which one of the multiple workers 5 is responsible for recovery work for each of the multiple production facilities 4. A worker ID is assigned to each of the multiple workers 5 as identification information for identifying each worker 5.

[0047] The learning device 1 includes a processing unit 11 (information processing device), a storage unit 12, and a communication unit 13. The determination device 2 includes a processing unit 41 (information processing device), a storage unit 42, and a communication unit 43. The processing units 11 and 41 include a processor such as a CPU. The storage units 12 and 42 include a HDD, SSD, semiconductor memory, or the like. The communication units 13 and 43 include a communication module compatible with any communication standard such as IP.

[0048] The storage unit 12 stores a program 31, operation history information 32, and an estimation model 33. The storage unit 42 stores a program 61, list information 62, and an estimation model 33. The storage units 12 and 42 include computer-readable non-volatile storage media, and the programs 31 and 61 are stored in the storage media.

[0049] The processing unit 11 has an acquisition unit 21, a learning unit 22, and a control unit 23 as functions realized by the processor of the processing unit 11 executing the program 31 read from the storage unit 12. The processing unit 41 has an acquisition unit 51, a determination unit 52, and a control unit 53 as functions realized by the processor of the processing unit 41 executing the program 61 read from the storage unit 42. Details of the processing content of each of these units will be described later.

[0050] First, the processing in the learning phase will be described.

[0051] FIG. 2 is a simplified diagram showing an example of operation history information 32. The operation history information 32 is a database containing multiple records. Each record corresponds to one stop of the production equipment 4. Each record has multiple fields related to an equipment ID, a stop cause, a stop time, a work start time, a recovery time, and a worker ID. The equipment ID indicates the equipment ID assigned to the stopped equipment, which is the stopped production equipment 4. The stop cause indicates the cause of the stop of the stopped equipment. Stop causes include material jamming, a product number change, frequent defects, maintenance, etc. The stop time indicates the time when the stopped equipment stopped. The work start time indicates the time when recovery work for the stopped equipment started. The recovery time indicates the time when the recovery work was completed and the stopped equipment resumed operation. The worker ID indicates the worker ID assigned to the worker 5 who performed the recovery work. The learning device 1 creates the operation history information 32 based on operation information or work information, etc. received from the production equipment 4 or the mobile terminal 6 via the communication network 3. The learning device 1 stores the created operation history information 32 in the storage unit 12. Note that the operation history information 32 may be managed separately as equipment operation performance data including history information related to the shutdown and recovery of stopped equipment, and work performance data including history information related to the recovery work of the worker 5.

[0052] FIG. 3 is a flowchart showing the processing executed by the processing unit 11 of the learning device 1 according to the first embodiment.

[0053] First, in step S01, the control unit 23 reads out the operation history information 32 from the storage unit 12, and the acquisition unit 21 acquires stopped equipment information including the equipment ID of the stopped equipment based on the operation history information 32.

[0054] Next, in step S02 , the acquisition unit 21 acquires stoppage cause information including the stoppage cause of the stopped equipment based on the operation history information 32 .

[0055] Next, in step S03, the acquisition unit 21 acquires work start time information including the work start time of the restoration work for the stopped equipment based on the operation history information 32.

[0056] Next, in step S04 , the acquisition unit 21 acquires restoration time information including the restoration time of the stopped equipment based on the operation history information 32 .

[0057] Next, in step S05 , the acquisition unit 21 acquires worker information including the worker ID of the worker 5 who was in charge of the recovery work for the stopped equipment, based on the operation history information 32 .

[0058] Next, in step S06A, the learning unit 22 performs machine learning using an arbitrary algorithm such as a neural network, using the stopped equipment information, the stoppage cause information, the work start time information, the recovery time information, and the worker information acquired from the operation history information 32 as learning data. The learning unit 22 generates an operation time model 33A that represents the required time for recovery work for each worker 5 and each cause of the stoppage through machine learning using the multiple pieces of learning data. The control unit 23 stores the generated operation time model 33A in the storage unit 12, including it in an estimation model 33. The control unit 23 also transmits the estimation model 33 from the communication unit 13 to the determination device 2 via the communication network 3. The determination device 2 stores the received estimation model 33 in the storage unit 42.

[0059] Next, the processing in the utilization phase will be described.

[0060] 4 is a simplified diagram showing an example of the list information 62. The list information 62 includes a plurality of pieces of list information managed for each worker 5. In FIG. １ ~5 ３ List information 62 corresponding to １ ~62 ３The list information 62 is a database containing multiple records. Each record corresponds to one recovery operation. Each record has multiple fields related to priority, equipment ID, shutdown cause, and estimated work time. The priority indicates the order in which the worker 5 is to perform recovery operations on stopped equipment. The stopped equipment with the highest priority corresponds to the stopped equipment on which the worker 5 is currently performing recovery operations. The stopped equipment with the second or lower priority corresponds to stopped equipment on which the worker 5 has not yet started recovery operations. The equipment ID indicates the equipment ID assigned to the stopped equipment. The shutdown cause indicates the cause of the shutdown of the stopped equipment. The estimated work time indicates an estimate of the work time from when the worker 5 starts to complete recovery operations on the stopped equipment. The estimated work time varies depending on the combination of the worker and the shutdown cause. The estimated work time included in the record with the highest priority corresponds to the remaining time of the recovery operation currently being performed by the worker. The determination device 2 updates the list information 62 in real time based on operation information, work information, etc. received from the production equipment 4 or the mobile terminal 6 via the communication network 3.

[0061] FIG. 5 is a flowchart showing the processing executed by the processing unit 41 of the determination device 2 according to the first embodiment.

[0062] First, in step S11, the acquisition unit 51 acquires worker information including the worker IDs of all workers 5 waiting in the factory.

[0063] When any of the production equipment 4 stops and becomes a stopped equipment, in step S12, the acquisition unit 51 acquires stopped equipment information including the equipment ID of the stopped equipment based on the operation information received from the stopped equipment via the communication network 3.

[0064] Next, in step S13, the acquisition unit acquires stoppage cause information including the stoppage cause of the stopped equipment based on the operation information.

[0065] Next, in step S14 , the control unit 53 reads the list information 62 from the storage unit 42 , and the acquisition unit 21 acquires the list information 62 .

[0066] Next, in step S15, the control unit 53 reads out the estimation model 33 from the storage unit 42, and the determination unit 52 calculates the restoration score when each worker 5 is assigned to be in charge of the stopped equipment.

[0067] 6 is a diagram showing the process of estimating work time. The determination unit 52 inputs data D1 indicating worker information, data D2 indicating stopped equipment information, data D3 indicating stoppage cause information, and data D4 indicating list information 62 into a work time model 33A included in the estimation model 33, to calculate a restoration score when each worker 5 is assigned to work on the stopped equipment. The restoration score indicates the elapsed time from the current time to the scheduled time when restoration work on the stopped equipment is completed when each worker 5 is assigned to work on the stopped equipment. The work time model 33A outputs data D10 indicating multiple restoration scores for multiple workers 5.

[0068] Next, in step S16, the determination unit 52 determines the worker 5 with the smallest restoration score as the worker 5 to be in charge of the stopped equipment.

[0069] Next, in step S17, the determination unit 52 determines the worker 5 who will be in charge of the stopped equipment, and then updates the list information 62 corresponding to that worker 5, thereby adding the stopped equipment and the cause of its stoppage to the list information 62. The control unit 53 stores the updated list information 62 in the storage unit 42.

[0070] 7 is a simplified diagram illustrating an example of the updated list information 62. In the example illustrated in FIG. 7, the determining unit 52 determines the worker 5 to be in charge of the stopped equipment. １ The control unit 53 determines the １ List information 62 corresponding to １ In the example shown in FIG. 7, a new record (the record with the second priority) relating to the restoration work of the stopped equipment is added to the １ The recovery score for this is 53 (minutes), which is the total value of the estimated work time.

[0071] Next, in step S18, the control unit 53 updates the list information 62 after updating. １ The worker in charge of the shutdown equipment is １ Mobile terminal 6 owned by１ The mobile terminal 6 １ The received updated list information 62 １ is displayed on the screen.

[0072] According to this embodiment, the list information 62 for each worker 5 indicates the production equipment 4 currently assigned to each worker 5 and the cause of its shutdown. By determining the assignment of responsibilities based on the shutdown equipment information, shutdown cause information, and list information 62, it is possible to appropriately determine the worker 5 who will be in charge of the shutdown equipment. As a result, it is possible to improve productivity throughout the entire production process.

[0073] Furthermore, according to this embodiment, by inputting the stoppage cause information and list information 62 into the work time model 33A to calculate the restoration score, the worker 5 to be in charge of the stopped equipment can be appropriately determined based on the restoration score.

[0074] Furthermore, according to this embodiment, it is possible to appropriately determine the worker 5 who will be in charge of the stopped equipment based on the elapsed time from the current time until the scheduled completion time of the restoration work for the stopped equipment.

[0075] Furthermore, according to this embodiment, the worker 5 who will have the shortest time elapsed between the current time and the scheduled completion time of the restoration work for the stopped equipment can be assigned to the stopped equipment, which results in further improvement in productivity throughout the entire production process.

[0076] Furthermore, according to this embodiment, by updating the list information 62, the worker 5 to be in charge of the newly stopped equipment that has occurred after the update can be appropriately determined based on the updated list information 62.

[0077] Furthermore, according to this embodiment, by sending the updated list information 62 to the mobile terminal 6, the worker 5 can easily refer to the updated list information 62, and can therefore properly carry out recovery work for the stopped equipment for which he or she is responsible.

[0078] Furthermore, according to this embodiment, the work time model 33A for determining the worker 5 who will be in charge of the stopped equipment can be appropriately generated by machine learning using the operation history information 32 as learning data.

[0079] Second Embodiment FIG. 8 is a flowchart showing processing executed by the processing unit 11 of the learning device 1 according to a second embodiment.

[0080] First, in step S01 , the control unit 23 reads out the operation history information 32 from the storage unit 12 , and the acquisition unit 21 acquires stopped equipment information based on the operation history information 32 .

[0081] Next, in step S02 , the acquisition unit 21 acquires stop cause information based on the operation history information 32 .

[0082] Next, in step S21, the acquisition unit 21 acquires stop time information including the stop time of the stopped equipment based on the operation history information 32.

[0083] Next, in step S03 , the acquisition unit 21 acquires work start time information based on the operation history information 32 .

[0084] Next, in step S04 , the acquisition unit 21 acquires recovery time information based on the operation history information 32 .

[0085] Next, in step S05 , the acquisition unit 21 acquires worker information based on the operation history information 32 .

[0086] Next, in step S06B, the learning unit 22 performs machine learning using the stopped equipment information, stop cause information, stop time information, work start time information, recovery time information, and worker information obtained from the operation history information 32 as learning data.

[0087] The learning unit 22 generates a work time model 33A that represents the required time for recovery work for each worker 5 and each cause of the outage through machine learning using a plurality of learning data. The learning data for generating the work time model 33A includes at least information on the cause of the outage, work start time information, recovery time information, and worker information.

[0088] Furthermore, the learning unit 22 generates a stoppage occurrence frequency model 33B that represents the stoppage occurrence frequency for each production facility 4 and for each stoppage cause through machine learning using a plurality of learning data. The stoppage occurrence frequency may be, for example, the mean time between failures. The learning data for generating the stoppage occurrence frequency model 33B includes at least stopped facility information, stoppage cause information, and stoppage time information.

[0089] Furthermore, the learning unit 22 uses the operation time model 33A and the stoppage occurrence frequency model 33B to perform a simulation that reproduces the stoppage of the production equipment 4 and the recovery work by the workers 5, thereby generating a productivity index value model 33C that calculates the productivity index value when each worker is assigned to work on the stopped equipment. The productivity index value may be, for example, the number of production units. The productivity index value model 33C has configurable parameters, and appropriate initial parameters are assigned at the start of machine learning. The learning unit 22 tries various work assignments through simulation, and generates the productivity index value model 33C by learning, through machine learning such as reinforcement learning, the parameters that result in the best productivity index value.

[0090] The control unit 23 stores the generated operation time model 33A, stoppage occurrence frequency model 33B, and productivity index value model 33C in the storage unit 12 as an estimation model 33. The control unit 23 also transmits the estimation model 33 from the communication unit 13 to the determination device 2 via the communication network 3.

[0091] FIG. 9 is a flowchart showing the processing executed by the processing unit 41 of the determination device 2 according to the second embodiment.

[0092] The processes in steps S11 to S15 are the same as those in the first embodiment.

[0093] Next, in step S22, the determination unit 52 calculates the stoppage occurrence frequency of the stopped equipment.

[0094] Next, in step S23, the determination unit 52 calculates the productivity index value when each worker 5 is assigned to work on the stopped equipment.

[0095] 10 is a diagram showing the estimation process of the productivity index value. The determination unit 52 inputs data D1 indicating worker information, data D2 indicating stopped equipment information, data D3 indicating stoppage cause information, and data D4 indicating list information 62 into an operation time model 33A included in the estimation model 33, to calculate a restoration score when each operator 5 is assigned to handle the stopped equipment. The operation time model 33A outputs data D10 indicating a plurality of restoration scores for a plurality of operators 5.

[0096] Furthermore, the determination unit 52 calculates the stoppage occurrence frequency of the stopped equipment by inputting the data D2 and D3 into the stoppage occurrence frequency model 33B included in the estimation model 33. The stoppage occurrence frequency model 33B outputs data D11 indicating the stoppage occurrence frequency of the stopped equipment.

[0097] Furthermore, the determination unit 52 inputs the data D10 and D11 into the productivity index value model 33C included in the estimation model 33, thereby calculating the productivity index value when each worker 5 is in charge of the stopped equipment. The productivity index value model 33C outputs data D12 indicating a plurality of productivity index values ​​for a plurality of workers 5. In calculating the productivity index value, the productivity index value of the entire production process can be improved by prioritizing recovery work for stopped equipment that has a low frequency of stoppage over stopped equipment that has a high frequency of stoppage.

[0098] Next, in step S16, the determination unit 52 determines the worker 5 with the best productivity index value as the worker 5 to be in charge of the stopped equipment. Note that when multiple pieces of production equipment 4 stop at the same or similar times, resulting in multiple pieces of stopped equipment simultaneously, the determination unit 52 calculates the sum of the productivity index values ​​for each of multiple combinations of multiple workers 5 and multiple pieces of stopped equipment. The determination unit 52 extracts the combination with the best sum of the productivity index, and determines one or more workers 5 to be in charge of the multiple pieces of stopped equipment corresponding to that combination.

[0099] The processes in steps S17 and S18 are the same as those in the first embodiment.

[0100] According to this embodiment, the worker 5 with the best productivity index value is assigned to be in charge of the stopped equipment, thereby further improving productivity in the entire production process.

[0101] Furthermore, according to this embodiment, even if multiple pieces of production equipment 4 are stopped at the same time, it is possible to appropriately determine one or more workers 5 to be in charge of the multiple pieces of stopped equipment.

[0102] Third Embodiment FIG. 11 is a flowchart showing a process executed by a processing unit 41 of a determination device 2 according to a third embodiment.

[0103] First, in step S31 , the control unit 53 reads the list information 62 from the storage unit 42 , and the acquisition unit 21 acquires the list information 62 .

[0104] Next, in step S32, the acquisition unit acquires progress information indicating the work progress status of each worker 5 based on the operation information or work information received from the production equipment 4 or the mobile terminal 6 via the communication network 3.

[0105] Next, in step S33, the determination unit 52 determines whether there is a deviation of a predetermined value or more between the work plan indicated in the list information 62 corresponding to each worker 5 and the work progress indicated in the progress information for each worker 5. For example, the determination unit 52 determines whether the error between the estimated work time and the actual work time for the stopped equipment on which the worker 5 is currently performing recovery work is 10% or more of the estimated work time.

[0106] If there is a discrepancy between the work plan and the work progress status that is equal to or greater than a predetermined value (step S33: YES), then in step S34, the determination unit 52 redetermines the assignments of the multiple production facilities 4 to the multiple workers 5. The determination unit 52 redetermines the assignments of all stopped facilities that have not yet been worked on by all workers 5 using the method of the first embodiment or the second embodiment.

[0107] In the redetermination of the work assignments, if the work progress of a certain worker 5 is more advanced than the work plan, or if the list information 62 of a certain worker 5 becomes empty, the determination unit 52, after the redetermination, assigns the stopped equipment that has not yet been worked on, which was assigned to another worker 5 before the redetermination, to the certain worker 5. The other worker 5 may be, for example, the worker 5 with the highest recovery score.

[0108] Furthermore, in the redetermination of the work assignment, if the work progress of a certain worker 5 is behind the work plan, the determination unit 52 assigns the stopped equipment that has not yet been worked on, which was assigned to the certain worker 5 before the redetermination, to another worker 5 after the redetermination. The other worker 5 may be, for example, the worker 5 with the smallest recovery score.

[0109] Next, in step S35, the determination unit 52 updates the list information 62 of the workers 5 involved in the redetermination after redetermination of the work assignments. The control unit 53 stores the updated list information 62 in the storage unit 42.

[0110] Next, in step S36, the control unit 53 transmits the updated list information 62 to the mobile terminal 6 carried by the worker 5 involved in the redetermination. The mobile terminal 6 displays the received updated list information 62 on the screen.

[0111] According to this embodiment, if a deviation of a predetermined value or more occurs between the work plan and the work progress for a certain worker 5, the work assignment is redetermined, thereby further improving productivity throughout the entire production process.

[0112] Furthermore, according to this embodiment, the productivity of the entire production process can be further improved by assigning the production equipment 4 that has not yet been worked on and that was assigned to another worker 5 to a worker 5 whose work progress is more advanced than the work plan.

[0113] Furthermore, according to this embodiment, the productivity of the entire production process can be further improved by having another worker take charge of the unworked production equipment 4 that was assigned to the worker 5 whose work progress is behind the work plan.

[0114] The present disclosure is widely applicable to a production system in which any one of a plurality of workers is responsible for recovery work on each of a plurality of pieces of production equipment.

Claims

1. An information processing method for determining the allocation of production equipment to workers in a production process in which one of a number of workers is responsible for recovery work of a number of pieces of production equipment, the information processing method comprising the steps of: acquiring stopped equipment information indicating stopped equipment, which is production equipment that has been stopped; acquiring stop cause information indicating the cause of the stoppage of the stopped equipment; acquiring list information by worker indicating the production equipment currently assigned to each worker and the cause of the stoppage; and determining the worker to be assigned to the stopped equipment based on the stopped equipment information, the stop cause information, and the list information.

2. The information processing method according to claim 1, wherein in determining the workers, the outage cause information and the list information are input into a task time model which represents the required time for recovery work by worker and by cause of outage, thereby calculating a recovery score when each worker is assigned to be in charge of the stopped equipment.

3. The information processing method according to claim 2, wherein the restoration score indicates the elapsed time from the present time to the scheduled time when restoration work for the stopped equipment is completed when each worker is in charge of the stopped equipment.

4. The information processing method according to claim 3, wherein in the determination of the operator, the operator who has the smallest restoration score is assigned to be in charge of the stopped equipment.

5. The information processing method according to claim 2, wherein in determining the worker, a frequency of shutdown of the stopped equipment is calculated, a productivity index value when each worker is assigned to be in charge of the stopped equipment is calculated based on at least one of the recovery score and the shutdown frequency, and the worker with the best productivity index value is assigned to be in charge of the stopped equipment.

6. The information processing method according to claim 5, wherein, when the stopped equipment includes multiple pieces of stopped equipment, the determination of the workers comprises calculating a sum of the productivity index values ​​for each of multiple combinations of the multiple workers and the multiple pieces of stopped equipment, and determining one or more workers to be in charge of the multiple pieces of stopped equipment corresponding to the combination that results in the best sum of the productivity index values.

7. The information processing method according to claim 1, further comprising: after determining a worker who will be in charge of the stopped equipment, updating the list information corresponding to that worker, thereby adding the stopped equipment and its cause of shutdown to the list information.

8. The information processing method according to claim 7, further comprising transmitting the updated list information to a mobile terminal carried by the worker in charge of the stopped equipment.

9. The information processing method according to claim 1, further comprising: acquiring progress information indicating the work progress of each worker; and, when a deviation of a predetermined value or more occurs between the work plan indicated in the list information corresponding to a certain worker and the work progress indicated in the progress information related to that worker, redetermining the allocation of responsibilities of the plurality of production equipment to the plurality of workers.

10. The information processing method according to claim 9, wherein, in redetermining the work assignments, if the work progress for the certain worker is more advanced than the work plan, the certain worker is made responsible for unoperated production equipment that was assigned to another worker.

11. The information processing method according to claim 9, wherein, in redetermining the work assignments, if the work progress for the certain worker is behind the work plan, the production equipment that has not been worked on and that was assigned to the certain worker is assigned to another worker.

12. A method for generating an estimation model for determining the allocation of production equipment to workers in a production process in which any one of a plurality of workers is responsible for recovery work of a plurality of pieces of production equipment, comprising: an information processing device acquires operation history information on the plurality of pieces of production equipment, including stopped equipment information indicating stopped equipment that is a stopped production equipment, stop cause information indicating the cause of the stoppage of the stopped equipment, work start time information indicating the start time of recovery work for the stopped equipment, recovery time information indicating the time when the stopped equipment was restored, and identification information of the worker in charge of the recovery work of the stopped equipment; and generates an estimation model for determining the worker to be assigned to the stopped equipment based on the stopped equipment information, the stop cause information, and list information by worker indicating the production equipment currently assigned to each worker and the cause of its stoppage, by machine learning using the operation history information as learning data.

13. An information processing device that determines the allocation of production equipment to workers in a production process in which one of multiple workers is responsible for recovery work of multiple pieces of production equipment, the information processing device acquires stopped equipment information indicating stopped production equipment, which is production equipment that has been stopped, acquires stoppage cause information indicating the cause of the stoppage of the stopped equipment, acquires list information by worker indicating the production equipment currently assigned to each worker and the cause of the stoppage, and determines the worker to be responsible for the stopped equipment based on the stopped equipment information, the stoppage cause information, and the list information.

14. A program for causing an information processing device to execute processing to determine the allocation of production equipment to workers in a production process in which one of a number of workers is responsible for recovery work on a number of pieces of production equipment, the processing comprising: acquiring stopped equipment information indicating stopped production equipment that is a stopped production equipment; acquiring stoppage cause information indicating the cause of the stoppage of the stopped equipment; acquiring list information by worker indicating the production equipment currently assigned to each worker and the cause of the stoppage; and determining the worker to be responsible for the stopped equipment based on the stopped equipment information, the stoppage cause information, and the list information.

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