Operation Analysis System

Abstract

The operation analysis system includes a production efficiency information map creation unit (231) that creates a production efficiency information map that is an information map showing the correspondence between production efficiency information and operation-related information, a production efficiency feature value calculation unit (233) that extracts individual information related to the production efficiency information of the target area from a plurality of pieces of operation-related information as elements, and calculates the aggregate value of the production efficiency information for each element as a production efficiency feature value for all combinations of the operation-related information and the production efficiency information, and a factor candidate extraction unit (234) that calculates a deviation degree, which is an index for evaluating the difference in the production efficiency feature value between the elements, for each type of operation-related information for all combinations of the operation-related information and the production efficiency information, and extracts the types of operation-related information in descending order of deviation degree from all combinations of the operation-related information and the production efficiency information of the target area. The operation analysis system reduces the burden on the user when it is introduced, and makes it possible to analyze the cause of the decrease in the production efficiency of the equipment.

Description

[Technical field]

[0001] The present disclosure relates to an operation analysis system that analyzes causes of declines in production efficiency of production equipment. [Background technology]

[0002] In factories, there is a need to improve the productivity of products by operating equipment such as processing machines. When a product is produced using equipment, the operation status of the equipment has various wastes or losses that are factors that reduce the productivity of the equipment, that is, various wastes or losses that are factors that reduce the production efficiency of the product in the equipment. Therefore, in order to improve the productivity of the equipment, it is necessary to detect the factors that reduce the production efficiency of the equipment, identify the cause of the occurrence of the factors, and further reduce the factors by taking measures. However, since the operation status of the equipment is affected by various factors, it is difficult to identify the cause of the occurrence of the factors that reduce the production efficiency of the equipment.

[0003] Patent Document 1 describes a productivity improvement system that extracts problems in product production and estimates the causes of the problems based on an evaluation value for product production calculated based on actual data on production results in the product production process. In the productivity improvement system described in Patent Document 1, multiple scenarios including judgment formulas for determining the occurrence of factors that reduce product productivity based on multiple pieces of information such as the day of the week and work hours are stored in advance, and the causes of problems in product production are estimated according to the scenarios.

[0004] Moreover, in the productivity improvement system described in Patent Document 1, cause / countermeasure data, which is information that indicates the correspondence between the causes of problems in product production that may occur in facilities such as factories and effective countermeasures for the problems, is stored in advance. The productivity improvement system described in Patent Document 1 refers to the cause / countermeasure data, adopts the countermeasure corresponding to the scenario identified as having the highest degree of suitability during cause estimation from among the countermeasures previously set for each scenario, and proposes countermeasures to present to the user. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2023-119612 A Summary of the Invention [Problem to be solved by the invention]

[0006] However, in the productivity improvement system described in the above Patent Document 1, the user must prepare a plurality of scenarios and cause / measure data in advance and set them in the productivity improvement system, which places a heavy burden on the user.

[0007] In addition, factors that reduce productivity and the causes and countermeasures for those factors differ for each factory or facility. For this reason, in the productivity improvement system described in Patent Document 1, the user must prepare multiple scenarios and cause / countermeasure data for each factory or facility in advance and set them in the productivity improvement system. However, if the user prepares multiple scenarios and cause / countermeasure data for each factory or facility in advance and sets them in the productivity improvement system, there is a problem in that it takes a lot of time and effort to introduce the productivity improvement system, which places a heavy burden on the user.

[0008] The present disclosure has been made in consideration of the above, and aims to provide an operation analysis system that imposes little burden on a user when installing and is capable of analyzing the cause of a decline in production efficiency of equipment. [Means for solving the problem]

[0009] In order to solve the above-mentioned problems and achieve the objectives, the operation analysis system disclosed herein includes a production efficiency information map creation unit that creates a production efficiency information map, which is an information map in which the production efficiency information is displayed using two or more types of operation-related information as display axes to show the correspondence between the production efficiency information and the operation-related information, based on production efficiency information, which is information related to the production of products in the production equipment and serves as an index for evaluating the production efficiency of the products in the production equipment, and operation-related information, which is information related to the production of products in the production equipment and serves as a candidate for causes of a decrease in the production efficiency of the products in the production equipment, and a focus area acquisition unit that acquires focus area designation information, which is information that designates a focus area selected in the production efficiency information map. The operation analysis system includes a production efficiency feature calculation unit that extracts individual information related to production efficiency information of a region of interest as elements from a plurality of pieces of operation-related information, and calculates an aggregate value of the production efficiency information for each element as a production efficiency feature for all combinations of the operation-related information and the production efficiency information, and a factor candidate extraction unit that calculates a deviation, which is an index for evaluating a difference in the production efficiency feature between the elements, for each type of operation-related information for all combinations of the operation-related information and the production efficiency information, and extracts types of operation-related information in descending order of deviation from among all combinations of the operation-related information and the production efficiency information of the region of interest. Effect of the Invention

[0010] According to the present disclosure, it is possible to obtain an operation analysis system that places little burden on the user when it is introduced and is capable of analyzing the cause of a decrease in production efficiency of equipment. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating a configuration example of an operation analysis system according to a first embodiment. [Diagram 2] FIG. 1 is a diagram illustrating an example of a configuration of a server included in an operation analysis system according to a first embodiment. [Diagram 3] FIG. 1 is a diagram showing an example of a production efficiency information map created in the operation analysis system according to the first embodiment; [Figure 4]FIG. 1 is a diagram illustrating an example of a configuration of a terminal device included in an operation analysis system according to a first embodiment. [Diagram 5] 1 is a flowchart showing an example of a process of the operation analysis system according to the first embodiment. [Figure 6] FIG. 1 is a first diagram showing an example of the concept of a method in which a factor candidate extraction unit of an operation analysis system according to a first embodiment calculates a deviation degree for each type of operation-related information; [Figure 7] FIG. 2 is a second diagram showing an example of the concept of a method in which the factor candidate extraction unit of the operation analysis system according to the first embodiment calculates a deviation degree for each type of operation-related information; [Figure 8] FIG. 13 is a diagram showing an example of information on potential factors of decline in production efficiency displayed on a display unit of a terminal device in the operation analysis system according to the first embodiment; [Figure 9] 11 is a flowchart showing an example of a process of the operation analysis system according to the second embodiment. [Figure 10] FIG. 13 is a diagram showing an example of the concept of a method in which a factor candidate extraction unit of the operation analysis system calculates a deviation degree in the second embodiment. [Figure 11] 13 is a flowchart showing an example of a process of the operation analysis system according to the third embodiment. [Figure 12] FIG. 4 is a diagram showing an example of two focus areas specified in the production efficiency information map shown in FIG. 3; [Figure 13] FIG. 13 is a diagram showing the production efficiency feature value when the operation-related information is a worker for the area A shown in FIG. [Figure 14] FIG. 13 is a diagram showing the production efficiency feature value when the operation-related information is a worker, for the region B shown in FIG. [Figure 15] FIG. 13 is a diagram showing a production efficiency feature value when the operation-related information is a day of the week, for the region A shown in FIG. [Figure 16] FIG. 13 is a diagram showing a production efficiency feature value when the operation-related information is a day of the week, for the region B shown in FIG. [Figure 17] A flowchart showing an example of a process of the operation analysis system according to the fourth embodiment. [Figure 18]FIG. 13 is a diagram showing an example of a production efficiency information map created by the operation analysis system in the fourth embodiment. [Figure 19] FIG. 13 is a diagram showing another example of the production efficiency information map created by the operation analysis system in the fourth embodiment. [Figure 20] FIG. 1 is a diagram showing a configuration in which the functions of the control unit according to the first to fourth embodiments are realized by hardware. [Figure 21] FIG. 1 is a diagram showing a configuration in which the functions of the control unit according to the first to fourth embodiments are realized by software. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] An operation analysis system according to an embodiment will be described in detail below with reference to the drawings.

[0013] Embodiment 1 FIG. 1 is a diagram showing a configuration example of an operation analysis system according to the first embodiment. The operation analysis system 1 according to the first embodiment is a system that provides appropriate support for improving the productivity of products in a facility by helping a user to understand the cause of a decline in the production efficiency of a product in the production facility 6, which is a facility for producing the product, in the production of the product by operating the production facility 6, thereby reducing the burden on the user. The operation analysis system 1 automatically analyzes information related to the operation status of the production facility 6 in the production of the product in the production facility 6, and presents the analysis result to the user as information on the cause of the decline in the production efficiency of the production facility 6. As a result, the operation analysis system 1 can help the user to understand the cause of the decline in the production efficiency of the product in the production facility 6, thereby reducing the burden on the user in analyzing the cause of the decline in the production efficiency of the production facility 6. In the following, the "decline in the productivity of the product in the production facility 6" may be simply referred to as the "decline in productivity". In addition, in the following, the "decline in the production efficiency of the product in the production facility 6" may be simply referred to as the "decline in production efficiency".

[0014] A user of the operation analysis system 1 according to the first embodiment is, for example, a manager who manages the production of products by the production facility 6, and an analyst who analyzes the operation status of the production facility 6, but the user is not limited to this.

[0015] As shown in FIG. 1, the operation analysis system 1 according to the first embodiment includes a server 2 and a terminal device 3.

[0016] In the operation analysis system 1, the server 2 is connected to the terminal device 3 so as to be able to communicate with each other via a network such as the Internet or an intranet, which is a global information and communication network. In the first embodiment, the server 2 is connected to the terminal device 3 so as to be able to communicate with each other via the Internet 4. That is, the server 2 and the terminal device 3 are connected to the network and are able to send and receive information to and from each other. The communication between the server 2 and the terminal device 3 may be wireless communication or wired communication.

[0017] The server 2 is an operation analysis server that automatically analyzes information related to the past operation status of the production facility 6 in order to support the work of improving the production efficiency of products in the production facility 6, and presents the analysis results to a user as information on the causes of the decline in production efficiency of the production facility 6. The server 2 is a server constructed in a cloud environment 5. The cloud environment 5 includes computer resources provided in a cloud service platform. The cloud service platform is provided by a cloud service provider, and includes, for example, PaaS (Platform as a Service) and the like. Since the server 2 is constructed in the cloud environment 5, it is sometimes called a cloud server. Note that an on-premise server may be used as the server 2.

[0018] A terminal device such as a desktop PC (Personal Computer) or a notebook PC is used as the terminal device 3. Note that a portable terminal device such as a tablet PC or a smartphone may be used as the terminal device 3. The terminal device 3 is used by a user of the operation analysis system 1.

[0019] The configuration of the operation analysis system 1 will be described in more detail below.

[0020] The server 2 holds production efficiency information and operation related information regarding past product production processes in the production facility 6 as information related to the operation status of the production of products in the production facility 6. The server 2 automatically analyzes information related to the past operation status of the production facility 6 using the production efficiency information and the operation related information, and presents the analysis result to the user as information on the causes of the decline in production efficiency of the production facility 6.

[0021] The production efficiency information is information related to the production of products in the production facility 6, and serves as an index for evaluating the production efficiency of products in the production facility 6. The production efficiency information includes raw data acquired in the production of products in the production facility 6, and information obtained by processing the raw data. Moreover, the production efficiency information is information that directly expresses waste or loss that is a cause of a decrease in the production efficiency of products in the production facility 6, and can be said to be information that serves as an index for evaluating the causes of a decrease in the production efficiency of the production facility 6.

[0022] The production efficiency information includes, for example, information such as "operation rate," "operational availability rate," "failure rate," "alert time rate," "basic unit," and "deviation from set value or standard processing time."

[0023] The "operation rate" is the ratio of the actual operation time of the production equipment 6 to the standard operation time.

[0024] The "availability rate" is the ratio of the time that the production equipment 6 was actually available to the total time that the production equipment 6 was in use.

[0025] "Failure rate" is the rate of defective products produced at production facility 6.

[0026] The "alert time rate" is the ratio of time during which an alert is issued during the production of products in the production facility 6.

[0027] The "basic unit" is the amount of material or the amount of time used or discharged in the production facility 6 to produce a certain output.

[0028] The "deviation from the set value or standard processing time" is the ratio of the deviation from the set value or standard processing time set for the production equipment 6.

[0029] The operation-related information is information related to the production of products in the production equipment 6, and is information that is a candidate for a cause of a decrease in the production efficiency of products in the production equipment 6. The operation-related information includes raw data acquired in the production of products in the production equipment 6. In other words, the operation-related information is information that does not directly express waste or loss that is a cause of a decrease in the production efficiency of products in the production equipment 6, and is information that does not serve as an index for evaluating the cause of a decrease in the production efficiency of the production equipment 6.

[0030] The operation-related information includes, for example, "worker information," "operation performance data," "processing performance data," "reference time," and "workpiece information."

[0031] "Worker information" is information about the worker who operated the production equipment 6 and the transition of workers.

[0032] "Operation record data" is operation record data of the production equipment 6, and includes data such as operation time, processing start time, processing end time, date, and day of the week when the production equipment 6 was operated.

[0033] The "processing performance data" is processing performance data in the production facility 6, and includes, for example, data such as processing parameters, processing programs, stop logs, and other status data when the production facility 6 performs processing.

[0034] The "reference time" is the time it typically takes to produce a product in the production facility 6, and is also called the standard time.

[0035] "Information on the workpiece" is information on the workpiece used in processing in the production facility 6, and includes standard time, processing cost, covered Material of the workpiece and covered This includes data such as the thickness of the workpiece.

[0036] FIG. 2 is a diagram illustrating an example of a configuration of a server included in the operation analysis system according to the first embodiment.

[0037] 2, the server 2 includes a server communication unit 21, a server storage unit 22, a server processing unit 23, and a server control unit 24. The above-mentioned components of the server 2 can exchange information with each other.

[0038] The server communication unit 21 is connected to the Internet 4, and communicates with devices external to the server 2 via the Internet 4. The server communication unit 21 communicates with the terminal device 3 via the Internet 4.

[0039] The server storage unit 22 stores various types of information, such as information acquired from outside the server 2 and information created inside the server 2, as information used for analyzing information related to the past operation status of the production facility 6 and for controlling the server 2. The server 2 stores an operation analysis server program, which is a program used for analyzing information related to the past operation status of the production facility 6. The server storage unit 22 has an analysis data storage unit 221.

[0040] The analysis data storage unit 221 stores production efficiency information and operation related information as information related to the past operation status of the production facility 6, which is used for analyzing the causes of the decline in production efficiency of the production facility 6.

[0041] The server processing unit 23 includes a production efficiency information map creation unit 231, a region of interest acquisition unit 232, a production efficiency feature amount calculation unit 233, and a factor candidate extraction unit 234. The above-mentioned components of the server processing unit 23 can exchange information with each other.

[0042] The production efficiency information map creation unit 231 acquires production efficiency information and operation related information from the analysis data storage unit 221, and creates production efficiency information map data, which is data for displaying a production efficiency information map on the terminal device 3, based on the acquired production efficiency information and operation related information. The production efficiency information map creation unit 231 stores the created production efficiency information map data in the analysis data storage unit 221 of the server storage unit 22. In addition, the production efficiency information map creation unit 231 transmits the created production efficiency information map data to the terminal device 3 via the server communication unit 21.

[0043] The production efficiency information map is an information map in which the production efficiency information is displayed in association with the operation-related information using two or more types of operation-related information as display axes, and the corresponding relationship between the production efficiency information and the operation-related information is shown. In other words, the production efficiency information map is an information map in which the corresponding relationship between the production efficiency information and the operation-related information is shown using two or more types of operation-related information as display axes. The production efficiency information map is data that displays one or more types of production efficiency information using multiple types of operation-related information such as time and day of the week as display axes.

[0044] Fig. 3 is a diagram showing an example of a production efficiency information map created in the operation analysis system according to the first embodiment. In the production efficiency information map 40 shown in Fig. 3, information on "operation rate" which is production efficiency information is displayed in association with information on two types of operation-related information, "operation time" and "day of the week", and a correspondence relationship between the operation-related information "operation time" and "day of the week" and the production efficiency information "operation rate" is shown. That is, in the production efficiency information map 40 shown in Fig. 3, the operation-related information "operation time" and "day of the week" are used as display axes, and a correspondence relationship between the operation-related information "operation time" and "day of the week" and the production efficiency information "operation rate" is shown.

[0045] 3, the value of the "operating rate" which is the production efficiency information is expressed by the size of the circle. This allows a user who checks the production efficiency information map on the terminal device 3 to easily and visually grasp the bias of the "operating rate" which is the production efficiency information.

[0046] The region of interest acquisition unit 232 acquires, from the terminal device 3 via the server communication unit 21, region of interest designation information that is information designating the region of interest selected in the production efficiency information map.

[0047] The area of ​​interest designation information is information that designates an area of ​​interest selected by a user in the production efficiency information map displayed by the production efficiency information map data. The area of ​​interest designation information is input to the terminal device 3 by a user who has checked the production efficiency information map on the terminal device 3, and is transmitted from the terminal device 3 to the area of ​​interest acquisition unit 232. The area of ​​interest acquisition unit 232 acquires the area of ​​interest designation information for one or more areas of interest from the terminal device 3. The area of ​​interest acquisition unit 232 transmits the acquired area of ​​interest designation information to the production efficiency feature amount calculation unit 233.

[0048] The focus area is an area in which a range of production efficiency information is specified in the production efficiency information map displayed by the production efficiency information map data. The focus area is a range of production efficiency information specified by a user, for example, in the production efficiency information map, which the user wants to use as a target for the analysis of factors behind the decline in production efficiency of products in the production facility 6, and which is a range of production efficiency information in which the user wants to identify factors behind the decline in production efficiency.

[0049] For example, a user looking at the production efficiency information map 40 shown in Fig. 3 can select an area corresponding to a time period or day of the week where circles with small production efficiency information values ​​are concentrated in the production efficiency information map 40 as a region of interest 41. For example, if the user believes that the operating rate is decreasing at a similar time between 10:00 and 15:00 on each day of the week from Monday to Saturday, the user can select the range from 10:00 to 15:00 on Monday to Saturday as the region of interest 41. The method of selecting the region of interest can be a method of specifying one circle in Fig. 3, a method of selecting the 15:00 hour period as a whole for the whole week, or a method of selecting the range from 10:00 to 15:00 on Monday to Saturday as a region of interest 41. Specify etc., are optional.

[0050] The production efficiency feature amount calculation unit 233 calculates the production efficiency feature amount for the region of interest designation information. That is, the production efficiency feature amount calculation unit 233 calculates the production efficiency feature amount for the region of interest designated in the production efficiency information map. The production efficiency feature amount calculation unit 233 extracts individual pieces of information related to the production efficiency information of the region of interest as elements from the multiple pieces of operation-related information, and calculates an aggregate value of the production efficiency information for each element as the production efficiency feature amount for all combinations of the operation-related information and the production efficiency information.

[0051] The production efficiency feature amount is calculated based on the production efficiency information of the target area, and serves as an index for evaluating the production efficiency of the production facility 6.

[0052] The production efficiency feature amount calculation unit 233 acquires the region of interest designation information from the region of interest acquisition unit 232. The production efficiency feature amount calculation unit 233 extracts one or more elements of operation-related information related to the production efficiency information of the region of interest designated in the region of interest designation information. The production efficiency feature amount calculation unit 233 extracts one or more elements of operation-related information for each piece of operation-related information from the multiple pieces of operation-related information.

[0053] Specifically, the production efficiency feature amount calculation unit 233 first acquires operation-related information related to the production efficiency information of the region of interest from the analysis data storage unit 221. The production efficiency feature amount calculation unit 233 can acquire the operation-related information from the analysis data storage unit 221 based on, for example, predetermined operation-related information acquisition conditions. Note that the method by which the production efficiency feature amount calculation unit 233 acquires operation-related information related to the production efficiency information of the region of interest specified in the production efficiency information map is not limited to the method using the operation-related information acquisition conditions.

[0054] The operation-related information acquisition condition is a condition under which the production efficiency feature amount calculation unit 233 acquires operation-related information related to the production efficiency information of a region of interest specified in the production efficiency information map from various types of operation-related information stored in the analysis data storage unit 221. The operation-related information acquisition condition is determined in advance by a user and stored in the production efficiency feature amount calculation unit 233. The user can set, for example, information associating information on the type of operation-related information that may be a fluctuation factor of the production efficiency information with the production efficiency information as the operation-related information acquisition condition for each production efficiency information.

[0055] Next, the production efficiency characteristic amount calculation unit 233 extracts one or more elements of each piece of operation-related information from the acquired plurality of pieces of operation-related information.

[0056] An element of operation-related information is individual information related to the production efficiency information of the focus area in each piece of operation-related information, and is a specific item included in each type of operation-related information. An element of operation-related information is a specific subordinate concept of each type of operation-related information. For example, when the type of operation-related information is "worker", specific worker names such as "worker A, worker B, worker C, ..." are exemplified as elements of operation-related information. When the type of operation-related information is "day of the week", specific days of the week such as "Monday, Tuesday, ..." are exemplified as elements of operation-related information. When the type of operation-related information is "time of day", specific times such as "8:00, 9:00, 10:00, ..." are exemplified as elements of operation-related information. Hereinafter, "elements of operation-related information" may be simply referred to as "elements".

[0057] Next, the production efficiency feature calculation unit 233 acquires production efficiency information of the area of ​​interest from the analysis data storage unit 221, and aggregates the production efficiency information of the area of ​​interest for each element of the operation-related information for all combinations of the extracted elements of the operation-related information and the production efficiency information of the area of ​​interest.

[0058] Aggregation of production efficiency information of a target area means calculation of an aggregate value for the target production efficiency information according to a predetermined calculation method. Examples of the aggregation method of production efficiency information of a target area include a method of calculating statistics such as the average, median, standard deviation, variance, maximum value, and minimum value for the target production efficiency information. Furthermore, when the elements of the operation-related information have a hierarchical structure, the production efficiency feature amount calculation unit 233 may aggregate the production efficiency information for each hierarchical unit of the elements of the operation-related information. An example of the hierarchical structure of the elements of the operation-related information is a hierarchical structure of a control program and a subprogram of the control program, which are elements of the operation-related information.

[0059] The method of calculation used to calculate the production efficiency information of the area of ​​interest is limited to one. figure For example, for the worker, which is the operation-related information, multiple aggregations may be performed, such as the average value, median, and standard deviation, for each element of the production efficiency information.

[0060] Next, the production efficiency feature amount calculation unit 233 normalizes the aggregated value of the production efficiency information of the region of interest for each element of the aggregated operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the region of interest. The production efficiency feature amount calculation unit 233 normalizes the extracted aggregated value by converting the aggregated value so that the range is, for example, from 0 to 1.

[0061] Then, the production efficiency feature amount calculation unit 233 acquires the normalized aggregated value as the production efficiency feature amount. Through the above processing, the production efficiency feature amount calculation unit 233 can calculate the production efficiency feature amount for each element of the operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the target area.

[0062] The normalization of the aggregated values ​​is performed to facilitate comparison of the variations in the aggregated values ​​between different types of production efficiency information. In other words, by using the normalized aggregated values ​​as the production efficiency feature quantities for each element of the operation-related information, it becomes possible to compare the variations and deviations of the production efficiency feature quantities when comparing multiple different types of production efficiency information.

[0063] The production efficiency feature calculation unit 233 transmits to the factor candidate extraction unit 234 the area of ​​interest designation information acquired from the area of ​​interest acquisition unit 232, information on the type of operation-related information acquired from the analysis data storage unit 221 based on the area of ​​interest designation information, information on elements of the operation-related information extracted from the operation-related information acquired from the analysis data storage unit 221, and information on each production efficiency feature for all combinations of the extracted elements of the operation-related information and the production efficiency information of the area of ​​interest.

[0064] The factor candidate extraction unit 234 extracts candidate factors of production efficiency decline from among all combinations of operation related information and production efficiency information of the region of interest, based on the degree of deviation obtained from the production efficiency feature amount calculated by the production efficiency feature amount calculation unit 233. The factor candidate extraction unit 234 calculates the degree of deviation for each type of operation related information for all combinations of operation related information and production efficiency information, and extracts operation related information in descending order of the degree of deviation from among all combinations of operation related information and production efficiency information of the region of interest.

[0065] The candidate factors for the decline in production efficiency are candidate factors for the decline in production efficiency of the production facility 6 that are analyzed in the operation analysis system 1.

[0066] The deviation is an index for evaluating the difference between the production efficiency feature values ​​among a plurality of pieces of operation-related information. In the first embodiment, the deviation is the prominence of the production efficiency feature value of an element having a significantly larger or smaller production efficiency feature value than other elements among a plurality of elements of operation-related information included in each type of operation-related information. In other words, the deviation is a value obtained by evaluating the difference between a plurality of production efficiency feature values ​​based on the magnitude relationship among the plurality of production efficiency feature values.

[0067] "Significantly" means that it meets a predetermined criterion. The predetermined criterion may be, for example, a criterion such as ±3σ or a significant difference that can be measured by general statistics, which is set in the factor candidate extraction unit 234 in advance, or may be calculated based on the statistics of the production efficiency feature. The method of calculating the deviation will be described later.

[0068] Specifically, the factor candidate extraction unit 234 calculates the degree of deviation for each type of operation-related information for all combinations of the operation-related information and the production efficiency information of the target region based on the production efficiency feature amount calculated by the production efficiency feature amount calculation unit 233. Then, the factor candidate extraction unit 234 extracts a predetermined number of types of operation-related information as candidates for production efficiency decline in order of the degree of deviation from all combinations of the operation-related information and the production efficiency information of the target region, i.e., from the multiple pieces of operation-related information for which the degree of deviation has been calculated. When the predetermined number is K, the factor candidate extraction unit 234 extracts the top K types of operation-related information with the highest degree of deviation from all types of operation-related information for which the degree of deviation has been calculated.

[0069] The factor candidate extraction unit 234 stores information on the candidate factors of production efficiency reduction for each of the top K pieces of operation-related information of the extracted type in the server storage unit 22. In addition, the factor candidate extraction unit 234 transmits the information on the candidate factors of production efficiency reduction to the terminal device 3 via the server communication unit 21.

[0070] Here, the information on the candidate factors of the production efficiency decline includes "information on the type of operation-related information", "information on the degree of deviation in the operation-related information", and "information on the name of an element that has a significantly prominent deviation in the production efficiency feature value from other elements among the multiple elements in the operation-related information".

[0071] An example of "information on the type of operation-related information" is information such as "worker." An example of "information on the deviation in the operation-related information" is information such as "the deviation of the worker is 0.9." An example of "information on the name of an element in which the deviation of the production efficiency feature amount from other elements among multiple elements in the operation-related information is significantly prominent" is information such as "worker B and worker D."

[0072] The terminal device 3 is a device that presents various information of the operation analysis system 1 to the user. The terminal device 3 displays a production efficiency information map created by the production efficiency information map creation unit 231 of the server processing unit 23 of the server 2, and receives attention area designation information that designates an attention area in the production efficiency information map. The user can view the production efficiency information map created by the production efficiency information map creation unit 231 of the server processing unit 23 of the server 2, using the terminal device 3. In addition, the user can view information on candidate factors of production efficiency decline created by the candidate factor extraction unit 234 of the server processing unit 23 of the server 2, using the terminal device 3.

[0073] Fig. 4 is a diagram illustrating an example of a configuration of a terminal device included in the operation analysis system according to the first embodiment. As illustrated in Fig. 4, the terminal device 3 includes an input unit 31, a display unit 32, a terminal communication unit 33, a terminal storage unit 34, and a terminal control unit 35. The components of the terminal device 3 can exchange information with each other.

[0074] The input unit 31 is a functional unit that is operated by a user when using the operation analysis system 1. The user uses the input unit 31 to perform various operations on the operation screen of the operation analysis system 1 displayed on the display unit 32. The input unit 31 accepts information input by the user and transmits input information corresponding to the information to the terminal control unit 35.

[0075] The display unit 32 displays information on the operations in the input unit 31 and information on the analysis function of candidate factors for decline in production efficiency by the operation analysis system 1. The display unit 32 is a display device such as an LCD (Liquid Crystal Display) or an organic EL (Electro Luminescence) display.

[0076] The terminal communication unit 33 communicates with the server communication unit 21 of the server 2 .

[0077] The terminal memory unit 34 is a memory unit that stores information used in the operation analysis system 1, and stores information used to control the terminal device 3, information inputted through the input unit 31, and information acquired from the server 2.

[0078] The terminal control unit 35 is a control unit that controls the overall processing of the terminal device 3. The terminal control unit 35 transmits input information received from the input unit 31 to the server processing unit 23 of the server 2. The terminal control unit 35 transmits input information corresponding to the operation content operated by the user on the operation screen of the operation analysis system 1 displayed on the display unit 32 of the terminal device 3 to the server processing unit 23 of the server 2, obtains screen data corresponding to the user's operation content from the server processing unit 23, and displays it on the display unit 32.

[0079] Next, the operation of the operation analysis system 1 according to the first embodiment will be described with reference to a flowchart. Fig. 5 is a flowchart showing an example of the process of the operation analysis system according to the first embodiment.

[0080] In step S110, a production efficiency information map is created. Specifically, the production efficiency information map creating unit 231 of the server processing unit 23 of the server 2 creates the production efficiency information map.

[0081] A user inputs analysis instruction information for instructing an analysis of factors behind a decline in production efficiency as an input to the input unit 31 on the operation screen of the operation analysis system 1 displayed on the display unit 32 of the terminal device 3. The production efficiency information map creation unit 231 creates a production efficiency information map based on the user's analysis instruction information input from the terminal device 3. That is, the production efficiency information map creation unit 231 acquires production efficiency information and operation-related information from the analysis data storage unit 221, and creates production efficiency information map data that is data for displaying a production efficiency information map based on the acquired production efficiency information and operation-related information.

[0082] In the first embodiment, the production efficiency information map creation unit 231 acquires one type of production efficiency information and two types of operation-related information from the analysis data storage unit 221 based on, for example, predetermined map creation conditions, and creates a production efficiency information map based on the acquired information. That is, the production efficiency information map creation unit 231 creates a production efficiency information map for a predetermined combination of production efficiency information and operation-related information. As shown in FIG. 3, for example, the production efficiency information map creation unit 231 creates a production efficiency information map in which information on "operation rate", which is one type of production efficiency information, is displayed in association with information on "operation time" and "day of the week", which are two types of operation-related information, and which shows the correspondence between the operation-related information "operation time" and "day of the week" and the production efficiency information "operation rate".

[0083] The map creation conditions are information that specifies one type of production efficiency information and two types of operation related information that are used when the production efficiency information map creation unit 231 creates a production efficiency information map. The map creation conditions include one or more sets of information on combinations of one type of production efficiency information and two types of operation related information. The map creation conditions are determined in advance and stored in the production efficiency information map creation unit 231.

[0084] A user can set information on any combination of production efficiency information and operation related information for which the user wishes to analyze the causes of a decline in production efficiency as a map creation condition. For example, a user can set information on a combination of production efficiency information and operation related information based on tacit knowledge as a map creation condition, and can set information on a combination of production efficiency information and operation related information suitable for analyzing the causes of a decline in production efficiency as a map creation condition. This allows the production efficiency information map creation unit 231 to create a production efficiency information map suitable for analyzing the causes of a decline in production efficiency based on tacit knowledge.

[0085] The production efficiency information map creating unit 231 creates a production efficiency information map for the set included in the map creation conditions.

[0086] Then, the production efficiency information map creation unit 231 transmits the created production efficiency information map data to the terminal control unit 35 of the terminal device 3 via the server communication unit 21. The terminal control unit 35 receives the production efficiency information map data transmitted from the production efficiency information map creation unit 231 via the terminal communication unit 33. Then, the process proceeds to step S120.

[0087] In step S120, the region-of-interest designation information is acquired. Specifically, the region-of-interest acquisition unit 232 of the server processing unit 23 of the server 2 acquires the region-of-interest designation information.

[0088] When the terminal control unit 35 of the terminal device 3 receives the production efficiency information map data, it uses the production efficiency information map data to display the production efficiency information map on the display unit 32, and presents the production efficiency information map to the user. After checking the production efficiency information map displayed on the display unit 32, the user selects one area of ​​interest on the production efficiency information map, and inputs area of ​​interest designation information for the selected area of ​​interest to the terminal device 3 using the input unit 31 of the terminal device 3. The terminal control unit 35 transmits the input area of ​​interest designation information to the area of ​​interest acquisition unit 232.

[0089] The region of interest acquisition unit 232 acquires the region of interest designation information by receiving the region of interest designation information transmitted from the terminal device 3. The region of interest acquisition unit 232 transmits the acquired region of interest designation information to the production efficiency feature amount calculation unit 233 of the server processing unit 23 of the server 2. The production efficiency feature amount calculation unit 233 receives the region of interest designation information transmitted from the region of interest acquisition unit 232. Then, the process proceeds to step S130.

[0090] In steps S130 to S150, the production efficiency feature amount is calculated based on the attention area designation information. Specifically, the production efficiency feature amount calculation unit 233 of the server processing unit 23 of the server 2 calculates the production efficiency feature amount for the attention area designated in the production efficiency information map based on the attention area designation information.

[0091] In step S130, elements of the operation-related information are extracted. When the production efficiency feature amount calculation unit 233 acquires the region-of-interest designation information, it acquires a plurality of pieces of operation-related information related to the production efficiency information of the region-of-interest designated in the region-of-interest designation information from the analysis data storage unit 221. Then, the production efficiency feature amount calculation unit 233 extracts one or more elements of the operation-related information from each of the acquired plurality of pieces of operation-related information. Then, the process proceeds to step S140.

[0092] In step S140, the production efficiency information of the target area is collected for each element of the operation-related information. The production efficiency feature amount calculation unit 233 collects the production efficiency information of the target area for each element of the operation-related information for all combinations of the elements of the operation-related information extracted in step S130 and the production efficiency information of the target area. Then, the process proceeds to step S150.

[0093] In step S150, the aggregated values ​​are normalized. The production efficiency feature amount calculation unit 233 normalizes the aggregated value of the production efficiency information of the region of interest for each element of the aggregated operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the region of interest.

[0094] Then, the production efficiency feature amount calculation unit 233 acquires the normalized aggregated value as the production efficiency feature amount. Through the above processing, the production efficiency feature amount calculation unit 233 calculates the production efficiency feature amount for each element of the operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the target area. Then, the process proceeds to step S160.

[0095] In step S160, the deviation of the production efficiency feature is calculated for each type of operation related information. The factor candidate extraction unit 234 calculates the deviation for each type of operation related information based on the production efficiency feature calculated by the production efficiency feature calculation unit 233 for all combinations of the operation related information and the production efficiency information of the target area.

[0096] A method for calculating the degree of deviation for each type of operation-related information will be described. The degree of deviation for each type of operation-related information may be any value that can highlight and evaluate the difference in production efficiency feature amount of the same type of operation-related information between elements of the operation-related information. In the first embodiment, for example, the maximum value of the difference in production efficiency feature amount between elements in the same operation-related information is calculated, and the maximum value of the difference in production efficiency feature amount between the elements can be used as the degree of deviation for each type of operation-related information.

[0097] Examples of a calculation method for calculating the degree of deviation for each type of operation-related information from the production efficiency feature for each element of the operation-related information include a method of calculating values ​​such as the difference between production efficiency feature values, the percentage of the difference between production efficiency feature values, the difference from a representative value representing the production efficiency feature values, and the percentage of the difference from a representative value representing the production efficiency feature values, for the elements of the target type of operation-related information. Examples of the representative value include the average value, median, and various percentiles as simple statistics. Alternatively, a representative value representing the production efficiency feature values ​​may be obtained and further aggregated by statistics to obtain the difference. Alternatively, the production efficiency feature values ​​of multiple elements of operation-related information may be relatively ranked, and the difference in the rankings may be obtained as the degree of deviation.

[0098] Also, the production efficiency feature may be further aggregated for each element, the above statistics may be calculated for each element, and a similar comparison may be performed to calculate the deviation. As an example, if there are six elements "worker" from worker A to worker F, the production efficiency feature for each worker is obtained, and the difference is calculated for all combinations (6C2) = 15 pairs. The difference itself may be the deviation, or the differences may be ranked relatively and the difference in rank may be used as the deviation.

[0099] Regardless of which calculation method is used, the value obtained by evaluating the difference between elements of a plurality of production efficiency feature amounts based on the magnitude relationship between the plurality of production efficiency feature amounts is the deviation degree for each type of operation-related information in embodiment 1.

[0100] There are production efficiency feature amounts that affect the decline in production efficiency of the production equipment 6 when they are large compared to the production efficiency feature amounts of other elements in the same operation-related information, and conversely, there are production efficiency feature amounts that affect the decline in production efficiency of the production equipment 6 when they are small compared to the production efficiency feature amounts of other elements in the same operation-related information. For example, a smaller value of the production efficiency feature amount for the operation rate has a greater impact on the decline in production efficiency of the production equipment 6. Conversely, a larger value of the production efficiency feature amount for the failure rate has a greater impact on the decline in production efficiency of the production equipment 6. Such a relationship between the size of the production efficiency feature amount and the decline in production efficiency of the production equipment 6 is self-evident in many cases.

[0101] Similarly, regarding the method of aggregating the production efficiency feature quantities, the magnitude of the aggregated value is related to the decline in production efficiency of the production equipment 6. For example, the relationship between the average value of the production efficiency feature quantities, the maximum value of the production efficiency feature quantities, and the minimum value of the production efficiency feature quantities and the decline in production efficiency of the production equipment 6 is basically the same as that of the original production efficiency information before aggregation. On the other hand, regarding the standard deviation of the production efficiency feature quantities, a larger value has a stronger effect on the decline in production efficiency of the production equipment 6 than a smaller value.

[0102] Therefore, in the operation analysis system 1, information regarding the relationship between each value of the production efficiency information and the method of aggregating the production efficiency information and the decline in production efficiency of the production equipment 6 is pre-stored in the production efficiency feature calculation unit 233 as attribute information.

[0103] The attribute information is information regarding the relationship between each value of the production efficiency information and each of the methods for aggregating the production efficiency information, and the decline in production efficiency of the production equipment 6. An example of the attribute information is information such as "When the production efficiency feature value of the failure rate is large compared to the production efficiency feature values ​​of other elements in the failure rate, it affects the decline in productivity" and "When the production efficiency feature value of the operation rate is small compared to the production efficiency feature values ​​of other elements in the operation rate, it affects the decline in productivity."

[0104] As mentioned above, these attribute information are basically self-evident knowledge and fixed, and do not require trial and error at the time of design or maintenance during operation, unlike the scenarios and tables used in the technology of Patent Document 1.

[0105] In addition, when calculating the deviation, the direction of the deviation is also taken into consideration. For example, if the deviation is in the direction of a decline in the production efficiency of the production equipment 6, the deviation is calculated as a positive value. If the deviation is in the opposite direction to the direction of the decline in production efficiency, the deviation is calculated as a negative value. The positive or negative value of the deviation value corresponds to whether the evaluation of the deviation in the evaluation of the decline in the production efficiency of the production equipment 6 is meaningful or not. A positive deviation value is a deviation value that is meaningful in the evaluation of the decline in the production efficiency of the production equipment 6. A negative deviation value is a deviation value that is meaningless in the evaluation of the decline in the production efficiency of the production equipment 6.

[0106] Considering workers as operation-related information, if all workers can perform uniformly at a high level, the production efficiency of the production facility 6 is considered to be good, and the deviation of workers is small. For example, if there is only one novice worker among multiple skilled workers, the deviation is calculated as a positive value. In this case, only the novice worker will perform poorly, so the evaluation of the deviation in the evaluation of the production efficiency of the production facility 6 is meaningful from the perspective of reduced productivity.

[0107] Conversely, if there is only one skilled worker among multiple novice workers, the deviation is calculated as a negative value. In this case, since only the skilled worker demonstrates high work performance, the deviation evaluation in the evaluation of the production efficiency of the production facility 6 is considered to be meaningless from the viewpoint of productivity decline. For this reason, the deviation is calculated as a negative value.

[0108] FIG. 6 is a first diagram showing an example of the concept of a method in which the factor candidate extraction unit of the operation analysis system according to the first embodiment calculates the degree of deviation for each type of operation-related information. FIG. 7 is a second diagram showing an example of the concept of a method in which the factor candidate extraction unit of the operation analysis system according to the first embodiment calculates the degree of deviation for each type of operation-related information. The horizontal axis of the graphs shown in FIG. 6 and FIG. 7 represents the elements of the operation-related information. Workers The vertical axis of the graphs in Fig. 6 and Fig. 7 shows the name of each worker. To members 6 and 7 show production efficiency feature values ​​for each type of operation-related information. The production efficiency feature value is, for example, a normalized average value of the operation rate, which is production efficiency information. In the graphs shown in Figs. 6 and 7, the value of the production efficiency feature value for worker D on the vertical axis is "1", and the bottom of the vertical axis is normalized to "0". Then, the deviation degree for each type of operation-related information is calculated based on the graphs shown in Figs. 6 and 7.

[0109] In the graph shown in Fig. 6, there is little deviation when comparing the production efficiency feature values ​​between workers. In other words, when worker B, who has the smallest production efficiency feature value, is used as the reference, there is little deviation between the production efficiency feature value of worker D, who has the largest production efficiency feature value, and that of worker B. The graph shown in Fig. 6 corresponds to a case where the cause of the decrease in the operating rate, which is production efficiency information, is not the work performance of each worker, but is due to a cause other than the worker.

[0110] In the graph shown in FIG. 7, the deviation of the production efficiency feature values ​​for specific workers B and D is large when workers C and F, whose production efficiency feature values ​​are the smallest, are used as a reference. The difference in the production efficiency feature values ​​between workers C and F, whose difference in the production efficiency feature values ​​between workers is the largest, is set as the deviation degree when the operation-related information is a worker. That is, the factor candidate extraction unit 234 calculates the difference in the production efficiency feature values ​​between workers, which is the difference in the production efficiency feature values ​​between elements, calculates the maximum value of the difference in the production efficiency feature values ​​between the elements, and sets the maximum value of the difference in the production efficiency feature values ​​between the elements as the deviation degree. Such a graph shown in FIG. 7 corresponds to a case where the cause of the decrease in production efficiency is specific workers B and D.

[0111] It should be noted that the graphs shown in Figures 6 and 7 are shown for explaining the concept of the method of calculating the deviation, and the factor candidate extraction unit 234 may calculate the deviation without creating graphs such as those shown in Figures 6 and 7. The factor candidate extraction unit 234 can also transmit a graph comparing the production efficiency feature amount for each element of the operation-related information as shown in Figures 6 and 7 to the terminal device 3 and present it to the user together with information on the candidate factors of the production efficiency decline.

[0112] The factor candidate extraction unit 234 calculates the difference in production efficiency feature values ​​between workers, which is the difference in production efficiency feature values ​​between elements, for operation-related information other than workers in all combinations of operation-related information and production efficiency information of the target area, and calculates the maximum value of the differences in production efficiency feature values ​​between elements, thereby similarly calculating the deviation of the production efficiency feature values ​​for each type of operation-related information.Then, the process proceeds to step S170.

[0113] In step S170, production efficiency reduction factor candidates are extracted. The factor candidate extraction unit 234 extracts a predetermined number of types of operation-related information as production efficiency reduction factor candidates from all combinations of operation-related information and production efficiency information of the target area, that is, from a plurality of pieces of operation-related information for which the deviation degrees have been calculated, in order of decreasing deviation degrees. The factor candidate extraction unit 234 stores information on the production efficiency reduction factor candidates for each of the extracted types of operation-related information in the server storage unit 22. In addition, the factor candidate extraction unit 234 transmits the information on the production efficiency reduction factor candidates to the terminal device 3 via the server communication unit 21. The terminal device 3 receives the information on the production efficiency reduction factor candidates transmitted from the factor candidate extraction unit 234. Thereafter, the process proceeds to step S180.

[0114] In step S180, information on the candidate factors of production efficiency reduction is displayed. When the terminal control unit 35 of the terminal device 3 receives the information on the candidate factors of production efficiency reduction transmitted from the candidate factor extraction unit 234, the terminal control unit 35 displays the information on the candidate factors of production efficiency reduction on the display unit 32, thereby presenting the candidate factors of production efficiency reduction to the user.

[0115] FIG. 8 is a diagram showing an example of information on the candidate factors for production efficiency reduction displayed on the display unit of the terminal device in the operation analysis system according to the first embodiment. In the information on the candidate factors for production efficiency reduction, information on the candidate factors for production efficiency reduction is displayed in descending order of the degree of deviation. In the information on the candidate factors for production efficiency reduction, "information on the ranking of the degree of deviation," "information on the type of operation-related information," "information on the degree of deviation," and "information on the name of the element in which the deviation of the production efficiency feature value from other elements among the multiple elements in the operation-related information is conspicuously prominent" are displayed. In the example of the information on the candidate factors for production efficiency reduction shown in FIG. 8, as the information on the candidate factor for production efficiency reduction with the largest degree of deviation, "1" is displayed as "information on the ranking of the degree of deviation," "worker" as "information on the type of operation-related information," "0.9" as "information on the degree of deviation," and "worker B and worker D" are displayed as "information on the name of the element in which the deviation of the production efficiency feature value from other elements among the multiple elements in the operation-related information is conspicuously prominent." In FIG. 8, the name of the element in which the deviation of the production efficiency feature amount from other elements among the multiple elements in the operation-related information is significantly prominent is abbreviated as the "significantly prominent element."

[0116] When the user checks the production efficiency reduction factor candidates displayed on the display unit 32 in step S180, the user may think that factors contributing to improving the production efficiency of the production facility 6 are not included in the production efficiency reduction factor candidates. In this case, the user inputs change instruction information for the production efficiency reduction factor candidates, which instructs changing the production efficiency reduction factor candidates, to the terminal device 3 using the input unit 31 of the terminal device 3. The terminal control unit 35 transmits the input change instruction information for the production efficiency reduction factor candidates to the factor candidate extraction unit 234.

[0117] When the factor candidate extraction unit 234 receives change instruction information for the production efficiency reduction factor candidates, it presents to the user production efficiency reduction factor candidates different from the production efficiency reduction factor candidates previously transmitted to the terminal control unit 35 of the terminal device 3. The factor candidate extraction unit 234 presents to the user production efficiency reduction factor candidates having a large degree of deviation next to the production efficiency reduction factor candidates previously transmitted to the terminal control unit 35 of the terminal device 3.

[0118] According to the operation analysis system 1 according to the above-described first embodiment, a production efficiency information map creating unit creates a production efficiency information map, which is an information map in which the production efficiency information is displayed with two or more types of operation-related information as display axes and a correspondence relationship between the production efficiency information and the operation-related information is shown, based on the production efficiency information, which is information related to the production of products in the production facility and serves as an index for evaluating the production efficiency of the products in the production facility, and the operation-related information, which is information related to the production of products in the production facility and serves as a candidate for a cause of a decrease in the production efficiency of the products in the production facility; and a focus area designation information creating unit creates a production efficiency information map, which is an information map in which the production efficiency information is displayed with two or more types of operation-related information as display axes and a correspondence relationship between the production efficiency information and the operation-related information is shown; an operation analysis system including: a region of interest acquisition unit that acquires information related to production efficiency information of the region of interest; a production efficiency feature calculation unit that extracts individual information related to the production efficiency information of the region of interest from a plurality of pieces of operation-related information as elements and calculates an aggregate value of the production efficiency information for each element as a production efficiency feature for all combinations of the operation-related information and the production efficiency information; and a factor candidate extraction unit that calculates a deviation, which is an index for evaluating the difference in production efficiency feature between the elements, for each type of operation-related information for all combinations of the operation-related information and the production efficiency information and extracts types of operation-related information in descending order of deviation from all combinations of the operation-related information and the production efficiency information of the region of interest.

[0119] As described above, the operation analysis system 1 according to the first embodiment automatically analyzes and estimates the cause of the decline in production efficiency of the production facility 6 based on the bias in the production efficiency feature amount for the elements of the operation-related information related to the production efficiency information of the target area. As a result, the operation analysis system 1 can present to the user appropriate candidates for the cause of the decline in production efficiency of the production facility 6 that are analyzed based on the production efficiency information and the operation-related information, without using prior information such as the scenario and cause / measure data as shown in Patent Document 1.

[0120] That is, the operation analysis system 1 can automatically analyze the causes of decline in the production efficiency of products at the production facility 6 by combining statistical processing that combines production efficiency information, such as the operation rate that serves as a production efficiency index for the production facility 6, which is equipment for producing products, with operation-related information, such as people, objects, and information involved in the production of products at the production facility 6, and interactive information input by the user. This allows the operation analysis system 1 to automatically identify various waste or loss factors that cause decline in the production efficiency of products at the production facility 6 and present them to the user, without using prior knowledge of the causes of the decline in the production efficiency of the production facility 6.

[0121] Furthermore, since the operation analysis system 1 estimates factors of decline in productivity of products in the production facility 6 based on the bias of the production efficiency feature amount for each element of the operation-related information, it can estimate factors of various wastes or losses that are factors of decline in production efficiency of products in the production facility 6, even if the user does not prepare in advance information such as the scenario and cause / measure data as shown in Patent Document 1. This allows the operation analysis system 1 to reduce the user's efforts in implementation.

[0122] Furthermore, in the operation of the production facility 6, new factors that reduce production efficiency may arise due to changes in the operation of the production facility 6 or the production facility 6 due to improvements in the production facility 6 and the work methods for producing products at the production facility 6, and changes in the products produced. Maintaining advance information such as the scenarios and cause / measure data as shown in Patent Document 1 in response to such changes in the environment in the operation of the production facility 6 also leads to an increase in the effort required to operate the system.

[0123] On the other hand, since the operation analysis system 1 does not use prior information such as scenarios and cause / measure data as shown in Patent Document 1, there is no increase in operational effort due to changes in the operating environment of the production facility 6.

[0124] Furthermore, the operation analysis system 1 includes a terminal device 3 as an interactive interface with the operation analysis system 1, and is able to incorporate the knowledge and judgment of the user into the estimation of the causes of the decline in production efficiency of products in the production facility 6. This allows the operation analysis system 1 to reflect the knowledge based on the user's experience as tacit knowledge in the estimation of the causes of the decline in production efficiency of products in the production facility 6, improving the accuracy of the estimation of the causes of the decline in production efficiency of products in the production facility 6.

[0125] Therefore, according to the operation analysis system 1 according to the first embodiment, it is possible to obtain an operation analysis system that places a small burden on the user during installation and is capable of analyzing the cause of a decrease in the production efficiency of the production facility 6.

[0126] Embodiment 2 In the second embodiment, other functions of the operation analysis system 1 according to the first embodiment will be described. In the second embodiment, the operation analysis system 1 performs a multi-axis evaluation in which a process of calculating a production efficiency feature amount is performed for a combination of two or more counting methods to calculate a deviation degree. In the second embodiment, the production efficiency feature amount calculation unit 233 calculates, as a production efficiency feature amount, a counted value of production efficiency information for each element of operation-related information for a combination of two or more counting methods. Also, in the second embodiment, the factor candidate extraction unit 234 calculates a deviation degree for each type of operation-related information for each combination of counting methods.

[0127] Hereinafter, details of the processing of the operation analysis system 1 in the second embodiment will be described with reference to a flowchart. Fig. 9 is a flowchart showing an example of the processing of the operation analysis system according to the second embodiment.

[0128] First, steps S110 to S130 are performed. Then, the process proceeds to step S210. In the second embodiment, the production efficiency feature amount is calculated in steps S130, S210, and S220.

[0129] In step S210, the production efficiency information of the target area is tallied for each element of the operation-related information for a combination of two or more counting methods. The production efficiency feature amount calculation unit 233 tallies the production efficiency information of the target area for each element of the operation-related information for all combinations of the elements of the operation-related information extracted in step S130 and the production efficiency information of the target area. Then, proceed to step S220.

[0130] Specifically, when the production efficiency feature amount calculation unit 233 acquires the region of interest designation information from the region of interest acquisition unit 232, it extracts one or more elements of operation-related information related to the production efficiency information of the region of interest designated in the region of interest designation information. That is, the production efficiency feature amount calculation unit 233 acquires the operation-related information related to the production efficiency information of the region of interest from the analysis data storage unit 221.

[0131] Next, the production efficiency feature calculation unit 233 acquires production efficiency information of the area of ​​interest from the analysis data storage unit 221, and aggregates the production efficiency information of the area of ​​interest for each element of the operation-related information for all combinations of the elements of the operation-related information extracted in step S130 and the production efficiency information of the area of ​​interest.

[0132] Here, the production efficiency feature amount calculation unit 233 creates two or more combinations of the methods for aggregating the production efficiency information of the region of interest. An example of a combination of the methods for aggregating the production efficiency information of the region of interest is a combination of "variance of production efficiency information" and "average value of production efficiency information." Hereinafter, the "combination of methods for aggregating the production efficiency information of the region of interest" may be simply referred to as a "combination of aggregating methods."

[0133] If all combinations of the counting methods were to be created, the number of combinations of the counting methods would be enormous. For this reason, it is realistic to create a maximum of three combinations of the counting methods in the production efficiency feature calculation unit 233. For combinations where it is obvious that there is little meaning in combining them, such as "standard deviation" and "variance," which can be calculated mutually, the creation of combinations may be omitted.

[0134] Next, the production efficiency feature quantity calculation unit 233 creates all combinations of the created "combination of counting methods" and "one type of operation related information" for all operation related information acquired from the analysis data storage unit 221. Examples of combinations of the "combination of counting methods" and "one type of operation related information" include combinations of "variance of production efficiency information" and "average value of production efficiency information" with "worker."

[0135] Then, the production efficiency feature amount calculation unit 233 calculates an aggregate value of the production efficiency information of the region of interest for each element of the operation-related information by a combination of two or more aggregation methods for all combinations of the elements of the operation-related information extracted in step S130 and the production efficiency information of the region of interest. That is, the production efficiency feature amount calculation unit 233 calculates two or more different types of aggregate values ​​as the aggregate value of the production efficiency information of the region of interest for each element of the operation-related information by calculating the aggregate value of the production efficiency information of the region of interest for each element of the operation-related information by each of the two or more aggregation methods.

[0136] In step S220, the aggregated values ​​are normalized. The production efficiency feature amount calculation unit 233 normalizes the aggregated value of the production efficiency information of the region of interest for each element of the aggregated operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the region of interest. Here, the production efficiency feature amount calculation unit 233 normalizes two or more different types of aggregated values ​​calculated in step S210 for each combination of the elements of the operation-related information and the production efficiency information of the region of interest.

[0137] Then, the production efficiency feature calculation unit 233 acquires the normalized aggregated value as the production efficiency feature. Through the above processing, the production efficiency feature calculation unit 233 calculates the production efficiency feature for each element of the operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the region of interest. In other words, the production efficiency feature calculation unit 233 calculates two or more different types of production efficiency feature for each combination of the elements of the operation-related information and the production efficiency information of the region of interest. Then, proceed to step S230.

[0138] In step S230, the deviation of the production efficiency feature is calculated for each type of operation-related information. The factor candidate extraction unit 234 calculates the deviation for each type of operation-related information for all combinations of operation-related information and production efficiency information of the target area based on the production efficiency feature calculated by the production efficiency feature calculation unit 233. More specifically, the factor candidate extraction unit 234 calculates the deviation for each combination of aggregation methods based on the production efficiency feature calculated by the production efficiency feature calculation unit 233 for all combinations of operation-related information and production efficiency information of the target area. In other words, the production efficiency feature calculation unit 233 calculates the deviation for combinations of two or more aggregation methods by using the aggregated value of the production efficiency information for each element as the production efficiency feature. Thereafter, steps S170 and Steps Go to S180.

[0139] FIG. 10 is a diagram showing an example of the concept of a method in which the factor candidate extraction unit of the operation analysis system calculates the deviation degree in the second embodiment. FIG. 10 shows a result of aggregating the production efficiency feature of the production efficiency information of the region of interest for each worker, which is an element of the operation-related information, in a case where the combination of the "combination of aggregation methods" and the "one type of operation-related information" is a combination of the "variance of production efficiency information" and the "average value of production efficiency information" and the "worker". The vertical axis of the graph shown in FIG. 10 indicates the "variance of production efficiency information", which is the production efficiency feature of the production efficiency information of the region of interest. The horizontal axis of the graph shown in FIG. 10 indicates the "average value of production efficiency information", which is the production efficiency feature of the production efficiency information of the region of interest. The black circles shown in FIG. 10 indicate workers, which are elements of the operation-related information.

[0140] In Fig. 10, the vertical axis value at a position moved vertically from the black circle of a worker along the vertical axis is the value of "variance of production efficiency information." In Fig. 10, the horizontal axis value at a position moved vertically from the black circle of a worker along the horizontal axis is the value of "average production efficiency information." And in Fig. 10, the maximum value of the degree of deviation from the nearest black circle among the distances between the black circles of workers is the deviation degree.

[0141] 10, workers A, C, E, and F are located near each other. On the other hand, workers B and D are farther away from workers A, C, E, and F who are located near each other. Furthermore, worker B is farther away from workers A, C, E, and F who are located near each other than worker D. The cause candidate extraction unit 234 determines the degree of separation between worker B and worker E, which is the maximum value of the degree of separation from the nearest worker among the distances between workers, as the degree of separation.

[0142] An example of a method for calculating the deviation degree in the embodiment 2 will be described. In the embodiment 2, similarly to the embodiment 1, the deviation degree may be a value that can highlight and evaluate the difference between the production efficiency feature amounts of the same type of operation-related information among the elements of the operation-related information.

[0143] As shown in Fig. 10, when the elements of the operation-related information and the production efficiency feature values ​​of the elements of the operation-related information are mapped on a plane, the factor candidate extraction unit 234 can calculate the maximum value of the distance between the nearest point among the distances between the points corresponding to the elements of the operation-related information mapped on a plane as the deviation degree. In other words, when the elements of the operation-related information and the production efficiency feature values ​​of the elements of the operation-related information are mapped on a plane, the deviation degree of a certain type of operation-related information is calculated as, for example, the maximum value of the distance between the nearest point among the distances between the elements of the operation-related information. In Fig. 10, the factor candidate extraction unit 234 can calculate the distance between the black circle of worker B and the black circle of worker E, which is the maximum value of the distance between the nearest point among the distances between the black circles that are points corresponding to the elements of the operation-related information mapped on a plane.

[0144] Representative methods used to calculate the distance between points corresponding to elements of operation-related information mapped onto a plane include statistics such as Euclidean distance, Manhattan distance, and Mahalanobis distance.

[0145] In addition, the distance between points corresponding to elements of operation-related information mapped onto a plane may be defined as a convex hull problem on a plane that searches for the outer frame of the point with the greatest distance, and the deviation may be calculated using an algorithm such as Graham Scan.

[0146] The factor candidate extraction unit 234 may calculate, as the deviation, the maximum value of the average value of the distances between the black circles, which are points corresponding to the elements of the operation-related information mapped onto a plane, and the k-nearest points in the k-nearest neighbor method, instead of the maximum value of the distances between the black circles, which are points corresponding to the elements of the operation-related information mapped onto a plane, and the k-nearest points. The k-nearest points are the top k points in order of the distance between the black circles, which are points corresponding to the elements of the operation-related information mapped onto a plane, in order of the distance. In other words, the factor candidate extraction unit 234 may calculate, as the deviation, the maximum value of the average value of the distances between the black circles, which are points corresponding to the elements of the operation-related information mapped onto a plane, and the top k points in order of the distance.

[0147] Alternatively, a representative value of the production efficiency feature may be calculated, and the maximum value of the difference from the representative value may be used as the deviation. When calculating the representative value, points on a plane may be categorized using a clustering algorithm such as the k-means method, and the distance from the center point may be calculated.

[0148] In either case, in the multi-axis evaluation, the deviation in the second embodiment is a value that can evaluate the magnitude of the production efficiency feature amount of each element of the operation-related information as well as the neighborhood relationship.

[0149] Note that information equivalent to that shown in FIG. 10 can be sent to the terminal device 3 together with information on potential causes of decline in production efficiency and presented to the user, but it need only be temporarily stored inside the server 2 of the operation analysis system 1 and does not necessarily need to be presented to the user.

[0150] As described above, in the second embodiment, the operation analysis system 1 automatically analyzes and estimates the cause of the decline in production efficiency of the production facility 6 based on the bias of the production efficiency feature amount for the element of the operation-related information related to the production efficiency information of the target area, similar to the first embodiment. As a result, in the second embodiment, the operation analysis system 1 can present to the user appropriate candidates for the cause of the decline in production efficiency of the production facility 6, analyzed based on the production efficiency information and the operation-related information, without using prior information such as the scenario and cause / measure data as shown in Patent Document 1, similar to the first embodiment. As a result, the operation analysis system 1 can reduce the effort of introducing the system and the effort of operating the system.

[0151] Embodiment 3 In the third embodiment, other functions of the operation analysis system 1 according to the first embodiment will be described. In the third embodiment, the operation analysis system 1 receives two pieces of focus area designation information and extracts candidates for factors causing a decrease in production efficiency. That is, the operation analysis system 1 acquires, from the terminal device 3, two pieces of focus area designation information for two locations designated by a user in a production efficiency information map displayed by production efficiency information map data. Then, the operation analysis system 1 calculates a production efficiency feature amount for each of the two focus areas designated by the two pieces of focus area designation information in the same procedure as in the first embodiment.

[0152] That is, in the third embodiment, the region of interest acquisition unit 232 acquires two pieces of region of interest designation information. In the third embodiment, the production efficiency feature calculation unit 233 calculates an aggregate value as a production efficiency feature for the two regions of interest designated in the region of interest designation information. Then, in the third embodiment, the factor candidate extraction unit 234 calculates the similarity of the production efficiency feature for the two regions of interest designated in the region of interest designation information.

[0153] In embodiment 3, the operation analysis system 1 accepts two focus area designation information, namely, a first focus area in the production efficiency information map where production efficiency is not relatively declining, and a second focus area in the production efficiency information map where production efficiency is relatively declining, and extracts candidate factors of decline in production efficiency.

[0154] In the third embodiment, two regions of interest, a first region of interest and a second region of interest, are specified in order to extract candidate factors of production efficiency decline for the second region of interest where production efficiency is relatively decreased in the production efficiency information map. That is, in the third embodiment, in order to extract candidate factors of production efficiency decline for the second region of interest where production efficiency is relatively decreased in the production efficiency information map, the first region of interest, which is an exemplary region in terms of production efficiency with relatively good production efficiency, is also specified as a region of interest for comparison with the second region of interest.

[0155] Therefore, in the third embodiment, the second region of interest in the production efficiency information map where production efficiency is relatively decreased can be said to be a region of interest from which candidate factors of decreased production efficiency are extracted. Also, in the third embodiment, the second region of interest in the production efficiency information map where production efficiency is relatively decreased is a region of interest in which the user wants to identify the factors of decreased production efficiency. Also, in the third embodiment, the second region of interest in the production efficiency information map where production efficiency is relatively decreased can be said to be a region of interest in the production efficiency information map where the value of production efficiency information is relatively low.

[0156] In addition, the first region of interest in the production efficiency information map where production efficiency is not relatively declining can be considered as a region of interest to be compared in extracting candidate factors of production efficiency decline in the second region of interest. In addition, the first region of interest in the production efficiency information map where production efficiency is not relatively declining can be considered as a region of interest in the production efficiency information map where the value of production efficiency information is relatively high.

[0157] When two areas of interest, a first area of ​​interest and a second area of ​​interest, are specified, i.e., when two areas of interest designation information are received, the operation analysis system 1 extracts candidate factors of production efficiency reduction in the second area of ​​interest by comparing the production efficiency characteristics of the first area of ​​interest with the production efficiency characteristics of the second area of ​​interest.

[0158] Specifically, when two areas of interest are specified in the production efficiency information map, a first area of ​​interest where production efficiency is not relatively decreased and a second area of ​​interest where production efficiency is relatively decreased in the production efficiency information map, the operation analysis system 1 extracts candidates for factors causing a decrease in production efficiency in the second area of ​​interest by comparing the production efficiency feature amount of the first area of ​​interest with the production efficiency feature amount of the second area of ​​interest with reference to the production efficiency feature amount of the first area of ​​interest for each type of operation-related information. That is, when the operation analysis system 1 receives two pieces of information specifying the area of ​​interest from which candidates for factors causing a decrease in production efficiency are extracted and the area of ​​interest of the comparison object, which is an exemplary area, the operation analysis system 1 extracts candidates for factors causing a decrease in production efficiency in the second area of ​​interest by comparing the production efficiency feature amount of the area of ​​interest from which candidates for factors causing a decrease in production efficiency are extracted with the production efficiency feature amount of the area of ​​interest of the comparison object, which is an exemplary area, with reference to the area of ​​interest of the comparison object, which is an exemplary area, for each type of operation-related information.

[0159] Hereinafter, details of the processing of the operation analysis system 1 in the third embodiment will be described with reference to a flowchart. Fig. 11 is a flowchart showing an example of the processing of the operation analysis system in the third embodiment.

[0160] First, step S110 is performed, and then the process proceeds to step S310. In the third embodiment, the production efficiency feature amount is calculated in steps S320 to S340.

[0161] In step S310, two pieces of attention area designation information are acquired. Specifically, the attention area acquisition unit 232 of the server processing unit 23 of the server 2 acquires the two pieces of attention area designation information from the terminal device 3 via the server communication unit 21. The two pieces of attention area designation information are pieces of attention area designation information for two locations designated by the user in the production efficiency information map displayed on the display unit 32 of the terminal device 3 by the production efficiency information map data. The attention area acquisition unit 232 transmits the two pieces of acquired attention area designation information to the production efficiency feature amount calculation unit 233 of the server processing unit 23 of the server 2. The production efficiency feature amount calculation unit 233 receives the two pieces of attention area designation information transmitted from the attention area acquisition unit 232. Then, the process proceeds to step S320.

[0162] Fig. 12 is a diagram showing an example of two areas of interest specified in the production efficiency information map shown in Fig. 3. In Fig. 12, area A and area B are specified as areas of interest.

[0163] Here, area A is an example of an area of ​​interest in which production efficiency is not relatively decreased in the production efficiency information map 40 shown in FIG. 3, and is the first area of ​​interest described above. Area B is an example of an area of ​​interest in which production efficiency is relatively decreased in the production efficiency information map 40 shown in FIG. 3, and is the second area of ​​interest described above. In FIG. 12, two areas of interest, area A and area B, are specified in order to extract candidate factors of production efficiency decrease for area B, which is the area of ​​interest in which production efficiency is relatively decreased. That is, in FIG. 12, area A, which is an exemplary area in terms of production efficiency, is also specified as an area of ​​interest for comparison in order to extract candidate factors of production efficiency decrease for area B.

[0164] In step S320, an element of operation-related information is extracted for each of the two areas of interest specified in the two pieces of area-of-interest designation information. When the production efficiency feature amount calculation unit 233 acquires the two pieces of area-of-interest designation information, it acquires a plurality of pieces of operation-related information related to the production efficiency information of the areas of interest specified in each of the two pieces of area-of-interest designation information from the analysis data storage unit 221. Then, the production efficiency feature amount calculation unit 233 extracts one or more elements of the operation-related information from each of the acquired pieces of operation-related information for each of the two areas of interest. Then, the process proceeds to step S330.

[0165] In step S330, for each of the two regions of interest specified in the two regions of interest designation information, production efficiency information of the regions of interest is tallied for each element of the operation-related information. The production efficiency feature amount calculation unit 233 tallies up the production efficiency information of the regions of interest for each element of the operation-related information for all combinations of the elements of the operation-related information extracted in step S320 and the production efficiency information of the regions of interest for each of the two regions of interest. Then, the process proceeds to step S340.

[0166] In step S340, the aggregated values ​​are normalized for each of the two regions of interest specified in the two regions of interest designation information. The production efficiency feature amount calculation unit 233 normalizes the aggregated value of the production efficiency information of the region of interest for each element of the aggregated operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the region of interest for each of the two regions of interest.

[0167] Then, the production efficiency feature calculation unit 233 acquires the normalized aggregate value as the production efficiency feature for each of the two regions of interest. Through the above processing, the production efficiency feature calculation unit 233 calculates the production efficiency feature for each element of the operation-related information for all combinations of the elements of the operation-related information and the production efficiency information of the regions of interest for each of the two regions of interest specified in the two regions of interest designation information. Then, the process proceeds to step S350.

[0168] In step S350, the similarity of the production efficiency feature amount between the two regions of interest is calculated for each type of operation-related information. The factor candidate extraction unit 234 calculates the similarity by comparing the production efficiency feature amount of the same operation-related information for each element of the operation-related information of the two regions of interest. That is, the factor candidate extraction unit 234 calculates the similarity by comparing the production efficiency feature amount of the operation-related information for one of the two regions of interest with the production efficiency feature amount of the operation-related information for the other of the two regions of interest for all the operation-related information extracted in step S320. Specifically, the factor candidate extraction unit 234 compares the production efficiency feature amount of the operation-related information for the comparison region of interest, which is an exemplary region, with the production efficiency feature amount of the operation-related information for the region of interest that is the extraction target of the production efficiency reduction factor candidate, and calculates the similarity for each type of operation-related information. The production efficiency feature amount of the operation-related information compared here is the production efficiency feature amount of the same type of operation-related information. Then, proceed to step S360.

[0169] In step S360, production efficiency reduction factor candidates are extracted. The factor candidate extraction unit 234 extracts a predetermined number of types of operation-related information as production efficiency reduction factor candidates from all combinations of operation-related information and production efficiency information of the target area, i.e., from a plurality of pieces of operation-related information whose similarities have been calculated, in order of decreasing similarity. The factor candidate extraction unit 234 stores information on the production efficiency reduction factor candidates for each of the extracted types of operation-related information in the server storage unit 22. In addition, the factor candidate extraction unit 234 transmits the information on the production efficiency reduction factor candidates to the terminal device 3 via the server communication unit 21. The terminal device 3 receives the information on the production efficiency reduction factor candidates transmitted from the factor candidate extraction unit 234. Thereafter, the process proceeds to step S180.

[0170] An example of a method for calculating similarity in the third embodiment will be described. In the third embodiment, the production efficiency feature amounts for the same operation-related information in two regions of interest are compared to calculate the similarity. That is, in the third embodiment, the production efficiency feature amounts for the same operation-related information are compared between two regions of interest to calculate the similarity. In the third embodiment, the production efficiency feature amounts for the same operation-related information are compared between the two regions of interest to find the similarity for each similarity analysis element between the two regions of interest.

[0171] The similarity analysis element is a target of the similarity analysis, and is a production efficiency feature amount corresponding to an element of the operation-related information.

[0172] As an example of calculating the similarity, the Euclidean distance, the Pearson correlation coefficient, the cosine similarity, etc., as in the second embodiment, are exemplified.

[0173] FIG. 13 is a diagram showing the production efficiency feature amount for the region A shown in FIG. 12 when the operation-related information is a worker. FIG. 14 is a diagram showing the production efficiency feature amount for the region B shown in FIG. 12 when the operation-related information is a worker. The horizontal axis of the graphs shown in FIG. 13 and FIG. 14 is the element of the operation-related information. Workers The vertical axis of the graphs in Fig. 13 and Fig. 14 shows the number of workers. To members 13 and 14 show production efficiency feature values ​​for worker D. The production efficiency feature value is, for example, an average value of operation rates. The production efficiency feature value is, for example, a normalized average value of operation rates, which is the production efficiency information. In the graphs shown in FIGS. 13 and 14, the value of the production efficiency feature value for worker D on the vertical axis is "1", and the bottom of the vertical axis is normalized to "0". Then, based on the graphs shown in FIGS. 13 and 14, the similarity when the operation-related information is a worker is calculated.

[0174] When comparing the production efficiency feature amounts of area A and area B, the factor candidate extraction unit 234 compares the production efficiency feature amount in Fig. 13 with the production efficiency feature amount in Fig. 14. The similarity in this case indicates how much the trends of the production efficiency feature amount in Fig. 13 and the production efficiency feature amount in Fig. 14 differ.

[0175] The factor candidate extraction unit 234, for example, calculates the average value of the production efficiency feature amounts of workers in area A and the average value of the production efficiency feature amounts of workers in area B, and compares the two to calculate the similarity. The factor candidate extraction unit 234 calculates the similarity for all operation-related information in all combinations of the extracted elements of operation-related information and the production efficiency information of the target area. Then, the factor candidate extraction unit 234 extracts a predetermined number of types of operation-related information in order of decreasing similarity from all combinations of the operation-related information and the production efficiency information of the target area, i.e., from the multiple pieces of operation-related information for which the similarity has been calculated, as candidates for production efficiency reduction factors.

[0176] FIG. 15 is a diagram showing the production efficiency feature amount when the operation-related information is the day of the week for the region A shown in FIG. 12. FIG. 16 is a diagram showing the production efficiency feature amount when the operation-related information is the day of the week for the region B shown in FIG. 12. The horizontal axis of the graphs shown in FIG. 15 and FIG. 16 indicates the day of the week, which is an element of the operation-related information. The vertical axis of the graphs shown in FIG. 15 and FIG. 16 indicates the production efficiency feature amount for each day of the week. The production efficiency feature amount is, for example, the average value of the operation rate. The production efficiency feature amount is, for example, the normalized average value of the operation rate, which is the production efficiency information. In the graphs shown in FIG. 15 and FIG. 16, the value of the production efficiency feature amount for Thursday on the vertical axis is "1", and the bottom of the vertical axis is normalized to "0". Then, based on the graphs shown in FIG. 15 and FIG. 16, the similarity degree when the operation-related information is the day of the week is calculated. In FIG. 15 and FIG. 16, "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", and "Saturday" are abbreviated as "Mon", "Tue", "Wed", "Thu", "Fri", and "Sat", respectively.

[0177] 15 and 16, when the operation-related information is a day of the week, the factor candidate extraction unit 234 calculates, for example, the average value of the production efficiency feature amount from Monday to Saturday in area A and the average value of the production efficiency feature amount from Monday to Saturday in area B, and compares the two to calculate the similarity. The factor candidate extraction unit 234 calculates the similarity for all the operation-related information in all combinations of the extracted elements of the operation-related information and the production efficiency information of the target area. Then, the factor candidate extraction unit 234 extracts, as candidates for production efficiency reduction factors, a predetermined number of types of operation-related information in ascending order of similarity from all combinations of the operation-related information and the production efficiency information of the target area, i.e., from the multiple pieces of operation-related information for which the similarity has been calculated.

[0178] For example, when comparing the similarity of the production efficiency feature amounts between area A and area B when the type of operation-related information is “worker” calculated based on Fig. 13 and Fig. 14 with the similarity of the production efficiency feature amounts between area A and area B when the type of operation-related information is “day of the week” calculated based on Fig. 15 and Fig. 16, the similarity of the production efficiency feature amounts when the type of operation-related information is “worker” is smaller than the similarity of the production efficiency feature amounts when the type of operation-related information is “day of the week”. In this case, the factor candidate extraction unit 234 can determine that “worker” is more likely to be a factor of the decrease in production efficiency in area B than “day of the week”.

[0179] From the extraction result of the candidate factors for the decline in production efficiency in the operation analysis system 1 in the above-mentioned first and second embodiments, it is possible to present to the user candidate factors for the decline in production efficiency of the production facility 6, such as "the productivity of a specific worker is low at a certain time on a certain day of the week". On the other hand, from the extraction result of the candidate factors for the decline in production efficiency in the operation analysis system 1 in the third embodiment, it is possible to present to the user candidate factors for the decline in production efficiency of the production facility 6, such as "the productivity of all workers is low between a plurality of days of the week and a plurality of times". In other words, by analyzing the extraction result in the operation analysis system 1 in the first to third embodiments, it is possible to present to the user a wider variety of candidate factors for the decline in production efficiency of the production facility 6.

[0180] In the above-mentioned first to third embodiments, the production efficiency feature is expressed as an analog value. On the other hand, there are cases where it is more appropriate for the production efficiency feature to be expressed as a categorical variable rather than an analog value, and the production efficiency feature can be expressed as a set relationship. In this case, the Jaccard coefficient can also be applied to calculate the similarity. For example, if the operation-related information is temperature, the production efficiency feature can be expressed as an analog value. On the other hand, examples of production efficiency feature that are better expressed as a categorical variable include categorical variables such as sunny, cloudy, rainy, and snowy.

[0181] When calculating the similarity by comparing production efficiency features for the same operation-related information, it is practical to compare two areas of interest. Even when calculating the similarity by comparing production efficiency features for the same operation-related information in three or more areas of interest, in addition to applying the similarity calculation algorithm described above, the similarity can be calculated by compressing the dimensions by principal component analysis as preprocessing and then applying the same algorithm.

[0182] As described above, in embodiment 3, when two or more areas of interest are selected as areas to be compared, the operation analysis system 1 can extract the top K elements that have a large difference between other operation-related information and the areas of interest, by comparing the production efficiency features extracted from each area of ​​interest.

[0183] Furthermore, in the third embodiment, the operation analysis system 1 extracts candidate factors for production efficiency reduction in the second region of interest by comparing the production efficiency feature value of the first region of interest, which is an exemplary region with relatively good production efficiency, with the production efficiency feature value of the second region of interest, which is a comparison region of interest, thereby improving the accuracy of extraction of candidate factors for production efficiency reduction in the second region of interest. As a result, in the third embodiment, the operation analysis system 1 can extract candidate factors for production efficiency reduction in the second region of interest more accurately than when only the second region of interest, which is the region of interest from which candidate factors for production efficiency reduction are extracted, is specified as the region of interest and candidate factors for production efficiency reduction in the second region of interest are extracted.

[0184] That is, in the third embodiment, when the focus area acquisition unit 232 acquires two pieces of focus area designation information, that is, focus area designation information designating a first focus area having a relatively high production efficiency information value in the production efficiency information map and focus area designation information designating a second focus area having a relatively low production efficiency information value in the production efficiency information map, the production efficiency feature amount calculation unit 233 calculates an aggregate value as a production efficiency feature amount for the two focus areas designated in the focus area designation information. Then, the factor candidate extraction unit 234 calculates the similarity of the production efficiency feature amount for the two focus areas designated in the focus area designation information for each type of operation-related information, and extracts the types of operation-related information in order of decreasing similarity from all combinations of the operation-related information and the production efficiency information of the focus areas.

[0185] In the third embodiment, similarly to the first embodiment, the operation analysis system 1 automatically analyzes and estimates the causes of the decline in production efficiency of the production equipment 6 based on the bias in the production efficiency feature values ​​for the elements of the operation-related information related to the production efficiency information of the target area. As a result, in the third embodiment, similarly to the first embodiment, the operation analysis system 1 can present to the user appropriate candidates for the causes of the decline in production efficiency of the production equipment 6 that are analyzed based on the production efficiency information and the operation-related information, without using prior information such as the scenario and cause / measure data as shown in Patent Document 1. As a result, the operation analysis system 1 can reduce the effort required for introducing the system and the effort required for operating the system.

[0186] Embodiment 4 In the fourth embodiment, a description will be given of other functions of the operation analysis system 1 according to the first embodiment. In the fourth embodiment, the operation analysis system 1 automatically searches for and creates a combination of one type of production efficiency information and two types of operation related information, and creates a production efficiency information map for the created combination of one type of production efficiency information and two types of operation related information.

[0187] In the first embodiment, the production efficiency information map creation unit 231 of the server processing unit 23 of the server 2 acquires one type of production efficiency information and two types of operation related information from the analysis data storage unit 221 in accordance with preset conditions, and creates a production efficiency information map based on the acquired one type of production efficiency information and two types of operation related information. That is, in the first embodiment, the production efficiency information map creation unit 231 acquires one type of production efficiency information and two types of operation related information from the analysis data storage unit 221 based on, for example, predetermined map creation conditions, and creates a production efficiency information map based on the acquired one type of production efficiency information and two types of operation related information.

[0188] In contrast to this, in the fourth embodiment, the production efficiency information map creation unit 231 automatically searches for and creates a combination of one type of production efficiency information and two types of operation-related information without using map creation conditions, and creates a production efficiency information map.

[0189] Hereinafter, details of the processing of the operation analysis system 1 in the fourth embodiment will be described with reference to a flowchart. Fig. 17 is a flowchart showing an example of the processing of the operation analysis system in the fourth embodiment.

[0190] In step S410, a production efficiency information map is created by automatically searching the production efficiency information and the operation related information. Specifically, the production efficiency information map creating unit 231 of the server processing unit 23 of the server 2 creates the production efficiency information map.

[0191] A user inputs analysis instruction information for instructing an analysis of factors behind a decline in production efficiency as an input to the input unit 31 on the operation screen of the operation analysis system 1 displayed on the display unit 32 of the terminal device 3. The production efficiency information map creation unit 231 creates a production efficiency information map based on the user's analysis instruction information input from the terminal device 3. That is, the production efficiency information map creation unit 231 acquires production efficiency information and operation-related information from the analysis data storage unit 221, and creates production efficiency information map data that is data for displaying a production efficiency information map on the terminal device 3 based on the acquired production efficiency information and operation-related information.

[0192] In the fourth embodiment, the production efficiency information map creation unit 231 automatically searches for and creates multiple combinations of one type of production efficiency information and two types of operation-related information without using map creation conditions, and creates a production efficiency information map. The production efficiency information map creation unit 231 automatically searches for and creates, for example, all combinations as multiple combinations of one type of production efficiency information and two types of operation-related information, and creates a production efficiency information map.

[0193] The production efficiency information map creation unit 231 automatically searches for a combination of one type of production efficiency information and two types of operation related information from among the multiple pieces of production efficiency information and operation related information stored in the analysis data storage unit 221, and creates multiple sets of combinations of one type of production efficiency information and two types of operation related information. Then, the production efficiency information map creation unit 231 creates a production efficiency information map for the created multiple sets of combinations. In other words, the production efficiency information map creation unit 231 creates multiple production efficiency information maps based on the created multiple sets of combinations.

[0194] Next, the production efficiency information map creating unit 231 selects one production efficiency information map having a large difference in production efficiency information and a large bias in the distribution of large and small production efficiency information from among the multiple created production efficiency information maps.

[0195] When a selection criterion is stored in advance in the production efficiency information map creation unit 231 as a criterion for selecting a production efficiency information map having a large difference in production efficiency information and a large bias in the distribution of large and small production efficiency information, the production efficiency information map creation unit 231 selects one production efficiency information map in accordance with the selection criterion. When a selection criterion is not stored in advance in the production efficiency information map creation unit 231 as a criterion for selecting a production efficiency information map having a large difference in production efficiency information and a large bias in the distribution of large and small production efficiency information, the production efficiency information map creation unit 231 selects one production efficiency information map according to a numerical value obtained by a predetermined testing method based on the statistics of the production efficiency information. Note that the production efficiency information map creation unit 231 can also select one or more production efficiency information maps.

[0196] Then, the production efficiency information map creation unit 231 transmits the selected one piece of production efficiency information map data to the terminal control unit 35 of the terminal device 3 via the server communication unit 21. The terminal control unit 35 receives the production efficiency information map data transmitted from the production efficiency information map creation unit 231 via the terminal communication unit 33. Then, the process proceeds to step S120.

[0197] After this, the processes from step S120 to step S180 are carried out based on the selected one production efficiency information map data.

[0198] Note that the user who has checked the production efficiency information map displayed on the display unit 32 selects one area of ​​interest in the production efficiency information map, as in the case of the first embodiment, and inputs area of ​​interest designation information for the area of ​​interest to the terminal device 3 using the input unit 31 of the terminal device 3. Here, if the user wants to change the production efficiency information map for selecting the area of ​​interest to another production efficiency information map, the user inputs production efficiency information map change instruction information for instructing to change the production efficiency information map for selecting the area of ​​interest to the terminal device 3 using the input unit 31 of the terminal device 3. The terminal control unit 35 transmits the input production efficiency information map change instruction information to the production efficiency information map creation unit 231.

[0199] When the production efficiency information map creation unit 231 receives change instruction information for the production efficiency information map, it presents to the user a production efficiency information map different from the production efficiency information map previously transmitted to the terminal control unit 35 of the terminal device 3. The production efficiency information map creation unit 231 selects, from the multiple created production efficiency information maps, one production efficiency information map having a large difference in production efficiency information and a large bias in the distribution of large and small production efficiency information next to the production efficiency information map previously transmitted to the terminal control unit 35 of the terminal device 3, and presents it to the user as the second production efficiency information map.

[0200] The user can select one area of ​​interest in the second production efficiency information map displayed on the display unit 32. Note that the user can select areas of interest in the third and subsequent production efficiency information maps by using the same process.

[0201] FIG. 18 is a diagram showing an example of a production efficiency information map created by the operation analysis system in the fourth embodiment. FIG. 19 is a diagram showing another example of a production efficiency information map created by the operation analysis system in the fourth embodiment. In the production efficiency information map 51 shown in FIG. 18, information on "operation rate" which is production efficiency information is displayed in association with information on two types of operation-related information, "operation time" and "day of the week", and a correspondence relationship between the operation-related information "operation time" and "day of the week" and the production efficiency information "operation rate" is shown. That is, in the production efficiency information map 51 shown in FIG. 18, the operation-related information "operation time" and "day of the week" are used as display axes, and a correspondence relationship between the operation-related information "operation time" and "day of the week" and the production efficiency information "operation rate" is shown.

[0202] In the production efficiency information map 52 shown in Fig. 19, information on "operating rate", which is production efficiency information, is displayed in association with information on two types of operation-related information, "operating time" and "date", and the correspondence relationship between the operation-related information "operating time" and "date" and the production efficiency information "operating rate" is shown. That is, in the production efficiency information map 52 shown in Fig. 19, the operation-related information "operating time" and "date" are used as the display axes, and the correspondence relationship between the operation-related information "operating time" and "date" and the production efficiency information "operating rate" is shown.

[0203] A production efficiency information map 51 shown in Fig. 18 is an example in which the difference between the sizes of the circles indicating production efficiency information is small, and the distribution of the sizes of the circles indicating production efficiency information is also small. A production efficiency information map having characteristics like the production efficiency information map 51 corresponds to a case in which the operating state of the production equipment 6 is stable, and the production efficiency of the production equipment 6 is stable. A production efficiency information map 52 shown in Fig. 19 is an example in which the difference between the sizes of the circles indicating production efficiency information is large, and the distribution of the sizes of the circles indicating production efficiency information is also large. A production efficiency information map having characteristics like the production efficiency information map 52 corresponds to a case in which the operating state of the production equipment 6 varies, and the production efficiency of the production equipment 6 is not stable.

[0204] In this case, since the production efficiency information map 51 shown in FIG. 18 has a small difference between the sizes of the circles indicating production efficiency information and also has a small bias in the distribution of the sizes of the circles indicating production efficiency information, the production efficiency information map creation unit 231 does not transmit the production efficiency information map 51 shown in FIG. 18 to the terminal control unit 35.

[0205] As described above, in the fourth embodiment, it is not necessary to previously set the production efficiency information and the operation related information to be acquired from the analysis data storage unit 221 in the production efficiency information map creation unit 231. As a result, the fourth embodiment can further reduce the effort required for introducing the operation analysis system 1, compared to the first to third embodiments described above.

[0206] Next, the hardware configuration of each of the control units 80 according to the first to fourth embodiments will be described. The control units 80 according to the first to fourth embodiments correspond to the server processing unit 23 and the server control unit 24 of the server 2, and the terminal control unit 35 of the terminal device 3, respectively. The functions of each of the control units 80 according to the first to fourth embodiments are realized by a processing circuit. The processing circuit may be dedicated hardware, or may be a processing device that executes a program stored in a storage device.

[0207] When the processing circuit is a dedicated hardware, the processing circuit may be a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit, a field programmable gate array, or a combination of these. Figure 20 is a diagram showing a configuration in which the functions of the control unit according to the first to fourth embodiments are realized by hardware. A logic circuit 81a that realizes the function of the control unit 80 is incorporated in the processing circuit 81.

[0208] When the processing circuit 81 is a processing device, the functions of the control unit 80 are realized by software, firmware, or a combination of software and firmware.

[0209] FIG. 21 is a diagram showing a configuration in which the functions of the control unit according to the first to fourth embodiments are realized by software. The processing circuit 81 has a processor 811 that executes a program 81b, a random access memory 812 that the processor 811 uses as a work area, and a storage device 813 that stores the program 81b. The processor 811 deploys the program 81b stored in the storage device 813 on the random access memory 812 and executes it, thereby realizing the function of the control unit 80. The software or firmware is written in a program language and stored in the storage device 813. The processor 811 can be exemplified by a central processing unit, but is not limited to this. The storage device 813 can be a semiconductor memory such as a random access memory (RAM), a read only memory (ROM), a flash memory, an erasable programmable read only memory (EPROM), or an electrically erasable programmable read only memory (EEPROM (registered trademark)). The semiconductor memory may be a non-volatile memory or a volatile memory. Further, in addition to a semiconductor memory, a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, or a DVD (Digital Versatile Disc) can be applied to the storage device 813. The processor 811 may output data such as a calculation result to the storage device 813 for storage, or may store the data in an auxiliary storage device (not shown) via the random access memory 812. By integrating the processor 811, the random access memory 812, and the storage device 813 on one chip, the functions of the control unit 80 can be realized by a microcomputer.

[0210] The processing circuit 81 realizes the functions of the control unit 80 by reading and executing the program 81b stored in the storage device 813. It can also be said that the program 81b causes a computer to execute procedures and methods for realizing the functions of the control unit 80.

[0211] In the processing circuit 81 for implementing the functions of the server processing unit 23 in the server 2, the programs 81b include an operation analysis server program.

[0212] In addition, the processing circuit 81 may be configured so that some of the functions of the control unit 80 are realized by dedicated hardware, and some of the functions of the control unit 80 are realized by software or firmware.

[0213] Thus, the processing circuitry 81 can realize each of the above-described functions by hardware, software, firmware, or a combination of these.

[0214] The configurations shown in the above embodiments are merely examples, and may be combined with other known technologies, or the embodiments may be combined with each other. Also, parts of the configurations may be omitted or modified without departing from the spirit of the invention. [Explanation of symbols]

[0215] 1 Operation analysis system, 2 Server, 3 Terminal device, 4 Internet, 5 Cloud environment, 6 Production equipment, 21 Server communication unit, 22 Server memory unit, 23 Server processing unit, 24 Server control unit, 31 Input unit, 32 Display unit, 33 Terminal communication unit, 34 Terminal memory unit, 35 Terminal control unit, 40, 51, 52 Production efficiency information map, 41 Focus area, 80 Control unit, 81 Processing circuit, 81a Logic circuit, 81b Program, 221 Analysis data storage unit, 231 Production efficiency information map creation unit, 232 Focus area acquisition unit, 233 Production efficiency feature calculation unit, 234 Factor candidate extraction unit, 811 Processor, 812 Random access memory, 813 Storage device.

Claims

1. a production efficiency information map creation unit that creates a production efficiency information map, which is an information map in which the production efficiency information is displayed using two or more types of operation-related information as display axes to show a correspondence relationship between the production efficiency information and the operation-related information, based on production efficiency information, which is information related to the production of the product in the production facility and serves as an index for evaluating the production efficiency of the product in the production facility, and operation-related information, which is information related to the production of the product in the production facility and serves as a candidate for a cause of a decrease in the production efficiency of the product in the production facility; an attention area acquisition unit that acquires attention area designation information that is information that designates an attention area selected in the production efficiency information map; a production efficiency feature quantity calculation unit that extracts individual pieces of information related to the production efficiency information of the region of interest as elements from the plurality of pieces of operation-related information, and calculates, for all combinations of the operation-related information and the production efficiency information, an aggregate value of the production efficiency information for each of the elements as a production efficiency feature quantity; a factor candidate extraction unit that calculates a deviation degree, which is an index for evaluating a difference in the production efficiency feature amount between the elements, for each type of the operation-related information for all combinations of the operation-related information and the production efficiency information, and extracts the types of the operation-related information in descending order of the deviation degree from among all combinations of the operation-related information and the production efficiency information of the region of interest; An operation analysis system comprising:

2. The factor candidate extraction unit extracting a predetermined number of types of the operation-related information in descending order of the degree of deviation; outputting information on candidate factors of production efficiency reduction, including, for each of the extracted types of operation-related information, information on the type of the operation-related information, information on the degree of deviation in the operation-related information, and information on the name of an element of which deviation of the production efficiency feature amount between other elements among a plurality of elements in the operation-related information satisfies a predetermined criterion; The operation analysis system according to claim 1 .

3. the production efficiency feature value calculation unit calculates, as the production efficiency feature value, a value obtained by normalizing an aggregate value of the production efficiency information; The operation analysis system according to claim 1 .

4. a terminal device that displays the production efficiency information map and receives attention area designation information that designates the attention area on the production efficiency information map; The operation analysis system according to claim 1 .

5. the production efficiency feature calculation unit calculates, for a combination of two or more counting methods, the counted value of the production efficiency information for each of the elements as the production efficiency feature; the factor candidate extraction unit calculates the degree of deviation for each type of the operation-related information for each combination of the counting methods; The operation analysis system according to claim 1 .

6. When the attention area acquisition unit acquires two pieces of attention area designation information, that is, the attention area designation information designating a first attention area in the production efficiency information map in which the value of the production efficiency information is relatively high, and the attention area designation information designating a second attention area in the production efficiency information map in which the value of the production efficiency information is relatively low, the production efficiency feature value calculation unit calculates the aggregate value as a production efficiency feature value for the two regions of interest designated in the region of interest designation information; the factor candidate extraction unit calculates a similarity between the two regions of interest specified in the region of interest designation information for each type of operation-related information, and extracts the types of operation-related information in ascending order of similarity from among all combinations of the operation-related information and the production efficiency information of the regions of interest; The operation analysis system according to claim 1 .

7. the production efficiency information map creation unit creates the production efficiency information map for a predetermined combination of the production efficiency information and the operation-related information; The operation analysis system according to claim 1 .

8. the production efficiency information map creation unit automatically searches for and creates a combination of one type of production efficiency information and two types of operation-related information from a plurality of pieces of the production efficiency information and a plurality of pieces of the operation-related information, and creates the production efficiency information map for the created combination of the one type of production efficiency information and the two types of operation-related information; The operation analysis system according to claim 1 .

9. an analysis data storage unit that stores the production efficiency information and the operation-related information; The operation analysis system according to claim 1 ,