Production management support device, production management support method and production management support program

Abstract

To improve productivity and optimization of safety and hygiene for workers.SOLUTION: A production management support device comprises: a worker information acquisition unit that acquires worker information about workers engaged in production; an environmental information acquisition unit that acquires environmental information about an environment, including machines used in the production; and an index generation unit that generates a safety and hygiene index related to the safety and hygiene of work, and a productivity index related to productivity of the work, based on the acquired worker information and environmental information.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a production management support device, a production management support method, and a production management support program. [Background technology]

[0002] Conventionally, a device has been proposed as a production management support device that generates profile information including the work capacity of a worker and the work capacity of the production equipment based on worker information on a worker who works in collaboration with production equipment and production equipment information on the production equipment, and further includes a profile information evaluation unit that evaluates the degree of change in the profile information based on reference profile information including the reference work capacity of the worker and the reference work capacity of the production equipment, a correction estimation unit that estimates a method of correcting the profile information and a correction effect resulting from the correction method based on the evaluation, and an instruction determination unit that determines correction instructions for a worker or production equipment to make a correction based on the corresponding correction method based on the estimated correction effect (see Patent Document 1).

[0003] However, while such devices aim to improve productivity in determining correction instructions for workers or production equipment, they do not take into consideration the safety of the workers.

[0004] Therefore, when the determined correction instructions were distributed to a worker or production equipment, there was a possibility that the risk of contact between the worker and the production equipment would increase or the burden on the worker would increase, resulting in harm to the worker. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2022 / 208652 Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention has been made in consideration of the above problems, and aims to achieve both improved productivity and optimized worker safety and health. [Means for solving the problem]

[0007] To solve the above problems, the present invention provides: A worker information acquisition unit that acquires worker information related to workers engaged in production; an environmental information acquisition unit that acquires environmental information relating to the environment, including machines used in the production; an index generating unit that generates a safety and health index related to safety and health and a productivity index related to productivity based on the acquired worker information and the acquired environmental information; The production management support device is characterized by comprising:

[0008] According to the present invention, it is possible to generate a safety and health index related to safety and health and a productivity index related to productivity. This makes it possible to accurately recognize not only productivity but also safety and health using the safety and health index and the productivity index, and therefore it is possible to use these indexes to achieve both improvement of productivity and optimization of worker safety and health. Here, workers engaged in production are not limited to workers who work with or operate machines, including production equipment, or perform work using tools, but also include production managers, machine maintenance personnel, and other people engaged in production.

[0009] In the present invention, The index generation unit may generate the safety and health index and the productivity index based on the acquired worker information and environmental information using a learning model that has been machine-learned to the worker information, the environmental information, the safety and health index, and the productivity index.

[0010] By using a machine learning model, it is possible to generate safety and health indicators and productivity indicators suitable for specific purposes based on various worker and environmental information.

[0011] In addition, in the present invention, the learning model may be a learning model that has been machine-learned to learn worker information related to the worker and environmental information related to the environment within a certain time range and a certain area.

[0012] In this way, it is possible to generate productivity indices and safety and health indices that are mutually related with respect to work, thereby obtaining useful information for achieving both improved productivity and optimized safety and health. Here, the certain time range includes, but is not limited to, for example, a production period of a certain product, a period previously set by a user, etc. Furthermore, the certain area includes, but is not limited to, a production area of ​​a certain product, each floor or each line of a factory, etc.

[0013] In the present invention, The worker information may include biometric information of the worker.

[0014] By including biometric information on workers in worker information, it becomes possible to achieve both improved productivity while taking into account the mental and physical condition of workers and the optimization of safety and health.

[0015] In the present invention, The worker information may include worker profile information for the worker.

[0016] The worker profile information is information specific to a worker. By including the worker profile information in the worker information, it becomes possible to simultaneously improve productivity and optimize safety and health by taking into account the information specific to the worker.

[0017] In the present invention, The environmental information may include machine profile information for the machine.

[0018] The machine profile information is information specific to a machine. By including the machine profile information in the environmental information, it is possible to achieve both productivity improvement and optimization of safety and health by taking into account the machine-specific information.

[0019] In the present invention, The worker information acquisition unit acquires time information associated with the worker information and the environmental information, The environmental information acquisition unit may acquire location information associated with the worker and the environmental information.

[0020] In this way, it is possible to generate productivity indices and safety and health indices that are interrelated with respect to work using time information and location information, thereby obtaining useful information for achieving both improved productivity and optimized safety and health.

[0021] In the present invention, The image generating unit may generate an image displaying changes over time of the safety and health index and the productivity index.

[0022] This makes it possible to recognize the changes over time in both safety and health indicators and productivity indicators, and by using these indicators it is possible to achieve both improved productivity and optimal worker safety and health.

[0023] In the present invention, The screen generating unit may generate a screen that displays the safety and health index and the productivity index in association with a time axis.

[0024] Since it is possible to compare and recognize the temporal relationship between changes in safety and health indicators and productivity indicators, these indicators can be used to achieve both improved productivity and the optimization of worker safety and health.

[0025] In the present invention, The system may further include a countermeasure decision unit that decides countermeasures to ensure the safety of the worker based on the safety and health index and the productivity index generated by the index generation unit.

[0026] This makes it possible to provide a countermeasure that can achieve both improved productivity and optimal safety and health.

[0027] In the present invention, a safety and health target receiving unit that receives an input of a target of the safety and health index; a productivity target receiving unit that receives an input of a target of the productivity index; Further equipped with The countermeasure decision unit may decide the countermeasure based on the received target of the safety and health index and the target of the productivity index.

[0028] This provides a solution that can achieve desired productivity and health and safety.

[0029] In the present invention, A production plan acquisition unit that acquires a production plan including the worker and the machine, The countermeasure may include changing the production plan.

[0030] In this way, it is possible to improve productivity while optimizing safety and health by taking into account production plans.

[0031] In the present invention, the worker information includes worker profile information for the worker; The action may include updating or adding to the worker profile information.

[0032] This allows future production plans to be drawn up based on new worker profile information, making it possible to achieve both improved productivity and optimized safety and health.

[0033] In the present invention, The countermeasures may include information for the worker and / or information for the machine.

[0034] The countermeasures include at least one of information about the worker and information about the machine, so that the countermeasures can be reflected in at least one of the worker and the machine. Information about the worker includes, but is not limited to, updates to work procedures and manuals, and work instructions to the worker. Information about the machine includes, but is not limited to, control instructions for the machine, installation of guards, changes to the layout and position of the machine, and the like.

[0035] In the present invention, The system may further include a worker information detection unit that detects the worker information.

[0036] In the present invention, An environmental information detection unit that detects the environmental information The above configuration may be adopted.

[0037] The present invention relates to Obtaining worker information regarding workers engaged in production; obtaining environmental information about an environment, including machines used in said production; generating a safety and health index related to safety and health based at least on the worker information; generating a productivity index related to productivity based on at least the environmental information; The production management support method includes the steps of:

[0038] According to the present invention, it is possible to generate a safety and health index related to safety and health and a productivity index related to productivity. This makes it possible to accurately recognize not only productivity but also safety and health using the safety and health index and the productivity index, and therefore it is possible to use these indexes to achieve both improvement of productivity and optimization of worker safety and health.

[0039] In the present invention, determining measures to ensure the safety of said workers based on said safety and health indicators and said productivity indicators; may include:

[0040] This makes it possible to provide a countermeasure that can achieve both improved productivity and optimal safety and health.

[0041] The present invention relates to A production management support program for causing a computer to execute the production management support method. Effect of the Invention

[0042] According to the present invention, it is possible to improve productivity while optimizing worker safety and health. [Brief description of the drawings]

[0043] [Figure 1] 1 is an overall configuration diagram of a production management system according to an embodiment of the present invention; [Diagram 2] 1 is a hardware configuration diagram of a production management support device according to an embodiment of the present invention. [Diagram 3] FIG. 2 is a diagram illustrating a hardware configuration of a control device according to an embodiment of the present invention. [Figure 4] 1 is a functional block diagram of a production management support device according to an embodiment of the present invention; [Diagram 5] 1 is a flowchart illustrating a process for measuring man-hours according to an embodiment of the present invention. [Figure 6] FIG. 11 is a diagram showing an example of basic data for calculating human productivity in an embodiment of the present invention. [Figure 7] FIG. 1 is a diagram showing an example of basic data for calculating an overall equipment efficiency in an embodiment of the present invention. [Figure 8] FIG. 1 is a diagram showing examples of safety and health indices in an embodiment of the present invention. [Figure 9] FIG. 11 is a diagram showing another example of the safety and health index in the embodiment of the present invention. [Figure 10] FIG. 13 is a diagram showing a display example of a productivity index and a safety and health index in an embodiment of the present invention. [Figure 11]FIG. 1 is a diagram illustrating a learning process of an index generation model in an embodiment of the present invention. [Figure 12] 1 is a flowchart showing a procedure of a countermeasure decision process in an embodiment of the present invention. [Figure 13] 13 is a flowchart illustrating another example of the procedure of the countermeasure decision process in the embodiment of the present invention. [Figure 14] FIG. 2 is a functional block diagram of a simulation unit in the embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0044] [Application example] Hereinafter, application examples of the present invention will be described with reference to the drawings. FIG. 1 shows a schematic configuration diagram of a production management system 100 including a production management support device 120 to which the present invention is applied.

[0045] The production management system 100 includes a production management device 110, a production management support device 120, a control device 130, a robot 140, an image sensor 150, a work environment sensor 160, a display device 170, a biometric information sensor 180, an alarm device 190, and a safety device 200.

[0046] The production management device 110 controls and monitors the production line including the robot 140 and the worker P, and acquires and records the production results.

[0047] The production management support device 120 supports the production management of a production line including a robot 140 and a worker P.

[0048] The control device 130 controls the robot 140 , the image sensor 150 , the working environment sensor 160 , the display device 170 , the alarm device 190 and the safety device 200 .

[0049] The robot 140 is an example of a machine of the present invention. The image sensor 150 photographs the robot 140 and the worker P. The work environment sensor 160 is a thermometer or the like that detects work environment information such as temperature related to a spatial range including at least the place where the worker P works. The biological information sensor 180 is a device such as an electrocardiograph that detects biological information (vital information) of the worker P such as heart rate and heart rate variability. The alarm device 190 is a device such as a patrol lamp that issues an alarm to the worker P. The safety device 200 is a device such as a proximity sensor or a photoelectric sensor that serves as a safety sensor used for the safety of the worker.

[0050] FIG. 4 is a block diagram showing the functional configuration of the production management support device 120. As shown in FIG. The system is equipped with a worker profile information acquisition unit 11, a worker profile information storage unit 1212, a worker operation information acquisition unit 13, a worker operation information storage unit 14, a worker biometric information acquisition unit 15, a worker biometric information storage unit 16, a machine profile information acquisition unit 17, a machine profile information storage unit 18, a machine operation information acquisition unit 19, a machine operation information storage unit 20, a work environment information acquisition unit 21, a work environment information storage unit 22, an image analysis unit 23, an index generation unit 24, a production status evaluation unit 25, an index storage unit 26, an evaluation criteria information storage unit 27, an evaluation result storage unit 28, a simulation unit 29, a countermeasure decision unit 30, an improvement information generation unit 31, an input unit 32, and an output unit 33.

[0051] The worker profile information acquired by the worker profile information acquisition unit 11 is information specific to the worker, and includes personal attribute information such as name, labor attribute information such as ID, qualification information such as licenses, and work ability information such as work speed.

[0052] The worker motion information is information that indicates the position, posture, and physical movements of the worker.

[0053] Worker biometric information includes heart rate, heart rate variability, acceleration (shock and vibration to the body), respiratory rate, and skin electrical activity due to sweating.

[0054] Machine profile information is information specific to a machine, and includes specification information such as model name, operational information such as line name, performance information such as accumulated operating time, machine capability information such as operating speed, and risk assessment information.

[0055] The machine operation information includes the operating status of the machine, the values ​​of parameters related to operation, the presence or absence of malfunctions, and measurement data such as vibrations detected by sensors installed inside the machine.

[0056] The work environment information is information about the working environment of the worker, and includes temperature, humidity, illuminance, carbon monoxide concentration, amount of suspended dust, noise level, vibration level, risk assessment information, etc. The work environment information also includes the presence or absence of objects such as obstacles in the work environment, information about the place where the worker is engaged in production, such as production line A, and information about the type of work to be performed in that place.

[0057] This worker profile information, worker operation information, worker biometric information, machine profile information, machine operation information and work environment information are each associated with time information so as to be synchronized within a certain period (time range), and information related to location information can be extracted as information within a certain area.

[0058] The index generating unit 24 of the production management support device 120 generates evaluation indexes for evaluating the production status. Here, a productivity index for evaluating the production status from the viewpoint of productivity and a safety and health index for evaluating the production status from the viewpoint of safety and health are generated based on worker profile information, worker operation information, worker biological information, machine profile information, machine operation information, and work environment information.

[0059] 10 is a graph showing the productivity indexes of performance rate and work efficiency, and the safety and health index of near misses on the same time axis. In the production management support device 120, such information can be displayed on the display constituting the output unit 33. In this way, by comparing and contrasting productivity indicators and safety and health indicators on the same time axis, it is possible to clearly recognize that workers' near misses are occurring due to machine stoppages in the area enclosed by the dashed dotted line. Therefore, rather than simply examining the production situation from the viewpoint of productivity, it is possible to also consider the viewpoint of worker safety and health, and it is possible to strike a balance between improving productivity and optimizing safety and health in order to make improvements.

[0060] Example 1 The following describes in detail the embodiments of the present invention with reference to the drawings (including the drawings already described in the above application examples). However, the specific configurations described in the embodiments are not intended to limit the scope of the present invention unless otherwise specified.

[0061] (Production Management System) FIG. 1 is a schematic diagram of a production management system 100 including a production management support device 120 according to the present embodiment. FIG. The production management system 100 includes a production management device 110, a production management support device 120, a control device 130, a robot 140, an image sensor 150, a working environment sensor 160, a display device 170, a biometric sensor 180, an alarm device 190, and a safety device 200. The control device 130, the robot 140, the image sensor 150, the working environment sensor 160, the display device 170, the alarm device 190, and the safety device 200 are communicatively connected to each other via a field network NT1. The control device 130 is communicatively connected to the production management device 110 and the production management support device 120 via a higher-level network NT2. Here, the biometric sensor 180 is connected to the higher-level network NT2. The network configuration is not limited to this. The number of robots 140 included in this production management system 100 is not limited, and only one robot is shown in FIG. 1 for the sake of explanation. The robot 140 is an example of a machine to which the production management system 100 is applied, and other machines include general manufacturing equipment, conveying equipment, inspection equipment, and the like. 1 shows only one worker P, but there is no limit to the number of workers P that are targets of the production management system 100. In the following, a worker P who works in collaboration with a machine will be described as an example, but the worker P is not limited to this and may be any person who is engaged in work directly or indirectly related to a machine.

[0062] The production management device 110 controls and monitors a production line including robots 140 and workers P, and acquires and records production results. The production management device 110 also has a production plan database (DB) 111. The production management device 110 is configured with computers, workstations, etc., and the hardware configuration of the production management device 110 is similar to that of the production management support device 120 described below, so a description thereof will be omitted. The production management device 110 does not necessarily have to be realized by a single physical configuration, and may be configured by multiple computers that cooperate with each other.

[0063] The production management support device 120 supports the production management of a production line including a robot 140 and a worker P. As shown in FIG. 2, the production management support device 120 is composed of a computer, a workstation, or the like. Such a computer or the like has a processor 121 such as a CPU or a DSP, a main memory unit 122 such as a read-only memory (ROM) or a random access memory (RAM), an auxiliary memory unit 123 such as an EPROM, a hard disk drive (HDD), or a removable medium, a communication unit 124 for communicating with devices such as the production management device 110 and the control device 130, an input unit 125 such as a keyboard or a mouse, and an output unit 126 such as a display, which are connected to each other by a bus B1. The removable medium is, for example, a flash memory such as a USB memory or an SD card, or a disk recording medium such as a CD-ROM, a DVD disk, or a Blu-ray disk. The auxiliary storage unit 123 stores an operating system (OS), various programs such as an evaluation index generation processing program and a countermeasure proposal decision processing program, various tables, etc., and the programs stored therein are loaded into the working area of ​​the main storage unit 122 and executed, and each component unit, etc. are controlled through the execution of the programs, thereby realizing each functional unit that serves a predetermined purpose, as described below. However, some or all of the functional units may be realized by hardware circuits such as ASIC and FPGA. However, the production management support device 120 does not necessarily have to be realized by a single physical configuration, and may be composed of multiple computers that cooperate with each other. Here, the input unit 125 corresponds to a safety and health target receiving unit and a productivity target receiving unit that receive input of targets for safety and health indicators and / or productivity indicators, which will be described later.

[0064] The control device 130 outputs control commands to the robot 140 to specify the driving, stopping, and operating speed of the robot 140, and controls the robot 140. The control device 130 also controls the image sensor 150 and the working environment sensor 160, acquires data output from these sensors, and transmits the data to the production management device 110 and the production management support device 120 as necessary. The control device 130 also controls the display device 170, the alarm device 190, and the safety device 200. As shown in Fig. 3, the control device 130 has a processor 131 such as a CPU or a DSP, a main memory unit 132 such as a read-only memory (ROM) or a random access memory (RAM), an auxiliary memory unit 133 such as an EPROM, a hard disk drive (HDD), or a removable medium, a communication unit 134 for communicating with devices such as the production management device 110, the production management support device 120, and the image sensor 150, an input unit 135 such as a keyboard or a mouse, and an output unit 136 such as a display, which are connected to each other by a bus B2. The removable medium is, for example, a flash memory such as a USB memory or an SD card, or a disk recording medium such as a CD-ROM, a DVD disk, or a Blu-ray disk. The auxiliary storage unit 133 stores an operating system (OS), a control program 133a created according to a controlled object such as a machine including the robot 140, a safety program 133b executed to ensure the safety of a worker P in a collaborative work between the worker P and the robot 140, and a robot control table 133c referenced when the safety program 133b is executed, and the programs stored therein are loaded into the working area of ​​the main storage unit 132 and executed, and each component part is controlled through the execution of the program, thereby realizing each functional part that serves a predetermined purpose as described below. However, some or all of the functional parts may be realized by a hardware circuit such as an ASIC or an FPGA. However, the control device 130 does not necessarily have to be realized by a single physical configuration, and may be composed of multiple computers that cooperate with each other. As the control device 130, a PLC (programmable controller) (PLC) that executes a control program (which may include sequence control and motion control) 133a can be adopted, but the control device 130 is not limited to this as long as it is a device that controls the robot 140.

[0065] Based on control commands from the control device 130, the robot 140 is driven, operates at a specified speed, and stops as necessary.

[0066] The image sensor 150 captures images of the robot 140 and the worker P. The image sensor 150 may be a normal camera (2D camera) or a stereo camera (3D camera). Alternatively, a sensing device capable of acquiring a distance profile to an object, such as a laser scanner or a distance measuring sensor, may be used. The image sensor 150 corresponds to the worker information detection unit and the environmental information detection unit of the present invention.

[0067] The work environment sensor 160 detects work environment information related to a spatial range including at least the place where the worker P performs work. The work environment information includes, but is not limited to, temperature, humidity, illuminance, carbon monoxide concentration, suspended dust amount, noise level, vibration level, etc. The work environment sensor 160 includes, but is not limited to, a thermometer, a hygrometer, a carbon monoxide sensor, a dust meter, a sound level meter, a vibration meter, etc. The work environment information also includes information such as the presence or absence of objects (including structures) such as obstacles in the work environment of the worker P. The image sensor 150 described above also functions as a work environment sensor that detects the presence or absence of such obstacles. The work environment sensor 160 corresponds to the environment information detection unit of the present invention.

[0068] The display device 170 is a device that displays information to be provided to the worker P.

[0069] The biological information sensor 180 is a device that detects biological information (vital information) of the worker P. Examples of the biological information sensor 180 include, but are not limited to, an electrocardiogram sensor, a pulse wave sensor, an acceleration sensor, an electrodermal activity sensor, and the like. Examples of biological information detected by the biological information sensor 180 include, but are not limited to, heart rate, heart rate variability, acceleration (shock and vibration to the body), respiratory rate, and electrodermal activity due to sweating. The biological information sensor 180 corresponds to the work information detection unit of the present invention.

[0070] The alarm device 190 is a device that issues an alarm to the worker P, and includes a patrol lamp, a speaker, a siren, etc. The above-mentioned display device 170 can also be used as the alarm device. Also, a mobile terminal held by the worker P can be used as the alarm device.

[0071] The safety device 200 is a device used for the safety of workers, and includes a proximity sensor or a photoelectric sensor as a safety sensor, a safety fence, a light curtain, an interlock switch, or the like.

[0072] (Production management support device) FIG. 4 is a block diagram showing the functional configuration of the production management support device 120. As shown in FIG. The device 120 includes a worker profile information acquisition unit 11, a worker profile information storage unit 1212, a worker motion information acquisition unit 13, a worker motion information storage unit 14, a worker biometric information acquisition unit 15, a worker biometric information storage unit 16, a machine profile information acquisition unit 17, a machine profile information storage unit 18, a machine motion information acquisition unit 19, a machine motion information storage unit 20, a work environment information acquisition unit 21, a work environment information storage unit 22, an image analysis unit 23, an index generation unit 24, a production status evaluation unit 25, an index storage unit 26, an evaluation criterion information storage unit 27, an evaluation result storage unit 28, a simulation unit 29, a countermeasure decision unit 30, and an improvement information generation unit 31. The device 120 also includes a screen generation unit that generates screen information to be displayed on a display constituting the output unit 126 or to be displayed on an external device such as a display device 170 via the communication unit 124. Each of these functional units is realized by loading a program stored in the auxiliary memory unit 123 into the main memory unit 122 and having the processor 121 interpret and execute the program. The worker profile information acquisition unit 11, the worker operation information acquisition unit 13, and the worker biometric information acquisition unit 15 constitute a worker information acquisition unit of the present invention. In addition, the machine profile information acquisition unit 17, the machine operation information acquisition unit 19, and the work environment information acquisition unit 21 constitute an environment information acquisition unit of the present invention.

[0073] The worker profile information acquisition unit 11 acquires worker profile information that is information specific to a worker. The worker profile information includes personal attribute information, such as name, sex, age, health examination results (height, weight, presence or absence of chronic illness and its contents), presence or absence of work restrictions and its contents, which are information specific to a worker, as well as labor attribute information, such as ID, department, job rank, qualification, years of experience, work experience, working hours, overtime work hours, and vacation acquisition record. The worker profile information also includes work ability information, such as work speed for individual tasks and work defect occurrence rate. In addition, the labor attribute information may include human relationship information, which is information about people related to the worker in the work (workers working on the same line, managers, etc.) at the time of work. In addition, the worker profile information may include a production plan related to the worker. The worker profile information acquisition unit 11 can acquire personal attribute information from a personnel management database, labor attribute information from a labor management database, and work ability information from a production management device 110, respectively, through a network. Here, the worker profile information acquisition unit 11 corresponds to the production plan acquisition unit of the present invention.

[0074] The worker profile information storage unit 12 is a specified area of ​​the auxiliary storage unit 123 that stores the worker profile information acquired by the worker profile information acquisition unit 11.

[0075] The worker motion information acquisition unit 13 acquires worker motion information related to the motion of a worker. The worker motion information is information indicating the position and posture of a worker and the physical movements of the worker. The worker motion information acquisition unit 13 can analyze the image captured by the image sensor 150 using the image analysis unit 23 described below and acquire the extracted worker motion in real time. The worker motion information acquisition unit 13 can also acquire worker motion information from a detection device worn or carried by a worker, such as an acceleration sensor.

[0076] The worker motion information storage unit 14 stores the worker motion information acquired by the worker motion information acquisition unit 13. The worker movement information storage unit 14 stores the worker movement information in a predetermined area of ​​the auxiliary storage unit 123. The worker movement information is stored in association with the target worker P using the ID of the worker P or the like. The worker movement information storage unit 14 stores the worker movement information in association with the time when the image was captured. The worker movement information may also be stored in association with the installation location of the image sensor that captured the image or a position or spatial range specified by the analysis results.

[0077] The worker biometric information acquiring unit 15 acquires biometric information of the worker. As described above, the biometric information includes heart rate, heart rate variability, respiratory rate, electrocutaneous activity due to sweating, acceleration (shock and vibration to the body), etc., and the worker biometric information acquiring unit 15 can acquire this biometric information from the biometric information sensor 180. There are no particular limitations on the biometric information, so long as it is information that indicates the mental and physical state of the worker.

[0078] The worker biometric information storage unit 16 is a specified area of ​​the auxiliary storage unit 123 that stores the biometric information of the worker P acquired by the worker biometric information acquisition unit 15. The worker biometric information storage unit 16 stores the worker P in association with the target worker by the ID of the worker P or the like. The worker biometric information storage unit 16 also stores the worker biometric information in association with the time when it was detected.

[0079] The machine profile information acquisition unit 17 acquires machine profile information that is information specific to the machine. When the machine is a robot, the machine profile information includes, but is not limited to, specification information such as model name, serial number, manufacturer name, and setting range of variable parameters (maximum movable range, maximum operating speed, etc.), operation information such as line name, manager, and defect history, performance information such as cumulative operating time, daily inspection record, maintenance record, and operation performance, operation plan, machine capability information such as operating speed and work defect rate calculated for each work object or work condition, and risk assessment information. The machine profile information may include a production plan related to the machine. The machine profile information acquisition unit 17 can acquire these pieces of information from the production management device 110. Here, the machine profile information acquisition unit 17 corresponds to the production plan acquisition unit of the present invention.

[0080] The machine profile information storage unit 18 is a predetermined area of ​​the auxiliary storage unit 123 that stores the machine profile information acquired by the machine profile information acquisition unit 17.

[0081] The machine operation information acquisition unit 19 acquires machine information related to the operation (operation) of the machine. The machine information includes the operating status of the machine, the values ​​of parameters related to the operation, the presence or absence of a malfunction, and measurement data (vibration, electromagnetic waves, current value, voltage value, power value, power amount, temperature, etc.) from sensors installed inside the machine. The machine information acquisition unit acquires the machine operation, the values ​​of parameters related to the operation, and the presence or absence of a malfunction from the control device 130 among the machine information. The worker operation information acquisition unit 13 may analyze the image captured by the image sensor 150 using the image analysis unit 23 described later and acquire the extracted machine operation. The measurement data may be acquired from a sensor installed outside the machine. The machine operation information acquisition unit 19 acquires these data in real time.

[0082] The machine operation information storage unit 20 is a predetermined area of ​​the auxiliary storage unit 123 that stores the machine operation information acquired by the machine operation information acquisition unit 19. The machine operation information storage unit 20 stores the machine operation information in association with the target machine by the machine ID or the like. The machine operation information storage unit 20 stores the machine operation information in association with time.

[0083] The work environment information acquisition unit 21 acquires work environment information related to the work environment (ambient environment) of the worker. As described above, the work environment information includes, but is not limited to, temperature, humidity, illuminance, carbon monoxide concentration, amount of suspended dust, noise level, vibration level, risk assessment information, and the like. The work environment information acquisition unit 21 acquires this work environment information from the work environment sensor 160. The work environment information includes information on objects (structures) such as obstacles in the work environment of the worker P. The information includes information on the presence or absence of obstacles (including objects), information on the location where the worker is engaged in production, such as production line A, and information on the type of work to be performed at that location. The work environment information acquisition unit 21 may analyze the image captured by the image sensor 150 using the image analysis unit 23 described below to acquire information on the presence or absence of obstacles or other objects in the work environment.

[0084] The working environment information storage unit 22 is a predetermined area of ​​the auxiliary storage unit 123 that stores the working environment information acquired by the working environment information acquisition unit 21. The working environment information storage unit 22 stores the working environment information in association with the detection time. The working environment information storage unit 22 stores the working environment information in association with the target position or spatial range of the working environment information depending on the installation location of the working environment sensor 160, etc. The working environment information storage unit 22 may also store work-related information by associating the working environment information with work.

[0085] In the following, the above-mentioned worker profile information, worker operation information, and worker biometric information may be collectively referred to as worker information, and the machine profile information, machine operation information, and work environment information may be collectively referred to as environmental information. Worker information and environmental information is information that can be extracted as information about workers and machines within a certain time range and within a certain area.

[0086] The image analysis unit 23 analyzes the image captured by the image sensor 150, and extracts information such as the movement of the worker P, the movement of the machine, and the presence or absence of obstacles around the worker P. Any appropriate method can be adopted for the recognition process of the worker P, the machine, the objects around the worker P, and the like.

[0087] The index generating unit 24 generates evaluation indexes for evaluating the production status. Here, a productivity index for evaluating the production status from the viewpoint of productivity and a safety and health index for evaluating the production status from the viewpoint of safety and health are generated based on the worker profile information, worker motion information, worker biometric information, machine profile information, machine operation information, and work environment information. The productivity index and the safety and health index are generated by combining at least one of the worker profile information, worker motion information, worker biometric information, machine profile information, machine operation information, and work environment information, and further performing arithmetic processing on them.

[0088] (Personnel Productivity) As the productivity evaluation index, various indices can be adopted. For example, the human productivity shown in the following formula (1) can be adopted. Human productivity = output man-hours ÷ production input man-hours (1) Here, the production input man-hours are the working hours minus the excluded man-hours such as the time spent supporting other departments or during improvement activities, and the output man-hours are the direct man-hours minus the work losses and defect losses. In addition, while human productivity is basically expressed by equation (1), it can also be expressed by the following equation (2), and can also be decomposed and operated and managed as shown in the following equation (2). Human productivity = work efficiency x production efficiency (2) Here, the work efficiency and production efficiency are indexes expressed by the following equations (3) and (4), respectively. Work efficiency = Productive man-hours ÷ Direct man-hours (3) Production efficiency = direct labor hours ÷ production labor hours (4) Here, the direct man-hours are the production man-hours minus indirect man-hours such as setup and waiting time. In addition, work efficiency and production efficiency, which are elements of human productivity, can also be used as productivity indices.

[0089] FIG. 5 is a flowchart illustrating the procedure for calculating the work efficiency of the process A. First, measurement of the man-hours for process A is started (step S11). When the measurement of man-hours is started, it is determined whether or not a work stoppage has occurred (step S12). Whether or not a work stoppage has occurred can be determined based on the machine operation information stored in the machine operation information storage unit 20 and the worker work information stored in the worker operation information storage unit 14. The relationship between the machine operation and the worker operation and the process can be determined based on the machine schedule stored in the machine profile information storage unit 18 and the worker schedule stored in the worker profile information. If no work stoppage occurs, the process proceeds to step S16.

[0090] When a work stoppage occurs, measurement of the work stoppage time is started (step S13). Then, after starting to measure the work stoppage time, it is determined whether or not the work has been returned to (step S14). The determination of whether or not the work has been returned to is repeated at an appropriate timing until the work has been returned to.

[0091] When the worker returns to work, the measurement of the work stoppage time is ended (step S15). Then, it is determined whether or not the process A has been completed (step S16). If step A is not completed, the process returns to step S12. When the process A is completed, the measurement of the man-hours for the process A is terminated (step S17), and the work efficiency of the process A is calculated and recorded in a predetermined area (step S18). Similarly, production efficiency can also be calculated, and personnel productivity can be calculated from the work efficiency and production efficiency thus calculated.

[0092] FIG. 6 shows examples of data on the thus measured completed man-hours, direct man-hours, and production input man-hours.

[0093] For example, for the product Lot No. xxxx1 on production line A on yy / zz / 20xx, the completed man-hours are recorded as 1200 man-hours, direct man-hours as 1140 man-hours, production input man-hours as 1080 man-hours, process 1 as 60, process 2 as 40, process 3 as 80, etc. The same data is recorded for the products Lot No. xxxx2 and Lot No. xxxx3 on production line A on the same day.

[0094] (Overall Equipment Effectiveness) Moreover, as a productivity index, the overall equipment effectiveness (OEE) shown in the following equation (5) can also be adopted. Overall equipment effectiveness = Availability × Performance rate × Quality rate (5) Here, the availability rate, performance rate, and quality rate are indexes expressed by the following formulas (6), (7), and (8), respectively. Time availability = operating time ÷ load time (6) Performance rate = net operating time ÷ operating time (7) Quality rate = Value operating time ÷ Net operating time (8) Here, load time is the time during operation when the machine is actually turned on and under load, net operation time is the time during operation (the time during load time when the machine is actually operating) during which the machine was able to perform at its original capacity, and value operation time is the time during net operation time when good products were produced. The quality rate can also be calculated using the following formula (9). Good product rate = (Processed quantity - Defective quantity) ÷ Processed quantity (9) The load time and the operating time can be calculated based on the machine operation information stored in the machine operation storage unit, and the yield rate can be calculated based on the machine operation information stored in the machine operation storage unit and the production management device 1. This can be calculated from the information recorded in the performance management database of 10. In addition, the availability rate, performance rate, and quality rate, which are elements of overall equipment effectiveness, can also be used as productivity indices.

[0095] FIG. 7 shows examples of data such as the availability rate, performance rate, non-defective product rate, load time, operating time, and net operating time that serve as the basis for calculating the overall equipment effectiveness.

[0096] For example, in production line A, on 20xx / yy / 01, the time availability rate was 0.9375, the performance availability rate was 0.9333, the non-defective product rate was 0.95, the load time was 8 hours, the operating time was 7.5 hours, and the net operating time was 7 hours, etc. These data are also recorded for production line A on 20xx / yy / 01 and 20xx / yy / 02 in the same way.

[0097] (Safety and health indicators) Various indices can be adopted as basic data for the safety and health indices, but the indices shown in FIG. 8 can be adopted as the work environment indices related to the work environment of worker P. These work environment indices are detected by the work environment sensor 160, acquired by the work environment information acquisition unit 21, and recorded in association with the work, and here, the work environment indices related to work A are shown. The work environment indices are acquired at a predetermined timing (here, at one-hour intervals) and recorded in chronological order. Here, data examples of the work environment indices are shown, including temperature (°C), humidity (%), illuminance (lx), carbon monoxide concentration (ppm), suspended dust amount (mg / m3), and noise level (db), but the work environment indices are not limited to these. For example, at 09:00:00 on yy / zz / 20xx, the temperature was recorded as 25.5°C, humidity as 67.1%, illuminance as 640lx, carbon monoxide concentration as 0ppm, suspended dust amount as 0.005mg / m3, and noise level as 54db, and these data were also recorded at 10:00:00 and 11:00:00 on the same day.

[0098] As the safety and health index or its basic data, the bioinformation of worker P or an index calculated from the bioinformation can be adopted. Such safety and health indexes include stress, drowsiness, concentration, fatigue, and near-miss conditions. This information can be calculated based on bioinformation such as heart rate, heart rate interval, and LF / HF. Here, LF / HF refers to the frequency components (LF values) in the low frequency (LF) band (0.004-0.15Hz) of the power spectrum related to the fluctuation of the heart rate interval and the high frequency (HF) band. This is the ratio of the frequency component (HF value) in the range (0.15-0.4Hz). This LF / HF can be used as an index of stress. In addition, a near-miss condition can be evaluated as an instantaneous rise in LF / HF.

[0099] FIG. 9 shows an example of biometric information or data based on it. Any of these or a combination of these, or data that has been further subjected to arithmetic processing, can be used as a safety index. Data related to each worker is recorded, and data related to a worker** is shown here. Worker biometric information related to safety and health indexes is acquired at a predetermined timing (here, every second) and recorded in chronological order. Here, examples of data such as heart rate (bpm), heart rate interval (ms), LF / HF, drowsiness / concentration, stress, and years of experience (years) are shown as worker biometric information related to safety and health indexes, but are not limited to these. Data that may change in real time among worker information related to safety and health indexes is acquired at a predetermined timing (here, every second) and recorded in chronological order. Years of experience may be acquired when data in the labor management database is updated. In addition, worker information related to safety and health indexes includes data that can be directly detected, such as heart rate, heart rate interval, etc., and data calculated based on detected data, such as LF / HF, drowsiness / concentration, and stress. For example, at 09:00:00 on yy / zz / 20xx, the heart rate of worker A is 80 bpm, the heart rate interval is 950 ms, the drowsiness / concentration level is 20, the stress level is 30, and the number of years of experience is 5. The year is recorded, and similar data is recorded at 09:00:01 and 09:00:02 on the same day.

[0100] The generated productivity index and safety and health index are stored in the index storage unit 26, which is a predetermined area of ​​the auxiliary storage unit 123.

[0101] The production management support device 120 holds the worker profile information, worker operation information, worker biological information, machine profile information, machine operation information, and work environment information, which are the data underlying the productivity index and the safety and health index, as information associated with time. Therefore, the productivity index and the safety and health index can be generated as information associated with time.

[0102] 10 is a graph showing the time-dependent changes in productivity indexes and safety and health indexes on the same time axis. The screen generation unit of the production management support device 120 can display such information on the display constituting the output unit 33. Here, the performance rate and work efficiency are displayed as productivity indicators, and the near miss value as a safety and health indicator, on the same time axis. In this way, by comparing and contrasting the productivity indicators and the safety and health indicators on the same time axis, it is possible to clearly see that near misses by workers occur due to machine stoppages in the area enclosed by the dashed dotted line. Therefore, rather than simply examining the production situation from the viewpoint of productivity, it is possible to also consider the viewpoint of worker safety and health, and it is possible to strike a balance between improving productivity and optimizing safety and health in order to make improvements.

[0103] The indexes generated by the index generating unit 24 may be generated from specific basic data through specific combinations and calculations, but the contents of the productivity indexes and safety and health indexes may be changed depending on the purpose. For example, the basic data may not only be replaced, but also the weighting of the basic data may be changed to generate productivity indexes and safety and health indexes according to the purpose. As will be described later, there may be cases where machine control, worker work procedures, and production plans are changed based on the productivity indexes and safety and health indexes. In this way, the productivity information and safety and health indexes after the machine control, etc. are changed can be obtained as feedback, so that the productivity indexes and safety and health indexes may be updated by selecting basic data for the productivity indexes and safety and health indexes and applying machine learning to the weighting thereof.

[0104] (Evaluation index generation model) FIG. 11 shows a learning processing unit 241 that generates an evaluation index generation model possessed by the index generation unit 24. The learning processing unit 241 receives inputs of the productivity index and the safety and health index stored in the index storage unit 26, the worker profile information stored in the worker profile information storage unit 12, the worker operation information stored in the worker operation information storage unit 14, the worker biometric information stored in the worker biometric information storage unit 16, the machine profile information stored in the machine profile information storage unit 18, the machine operation information stored in the machine operation information storage unit 20, and the work environment information stored in the work environment information storage unit 22. The worker profile information, the worker operation information, the worker biometric information, the machine profile information, the machine operation information, and the work environment information are associated as information within a certain time range and a certain area. The learning processing unit 241 generates an index generation model 243 that generates a productivity evaluation index and a safety and health index by having the learning model 242 learn all or a part of the information as learning data. The learning processing unit 241 is realized by reading out a learning model generation program stored in a predetermined area of ​​the auxiliary storage unit 123 and executing it in the processor 121. The generated index generation model 243 is stored in a predetermined area of ​​the auxiliary storage unit 123 and is used to generate productivity indexes and safety and health indexes in the index generation unit 24.

[0105] The simulation unit 29 performs a simulation of changes to the machines and work procedures when the production status evaluation unit 25 evaluates that there is a predetermined change. The simulation will be described in detail later.

[0106] The countermeasure decision unit 30 decides on changes to the machine and / or changes to the work procedure as countermeasures based on the results of the simulation in the simulation unit 29.

[0107] The improvement information generating unit 31 generates information for improvement such as control commands for the machine, updated information for work procedures and manuals, and work instructions for workers, in accordance with the countermeasures. The control commands for the machine are transmitted from the output unit 42 to the control device 130, and the work procedures and the like are notified in a predetermined manner and used for training workers, and work instructions are given in accordance with the updated work procedures.

[0108] (Countermeasure decision process) Figures 12 and 13 are flow charts for explaining the processing including the generation of productivity indexes and safety and health indexes and the determination of countermeasures. Figure 12 shows the processing starting from a change in the safety and health index, and Figure 13 shows the processing starting from a change in the productivity index. The processing including the generation of productivity indexes and safety and health indexes and the determination of countermeasures described here corresponds to the production management support method of the present invention.

[0109] In FIG. 12, first, the index generating unit 24 acquires worker information and environmental information (step S21).

[0110] Next, the index generating unit 24 generates a productivity index and a safety and health index based on the worker information and the environmental information (step S22).

[0111] The production status evaluation unit 25 judges whether or not an incident has occurred based on the safety and health index information (step S23). The presence or absence of an incident is judged by comparing the safety and health index with a threshold value set for the relevant safety and health index stored in the evaluation criteria information storage unit 27. An incident may be, for example, but is not limited to, the occurrence of a near miss or the detection of an excessive stress state. A table in which threshold values ​​are registered may be switched depending on the target worker, machine, and work environment. In addition, the occurrence of an incident may be determined by an incident determination model that has learned productivity indicators, safety and health indicators, and worker and environmental information.

[0112] The determination of the presence or absence of an incident is repeated for the safety and health index generated from the acquired range of worker information and environmental information. If there is no incident for the safety and health index generated from the acquired range of worker information and environmental information, the process ends.

[0113] If it is determined that an incident has occurred, the production status evaluation unit 25 checks the productivity index at the time of the incident (step S24) and determines whether the cause of the incident is the machine or the worker (step S25). The cause of the incident can be determined by storing a predetermined incident cause determination table in the evaluation criteria information storage unit 27 and the production status evaluation unit 25 making a determination based on this cause determination table. An incident cause determination model generated by learning incident occurrence cases and cause determination results may be stored in the evaluation criteria information storage unit 27 and the production status evaluation unit 25 may make a determination based on this incident cause determination model. For example, an incident may occur due to a decrease in productivity index, such as when a worker approaches a hazard without stopping the machine during a momentary stop, and the machine suddenly starts moving again when the momentary stop is lifted. Incidents may occur without any reduction in productivity, such as a near miss with a source, or may result in a reduction in productivity due to an incident, such as high levels of fatigue or stress in a particular task, which reduces the productivity index.

[0114] The production status evaluation unit 25 judges the cause of the incident based on the safety and health index and the productivity index, extracts countermeasures based on the countermeasures table, and performs a simulation, which will be described later. The countermeasures table is stored in the evaluation criteria information storage unit 27.

[0115] Various variations are possible in extracting countermeasures based on productivity indexes and safety and health indexes, and some examples are described below. Countermeasures include control commands for machines, updating of work procedures and manuals, work instructions for workers, changes to production plans, etc. Furthermore, the worker property information recorded in the production management device 110 or the labor management database includes information on capabilities such as work speed, which is the basis for production planning, and therefore this may be updated as a countermeasure or added as new worker-specific information. Similarly, the machine property information recorded in the production management device 110 includes information on machine capabilities such as operating speed, which is the basis for production planning, and therefore this may be updated as a countermeasure or added as machine-specific information.

[0116] If the worker's stress level is still acceptable while he or she is waiting to work and the machine's operating speed is also acceptable, a countermeasure can be suggested in which the worker is instructed to work faster and the machine is also instructed to speed up its processing speed. At this time, if a worker's performance is declining, countermeasures can be suggested, such as adding support and assistance from other workers or reviewing worker placement.

[0117] In addition, if a worker's stress exceeds a threshold and is placing a burden on the worker, or if temperature, noise, etc. exceed a threshold, changes or improvements to machinery can be suggested as countermeasures.

[0118] In addition, if a worker is detected to be in a startled state, the system can determine the impact on production from the state of the machine based on the worker's location and work content at the time, and suggest countermeasures such as instructing changes to the operating speed, direction, timing, etc. of the machine that started the worker.

[0119] The table for determining such countermeasures may be switched based on the type of worker, such as the worker's proficiency level, physique, dominant hand, average moving speed, average heart rate, etc., or the type of machine, such as the type, manufacturer, size, amount of power used, period of use, etc.

[0120] In step S25, if the machine change process simulation unit 51 determines that the cause of the incident is a machine, it performs a simulation of the process when changes are made to the machine extracted as a countermeasure (step S26).

[0121] 14 is a block diagram showing the configuration of the simulation unit 29 of the production management support device 120. The simulation unit 29 includes a machine change process simulation unit 51, a machine risk assessment simulation unit 52, a work procedure change process simulation unit 53, and a worker risk assessment simulation unit .

[0122] The machine change process simulation unit 51 performs a simulation to estimate the effect of implementing the countermeasures extracted by the production status evaluation unit 25. The effect of the countermeasures can be judged, for example, by the closeness to a predetermined target value set for a productivity index and / or a safety and health index. .

[0123] The machine change process simulation unit 51 determines the correction instructions (i.e., the control contents) to be applied to the machine based on the estimated effect. If it is estimated that the desired effect will not be obtained, the production status evaluation unit 25 extracts another countermeasure and performs the machine change process simulation again.

[0124] The control of the machine may include changing parameter settings, changing target value settings, changing operation modes, modifying production plans, issuing replanning commands, or changing warning conditions.

[0125] Returning to the explanation of Figure 12. Following step S26, the machine risk assessment simulation unit 52 performs a simulation of a risk assessment when a change is made to the machine (step S27).

[0126] The machine risk assessment simulation unit 52 simulates the risk when the control contents determined by the machine change process simulation unit 51 are applied to the machine.

[0127] The machine risk assessment simulation unit 52 includes a hazard source identification unit 531 , a risk estimation unit 532 , a risk evaluation unit 533 , and a risk reduction processing unit 534 .

[0128] The hazard identification unit 521 acquires the work environment information and hazard data, identifies the hazard, and specifies the hazard area. For example, the hazard source identification unit 521 identifies elements having a driving source, such as a robot arm, an end effector, and a conveyor as a peripheral device, as a hazard source. The hazard source identification unit 521 also judges whether or not the movement range of the hazard source overlaps with the movement range of the worker. The hazard source identification unit 521 judges an area where the movement range of the hazard source overlaps with the movement range of the worker as a hazard area. The hazard source identification unit 521 judges whether or not there is a risk of a human body being trapped between the hazard sources from the movement range of the hazard source. The hazard source identification unit 521 judges whether or not there is a risk of a human body being trapped between the hazard source and a surrounding object such as a desk, a wall, a pillar, or a door from the movement range of the hazard source. The hazard source identification unit 521 also judges an area where there is a risk of a human body being trapped as a hazard area. Note that the method of identifying the hazard source and specifying the hazard area is not limited to the above-mentioned method.

[0129] The risk estimation unit 522 executes risk estimation. The risk estimation unit 522 identifies possible hazardous events for the identified hazard source and the specified hazardous area by risk estimation. The risk estimation unit 522 also identifies injuries to the human body that may occur due to the possible hazardous events.

[0130] When the working range of the worker and the working range of the robot arm overlap, a "collision with the robot arm" is listed as a hazardous event. When the distance between the working range of the worker and the working range of the robot arm is narrower than a specified interval, the worker may collide with the robot arm. In this case, a "collision with the robot arm" is listed as a hazardous event. When the distance between the working range of the robot arm and the surrounding object is narrower than a specified interval, a "getting caught between the robot arm and the surrounding object" is listed as a hazardous event. When the working range of the robot arm is a "collision with the robot arm", an example of an injury is "bruise or fracture". When the working range of the robot arm is a "getting caught between the robot arm and the surrounding object", an example of an injury is "severe injury of a fracture or more". The risk estimation unit 522 determines these hazardous events and these injuries based on the hazard source data. Risk estimation The risk assessment unit 522 performs risk assessment using factors such as the magnitude of the hazard, the frequency of exposure, and the likelihood of avoiding harm.

[0131] The risk estimation unit 522 can employ an appropriate method for risk estimation, such as a risk graph method using a tree diagram, a risk matrix method using a table, a numerical scoring method performing addition and multiplication of values, or a hybrid tool method combining these.

[0132] The risk estimation unit 522 determines a risk level of several levels (e.g., six levels) representing the degree of harm, based on, for example, the severity of the injury, the frequency of exposure, and the possibility of avoidance. For example, risk level 1 is the least severe of the six risk levels. Risk level 6 can be the most severe of the six risk levels.

[0133] The risk assessment unit 523 executes risk assessment. The risk assessment unit 523 evaluates whether or not the risk resulting from the risk estimation is a tolerable risk. The risk assessment unit 523 evaluates the risk by comparing the result of the risk estimation, that is, the risk level judgment result, with a threshold value. For example, when the value indicating the risk level is equal to or less than the threshold value, the risk assessment unit 523 evaluates the risk as being tolerable. On the other hand, when the value indicating the risk level is greater than the threshold value, the risk assessment unit 523 evaluates the risk as being unacceptable.

[0134] If the risk is an unacceptable risk, the worker risk assessment simulation unit 54 instructs the risk reduction processing unit 524 to perform risk reduction processing for the risk assessed as an unacceptable risk.

[0135] The risk reduction processing unit 524 judges whether or not risk reduction is possible for a risk judged to be unacceptable. The risk reduction processing unit 524 acquires safety device data. The risk reduction processing unit 524 judges whether or not risk reduction is possible by using the safety device 200 based on the safety device data.

[0136] The risk reduction processing unit 524 judges whether risk reduction by safeguard and additional protection measures is possible based on the safety device data. If it is judged that risk reduction is possible by any of the measures, the risk reduction processing unit 524 judges that risk reduction is possible, and if it is judged that risk reduction is impossible by any of the measures, it judges that risk reduction is impossible and ends the risk reduction processing.

[0137] If the risk reduction processing unit 524 determines that risk reduction is impossible, the production status evaluation unit 25 extracts another countermeasure, and the simulation unit 29 instructs the machine change process simulation unit 51 to simulate the new countermeasure, and the same process is repeated until risk reduction is possible.

[0138] If the risk assessment unit 533 assesses the risk as being tolerable, or if the risk reduction processing unit 534 determines that the risk can be reduced, the countermeasure decision unit 30 decides on each measure as a countermeasure based on the machine risk assessment simulation (step S28).

[0139] Based on the countermeasure determined in step S28, the improvement information generating unit 31 generates a control command, and reflects the countermeasure in the machine (step S29).

[0140] Then, the process proceeds to step S33, where the improvement information generating unit 31 selects the The countermeasures that have been implemented are reflected in the work procedures, for example, by updating the work procedures to reflect the countermeasures.

[0141] If it is determined in step S25 that the cause of the incident is the worker, the work procedure change process simulation unit 53 performs a simulation (step S30) of the process when a change is made to the worker's work procedure.

[0142] The work procedure change process simulation unit 53 performs a simulation to estimate the effect of implementing the countermeasures extracted by the production status evaluation unit 25. The effect of the countermeasures can be judged, for example, by the proximity to a predetermined target value set for a productivity index and / or a safety and health index.

[0143] Returning to the explanation of Figure 12. Following step S30, the worker risk assessment simulation unit 54 performs a simulation of a risk assessment when a change is made to the worker's work procedure (step S31).

[0144] The worker risk assessment simulation unit 54 simulates the risk when the command content determined by the work procedure change process simulation unit 53 is applied to the worker P.

[0145] The worker risk assessment simulation unit 54 includes a hazard identification unit 541, a risk estimation unit 542, a risk assessment unit 543, and a risk reduction processing unit 544. The functions of the hazard identification unit 541, the risk estimation unit 542, the risk assessment unit 543, and the risk reduction processing unit 544 are similar to those of the hazard identification unit 521, the risk estimation unit 522, the risk assessment unit 523, and the risk reduction processing unit 524 of the machine risk assessment simulation unit 52, and therefore the description thereof will be omitted.

[0146] If the risk assessment unit 543 assesses the risk as being tolerable, or if the risk reduction processing unit 544 determines that the risk can be reduced, the countermeasure decision unit 30 decides on each measure as a countermeasure based on the worker risk assessment simulation (step S32).

[0147] Then, the countermeasures determined in step S32 are reflected in the work procedure (step S33).

[0148] Then, the improvement information generating unit 31 issues instructions to educate workers about the updated work procedures and instructions based on the updated work procedures (step S34).

[0149] With reference to FIG. 13, a process including the generation of productivity indexes and safety and health indexes and the determination of countermeasures, starting from a change in the productivity index, will be described.

[0150] First, the index generating unit 24 acquires worker information and environmental information from each storage unit 12 or the like (step S41).

[0151] Next, the index generating unit 24 generates a productivity index and a safety and health index based on the worker information and the environmental information (step S42).

[0152] Based on the environmental information, it is determined whether or not the productivity index has changed (step S43). The presence or absence of a change in the productivity index is determined by comparing the productivity index with a threshold value set for the productivity index stored in the evaluation criterion information storage unit 27. The table in which the thresholds are registered may be switched depending on the target worker, machine, and work environment. Also, the occurrence of an incident may be judged by a judgment model that has learned productivity indicators, safety and health indicators, and worker and environmental information.

[0153] The determination of whether or not there is a change in the productivity index is repeated for the acquired range of worker information and environmental information. If there is no change in the productivity index for the acquired range of worker information and environmental information, the process ends.

[0154] If it is determined that there is a fluctuation in the productivity index, it is determined whether the cause of the productivity index fluctuation is the machine or the worker (step S44). For example, it is determined whether fluctuations in productivity indicators are due to machinery, such as when a machine malfunctions, or whether they are due to workers, such as when the fluctuations are due to variations in labor hours caused by differences in workers' years of experience, level of proficiency, etc. The factors of productivity index fluctuations can be judged by the production status judgment unit based on a predetermined productivity index fluctuation factor judgment table stored in the evaluation criteria information storage unit 27. A productivity index fluctuation factor judgment model generated by learning productivity index fluctuation occurrence cases and factor judgment results may be stored in the evaluation criteria information storage unit 27, and the production status evaluation unit 25 may make a judgment based on this productivity index fluctuation factor judgment model. The processes from step S44 to step S53 are the same as the processes from step S25 to step S34 shown in FIG. 12, and therefore a detailed description thereof will be omitted.

[0155] The production status evaluation unit 25 judges the cause of the productivity index fluctuation, extracts countermeasures based on the countermeasures table, and performs a simulation described later. The countermeasures table is stored in the evaluation criterion information storage unit 27.

[0156] If it is determined in step S44 that the cause of the productivity index fluctuation is a machine, the machine change process simulation unit 51 simulates the process when a change is made to the machine extracted as a countermeasure (step S45).

[0157] Then, the machine risk assessment simulation unit 52 performs a simulation of a risk assessment when a change is made to the machine (step S46).

[0158] Countermeasures are determined based on the worker risk assessment simulation (step S47).

[0159] The policy determined in step S47 is reflected in the machine (step S48).

[0160] In step S44, if it is determined that the cause of the productivity index fluctuation is the worker, the work procedure change process simulation unit 53 performs a simulation of the process when a change is made to the worker's work procedure (step S49).

[0161] Then, the worker risk assessment simulation unit 54 performs a simulation of a risk assessment when a change is made to the worker's work procedure (step S50).

[0162] Countermeasures are determined based on the worker risk assessment simulation (step S51).

[0163] Then, the countermeasures determined in step S51 are reflected in the work procedure (step S52).

[0164] Then, instructions are given to educate workers about the updated work procedures and instructions are given based on the updated work procedures (step S53).

[0165] In this way, the production management support device 120 enables production management that takes into consideration not only productivity but also safety and health by using a productivity index that evaluates productivity and a safety and health index that evaluates safety and health. In addition, it is possible to optimize production management through the productivity index and the safety and health index.

[0166] In addition, in order to make it possible to compare the constituent elements of the present invention with the configurations of the embodiments, the constituent elements of the present disclosure will be described below with the reference numerals in the drawings. <Appendix 1> A worker information acquisition unit (11, 13, 15) for acquiring worker information on workers (P) engaged in production; An environmental information acquisition unit (17, 19, 21) that acquires environmental information related to the environment, including a machine (140) used in the production; an index generating unit (24) that generates a safety and health index related to safety and health and a productivity index related to productivity based on the acquired worker information and the acquired environmental information; A production management support device (120) comprising: <Appendix 2> The production management support device (120) described in Appendix 1 is characterized in that the index generation unit (24) generates the safety and health index and the productivity index based on the acquired worker information and environmental information using a learning model (243) that has been machine-learned to the worker information, the environmental information, the safety and health index, and the productivity index. <Appendix 3> The production management support device (120) described in Appendix 2, characterized in that the learning model (120) is a learning model (120) that has been machine-learned to learn worker information related to the worker and environmental information related to the environment within a certain time range and a certain area. <Appendix 4> The production management support device (120) according to any one of appendix 1 to 3, wherein the worker information includes biometric information of the worker. <Appendix 5> The production management support device (120) according to any one of appendix 1 to 4, wherein the worker information includes worker profile information of the worker. <Appendix 6> The production management support device (120) according to any one of appendixes 1 to 5, wherein the environmental information includes machine profile information of the machine. <Appendix 7> The worker information acquisition unit (11, 13, 15) acquires time information associated with the worker information and the environmental information, The production management support device (120) according to any one of claims 1 to 6, wherein the environmental information acquisition unit (17, 19, 21) acquires location information associated with the worker and the environmental information. <Appendix 8> The production management support device (120) according to any one of claims 1 to 7, further comprising a screen generating unit (24) that generates a screen displaying changes over time of the safety and health index and the productivity index. <Appendix 9> The production management support device according to claim 8, wherein the screen generation unit (24) generates a screen that displays the safety and health index and the productivity index in association with a time axis. <Appendix 10> The production management support device (120) according to any one of appendix 1 to 9, further comprising a countermeasure decision unit (30) that decides countermeasures for ensuring the safety of the worker based on the safety and health index and the productivity index generated in the index generation unit (24). <Appendix 11> a safety and health target receiving unit (32) that receives an input of a target of the safety and health index; a productivity target receiving unit (32) that receives an input of a target of the productivity index; Further equipped with The production management support device (120) described in appendix 10, wherein the countermeasure decision unit (30) decides on the countermeasure based on the received targets of the safety and health index and the productivity index. <Appendix 12> A production plan acquisition unit (11, 17) for acquiring a production plan including the workers and the machines, The production management support device (12) according to appendix 10 or 11, characterized in that the countermeasure includes a change to the production plan. <Appendix 13> the worker information includes worker profile information for the worker; The production management support device (120) according to any one of appendices 10 to 12, wherein the countermeasure includes updating or adding the worker profile information. <Appendix 14> The production management support device (120) according to any one of appendices 10 to 13, wherein the countermeasures include at least one of information for the worker and information for the machine. <Appendix 15> A worker information detection unit (130, 150) for detecting the worker information The production management support device (120) according to any one of appendix 1 to 14, comprising: <Appendix 16> An environmental information detection unit (150, 180) for detecting the environmental information The production management support device (120) according to any one of appendix 1 to 15, comprising: <Appendix 17> A step of acquiring worker information regarding workers engaged in production (S21, S41); Obtaining environmental information relating to the environment, including machines used in the production (S21, S41); A step of generating a safety and health index related to safety and health based on at least the worker information (S22, S42); A step of generating a productivity index related to productivity based on at least the environmental information (S22, S42); A production management support method including: <Appendix 18> A step of determining measures to ensure the safety of the workers based on the safety and health indicators and the productivity indicators (S32, S51). 18. The production management support method according to claim 17, further comprising: <Appendix 19> 19. A production management support program for causing a computer to execute the production management support method according to claim 17 or 18. [Explanation of symbols]

[0167] 11. Worker Profile Information Acquisition Department 13. Worker motion information acquisition unit 15. Worker Biometric Information Acquisition Department 17 Machine profile information acquisition unit 19...Machine operation information acquisition section 21...Work environment information storage unit 24...Indicator generation section 120 Production management support device

Claims

1. A worker information acquisition unit that acquires worker information related to workers engaged in production; an environmental information acquisition unit that acquires environmental information relating to the environment, including machines used in the production; an index generating unit that generates a safety and health index related to safety and health and a productivity index related to productivity based on the acquired worker information and the acquired environmental information; A production management support device comprising:

2. The production management support device of claim 1, characterized in that the index generation unit generates the safety and health index and the productivity index based on the acquired worker information and environmental information using a learning model that has been machine-learned to the worker information, the environmental information, the safety and health index, and the productivity index.

3. The production management support device according to claim 2, characterized in that the learning model is a learning model that has been machine-learned to learn the worker information related to the worker and the environmental information related to the environment within a certain time range and a certain area.

4. 3. The production management support device according to claim 1, wherein the worker information includes biometric information of the worker.

5. 3. The production management support device according to claim 1, wherein the worker information includes worker profile information of the worker.

6. 3. The production management support device according to claim 1, wherein the environmental information includes machine profile information of the machine.

7. The worker information acquisition unit acquires time information associated with the worker information and the environmental information, 3. The production management support device according to claim 1, wherein the environmental information acquisition unit acquires location information associated with the worker and the environmental information.

8. 3. The production management support device according to claim 1, further comprising a screen generating unit for generating a screen displaying changes over time of the safety and health index and the productivity index.

9. 9. The production management support device according to claim 8, wherein the screen generation unit generates a screen that displays the safety and health index and the productivity index in association with a time axis.

10. The production management support device according to claim 1 or 2, characterized in that it further comprises a countermeasure determination unit that determines countermeasures to ensure the safety of the workers based on the safety and health indexes and the productivity indexes generated in the index generation unit.

11. a safety and health target receiving unit that receives an input of a target of the safety and health index; a productivity target receiving unit that receives an input of a target of the productivity index; Further equipped with 11. The production management support device according to claim 10, wherein the countermeasure decision unit decides the countermeasure based on the received targets of the safety and health index and the received targets of the productivity index.

12. A production plan acquisition unit that acquires a production plan including the worker and the machine, 11. The production management support device according to claim 10, wherein the countermeasure includes a change to the production plan.

13. the worker information includes worker profile information for the worker; The production management support device according to claim 10 , wherein the countermeasure includes updating or adding the worker profile information.

14. 11. The production management support device according to claim 10, wherein the countermeasure includes at least one of information for the worker and information for the machine.

15. A worker information detection unit that detects the worker information.

3. The production management support device according to claim 1, further comprising:

16. An environmental information detection unit that detects the environmental information 3. The production management support device according to claim 1, further comprising:

17. Obtaining worker information regarding workers engaged in production; obtaining environmental information about an environment, including machines used in said production; generating a safety and health index related to safety and health based at least on the worker information; generating a productivity index related to productivity based on at least the environmental information; A production management support method including:

18. determining measures to ensure the safety of said workers based on said safety and health indicators and said productivity indicators; 20. The production management support method according to claim 17, further comprising:

19. 19. A production management support program for causing a computer to execute the production management support method according to claim 17 or 18.

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