Information processing method, information processing device, work device management method, work device management system control method, work device management system, article manufacturing method, program, and recording medium.

Abstract

To enable the determination of suitable work equipment for use at the intended site. [Solution] In an information processing method performed by a processing unit, the processing unit acquires first information regarding the cumulative fatigue level accumulated in a plurality of work devices (S2), calculates second information regarding the predicted fatigue level that will occur at the planned usage site for the plurality of work devices (S4), and determines which work device to be used at the planned usage site from among the plurality of work devices based on the first information and the second information (S6).

Description

Technical Field

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[0001] The present invention relates to an information processing method, an information processing apparatus, a management method for a working apparatus, a control method for a working apparatus management system, a working apparatus management system, a method for manufacturing an article, a program, and a recording medium.

Background Art

[0002] For example, there has been proposed a method for calculating the fatigue degree of equipment that would occur due to operating (flying) equipment such as an aircraft fuselage (see Patent Document 1). Further, in the invention of Patent Document 1, it is disclosed that for a plurality of aircraft, the fatigue degree of each aircraft is leveled by cyclically operating in a plurality of regions. <00​​​​​​​​​​​​​​​​​​​​​​​​​​​​The invention described in Patent Document 1 merely cycles through the next destination to equalize the fatigue level of each aircraft's airframe, and operates the aircraft to the assigned destination regardless of fatigue level, and does not necessarily select an aircraft suitable for the next destination. Similarly, the invention described in Patent Document 2 does not accurately calculate the load generated on the transport robot along the next planned transport route, and therefore does not necessarily ensure that a transport robot suitable for the next planned transport route is accurately selected.

[0006] Therefore, the present invention aims to provide an information processing method, an information processing device, a work device management method, a work device management system control method, a work device management system, a method for manufacturing articles, a program, and a recording medium that can determine a work device suitable for use at a planned site. [Means for solving the problem]

[0007] One aspect of the present invention is an information processing method performed by a processing unit, characterized in that the processing unit acquires first information relating to the cumulative fatigue level accumulated in a plurality of work devices, calculates second information relating to the predicted fatigue level for the plurality of work devices based on the cumulative fatigue level and the predicted additional fatigue level that will occur at the planned usage site, and determines which work device to be used at the planned usage site from among the plurality of work devices based on the second information.

[0008] One aspect of the present invention is an information processing device having a processing unit, wherein the processing unit acquires first information relating to the cumulative fatigue level accumulated in a plurality of work devices, calculates second information relating to the predicted fatigue level for the plurality of work devices based on the cumulative fatigue level and the predicted fatigue level to occur at the planned usage location, and determines which work device to be used at the planned usage location from among the plurality of work devices based on the second information.

[0009] One aspect of the present invention is a control method for a work device management system comprising an information processing device having a processing unit, a plurality of work devices, and a management device for managing work devices deployed at a site of use, wherein the management device acquires first information relating to the cumulative fatigue level generated by the deployed work devices, the processing unit acquires the first information from the management device and calculates second information relating to the predicted fatigue level for the plurality of work devices based on the cumulative fatigue level and the predicted fatigue level to be generated at the site of use, and determines which work device to be used at the site of use from among the plurality of work devices based on the second information.

[0010] One aspect of the present invention is a work device management system comprising an information processing device having a processing unit, a plurality of work devices, and a management device for managing the work devices deployed at a site of use, wherein the management device acquires first information relating to the cumulative fatigue level generated by the deployed work devices, the processing unit acquires the first information from the management device and calculates second information relating to the predicted fatigue level for the plurality of work devices based on the cumulative fatigue level and the predicted fatigue level to be generated at the site of use, and determines which work device to be used at the site of use from among the plurality of work devices based on the second information. [Effects of the Invention]

[0011] According to the present invention, it is possible to determine a work device suitable for use at the intended site. [Brief explanation of the drawing]

[0012] [Figure 1] This is a schematic block diagram showing the robot management system according to the first embodiment. [Figure 2] This is a block diagram showing the information processing device according to the first embodiment. [Figure 3] This is a block diagram of the control device according to the first embodiment. [Figure 4] This is a flowchart showing the robot selection process according to the first embodiment. [Figure 5] It is a diagram showing a display screen of robot motion design according to the first embodiment. [Figure 6] It is a diagram showing a display screen of robot addition / editing according to the first embodiment. [Figure 7] It is a diagram showing a display screen of predicted fatigue degree calculation setting according to the first embodiment. [Figure 8] It is a diagram showing a display screen of lent airframe selection setting according to the first embodiment. [Figure 9] It is a diagram showing a display screen of lent airframe selection setting according to the second embodiment. [Figure 10] It is a block diagram schematically showing a robot management system according to the third embodiment.

Modes for Carrying Out the Invention

[0013] <The First Embodiment> Hereinafter, the first embodiment will be described with reference to the drawings.

[0014] [Object of the First Embodiment] For example, an industrial robot (hereinafter, also simply referred to as a "robot") is often used in a production line as manufacturing equipment for manufacturing articles, and once installed, it has the characteristic that it cannot be easily relocated. When reinstalling, the motion design of the robot, interference confirmation with the surroundings, teaching work, etc. must be redone, which involves a great deal of labor. For example, as in the above Patent Document 2, a mechanism for calculating the current fatigue degree from actual data obtained by operating the equipment once and then distributing the next task is not, for example, accurate in predicting the fatigue degree of the next task. That is, since there is not a great deal of labor involved in changing the task, based on the fatigue degree of the next task, the dispersion of the fatigue degree can be achieved in the next next task. However, in the case of an industrial robot as described above, due to the fact that it cannot be easily reinstalled, there is a problem that it is difficult to apply the method as in the above Patent Document 2.

[0015] In addition, a service for renting industrial robots is also being considered. In such a rental service, maintenance of the returned robots is usually carried out regardless of the degree of wear, and they are then lent to the next borrower. However, if it were possible to accurately know in advance the degree of fatigue that is expected to accumulate at the next borrower (hereinafter referred to as the "intended borrower"), for example, only the parts that require maintenance before lending could be maintained and then lent, which would lead to a reduction in the maintenance man-hours at the intended borrower and result in profit for the operator. Viewed another way, performing maintenance in advance in view of the degree of fatigue that will occur at the intended borrower before shipping would increase the accuracy of the maintenance plan at the intended borrower. And since this would lead to a reduction in the number of maintenance times and an increase in the operating hours, it would be beneficial to the users of the intended borrower. Thus, even for robots that are not easily reinstalled, by accurately predicting the future degree of fatigue and realizing the allocation of the next task, a rental mechanism that benefits both the operator and the user can be constructed.

[0016] In the operation of an aircraft as in Patent Document 1, it is difficult to predict future fatigue during the operation design stage because the fatigue during flight is greatly affected by factors such as weather. Also, in the form of a transport robot as in Patent Document 2, since the transport service determines its operation in response to requests from service recipients, it is difficult to accurately predict how much of which operation will be performed during the operation design stage.

[0017] On the other hand, industrial robots are installed on production lines where environmental conditions such as temperature and humidity are controlled, and most of them are used in a form where the same operations are repeated. Therefore, it is possible to relatively accurately predict the degree of fatigue of the robot over a certain period, and it is also possible to assume in advance the influence of temperature and humidity.

[0018] Therefore, the first embodiment described below aims to accurately predict the degree of fatigue applied to the robot from motion design information for performing a task at the next planned use site, and to select the robot most suitable for performing the task from among multiple robots. This focuses on the characteristics of industrial robots that "the influence received from external factors is kept constant" and "they basically repeat the same motion." The details of the first embodiment for achieving this objective are described below.

[0019] [Robot Management System] First, an overview of the robot management system as a work device management system according to the first embodiment will be explained using Figures 1 to 3. Figure 1 is a schematic block diagram showing the robot management system according to the first embodiment. Figure 2 is a block diagram of the information processing device according to the first embodiment. Figure 3 is a block diagram of the management device according to the first embodiment. The information processing device 101 shown in Figure 1 is a block diagram showing the functions achieved by the hardware configuration of the information processing device 101 shown in Figure 2. Similarly, the management device 201 of the first production line shown in Figure 1 is a block diagram showing the functions achieved by the hardware configuration of the management device 201 shown in Figure 3.

[0020] (Configuration of information processing device) First, the hardware configuration of the information processing unit 101 of the robot management system 1 will be explained using Figure 2. As shown in Figure 2, the information processing unit 101 includes a CPU (Central Processing Unit) 102, which is an example of a processor. The CPU 102 is an example of a processing unit. The information processing unit 101 also includes a ROM (Read Only Memory) 103, a RAM (Random Access Memory) 104, and an HDD (Hard Disk Drive) 105 as storage units. Furthermore, the information processing unit 101 includes a recording disk drive 106, and an input / output interface consisting of a display unit 108, a keyboard 109, and a mouse 110 as operation units.

[0021] The CPU 102, ROM 103, RAM 104, HDD 105, recording disk drive 106, display 108, keyboard 109, and mouse 110 are connected to each other by a bus so that they can communicate with one another. The ROM 103 stores the basic programs related to the operation of the computer. The RAM 104 is a storage device that temporarily stores various data, such as the results of calculations performed by the CPU 102. The HDD 105 stores the results of calculations performed by the CPU 102 and various data acquired from external sources, as well as a program 107 for executing various processes described later. Program 107 is application software that enables the CPU 102 to perform various processes described later. Therefore, the CPU 102 can perform various processes described later by executing program 107 stored in the HDD 105. The HDD 105 also has an area that serves as a database 120 for recording data such as various models obtained from the results of the various processes described later. The recording disk drive 106 can read various data and programs recorded on the recording disk 150. This database 120 includes, in more detail, the storage area for various types of information of the motion design unit 162, the storage area for the robot information storage unit 166, and so on.

[0022] In this embodiment, the non-temporary recording medium readable by the computer is the HDD 105, and the program 107 is recorded on the HDD 105, but this is not the only possible representation. The program 107 may be recorded on any non-temporary recording medium readable by the computer. Examples of recording media that can be used to supply the program 107 to the computer include flexible disks, hard disks, optical disks, magneto-optical disks, magnetic tapes, non-volatile memory, and the like.

[0023] Furthermore, a management device 201, which will be described in more detail later, is connected to the information processing device 101. From the management device 201, actual operating information of the robot 900, which will be described in more detail later, is transmitted to the CPU 102. In this embodiment, the robot 900 has a multi-jointed arm as a manipulator, and is a so-called multi-joint robot that rotates or extends each axis in its joints 901 (see Figures 5 and 6).

[0024] (Configuration of the control system for the first production line) Next, the hardware configuration of the control device 201 of the first production line will be explained using Figure 3. The control device 201 includes a CPU 204, which is an example of a processor. The CPU 204 is an example of a control unit. The control device 201 also includes a ROM 205, RAM 206, and HDD 207 as storage units. Furthermore, the control device 201 includes a recording disk drive 208 and an input / output interface 209.

[0025] The CPU 204, ROM 205, RAM 206, HDD 207, recording disk drive 208, and interface 209 are connected to each other by a bus, enabling communication. The ROM 205 stores the basic program related to the operation of the computer. The RAM 206 is a memory device that temporarily stores various data, such as the results of calculations performed by the CPU 204. The HDD 207 stores the results of calculations performed by the CPU 204 and various data acquired from external sources, as well as a program 210 that causes the CPU 204 to perform various processes described later. Program 210 is application software that enables the CPU 204 to perform various processes described later. Therefore, the CPU 204 can perform control processing by executing the program 210 stored in the HDD 207, and control the movement of the manipulator (each joint 901) of the robot 900 (not shown in the illustration). The recording disk drive 208 can read various data and programs stored on the recording disk 250.

[0026] In this embodiment, the non-temporary recording medium readable by the computer is the HDD207, and the program 210 is recorded on the HDD207, but this is not the only possible representation. The program 210 may be recorded on any non-temporary recording medium readable by the computer. Examples of recording media that can be used to supply the program 210 to the computer include flexible disks, hard disks, optical disks, magneto-optical disks, magnetic tapes, non-volatile memory, and the like.

[0027] In this embodiment, information processing and control processing are performed by one computer, i.e., one CPU, but this is not the only option. Information processing and control processing may be performed by multiple computers, i.e., multiple CPUs 102, 204.

[0028] (Configuration of the robot management system) As shown in Figure 1, the robot management system 1 according to the first embodiment comprises an information processing device 101, a first production line management device 201, and a plurality of robots 900. The first production line, as a production facility, is the destination to which the robots 900 are leased, and in this embodiment, it refers to the production line before the robots 900 are returned. The second production line, which is not shown in Figure 1 (see Figure 10), as a production facility, is the destination to which the robots 900 returned from the first production line will be leased next, and in other words, it refers to the production line of the destination to which the robots 900 are leased. The robots 900 are so-called industrial robots (see, for example, Figures 5 and 6), and are composed of, for example, six-axis articulated robots, with each joint 901 having a motor and a reduction gear 902 as a mechanism for reducing its rotation.

[0029] The control device 201 has a communication unit 261 configured with an interface 209 (see Figure 3), and the communication unit 266 is configured to communicate with multiple robots 900 and the information processing device 101 in the first production line. The control device 201 also includes a machine information storage unit 262 and a machine information acquisition unit 263.

[0030] The machine information acquisition unit 263 acquires machine operation information, which consists of values ​​from various devices and sensors that make up the first production line. This machine operation information includes, for example, temperature, humidity, the motor rotation speed of each joint 901 per operation cycle of the robot 900, the device utilization rate, and the cycle time. However, it does not include only these items; all information obtained during operation is included. The machine information acquisition unit 263 transmits the machine operation information acquired from the first production line to the machine information storage unit 262, where it is stored. The machine information storage unit 262 generally plays a role similar to that of a MES (Manufacturing Execution System), such as a log server or operation management system. The machine operation information collected in this way is transmitted to the information processing device 101 via the communication unit 261.

[0031] The information processing device 101 includes a communication unit 161, an operation design unit 162, and a user interface unit 163, which function through the hardware configuration described above. The information processing device 101 also includes a simulation unit 164, a fatigue level estimation unit 165, a robot information storage unit 166, and a robot selection unit 167, which function through the hardware configuration described above.

[0032] For example, a user, who is a designer, uses the information processing device 101 to design the operation of the robot 900, that is, to generate an operation program as operation setting information that sets the operation of the robot 900 on the production line. The operation program can be designed for use on any production line, but in this embodiment in particular, an operation program is generated for the planned lender (i.e., the second production line) to which the robot 900 will be lent.

[0033] Specifically, the designer inputs motion design information to the information processing device 101 via the user interface unit 163 (keyboard 109, mouse 110) to design and set the motion program for the robot 900. The input motion design information is processed and taken in by the motion design unit 162 (CPU 102), which has CAD modeling functions and robot motion program creation functions, and an motion program is generated according to this information. The response from the motion design unit 162 is displayed to the designer via the user interface unit 163 (display 108).

[0034] In other words, the motion design information for designing the operation program for the robot 900 at the planned rental location is input by the designer to the motion design unit 162. Here, the motion design information includes the 3D model and internal structure of the robot 900, the 3D model and equipment configuration of the production line, and the already generated operation program for the robot 900. The motion design information also includes the operating speed and acceleration of each part of the robot 900, end-effector weight, motor rotation speed, operation cycle time, number of operating cycles, operating rate, the rental period to the rental location (planned rental location), and environmental information such as temperature and humidity of the operating site.

[0035] While not all of these items are necessary for motion design information, it includes all information that has been revealed during the design phase of the robot 900's motion. Furthermore, motion design information also includes information that becomes clear by combining the items mentioned above. For example, this includes the motor rotation speed at each joint 901 per cycle of robot motion, which becomes clear by combining the internal structure of the robot 900, the already designed motion program, speed, and acceleration. The information revealed by this combination is displayed to the designer via the user interface unit 163 (display 108).

[0036] Furthermore, the functions of the motion design unit 162 are not limited to the CAD modeling function and robot motion program creation function described above. For example, it may also include functions commonly found in CAD software and simulation software, such as structural analysis functions and motion preview functions.

[0037] The robot information storage unit 166 stores and accumulates information input to the information processing device 101. Specifically, the robot information storage unit 166 stores all the information known at the operational design stage of the robot 900, such as the internal structure of the industrial robot, the designed operation program, speed, acceleration, loan period to the planned loaner, cycle time, and operating rate. The robot information storage unit 166 also stores and accumulates actual machine operation information transmitted from the management device 201. This actual machine operation information includes information about when the robot 900 was operated, and by cumulatively adding the fatigue level from this information, it can be stored as the first information regarding the cumulative fatigue level currently accumulated in the robot 900 (hereinafter simply referred to as "cumulative fatigue level"). Since the robot 900 is a multi-joint robot with multiple joints 901 each having a reduction gear 902, this cumulative fatigue level is managed internally within the information processing device 101 for each of the multiple joints of the robot 900. Furthermore, the cumulative fatigue level includes a value of 0. In other words, any robot 900 that has not yet been loaned out can be managed with a cumulative fatigue level of 0. In this case, the prospective borrower may use the predicted additional fatigue level, described later, as the predicted fatigue level when selecting which robot 900 to loan out.

[0038] The simulation unit 164 uses the information from the robot information storage unit 166 to calculate second information regarding the predicted additional fatigue level in the process at the planned borrowing location (hereinafter simply referred to as "predicted additional fatigue level"). Here, the predicted additional fatigue level in the process at the planned borrowing location means the fatigue level that is predicted to accumulate in the robot 900 during the borrowing period, in addition to the fatigue level currently accumulated in the robot 900. The predicted additional fatigue level can be obtained, for example, by multiplying the number of operating cycles during the borrowing period by the motor rotation speed of each joint 901 in one cycle operation. This predicted additional fatigue level is also managed internally by the information processing device 101 for each of the multiple joints of each robot 900.

[0039] The fatigue estimation unit 165 calculates the predicted future fatigue level of the robot 900 based on the predicted additional fatigue level at the borrower's process calculated by the simulation unit 164 and the cumulative fatigue level of the robot 900 stored in the robot information storage unit 166. The predicted future fatigue level of the robot 900 represents, for example, the fatigue level accumulated in the robot 900 at the end of the borrower's loan period. That is, it can be obtained by adding the predicted additional fatigue level at the borrower's process calculated by the simulation unit 164 and the cumulative fatigue level of the robot 900 stored in the robot information storage unit 166. However, the calculation method is not limited to this and can be freely designed by the designer as appropriate. The calculation of the predicted future fatigue level of the robot is performed for all of the multiple robots 900 that are candidates for loan. Furthermore, this predicted fatigue level is also managed internally within the information processing device 101 for each of the multiple joints of each robot 900.

[0040] The fatigue levels of multiple robots 900 calculated by the fatigue level estimation unit 165 are output to the robot information storage unit 166 and the robot selection unit 167. The robot information storage unit 166, upon receiving the predicted fatigue level information, updates the cumulative fatigue level of the robots 900 that have been selected and determined to be loaned to a prospective lender by overwriting it with the predicted fatigue level. This update is performed at the time it is decided that the robot 900 will be loaned.

[0041] The robot selection unit 167 determines and selects the most suitable robot 900 to lend from among the multiple robots 900 currently available for lending, based on the predicted fatigue level input from the fatigue level estimation unit 165. The logic for determining the most suitable robot 900 can be input by the designer via the user interface unit 163. In this embodiment, for example, a determination process can be input in which the difference between the predicted fatigue level at each joint 901 of the robot 900 and the threshold set for each joint 901 is calculated, and the robot 900 with the smallest total value is determined to be the robot 900 to lend. The result of the robot selection unit 167's determination of the most suitable robot 900 to lend is notified to the designer via the user interface unit 163 (display 108).

[0042] Regarding the selection method for choosing the most suitable robot 900 to lend out, it may be a method in which the designer selects from multiple selection methods pre-implemented in the system, or it may be a method that the designer can freely program. Furthermore, it is not limited to these, but any method that achieves the objective of determining which robot 900 to lend out from among the multiple robot 900s owned is acceptable.

[0043] [Robot Selection Process] Next, the robot selection process for selecting the most suitable robot 900 to lend to the prospective borrower in the robot management system 1 described above will be explained using Figures 4 to 8. Figure 4 is a flowchart of the robot selection process according to the first embodiment. Figure 5 is a diagram showing the display screen for robot motion design according to the first embodiment. Figure 6 is a diagram showing the display screen for robot addition and editing according to the first embodiment. Figure 7 is a diagram showing the display screen for predictive fatigue calculation settings according to the first embodiment. Figure 8 is a diagram showing the display screen for loan unit selection settings according to the first embodiment. Note that Figure 2 is the robot selection process executed by the CPU 102 of the information processing device 101, but it is shown in accordance with the process executed by the designer, so it can also be called the designer's workflow. In addition, the display screens shown in Figures 5 to 8 can also be called user interface screens on which the designer makes settings, edits, adds, and decisions.

[0044] First, the CPU 102 of the information processing device 101 designs the production line in which the rented robot 900 will operate, based on the designer's input (S1). Specifically, the designer operates the robot selection button 401 and the model creation button 411 on the robot motion design display screen 400 shown in Figure 5 to generate models of the robot 900 and surrounding objects (parts, stands, etc.) in a virtual space. Then, by operating this model, the actual production operation is simulated, including checking for interference between the robot 900 and surrounding objects. The generation of this model and the simulation can be checked in the motion preview display area 413. Note that if it is determined that checking for interference between the robot and surrounding objects and simulating production operation are unnecessary, this step does not need to be performed.

[0045] Next, the CPU 102 of the information processing device 101 sets information (i.e., motion design information) for multiple robots 900 that are candidates for loan based on the designer's input (S2). Specifically, the designer inputs and sets information for multiple robots 900 that are candidates for loan by operating the robot add / edit button 505 on the robot add / edit display screen 500. The information for multiple robots 900 that are candidates for loan here includes all information related to industrial robots, such as the 3D model, internal structure, model number, serial number, usage history, maintenance history, and cumulative fatigue level, and is not particularly limited. The input information for multiple robots that are candidates for loan is stored in the robot information storage unit 166 in a state where it is possible to identify which robot each piece of information belongs to. At this time, information that becomes clear by combining the input robot information is also stored.

[0046] Next, the CPU 102 of the information processing device 101 designs an operation program for each of the multiple robots 900, using the information set in step S2, based on the designer's input (S3). Specifically, for example, the designer operates the robot selection button 402 on the robot motion design display screen 400 shown in Figure 5 to select one of the multiple robots 900. The selected robot 900 is displayed in the selected robot display area 408, and the operation program for that robot 900 is displayed in the operation program display area 409. In other words, the CPU 102 displays a screen (operation program display area 409) on the display 108 that previews the work (i.e., the operation program) that a predetermined robot 900 (predetermined work device) among the multiple robots 900 will perform on the second production line. Then, the CPU 102 designs the operation program for the selected robot 900 by operating the teaching point editing button 412 in the operation preview display area 413, etc. The display in the operation program display area 409 may be written in robot language or in a visual language format, and is not particularly limited to that.

[0047] The CPU 102 will display on the display screen 400 for robot motion design the following information together on the display 108: an image corresponding to a specific robot 900 among multiple robots 900 (selected robot display area 408), the cumulative fatigue level of the specific robot 900 (current fatigue level display area 406) and the predicted fatigue level (predicted fatigue level display area 407), the program for the work that the specific robot 900 will perform on the second production line (motion program), and a screen that previews the work that the specific robot 900 will perform on the second production line (motion preview display area 413).

[0048] Next, the CPU 102 of the information processing device 101 designs a logic for predicting fatigue levels based on the designer's input and using the information set up to this point (S4). Specifically, for example, the designer presses the fatigue level calculation element setting button 501 on the robot addition / editing display screen 500, and transitions to the predicted fatigue level calculation setting display screen 600 shown in Figure 7. On this predicted fatigue level calculation setting display screen 600, the designer can freely design the elements and calculation formulas for calculating fatigue levels. That is, on the predicted fatigue level calculation setting display screen 600, by operating the element addition button 601, the designer can arbitrarily read information for each item from the information stored in the robot information storage unit 166, and a list of the read items is displayed in the list display area 603. It is also possible to delete unnecessary items from the read items by operating the element deletion button 602. The designer can freely design a predicted fatigue level calculation formula using these read elements and display it in the calculation formula display area 604. The formula for calculating predicted fatigue level can use arithmetic operations, general functions, or custom-made functions, but is not limited to these.

[0049] A designer can design a predictive fatigue calculation formula, for example, as follows: First, an arbitrary coefficient a is added to each joint 901 of the robot 900 that is a candidate for loan. Here, the arbitrary coefficient a refers to a parameter that the designer wants to add variably to each joint 901, such as a value based on the end-effector weight or the strength of each joint 901. Here, an arbitrary coefficient a is used for the sake of simplifying the calculation formula, but parameters stored in the robot information storage unit 166 may also be used, and there are no restrictions on the number or type used. Next, the amount of movement b of each joint 901 in one cycle is calculated. The amount of movement b of each joint 901 in one cycle can be calculated based on the structure of the robot 900's joints 901 and the motion program (motion commands and teaching points, velocity, acceleration). Furthermore, the number of operating cycles c during the loan period is defined. Here, the number of operating cycles c during the loan period can be calculated based on the device cycle time, utilization rate, and loan period information. The amount of movement b of each joint 901 in one cycle operation and the number of operating cycles c during the loan period are pieces of information that can be determined by multiplying the input robot 900 information. For example, if the information is stored in the robot information storage unit 166, it can be read from there; otherwise, it can be calculated by writing a formula in the relevant operation. Finally, a formula is defined as the calculation formula for the predicted fatigue level H, which adds the result of multiplying an arbitrary coefficient a by the amount of movement b of each joint 901 in one cycle operation and the number of operating cycles c during the loan period to the cumulative fatigue level d. The subscript "j" in the calculation formula for the predicted fatigue level H shown in the calculation formula display area 604 indicates the joint number of the robot 900.

[0050] After setting up the predicted fatigue level calculation as described above, the designer can press the predicted fatigue level calculation execution button 502 on the robot addition / editing display screen 500 shown in Figure 6 to predict the future fatigue level of each of the multiple robots 900 in their possession. The current fatigue level and the predicted fatigue level are then stored in the robot information storage unit 166 and displayed in the current fatigue level display area 506 and the predicted fatigue level display area 508, respectively, and notified to the designer.

[0051] Next, the CPU 102 of the information processing device 101 designs a logic to select a robot 900 suitable for loan to a prospective borrower, based on the designer's input (S5). The logic for selecting a robot 900 suitable for loan may be a method in which the designer chooses from multiple selection methods pre-implemented within the system, or it may be a method that can be freely programmed. Here, an example of the latter method, which allows for free programming, will be explained.

[0052] Specifically, for example, a designer presses the loan robot selection setting button 503 on the robot addition / editing display screen 500, transitioning to the loan robot selection setting display screen 700 shown in Figure 8. On this loan robot selection setting display screen 700, the designer can freely design the elements for loan robot selection and the loan robot selection determination formula. That is, by operating the element addition button 701, each item can be arbitrarily read from the information stored in the robot information storage unit 166, and a list of the read items is displayed in the list display area 704. It is also possible to delete unnecessary items from the read items by operating the element deletion button 702. Furthermore, by pressing the threshold addition button 703, it is possible to add an arbitrary threshold as an element. The designer can freely design the loan robot selection determination formula using these read elements and display it in the calculation formula display area 705. The loan robot selection determination formula can use arithmetic operations, general functions, or custom functions, but is not limited to these.

[0053] The designer can design a loan robot selection determination formula, for example, as follows: First, the element addition button 701 is operated to read the predicted fatigue level Hij from the robot information storage unit 166. Next, the threshold addition button 703 is operated to register the fatigue level threshold Tj for each joint 901 that is determined to require maintenance. Here, the subscript "j" in the predicted fatigue level Hij and threshold Tj represents the joint number of the robot 900 on hand, and the subscript "i" in the predicted fatigue level Hij represents the serial number of the robot 900 on hand. Note that this expression is used for the sake of simplifying the formula, but the method is not limited to any method that allows the content of the displayed information to be understood. Here, the difference between the predicted fatigue level Hij and the threshold Tj for each joint 901 is calculated, and the sum of the differences for each joint 901, Di, is calculated for each robot. Then, a calculation formula is defined as the loan robot selection determination formula, which determines that the robot 900 with the smallest sum of Di is the robot 900 to be loaned (loan robot R).

[0054] After setting the rental robot selection as described above, the CPU 102 of the information processing device 101 selects and determines the robot 900 most suitable for rental from among the multiple robots 900 available, based on the designer's input (S6). Specifically, the designer operates the rental robot selection execution button 504 on the robot addition / editing display screen 500 shown in Figure 6, thereby selecting the robot 900 most suitable for rental from among the multiple robots 900 available. The selected robot 900 is then notified to the designer. In detail, for "Robot 1" to "Robot 4" shown in Figure 6, a score is calculated and displayed in the score display area 507 based on the sum of the differences between the threshold Ti and the predicted fatigue Hij of each joint 901 (see the predicted fatigue display area 508). Specifically, images corresponding to multiple robots 900, the cumulative fatigue level of each robot 900 (original fatigue level: display area 506), and the predicted fatigue level (display area 508) are associated and displayed on the display 108. The robot with the best score is then selected and displayed in the selected robot display area 408 on the robot motion design display screen 400 shown in Figure 5 (in Figure 5, "Robot 2" is displayed). In this embodiment, as an example, a score is assigned to each robot 900 and notified to the designer, but any method that can identify the robot 900 best suited to the robot 900 to be lent out is acceptable.

[0055] The designer then checks the results on the robot motion design display screen 400 shown in Figure 5, and confirms which robot 900 to lend by operating the loan robot confirmation button 404 while the robot 900 to lend is selected.

[0056] [Summary of the First Embodiment] As explained above, in the information processing method of the information processing device 101 in the robot management system 1 according to the first embodiment, first, the CPU 102 acquires the cumulative fatigue level accumulated in the loan destination (first production line) of the multiple robots 900. Specifically, this cumulative fatigue level is calculated based on actual machine operation information acquired from the management device 201 of the first production line (see S2). In other words, the fatigue level currently possessed by the multiple robots 900 is acquired.

[0057] Next, the CPU 102 calculates information regarding the predicted additional fatigue level for multiple robots 900 at the planned loan destination (second production line). Specifically, the predicted additional fatigue level is calculated (simulated) by the simulation unit 164 using fatigue prediction logic, based on the motion program for the planned loan destination process designed by the motion design unit 162 (see S3) (see S4). In addition, when calculating the predicted additional fatigue level, the fatigue level of each joint 901 of the multi-joint robot robot 900 (especially the reduction gear 902 within it) is calculated. In other words, the fatigue level of the part of the robot 900 with the lowest durability is calculated, which improves the accuracy of the durability calculation.

[0058] Then, the CPU 102 determines and selects the robot 900 to be used by the intended borrower from among the multiple robots 900, based on the cumulative fatigue level and the predicted additional fatigue level. Specifically, for the multiple robots 900 on hand, it calculates the predicted fatigue level Hij by adding the predicted additional fatigue level to the cumulative fatigue level obtained above, and determines and selects the robot 900 that has the smallest difference between the predicted fatigue level Hij and the threshold Tj (see S5 and S6).

[0059] This makes it possible to accurately determine which Robot 900 is suitable for use at the planned loan site (second production line). In particular, by generating an operation program that determines the operation of Robot 900 at the planned loan site and performing a simulation based on that operation program, it is possible to accurately calculate the predicted additional fatigue that will occur at the planned loan site, enabling accurate determination of robot selection.

[0060] Furthermore, by determining and selecting the robot 900 with the smallest difference between the predicted fatigue level Hij and the threshold Tj, it is possible to select a robot 900 that can just barely withstand use at the planned loan destination (second production line). This allows robots 900 with low cumulative fatigue to be kept on hand, and if there is another planned loan destination with a higher predicted additional fatigue level, it becomes possible to loan out the robot 900 with low cumulative fatigue. Therefore, it is possible to prevent situations where, for example, a surplus robot 900 is loaned out first, making it impossible to loan out robots 900 to other planned loan destinations, and thus it becomes possible to loan out multiple robots 900 without waste.

[0061] In the first embodiment described above, lending (renting) multiple robots 900 to other businesses was used as an example, but this is not the only example. For example, if the same business (within the same company) deploys the most suitable robot 900 to multiple production lines, the user does not have to be another business, meaning that it does not matter who owns the robot 900.

[0062] <Second Embodiment> Next, a second embodiment, which is a modified version of the first embodiment described above, will be explained with reference to Figure 9. Figure 9 is a diagram showing the display screen for selecting a rental unit according to the second embodiment. In this explanation of the second embodiment, the same reference numerals are used for parts that are the same as those in the first embodiment, and their explanations are omitted.

[0063] In the first embodiment described above, a robot 900 was selected based on a small difference between the predicted fatigue level Hij and the threshold Tj. This selects a robot 900 that can barely withstand use at the intended lending site, but it leaves no margin for error if, for example, there are changes in operating hours or production plans. As a result, the actual fatigue level of the loaned robot 900 may be higher than the predicted fatigue level, requiring maintenance during the loan period and potentially leading to a temporary shutdown of the production line. In this second embodiment, to solve this problem, a safety factor is applied when selecting the robot 900.

[0064] In detail, when the CPU 102 of the information processing device 101 designs a logic (S5) to select a robot 900 suitable for loan to a prospective borrower based on the designer's input, a safety factor is set in the loan robot selection determination formula. Specifically, on the loan robot selection setting display screen 1700 shown in Figure 9, the designer can arbitrarily read each item from the information stored in the robot information storage unit 166 by operating the element addition button 1701. The list of read items is then displayed in the list display area 1704. It is also possible to delete unnecessary items from the read items by operating the element deletion button 1702. Furthermore, it is possible to add an arbitrary threshold as an element by pressing the threshold addition button 1703.

[0065] When the designer designs the loan robot selection determination formula using these read-out elements, they add a safety factor FoS, as shown in the calculation formula display area 1705. That is, the safety factor FoS is a coefficient multiplied by the predicted fatigue level Hj, and "Hj × FoS" can be defined as the predicted safe fatigue level. Then, in the loan robot selection determination formula, by setting the formula to "Hj × FoS ≤ Tj" as a condition that the predicted safe fatigue level is lower than the threshold Tj of fatigue level requiring maintenance, the possibility of maintenance being required during the loan period can be reduced. In other words, in this second embodiment, it is checked whether the value obtained by multiplying the predicted fatigue level Hj of each joint 901 of the robot 900 by the safety factor FoS is below the threshold Tj. Then, if the predicted fatigue level Hj obtained by multiplying by the safety factor FoS is lower than the threshold Tj for all joints 901, the values ​​of each joint 901 are added together to obtain the total value Di for the robot 900. Perform the same calculation on all of the available Robot 900s, and select the Robot 900 with the lowest total value Di to lend out.

[0066] As explained above, in the second embodiment, for robots 900 whose value obtained by multiplying the predicted fatigue degree Hj by the safety factor FoS does not exceed the threshold Tj, a total value Di is calculated, and the robot 900 with the lowest total value Di is determined and selected as the robot 900 to be loaned. This makes it possible to select the robot 900 that is least likely to require maintenance at the intended borrower.

[0067] Furthermore, the other configurations, operations, and effects of the second embodiment described above are the same as those of the first embodiment, so their description will be omitted.

[0068] <Third Embodiment> Next, a third embodiment, which is a modified version of the first embodiment described above, will be explained with reference to Figure 10. Figure 10 is a schematic block diagram showing the robot management system according to the third embodiment. In this explanation of the third embodiment, the same reference numerals are used for parts similar to those in the first embodiment, and their explanations are omitted.

[0069] For example, if the loan period for robot 900 is long, and maintenance of robot 900 is originally required during the loan period, a maintenance plan for robot 900 may be created. However, after robot 900 has started operation, for example, if there is a change in the initially planned production schedule and an increase in product (goods) production is required, the daily operating hours or loan period of robot 900 may be extended. In such cases, it may be necessary to change the maintenance plan for robot 900. In this third embodiment, such cases are dealt with by the method described below.

[0070] In the robot management system 1 of this third embodiment, as shown in Figure 10, in addition to the management device 201-1 of the first production line which was the borrower, the management device 201-2 of the second production line which was scheduled to be borrowed is also connected to the information processing device 101 in a communicable manner. The configuration of these management devices 201-1 and 201-2 is the same as that of the management device 201 described in the first embodiment, so a description of them will be omitted.

[0071] After the robot 900 is loaned out and begins operation, the control device 201-2 of the second production line transmits actual machine operation information to the information processing device 101. In other words, the information processing device 101 acquires the fatigue level of the robot 900 operating on the second production line. This fatigue level is recorded in the robot information storage unit 166 and may be updated as needed, for example, as a cumulative fatigue level. If there is a discrepancy between the information at this time and the information assumed during the robot motion design stage, the relevant information is overwritten and updated. Examples of such discrepancies include the equipment utilization rate, cycle time, and the robot's motion program (including teaching points, speed, and acceleration).

[0072] Then, if there is a discrepancy between the predicted fatigue level predicted (assumed) based on the robot motion design and the fatigue level information transmitted from the management device 201-2, the CPU 102 of the information processing device 101 recalculates the predicted fatigue level. It then notifies the designer of the prediction result. Specifically, for example, if it is determined that there will be a change in the timing or number of maintenance until the end of the loan period, the CPU 102 notifies the designer of this fact via the user interface unit 163 (display 108, etc.), that is, it notifies the designer of the prediction result. This makes it possible to propose changes to the maintenance plan.

[0073] Furthermore, in production lines that have already begun operation, there may be situations where changes to the originally planned maintenance schedule cannot be accepted. For example, this could occur if the preceding and succeeding production processes cannot be changed, or if the maintenance days for the production line are predetermined.

[0074] In this case, a proposed modification of the robot 900's movements that allows it to comply with the originally planned maintenance schedule is created using the functions of the motion design unit 162 and the simulation unit 164. Creating this proposed modification of the robot's movements means changing the movements to reduce the load applied to the joints 901 where the predicted fatigue level exceeds a threshold. For example, this could involve changing the robot's motion program (teaching points, velocity, acceleration). This process of generating such proposed modifications may be performed fully automatically by the information processing device 101, or the designer may manually redesign the robot's movements in accordance with the changes in the predicted fatigue level.

[0075] As described above, in the third embodiment, the information processing device 101 acquires actual machine operation information from the second production line where the robot 900 has started operating. The information processing device 101 then updates the predicted fatigue level of the operating robot 900 based on this actual machine operation information. This makes it possible for designers to investigate the effects and take countermeasures.

[0076] Furthermore, the other configurations, operations, and effects of the third embodiment described above are the same as those of the first embodiment, so their description will be omitted.

[0077] <Possibility of other embodiments> In the first to third embodiments described above, the robot 900 was described as an industrial robot as an example, but it is not limited to this. For example, as a work device that performs actions related to work, it could be a cleaning robot, a serving robot in a restaurant, a transport robot or delivery drone that carries luggage, a pet robot, or any other robot or mobile device that performs various tasks. In other words, it can be any work device that accumulates fatigue at the place of use or planned place of use. Furthermore, as an industrial robot, it could be any type of robot arm, such as a horizontal articulated robot arm, a parallel link robot arm, or a Cartesian robot.

[0078] Furthermore, in the first to third embodiments, the reduction gear 902 of the robot 900 was described as an example of a mechanical part, but it is not limited to this. For example, any mechanism used in the robot 900, such as sensors, links, or motors, may be used as the mechanical part to measure or predict the degree of fatigue.

[0079] Furthermore, in the first to third embodiments, a method was described in which the cumulative fatigue level and predicted fatigue level are calculated for each of the multiple joints in the robot 900. However, the method is not limited to this; for example, if a particular joint is subjected to a heavy load and is the joint that will be the first to require maintenance, the cumulative fatigue level and predicted fatigue level may be obtained or calculated only for that particular joint. This can reduce the processing load on the information processing device 101.

[0080] Furthermore, in the first to third embodiments, the explanation was given assuming that the robot 900 is leased to one intended use location (intended loan location). However, the system is not limited to this, and it is also possible to calculate the predicted fatigue level for two or more intended use locations and determine and select the robot 900 to be used at those locations based on that calculation. In other words, suppose there is a second intended use location with different operation from the first intended use location. In this case, first, the processing unit (CPU 102) calculates second information regarding the predicted fatigue level for multiple work devices (robots 900) based on the cumulative fatigue level and the predicted additional fatigue level that will occur at the first intended use location. Furthermore, the processing unit calculates third information regarding the predicted fatigue level based on the cumulative fatigue level and the predicted additional fatigue level that will occur at the second intended use location. Then, based on the second and third information, the processing unit determines which work device to use at the first intended use location and which work device to use at the second intended use location from among the multiple work devices. By configuring the system in this way, it is possible to select and deploy the most suitable work device for multiple intended use locations.

[0081] This disclosure can also be implemented by supplying a program that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be implemented by a circuit (e.g., an ASIC) that implements one or more functions.

[0082] Summary of this disclosure This disclosure includes at least the following: (Method 1) In an information processing method performed by a processing unit, The aforementioned processing unit, First information regarding the cumulative fatigue level accumulated in multiple work devices is obtained, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted additional fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. An information processing method characterized by the following: (Method 2) The aforementioned plurality of work devices have a mechanism that performs operation, The first information is information relating to the cumulative fatigue level in the mechanism, The second piece of information is information relating to the predicted fatigue level in the mechanism. The information processing method according to Method 1, characterized in that (Method 3) The aforementioned multiple work devices are articulated robots having multiple joints including the aforementioned mechanism, The first information is information regarding the cumulative fatigue level managed for each of the multiple joints, The second information is information regarding the predicted fatigue level managed for each of the multiple joints. The information processing method according to method 2, characterized in that (Method 4) The aforementioned multiple work devices are articulated robots having multiple joints including the aforementioned mechanism, The first information is information relating to the cumulative fatigue level in a specific joint among the plurality of joints, The second piece of information is information relating to the predicted degree of fatigue in a specific joint among the plurality of joints. The information processing method according to method 2, characterized in that (Method 5) The aforementioned predicted additional fatigue level is information calculated based on the operation setting information that sets the operation of the work device at the intended use location. An information processing method according to any one of methods 1 to 4, characterized by the above. (Method 6) The aforementioned work device is a robot having an arm, The aforementioned operation setting information includes at least one of the following: teaching point, operating speed, acceleration, end-effector weight, motor rotation speed, number of operating cycles, and operating cycle time. The information processing method according to method 5, characterized in that (Method 7) The aforementioned intended user is the first intended user, There is a second intended use location whose operation differs from the first intended use location. The aforementioned processing unit, For the aforementioned multiple work devices, a third piece of information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted additional fatigue level that will occur at the second planned use location. Based on the second and third pieces of information, the work device to be used at the first planned location and the work device to be used at the second planned location are determined from among the plurality of work devices. An information processing method according to any one of methods 1 to 6, characterized by the above. (Method 8) The aforementioned processing unit, Based on the second piece of information, the difference between the predicted fatigue level and the fatigue level threshold requiring maintenance is calculated. From among the aforementioned plurality of work devices, the work device that minimizes the difference is determined to be used at the intended location. An information processing method according to any one of methods 1 to 7, characterized by the above. (Method 9) The aforementioned processing unit, Based on the second information, the predicted safety fatigue level is calculated by multiplying the predicted fatigue level by a safety factor. From among the aforementioned plurality of work devices, a work device is determined to be used at the planned site, in which the predicted safe fatigue level is less than the fatigue level threshold requiring maintenance. An information processing method according to any one of methods 1 to 7, characterized by the above. (Method 10) The processing unit, after actually operating the work device at the intended use site, Obtain actual operational information and update the information described in the second section above. The information processing method according to method 8 or 9, characterized by the features described above. (Method 11) The processing unit, after actually operating the work device at the intended use site, If, based on the updated second information, it is predicted that the predicted fatigue level will exceed the threshold, the system will provide notification regarding the prediction result. The information processing method according to method 10, characterized in that (Method 12) The processing unit, after actually operating the work device at the intended use site, If the predicted fatigue level is predicted to exceed the threshold, operation setting information is calculated to set the operation of the work device so that the predicted fatigue level does not exceed the threshold. The information processing method according to method 11, characterized in that... (Method 13) The aforementioned cumulative fatigue level is the cumulative fatigue level that occurred at the point of use. The aforementioned user is the lender to whom the loaned work equipment is returned. The aforementioned intended user is the intended lender who will lend the work equipment determined above from among multiple work equipment. An information processing method according to any one of methods 1 to 12, characterized by the above. (Method 14) The aforementioned processing unit, Images corresponding to the plurality of work devices and the first information and second information for the plurality of work devices are displayed on the display unit in association with each other. The information processing method according to any one of claims 1 to 13. (Method 15) The aforementioned processing unit, A screen showing a preview of the work to be performed at the intended location by a predetermined work device among the plurality of work devices is displayed on the display unit. The information processing method according to any one of claims 1 to 14. (Method 16) The aforementioned processing unit, The display unit displays together an image corresponding to a predetermined work device among the plurality of work devices, first information and second information of the predetermined work device, a program for the work to be performed by the predetermined work device at the planned usage location, and a screen for previewing the work to be performed by the predetermined work device at the planned usage location. The information processing method according to any one of claims 1 to 15. (Composition 17) In an information processing device having a processing unit, The aforementioned processing unit, First information regarding the cumulative fatigue level accumulated in multiple work devices is obtained, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. An information processing device characterized by the following: (Method 18) From among multiple work devices, the work device determined by the information processing method described in any one of methods 1 to 16 is managed to be deployed to the intended use location. A method for managing work equipment characterized by the following features. (Method 19) A control method for a work device management system comprising an information processing device having a processing unit, a plurality of work devices, and a management device for managing the work devices deployed at the site of use, The management device acquires first information regarding the cumulative fatigue level generated in the deployed work equipment, The aforementioned processing unit, The first information is obtained from the management device, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. A control method for a work device management system characterized by the following: (Composition 20) A work device management system comprising an information processing device having a processing unit, a plurality of work devices, and a management device for managing the work devices deployed at the site of use, The management device acquires first information regarding the cumulative fatigue level generated in the deployed work equipment, The aforementioned processing unit, The first information is obtained from the management device, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. A work device management system characterized by the following: (Method 21) The aforementioned intended use is a production facility for manufacturing goods. A work device determined by the information processing method described in any one of Methods 1 to 16 is installed in the production equipment. The deployed work equipment is used to manufacture goods. A method for manufacturing an article characterized by the following: (Composition 22) A program for causing a computer to execute one of the information processing methods described in any one of Methods 1 through 16. (Composition 23) A computer-readable recording medium on which the program described in configuration 22 is recorded. [Explanation of Symbols]

[0083] 101…Information processing unit / 102…CPU (processing unit) / 108…Display (display unit) / 201…Management device / 900…Robot (working device) / 901…Joint / 902…Gear reducer (mechanism) / FoS…Safety factor / Hj…Predicted fatigue level / Tj…Threshold / d…Cumulative fatigue level

Claims

1. In an information processing method performed by a processing unit, The aforementioned processing unit, First information regarding the cumulative fatigue level accumulated in multiple work devices is obtained, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted additional fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. An information processing method characterized by the following:

2. The aforementioned plurality of work devices have a mechanism that performs operation, The first information is information relating to the cumulative fatigue level in the mechanism, The second piece of information is information relating to the predicted fatigue level in the mechanism. The information processing method according to feature 1.

3. The aforementioned multiple work devices are articulated robots having multiple joints including the aforementioned mechanism, The first information is information relating to the cumulative fatigue level managed for each of the multiple joints, The second information is information relating to the predicted fatigue level managed for each of the multiple joints. The information processing method according to feature 2.

4. The aforementioned multiple work devices are articulated robots having multiple joints including the aforementioned mechanism, The first information is information relating to the cumulative fatigue level in a specific joint among the plurality of joints, The second piece of information is information relating to the predicted degree of fatigue in a specific joint among the plurality of joints. The information processing method according to feature 2.

5. The aforementioned predicted additional fatigue level is information calculated based on the operation setting information that sets the operation of the work device at the intended use location. The information processing method according to feature 1.

6. The aforementioned work device is a robot having an arm, The aforementioned operation setting information includes at least one of the following: teaching point, operating speed, acceleration, end-effector weight, motor rotation speed, number of operating cycles, and operating cycle time. The information processing method according to feature 5.

7. The aforementioned intended user is the first intended user, There is a second intended use that operates differently from the first intended use, The aforementioned processing unit, For the aforementioned multiple work devices, a third piece of information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted additional fatigue level that will occur at the second planned use location. Based on the second and third pieces of information, the work device to be used at the first planned location and the work device to be used at the second planned location are determined from among the plurality of work devices. The information processing method according to feature 1.

8. The aforementioned processing unit, Based on the second piece of information, the difference between the predicted fatigue level and the fatigue level threshold requiring maintenance is calculated. From among the aforementioned plurality of work devices, the work device that minimizes the difference is determined to be used at the intended location. The information processing method according to feature 1.

9. The aforementioned processing unit, Based on the second information, the predicted safety fatigue level is calculated by multiplying the predicted fatigue level by a safety factor. From among the aforementioned plurality of work devices, a work device is determined to be used at the planned site, in which the predicted safe fatigue level is less than the fatigue level threshold requiring maintenance. The information processing method according to feature 1.

10. The processing unit, after actually operating the work device at the intended use site, Obtain actual operational information and update the second information described above. The information processing method according to feature 8.

11. The processing unit, after actually operating the work device at the intended use site, If, based on the updated second information, it is predicted that the predicted fatigue level will exceed the threshold, the system will provide notification regarding the prediction result. The information processing method according to feature 10.

12. The processing unit, after actually operating the work device at the intended use site, If the predicted fatigue level is predicted to exceed the threshold, operation setting information is calculated to set the operation of the work device so that the predicted fatigue level does not exceed the threshold. The information processing method according to feature 11.

13. The aforementioned cumulative fatigue level is the cumulative fatigue level that occurred at the point of use. The aforementioned user is the lender to whom the loaned work equipment is returned. The aforementioned intended user is the intended lender who will lend the work equipment determined above from among multiple work equipment. The information processing method according to feature 1.

14. The aforementioned processing unit, Images corresponding to the plurality of work devices and the first information and second information for the plurality of work devices are displayed on the display unit in association with each other. The information processing method according to feature 1.

15. The aforementioned processing unit, A screen showing a preview of the work to be performed at the intended location by a predetermined work device among the plurality of work devices is displayed on the display unit. The information processing method according to feature 1.

16. The aforementioned processing unit, The display unit displays together an image corresponding to a predetermined work device among the plurality of work devices, first information and second information of the predetermined work device, a program for the work to be performed by the predetermined work device at the planned usage location, and a screen for previewing the work to be performed by the predetermined work device at the planned usage location. The information processing method according to feature 1.

17. In an information processing device having a processing unit, The aforementioned processing unit, First information regarding the cumulative fatigue level accumulated in multiple work devices is obtained, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. An information processing device characterized by the following:

18. From among multiple work devices, the work device determined by the information processing method described in claim 1 is managed to be deployed to the intended use location. A method for managing work equipment characterized by the following features.

19. A control method for a work device management system comprising an information processing device having a processing unit, a plurality of work devices, and a management device for managing the work devices deployed at the site of use, The management device acquires first information regarding the cumulative fatigue level generated in the deployed work equipment, The aforementioned processing unit, The first information is obtained from the management device, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. A control method for a work device management system characterized by the following:

20. A work device management system comprising an information processing device having a processing unit, a plurality of work devices, and a management device for managing the work devices deployed at the site of use, The management device acquires first information regarding the cumulative fatigue level generated in the deployed work equipment, The aforementioned processing unit, The first information is obtained from the management device, For the aforementioned multiple work devices, second information regarding predicted fatigue is calculated based on the cumulative fatigue level and the predicted fatigue level that will occur at the intended use site. Based on the second information, the work device to be used at the planned location is determined from among the plurality of work devices. A work device management system characterized by the following:

21. The aforementioned intended use is a production facility for manufacturing goods. A work device determined by the information processing method described in any one of claims 1 to 16 is installed in the production equipment. The deployed work equipment is used to manufacture goods. A method for manufacturing an article characterized by the following:

22. A program for causing a computer to execute the information processing method described in any one of claims 1 to 16.

23. A computer-readable recording medium on which the program described in claim 22 is recorded.

Images