Anomaly handling apparatus, network system, and method providing steps for anomalies generated in a robot system

Abstract

A technology capable of appropriately dealing with various abnormalities that can occur in a robot system has been demanded in the past. An abnormality processing device (90) includes: a storage section (64) that stores a plurality of steps for dealing with a plurality of abnormalities, respectively, in association with abnormality determination information that determines the abnormalities; an abnormality detection section (74) that detects an abnormality based on action state data of a robot system (12); a data acquisition section (78) that acquires abnormality determination information of the abnormality detected by the abnormality detection section (74); and a step acquisition section (80) that acquires a step corresponding to the abnormality determination information acquired by the data acquisition section (78) from among the plurality of steps stored in the storage section (64).

Description

Technical Field

[0001] This disclosure relates to anomaly handling apparatus, network systems, and methods that provide steps for handling anomalies generated in a robotic system. Background Technology

[0002] Devices are known to display the work steps that an operator should perform on the work line when an anomaly occurs in a robot system (e.g., Patent Document 1).

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent Application Publication No. 2014-223694 Summary of the Invention

[0006] The problem that the invention aims to solve

[0007] In robotic systems, various anomalies may occur, such as malfunctioning robot movements and abnormal readings from the various sensors installed on the robot. Previously, technologies capable of appropriately handling these anomalies were required.

[0008] Methods for solving problems

[0009] An anomaly handling apparatus provides steps for responding to anomalies generated in a robot system, comprising: a storage unit that stores multiple steps for responding to various anomalies in association with anomaly determination information for determining the anomaly; an anomaly detection unit that detects anomalies based on motion state data of the robot system; a data acquisition unit that acquires the anomaly determination information of the anomalies detected by the anomaly detection unit; and a step acquisition unit that acquires a step corresponding to the anomaly determination information acquired by the data acquisition unit from the multiple steps stored in the storage unit.

[0010] A method for providing steps for anomalies generated in a robot system includes storing multiple steps for dealing with various anomalies in a storage unit, associating them with anomaly determination information for determining the anomaly, detecting anomalies based on motion state data of the robot system, obtaining anomaly determination information for the detected anomalies, and retrieving steps corresponding to the obtained anomaly determination information from the multiple steps stored in the storage unit.

[0011] Invention Effects

[0012] According to this disclosure, steps for dealing with various anomalies that may occur in a robotic system can be automatically obtained and provided. Therefore, a variety of anomalies can be handled appropriately and easily. Attached Figure Description

[0013] Figure 1This is a block diagram of a network system according to one implementation method.

[0014] Figure 2 yes Figure 1 An example of a robot system is shown.

[0015] Figure 3 This is a block diagram of a network system according to another implementation.

[0016] Figure 4 This is a flowchart illustrating an example of a method for providing steps to address anomalies that occur in a robotic system.

[0017] Figure 5 This is a flowchart illustrating another example of a method for providing steps to address anomalies that occur in a robotic system.

[0018] Figure 6 This is a block diagram of a network system implemented in yet another way. Detailed Implementation

[0019] Hereinafter, embodiments of the present disclosure will be described in detail based on the accompanying drawings. Furthermore, in the various embodiments described below, the same elements will be labeled with the same reference numerals, and repeated descriptions will be omitted. First, refer to... Figure 1 The following describes one embodiment of the network system 10. The network system 10 includes a robot system 12, a preventive maintenance device 14, an external device 16, and a communication network 18.

[0020] Robot system 12 is an industrial robot system that performs predetermined operations on a workpiece. Preventive maintenance device 14 obtains motion status data OD, which represents the motion state of robot system 12, from robot system 12, and monitors anomalies AB generated in robot system based on motion status data OD.

[0021] External device 16 is a desktop or portable PC or server, etc. Communication network 18, such as a LAN (internal network) or the Internet, connects the robot system 12, the preventive maintenance device 14, and the external device 16 in a communicative manner. As an example, the robot system 12 can be located in a first building with a work line, the preventive maintenance device 14 in a second building different from the first building, and the external device 16 in a third building different from the first and second buildings.

[0022] Figure 2 This represents an example of robot system 12. Robot system 12 includes robot 20 and sensor 22. Figure 1 ) and control device 24. In Figure 2In the example shown, robot 20 is a vertical joint robot with a transport vehicle 26, a robot base 28, a rotating body 30, a lower arm 32, an upper arm 34, a wrist 36, and an end effector 38. The transport vehicle 26 can be, for example, an automated guided vehicle (AGV) that moves autonomously according to instructions from a control device 24, or a manually operated transport vehicle that is manually moved by an operator A1. Robot 20 can be moved to any location via the transport vehicle 26.

[0023] The robot base 28 is fixed to the transport vehicle 26. The rotating body 30 is mounted on the robot base 28 in a manner that allows it to rotate about a vertical axis. The lower arm 32 is mounted on the rotating body 30 in a manner that allows it to rotate about a horizontal axis, and the upper arm 34 is mounted on the front end of the lower arm 32 in a manner that allows it to rotate.

[0024] The wrist 36 is disposed at the front end of the upper arm 34 in a manner that allows it to rotate about two mutually orthogonal axes. An end effector 38 is detachably mounted at the front end of the wrist 36 (a so-called wrist flange). The end effector 38 is, for example, a robotic hand, a cutting tool, or a welding torch, and performs a predetermined operation on the workpiece (workpiece handling, cutting, or welding, etc.). Furthermore, the robotic hand may have multiple fingers for grasping the workpiece, or it may have an adsorption disk that generates negative pressure between itself and the workpiece to hold it in place.

[0025] Servo motors 40 are installed in each component of robot 20 (conveyor 26, robot base 28, rotating body 30, lower arm 32, upper arm 34, wrist 36). Figure 1 Servo motor 40 drives the movable components of robot 20 (conveyor 26, rotating body 30, lower arm 32, upper arm 34, wrist 36) according to instructions from control device 24.

[0026] Sensor 22 detects motion state data OD. For example, motion state data OD may include the rotational position Pm, rotational speed Vm, rotational acceleration αm, current value I, and load torque τ of the servo motor 40. In this case, sensor 22 may have a rotation detection sensor 22A (encoder or Hall element, etc.) for detecting the rotational position of the servo motor 40, a current sensor 22B for detecting the current value of the servo motor 40, and a torque sensor 22C for detecting the load torque of the servo motor 40.

[0027] Additionally, the motion state data OD may also include the position Pc, velocity Vc, and acceleration αc of the movable components (e.g., end effector 38) of the robot 20. The position Pc, velocity Vc, and acceleration αc of the movable components (end effector 38) of the robot 20 can be obtained, for example, from the detection values ​​(specifically, rotational position Pm) of the rotation detection sensor 22A.

[0028] Furthermore, if the end effector 38 is a robotic hand with multiple fingers, the motion state data OD may include the pressure P of the cylinders that open and close the multiple fingers. Also, if the end effector 38 is a robotic hand with a suction plate, the motion state data OD may include the pressure P generated by the suction plate. In these cases, the sensor 22 may be a pressure sensor 22D that detects the pressure P.

[0029] Additionally, the motion state data OD may include the battery voltage E used to actuate the control device 24 or the rotation detection sensor 22A. In this case, the sensor 22 may have a voltage sensor 22E that detects the voltage E. Furthermore, the motion state data OD may include the external force F applied to the robot 20. In this case, the sensor 22 may have a force sensor 22F that detects the external force F.

[0030] Additionally, sensor 22 may include a vision sensor 22G positioned at a known location relative to robot 20. This vision sensor 22G captures image data ID of the workpiece as motion state data OD and supplies it to control device 24. In this case, vision sensor 22G can provide control device 24 with determination information regarding whether the image data ID of the workpiece was properly captured, along with the image data ID.

[0031] Thus, sensor 22 has at least one sensor 22A, 22B, 22C, 22D, 22E, and 22F, which detects at least one motion state data OD (rotational position Pm, rotational speed Vm, rotational acceleration αm, current value I, load torque τ, position Pc, speed Vc, acceleration αc, pressure P, voltage E, external force F, and image data ID). Furthermore, the motion state data OD is not limited to the examples above and may include any other arbitrary data; sensor 22 may also be configured to detect this data.

[0032] The control device 24 is located outside the robot 20 (or inside the conveyor 26) and controls the movements of the robot 20. For example... Figure 1 As shown, the control device 24 is a computer having a processor 42, a storage unit 44, an I / O interface 46, an input device 48, and a display device 50. The processor 42 may have a CPU or a GPU, and is communicatively connected to the storage unit 44, the I / O interface 46, the input device 48, and the display device 50 via a bus 52.

[0033] The storage unit 44 includes RAM or ROM, which temporarily or permanently stores various data used in the computational processing performed by the processor 42, as well as various data generated during the computational processing. The I / O interface 46 includes, for example, an Ethernet port, a USB port, a fiber optic connector, or an HDMI terminal, and communicates with external devices via wired or wireless means under instructions from the processor 42. In this embodiment, the I / O interface 46 is connected to the communication network 18, the sensor 22, and the servo motor 40.

[0034] Input device 48 includes a keyboard, mouse, or touch panel, etc., to receive data input from the operator. Display device 50 includes a liquid crystal display or organic EL display, etc., to display various data. Input device 48 and display device 50 can be separately installed from the frame of control device 24, or they can be integrated with the frame of control device 24.

[0035] The processor 42 obtains motion status data OD (rotational position Pm, rotational speed Vm, rotational acceleration αm, current value I, load torque τ, position Pc, speed Vc, acceleration αc, pressure P, voltage E, external force F, image data ID, etc.) from the sensor 22, and continuously (e.g. periodically) transmits the obtained motion status data OD to the preventive maintenance device 14 via the communication network 18.

[0036] The preventive maintenance device 14 is a computer having a processor 62, a storage unit 64, an I / O interface 66, an input device 68, and a display device 70. Furthermore, the structure of the processor 62, storage unit 64, I / O interface 66, input device 68, and display device 70 is the same as that of the processor 42, storage unit 44, I / O interface 46, input device 48, and display device 50 described above, therefore, repeated descriptions are omitted.

[0037] The processor 62 is communicatively connected to the storage unit 64, the I / O interface 66, the input device 68, and the display device 70 via the bus 72. The I / O interface 66 is connected to the communication network 18, and the processor 62 obtains the operation status data OD from the control device 24 through the communication network 18 and stores it in the storage unit 64.

[0038] The processor 62 detects anomalies AB in the robot system 12 based on the acquired motion state data OD. For example, the processor 62 determines whether the motion state data OD differs from a predetermined reference. Specifically, the processor 62 determines whether the value of the motion state data OD (rotational position Pm, rotational speed Vm, rotational acceleration αm, current value I, load torque τ, position Pc, speed Vc, acceleration αc, pressure P or voltage E) obtained from the sensor 22 exceeds a predetermined reference value β (OD > β or OD < β). If the value of the motion state data OD exceeds the reference value β, it is determined that the motion state data OD differs from the reference.

[0039] For example, if the end effector 38 is a robot with a suction cup, by monitoring the pressure P obtained from the pressure sensor 22D, it can be determined whether the end effector 38 has properly gripped the workpiece using the suction cup. The processor 62 will detect when the pressure P exceeds the reference value β. P And rise (P>β) P or decrease (P < β) P In the event of a situation where the end effector 38 experiences a poor gripping anomaly AB1, the processor 62 can detect this anomaly. Additionally, the processor 62 detects an anomaly AB1 when the voltage E obtained from the voltage sensor 22E exceeds the reference value β. E And decrease (E < β) E In the case of ), an abnormality AB2, in which a voltage drop occurs in the battery of the control device 24 or the rotation detection sensor 22A, can be detected.

[0040] Additionally, the processor 62 detects an external force F obtained from the force sensor 22F that exceeds the reference value β. F1 In the case of (F < β) F1 Or F > β F1 It can detect an anomaly AB3, which indicates that the force sensor 22F is malfunctioning (i.e., faulty), or an anomaly AB4, which indicates that the robot 20 has collided with the surrounding environment (or operator A1).

[0041] Furthermore, when the processor 62 obtains the image data ID captured by the vision sensor 22G as motion state data OD, it can refer to the determination information contained in the image data ID. If the determination information indicates that the image data ID was not properly captured, the processor 62 determines that the motion state data OD (image data ID) is different from the reference. Thus, the processor 62 can detect the abnormality AB5 caused by the vision sensor 22G failing to capture the image.

[0042] Alternatively, if the image data ID does not contain determination information, the processor 62 can also determine whether the image data ID differs from the reference based on the image data ID. Specifically, during the operation performed by the robot 20, the control device 24 of the robot system 12 uses the vision sensor 22G to capture images of the markers set at known locations on the robot 20.

[0043] The processor 62 obtains the image data ID of the captured marker from the robot system 12 and retrieves the marker's position from the image data ID. If the marker's position deviates from a predetermined reference point, it can be determined that the image data ID is different from the reference. In this way, the processor 62 can detect an anomaly AB5, indicating a poor image capture, based on the image data ID.

[0044] As another example, processor 62 can also use a learning model LM constructed through machine learning to detect anomalies AB in robot system 12. The learning model LM represents the correlation between motion state data OD (e.g., pressure P) and anomalies AB generated in robot system 12 (e.g., anomaly AB1 of poor gripping by end effector 38), and can be constructed, for example, by repeatedly feeding motion state data OD and a learning dataset DS1 representing the judgment data of the presence or absence of anomalies AB to a machine learning device (e.g., supervised learning).

[0045] The processor 62 sequentially inputs motion state data OD, which is continuously obtained from the robot system 12, into the learning model LM. The learning model LM identifies and outputs an anomaly AB that is highly correlated with changes in the motion state data OD input during a predetermined period.

[0046] In this way, processor 62 can detect anomalies (AB) generated in robot system 12 based on motion state data (OD) and learning model (LM). By using the learning model (LM), processor 62 can predict the malfunction of components of robot system 12 (e.g., servo motor 40 or sensor 22) due to the occurrence of anomalies (AB). Furthermore, processor 62 can also be configured to perform the functions of the aforementioned machine learning device.

[0047] As described above, in this embodiment, the processor 62 serves as an anomaly detection unit 74 that detects anomalies AB based on action state data OD. Figure 1 In this embodiment, the storage unit 64 stores multiple steps PR for responding to various anomalies AB that may occur in the robot system 12, along with anomaly determination information SI for determining the anomaly AB.

[0048] As an example, the anomaly identification information SI has an anomaly identification code SI1 assigned individually to multiple anomalies AB (e.g., anomalies AB1, AB2, AB3, AB4, ...). Specifically, the anomaly identification code SI1 consists of multiple strings (so-called error codes) and is inherently assigned to each of the multiple anomalies AB.

[0049] For example, an anomaly AB1, which is a poor gripping condition of the end effector 38, is assigned an anomaly identification code SI1 with the string "AB001"; an anomaly AB2, which is a voltage drop in the battery, is assigned an anomaly identification code SI1 with the string "AB002"; an anomaly AB3, which is a poor movement of the force sensor 22F, is assigned an anomaly identification code SI1 with the string "AB003"; an anomaly AB4, which is a collision between the robot 20 and surrounding objects, is assigned an anomaly identification code SI1 with the string "AB004"; and an anomaly AB5, which is a poor image capture condition of the vision sensor 22G, is assigned an anomaly identification code SI1 with the string "AB005".

[0050] On the other hand, steps (PRs) for responding to various anomalies (AB) are prepared in advance for each AB. For example, a step PR may have image data of text explaining the step PR, or image data of static or dynamic images showing the actions of operator A1 in performing the step PR, explaining the steps operator A1 takes to respond to the AB using text, static images, or dynamic images. For example, step PR1 for responding to an AB1 of poor gripping by the end effector 38 with a suction plate may have image data explaining the steps of checking the suction plate or the air valve that creates negative pressure on the suction plate.

[0051] Furthermore, step PR2, which addresses the abnormality AB2 caused by a drop in battery voltage, includes image data illustrating the steps for replacing the battery. Additionally, step PR4, which addresses the abnormality AB4 caused by a collision between the robot 20 and its surrounding environment, includes image data illustrating the steps for confirming whether such a collision occurred. Finally, step PR5, which addresses the abnormality AB5 caused by a malfunction in the vision sensor 22G, includes image data illustrating the steps for confirming the placement of the vision sensor 22G, inspecting its components (e.g., lenses), and calibrating the vision sensor 22G.

[0052] The storage unit 64 stores the steps PR (e.g., steps PR1, PR2, ...) in association with the anomaly determination information SI (e.g., anomaly identification code SI1: "AB001", "AB002", "AB003", ...). The operator A2 (e.g., the designer of the work line) of the preventive maintenance device 14 operates the input device 68 to input multiple steps PR (step PR1, etc.) and the anomaly determination information SI (anomaly identification code SI1: "AB001", etc.) associated with those steps PR.

[0053] The processor 62 receives input from step PR and the exception determination information SI via the input device 68. Therefore, in this embodiment, the processor 62 serves as an input receiving unit 76 that receives input from step PR and the exception determination information SI. Figure 1 The storage unit 64 stores the step PR and the exception determination information SI received by the processor 62 in association. In this way, the step PR and the exception determination information SI (specifically, the exception identification code SI1) are stored in the storage unit 64 in advance.

[0054] When the processor 62 detects an anomaly AB while functioning as the anomaly detection unit 74, it acquires anomaly determination information SI to identify the anomaly AB. For example, the storage unit 64 also stores a data table DT1 that associates the type of the anomaly AB (e.g., a gripping anomaly AB1) with the anomaly identification code SI1 (e.g., "AB001") assigned to that anomaly AB. The processor 62 refers to the data table DT1 and acquires the anomaly identification code SI1 assigned to the detected anomaly AB as the anomaly determination information SI.

[0055] As another example, processor 62 can also use the learning model LM described above to determine the abnormal AB based on the action state data OD, and obtain the abnormal identification code SI1 assigned to the abnormal AB. The learning model LM can be constructed by repeatedly providing the action state data OD, the determination data indicating whether there is an abnormal AB, and the abnormal identification code SI1 assigned to the abnormal AB to the machine learning device.

[0056] The processor 62 sequentially inputs the motion state data OD obtained from the robot system 12 into the learning model LM. The learning model LM outputs the identified anomaly AB along with the anomaly identification code SI1 assigned to the anomaly AB. Thus, the processor 62 can obtain the anomaly AB and the anomaly identification code SI1 generated in the robot system 12 based on the motion state data OD. Therefore, in this embodiment, the processor 62 serves as a data acquisition unit 78 for obtaining the anomaly determination information SI (specifically, the anomaly identification code SI1) of the detected anomaly AB. Figure 1 To fulfill its function.

[0057] Next, the processor 62 retrieves the step PR corresponding to the acquired anomaly determination information SI from the plurality of step PRs stored in the storage unit 64. For example, if the processor 62 detects an anomaly AB1 with poor gripping and obtains the anomaly identification code SI1 "AB001" assigned to the anomaly AB1 as anomaly determination information SI, it retrieves and obtains the image data of step PR1 associated with the anomaly identification code SI1 "AB001" from the plurality of step PRn (n = 1, 2, 3, ...) stored in the storage unit 64. Thus, in this embodiment, the processor 62 serves as the step acquisition unit 80 for acquiring the step PR corresponding to the acquired anomaly determination information SI. Figure 1 To fulfill its function.

[0058] Then, the processor 62 provides the acquired image data of step PR to the display device 70 via bus 72, and displays step PR as an image on the display device 70. Additionally, the processor 62 sends the acquired image data of step PR to the communication network 18 via I / O interface 66, and supplies it to the control device 24 via the communication network. The processor 42 of the control device 24 obtains the image data of step PR via I / O interface 46 and displays step PR as an image on the display device 50.

[0059] Thus, in this embodiment, the processor 62 serves as the display control unit 82 of the display devices 50 and 70, which displays the obtained step PR as an image. Figure 1 In addition, the processor 62 can also function as a display control unit 82, replacing the display device 50 (or otherwise), and causing the display device (not shown) provided on the work line to display the obtained step PR.

[0060] As described above, in this embodiment, the storage unit 64 stores multiple steps PR in association with the anomaly determination information SI, and the processor 42 functions as an anomaly detection unit 74, an input receiving unit 76, a data acquisition unit 78, a step acquisition unit 80, and a display control unit 82, providing steps PR for responding to anomalies AB generated in the robot system 12.

[0061] Therefore, the storage unit 64 and the processor 42 (abnormal detection unit 74, input receiving unit 76, data acquisition unit 78, step acquisition unit 80, and display control unit 82) constitute an abnormality handling device 90 for providing step PR to deal with abnormality AB. Figure 1 Thus, in this embodiment, the anomaly handling device 90 is installed in the prevention and maintenance device 14.

[0062] In the anomaly handling device 90, the storage unit 64 stores multiple step PRs associated with anomaly determination information SI, the anomaly detection unit 74 detects anomalies AB based on motion state data OD, and the data acquisition unit 78 acquires the anomaly determination information SI (specifically, anomaly identification code SI1) of the anomaly AB detected by the anomaly detection unit 74, and retrieves the step PR corresponding to the anomaly determination information SI acquired by the data acquisition unit 78 from the multiple step PRs stored in the storage unit 64. According to this structure, step PRs for handling various anomalies AB that may occur in the robot system 12 can be automatically acquired and provided. Therefore, various anomalies AB can be handled appropriately and easily.

[0063] Furthermore, in the anomaly handling device 90, the input receiving unit 76 receives the step PR and the anomaly determination information SI (anomaly identification code SI1) as input, and the storage unit 64 stores the step PR and the anomaly determination information SI received by the input receiving unit 76 in association. According to this structure, since the operator A2 can arbitrarily input the step PR and the anomaly determination information SI, the step PR and the anomaly determination information SI can be added, deleted, or edited as needed, thereby updating to the latest data.

[0064] Furthermore, in the anomaly handling device 90, the anomaly determination information SI has an anomaly identification code SI1 assigned individually to various anomalies AB. The data acquisition unit 78 acquires the anomaly identification code SI1 assigned to the anomaly AB detected by the anomaly detection unit 74 as the anomaly determination information SI. According to this structure, the processor 62 functions as a step acquisition unit 80, and can easily and quickly retrieve the step PR for dealing with the generated anomaly AB based on the anomaly identification code SI1.

[0065] Furthermore, in the anomaly handling device 90, the display control unit 82 displays the steps PR acquired by the step acquisition unit 80 as images on the display devices 50 and 70. By visually confirming the images of the steps PR displayed on the display devices 50 and 70, the operator A1 of the work line and the operator A2 of the preventive maintenance device 14 can easily understand the steps PR used to deal with anomalies AB. Moreover, even without professional knowledge, operator A1 can appropriately deal with anomalies AB on the work line by following the steps PR displayed on the display device 50.

[0066] Furthermore, the processor 62 functions as a display control unit 82, transmitting the image data of step PR acquired by the step acquisition unit 80 to the external device 16 via the communication network 18, so that the display device (not shown) installed on the external device 16 can display it. In this case, the operator A3 of the external device 16 (e.g., the production line manager) can also easily understand the step PR used to deal with the abnormality AB.

[0067] Furthermore, in step PR, instead of image data (or otherwise), there may be audio data explaining step PR using sound. In this case, the processor 62 can output the audio data of step PR through a speaker provided in the preventive maintenance device 14 (or control device 24). When step PR only has audio data, the display control unit can be omitted from the fault handling device 90.

[0068] Alternatively, the input receiving unit 76 can be omitted from the fault handling device 90. For example, the step PR and the fault determination information SI can be prepared using the external device 16 of the fault handling device 90 and downloaded to the preventive maintenance device 14 via the communication network 18 (or external memory).

[0069] Furthermore, depending on the type of anomaly AB that occurs, operator A1 may need to detach robot 20 from the production line. For example, for anomaly AB2 caused by a drop in battery voltage, operator A1 can replace the battery, thus enabling the issue to be addressed on the production line. On the other hand, for anomaly AB3 caused by a malfunction of force sensor 22F, since force sensor 22F cannot be replaced, there is a situation where operator A1 cannot address the issue on the production line.

[0070] In this situation, in order to continue operation on the production line, it is necessary to detach the robot 20, which is equipped with force sensor 22F, from the production line. Therefore, step PR3 for dealing with the abnormality AB3 of malfunction of force sensor 22F includes, for example, step PR31 of detaching robot 20 from the production line, and step PR3 of having operator A1 manually perform the work performed by robot 20 on the production line instead of robot 20. _2 .

[0071] Specifically, step PR3 that separates robot 20 _1 Image data may include text describing the steps of operating the conveyor 26 to remove the robot 20 from the work line, or static or dynamic images showing the actions of operator A1 performing those steps. Additionally, step PR3, which separates the robot 20... _1 Image data may include text describing the steps of disconnecting the communication connection between the control device 24 and its host controller (not shown), or static or dynamic images representing the actions of operator A1 in performing the steps.

[0072] On the other hand, step PR3 allows operator A1 to perform the work. _2Image data may contain text describing the steps (e.g., workpiece handling steps) that operator A1 should perform in place of robot 20 in the work line after robot 20 is separated, or still or moving images representing the actions of operator A1 in performing those steps.

[0073] When the processor 62 detects an anomaly AB3 indicating a malfunction in the force sensor 22F, it functions as a data acquisition unit 78, acquiring the anomaly identification code SI1 "AB003" assigned to the anomaly AB3. It then functions as a step acquisition unit 80, retrieving and acquiring step PR3 associated with the anomaly identification code SI1 "AB003" from the storage unit 64. Next, the processor 62 functions as a display control unit 82, providing image data of step PR3 to the display devices 50 and 70, causing the display devices 50 and 70 to sequentially display step PR3. _1 Images and steps PR3 _2 The image.

[0074] With this structure, in order to deal with anomaly AB3, operators A1 and A2 can easily understand step PR3, where robot 20 separates from the work line. _1 And the steps PR3 for the tasks that operator A1 should perform after separation. _2 As a result, operator A1 performs the tasks of robot 20, thereby enabling the work to continue on the production line.

[0075] Furthermore, regarding the anomaly AB of step PR3, which requires the robot 20 to perform separation and tasks, other anomalies may exist besides the anomaly AB3 of the force sensor 22F malfunctioning. For example, anomalies AB5' of the vision sensor 22G failing to capture images and AB6 of the sensor 22's detection value (e.g., the detection value is consistently zero) also require step PR3. Step PR3 is associated with the anomaly identification codes SI1 (e.g., "AB003", "AB005", and "AB006") assigned to these anomalies AB3, AB5', and AB6, and stored in the storage unit 64.

[0076] Next, refer to Figure 3 Other functions of the preventive maintenance device 14 will be explained. In this embodiment, in addition to functioning as the aforementioned abnormality detection unit 74, input receiving unit 76, data acquisition unit 78, step acquisition unit 80, and display control unit 82, the processor 62 also functions as an approval / disapproval determination unit 84, a notification generation unit 86, and a communication control unit 88. Hereinafter, refer to... Figure 4 The operating procedure of the preventive maintenance device 14 is explained. Figure 4The process shown begins when processor 62 receives an action start instruction from operator A2, the host controller, or the computer program.

[0077] In step S1, the processor 62 begins to perform an operation to acquire motion status data OD. Specifically, as described above, the processor 62 begins to continuously (e.g., periodically) acquire motion status data OD from the control device 24 via the communication network 18.

[0078] In step S2, the processor 62 functions as an anomaly detection unit 74, and determines whether an anomaly AB is detected based on the action state data OD using the method described above. If the processor 62 detects an anomaly AB, it determines "yes" and proceeds to step S3; otherwise, if no anomaly AB is detected, it determines "no" and proceeds to step S5.

[0079] In step S3, the processor 62 determines whether the robot 20 needs to be separated from the work line based on the anomaly determination information SI. Specifically, the processor 62 functions as a data acquisition unit 78, acquiring the anomaly identification code SI1 of the anomaly AB detected in the most recent step S2 as the anomaly determination information SI.

[0080] Then, the processor 62 determines whether the obtained anomaly identification code SI1 matches the code SI1 required to detach the robot 20 from the work line. X For example, the anomalies AB3, AB5', and AB6 mentioned above are assigned the anomaly identification code SI1: "AB003", "AB005'", and "AB006" are classified as code SI1. X .

[0081] In step S3, processor 62 obtains the code SI1 that has been classified. X If the anomaly identification code SI1 (e.g., "AB003", "AB005", or "AB006") is found, the process is determined to be "yes" and proceeds to step S6. On the other hand, if an anomaly identification code SI1 is not found, the process proceeds to step S6. X If the abnormal identification code SI1 is not found, proceed to step S4.

[0082] In step S4, the processor 62 functions as a step acquisition unit 80, and retrieves the step PR corresponding to the anomaly determination information SI (specifically, anomaly identification code SI1) obtained in the most recent step S3 from the multiple step PRs stored in the storage unit 64 using the method described above. Furthermore, the processor 62 functions as a display control unit 82, displaying the acquired step PR as an image on the display devices 50 and 70 (and the display device of the external device 16).

[0083] In step S5, the processor 62 determines whether it has received an operation termination command from operator A2, the host controller, or the computer program. If the processor 62 receives an operation termination command, it determines "yes" and terminates the operation. Figure 4 The process shown, on the other hand, if no action end instruction is received, it is determined as "no" and returns to step S2.

[0084] On the other hand, if the determination in step S3 is "yes", the processor 62 determines in step S6 whether it can handle the anomaly AB detected in the most recent step S2. Here, there is a situation where the operator A1 cannot detach the robot 20 from the work line (for example, the operator A1 is not allowed to operate the conveyor 26, or the robot 20 was originally fixed to the work line and could not move because it did not have the conveyor 26).

[0085] Furthermore, even after robot 20 has been separated, there are situations where operator A1 is unable to perform the tasks assigned to robot 20 (e.g., robot 20 performing laser processing). In these cases, operator A1 is unable to respond to detected anomalies AB on the production line.

[0086] Therefore, in step S6, processor 62 simultaneously obtains anomaly determination information SI and availability determination information DI for determining whether anomaly AB can be handled, and determines whether anomaly AB can be handled based on availability determination information DI. For example, availability determination information DI includes identification code DI1 (manufacturing number, model, etc.) for identifying robot 20, and identification code DI1 for robots that cannot be separated from the production line. X Data table DT2.

[0087] As another example, could it be determined that information DI includes an identification code DI2 that identifies the task performed by robot 20 (e.g., an identification code representing laser processing) and an identification code DI2 that stores tasks that operator A1 cannot perform? X Data table DT3. These identification codes DI1 and DI2, as well as data tables DT2 and DT3, are, for example, pre-stored in the storage unit 44 of the control device 24.

[0088] The processor 62 functions as a data acquisition unit 78, acquiring the anomaly determination information SI (anomaly identification code SI1) of the anomaly AB detected in the most recent step S2, and obtaining the identification code DI1 (or DI2) and the data table DT2 (or DT3) from the control device 24 via the communication network 18.

[0089] Then, the processor 62 determines whether the obtained identification code DI1 (or DI2) matches the identification code DI1 contained in the data table DT2 (or DT3). X (or DI2)X If the condition is met, the process determines "yes" and proceeds to step S8; otherwise, if the condition is not met, the process determines "no" and proceeds to step S7. Thus, in this embodiment, the processor 62 serves as the yes / no determination unit 84. Figure 3 The yes / no determination unit 84 performs its function by determining whether it can handle the abnormal AB based on the yes / no determination information DI.

[0090] In step S7, the processor 62 functions as the step acquisition unit 80, acquiring the step PR3 (specifically, step PR3) corresponding to the anomaly determination information SI (e.g., anomaly identification code SI1: "AB003", "AB005", or "AB006") acquired in the most recent step S3, which involves the separation and task execution of the robot 20. _1 and PR3 _2 ).

[0091] Furthermore, the processor 62 functions as a display control unit 82, displaying the obtained step PR3 as an image on display devices 50 and 70 (and the display device of external device 16). As a result, the operator A1 of the production line can easily understand step PR3, which involves separating the robot 20 from the production line. _1 And the steps PR3 for the tasks that should be performed after the separation of robot 20. _2 Even without specialized knowledge, these steps (PR3) can be performed on the production line. _1 and PR3 _2 .

[0092] In step S8, the processor 62 generates notification data ND to indicate that it cannot handle the anomaly AB detected in the most recent step S2, and sends it to the external device 16. Specifically, as image data or sound data, the processor 62 generates notification data ND, for example, a warning indicating "an unmanageable anomaly has occurred in the robot system." Thus, in this embodiment, the processor 62 serves as the notification generation unit 86 that generates notification data ND when it is determined in step S6 that the anomaly AB cannot be handled (i.e., the determination is "yes"). Figure 3 To fulfill its function.

[0093] Then, the processor 62 sends the generated notification data ND to the external device 16, which is pre-registered in the storage unit 64 as the destination, via the communication network 18. Alternatively, the processor 62 can also send the notification data ND to the external device 16 via email.

[0094] Therefore, the operator A3 of the external device 16 (e.g., the production line manager) can easily identify unmanageable anomalies AB that have occurred in the robot system 12. Thus, in this embodiment, the processor 62 acts as a communication control unit 88 that sends the generated notification data ND to the external device 16. Figure 3 The processor 62 terminates its function after executing step S8. Figure 4 The process.

[0095] As described above, in this embodiment, the processor 42 functions as an anomaly detection unit 74, an input receiving unit 76, a data acquisition unit 78, a step acquisition unit 80, a display control unit 82, an approval / disapproval determination unit 84, a notification generation unit 86, and a communication control unit 88, providing the step PR stored in the storage unit 64.

[0096] Therefore, the storage unit 64 and the processor 42 (abnormal detection unit 74, input receiving unit 76, data acquisition unit 78, step acquisition unit 80, display control unit 82, approval / disapproval unit 84, notification generation unit 86, and communication control unit 88) constitute an abnormality handling device 100 for providing step PR to deal with abnormalities AB. Figure 1 Thus, in this embodiment, the anomaly handling device 100 is installed in the prevention and maintenance device 14.

[0097] In the anomaly handling device 100, the data acquisition unit 78 acquires anomaly determination information SI and feasibility determination information DI. The feasibility determination unit 84 determines whether anomaly AB can be handled based on the feasibility determination information DI. If the feasibility determination unit 84 determines that anomaly AB cannot be handled, the notification generation unit 86 generates notification data ND to notify the situation. According to this structure, when anomaly AB that operator A1 cannot handle on the work line occurs in the robot system 12, the situation can be automatically notified.

[0098] Furthermore, in the anomaly handling device 100, the communication control unit 88 sends the notification data ND generated by the notification generation unit 86 to the external device 16 of the anomaly handling device 100. According to this structure, it is possible to automatically notify the operator A3 (e.g., the production line manager) of the external device 16 of any unmanageable anomaly AB.

[0099] Furthermore, in step S4 described above, the processor 62 can also provide step PR in stages based on the input data IP from the operator. For example, step PR5 for responding to the abnormality AB5 of poor image capture by the vision sensor 22G includes step PR5 for confirming the setting position (or component) of the vision sensor 22G. _1 And the step PR5 for calibrating the 22G vision sensor. _2 .

[0100] In this case, processor 62 first obtains step PR5 in step S4. _1 The processor 62 then causes the display device 50 to display an input image, which is used to input the offset of the setting position of the visual sensor 22G. Operator A1 proceeds according to step PR5. _1 After confirming whether there is any deviation in the setting position of the vision sensor 22G, if the deviation is eliminated, the operation input device 48 inputs input data IP1 indicating that the abnormality AB5 has been dealt with to the input image displayed on the display device 50.

[0101] On the other hand, in the absence of any offset in the setting position of the visual sensor 22G, operator A1 operates the input device 48 to input input data IP2, indicating the absence of such offset, into the input image displayed on the display device 50. Processor 62 terminates step S4 upon receiving input data IP1 from control device 24, and proceeds to step PR5 for calibration upon receiving input data IP2 from control device 24. _2 The display device 50 then displays the information. Thus, by providing step PR in stages during step S4, operator A1 can respond appropriately based on the status of the robot system 12.

[0102] Next, refer to Figure 5 right Figure 3 Another function of the preventive maintenance device 14 shown will be explained. Furthermore, in Figure 5 In the process shown, for the relationship with Figure 4 The same process flow is labeled with the same step numbers, and duplicate descriptions are omitted. (Starting) Figure 5 Following the process shown, processor 62 and Figure 4 The process is executed in the same way, following steps S1 to S4.

[0103] Following step S4, in step S3', processor 62 determines whether robot 20 needs to be separated from the work line based on input data IP from operator A1. Here, in step S4, step PR for handling exception AB is provided to operator A1. Even if operator A1 executes step PR, exception AB may sometimes still not be handled.

[0104] As an example, suppose that in step S2, the processor 62 detects that the external force F obtained by the force sensor 22F exceeds the reference value β. F2 And increase (F>β) E2The processor 62 detects an anomaly AB4, indicating that the robot 20 has collided with an object in the surrounding environment. In this case, the processor 62 determines "no" in step S3, and in step S4, it acquires step PR4 (i.e., image data describing the steps for confirming whether there is a collision) for dealing with anomaly AB4, and displays it on the display device 50 of the control device 24.

[0105] Simultaneously, the processor 62 provides the control device 24 with an input image indicating whether the robot 20 has collided with surrounding objects, and displays it on the display device 50. Operator A confirms whether the robot 20 has collided with surrounding objects according to step PR4. If a collision exists, actions are taken to eliminate the collision, such as moving the surrounding objects backward. This allows for handling of anomaly AB4. In this case, operator A operates the input device 48 to input input data IP1, indicating a collision with surrounding objects, into the input image displayed on the display device 50.

[0106] On the other hand, if operator A confirms in step PR4 that there is no collision between robot 20 and surrounding objects, the external force F exceeds the reference value β. F2 The increased anomaly may be caused by an anomaly AB3 in which the force sensor 22F malfunctions and cannot be handled by operator A. In this case, operator A operates the input device 48 and inputs input data IP2, indicating that there is no collision with surrounding objects, into the input image displayed on the display device 50.

[0107] As another example, suppose the processor 62 detects an anomaly AB5 in step S2 indicating a malfunction in the image captured by the vision sensor 22G. In this case, the processor 62 determines "No" in step S3, and in step S4, acquires step PR5 (i.e., image data describing the steps of confirming and calibrating the vision sensor 22G) for dealing with the anomaly AB5, and displays it on the display device 50 of the control device 24.

[0108] Simultaneously, processor 62 provides control device 24 with an input image indicating whether abnormality AB5 has been eliminated, and displays it on display device 50. Operator A performs necessary procedures such as calibration according to step PR5. If the result is that abnormality AB5 has been eliminated, operator A operates input device 48 to input input data IP1 indicating that abnormality AB5 has been eliminated into the input image displayed on display device 50.

[0109] On the other hand, if operator A1 fails to eliminate abnormality AB5 even after following step PR5, an abnormality AB5' that operator A cannot handle arises. In this case, operator A1 operates input device 48 and inputs input data IP2, indicating that abnormality AB5 has not been eliminated, to the input image displayed on display device 50. The processor 42 of control device 24 transmits the input data IP1 or IP2 input by operator A1 as described above to preventive maintenance device 14 via communication network 18.

[0110] In step S3', if processor 62 receives input data IP2 from control device 24, it determines that robot 20 needs to be separated (i.e., yes), and proceeds to step S6. On the other hand, if it receives input data IP1 from preventive maintenance device 14, it determines that robot 20 does not need to be separated (i.e., no), and proceeds to step S5. Then, processor 62 and... Figure 4 Similarly, steps S6 to S8 or step S5 are executed sequentially.

[0111] As described above, in this embodiment, the processor 62 determines whether robot 20 needs to be separated based on the anomaly determination information SI in step S3, and after providing step PR in step S4, it determines again whether robot 20 needs to be separated in step S3' based on the input data IP from operator A1. According to this structure, even if it is assumed that anomaly AB cannot be handled by step PR as prompted in step S4, the operation can continue by separating robot 20 in step S7. This reduces the possibility of operation interruption.

[0112] Furthermore, in the above embodiments, the case where the anomaly handling devices 90 and 100 are installed in the preventive maintenance device 14 is described. However, it is not limited to this, at least one of the components of the anomaly handling devices 90 or 100 (i.e., the storage unit 64, the anomaly detection unit 74, the input receiving unit 76, the data acquisition unit 78, the step acquisition unit 80, the display control unit 82, the approval / disapproval determination unit 84, the notification generation unit 86, and the communication control unit 88) may also be installed in the control device 24.

[0113] Figure 6 This indicates that it was done in this way. In Figure 6 In the network system 10 shown, the storage unit 64, input receiving unit 76, data acquisition unit 78, step acquisition unit 80, display control unit 82, approval / disapproval unit 84, notification generation unit 86 and communication control unit 88 of the fault handling device 100 are installed in the prevention and maintenance device 14. On the other hand, the fault detection unit 74 of the fault handling device 100 is installed in the control device 24.

[0114] exist Figure 6In the network system 10 shown, the processor 42 of the control device 24 and the processor 62 of the preventive maintenance device 14 communicate with each other while performing operations. Figure 4 or Figure 5 The process is shown below. Specifically, in step S1, the processor 42 of the control device 24 begins to acquire motion state data OD from the sensor 22. In step S2, it functions as an anomaly detection unit 74 and, similar to the above embodiment, determines whether an anomaly AB is detected based on the motion state data OD.

[0115] When an anomaly AB is detected in step S2 (i.e., it is determined to be true), the processor 42 of the control device 24 provides the anomaly determination information SI (specifically, the anomaly identification code SI1) of the detected anomaly AB to the preventive maintenance device 14 via the communication network 18. The processor 62 of the preventive maintenance device 14 functions as a data acquisition unit 78, and obtains the anomaly determination information SI from the control device 24. Steps S3 to S8 are executed sequentially in the same manner as in the above embodiment.

[0116] Furthermore, the anomaly handling device 90 or 100 may also be installed in the control device 24. In this case, the storage unit 44 of the control device 24 stores multiple steps PR associated with anomaly determination information SI, and the processor 42 of the control device 24 functions as an anomaly detection unit 74, an input receiving unit 76, a data acquisition unit 78, a step acquisition unit 80, a display control unit 82, an approval / disapproval determination unit 84, a notification generation unit 86, and a communication control unit 88.

[0117] Furthermore, the anomaly determination information SI is not limited to the anomaly identification code SI1, but may also include other arbitrary data used to determine anomalies AB. For example, the anomaly determination information SI may include a data identification code SI2 assigned separately to various motion state data OD detected by sensor 22 (e.g., rotational position Pm, rotational speed Vm, rotational acceleration αm, current value I, load torque τ, position Pc, speed Vc, acceleration αc, pressure P, voltage E, external force F, and image data ID, etc.).

[0118] The storage unit 64 (or 44) stores multiple steps PR along with data identification codes SI2. For example, a data identification code SI2 “DATA-E” is assigned to the voltage E detected by the voltage sensor 22E, and the step PR2 (image data describing the battery replacement steps) related to the abnormality AB2 of voltage E can be stored in the storage unit 64 along with the data identification code SI2 “DATA-E”.

[0119] Alternatively, multiple data identification codes SI2 can be assigned to a single type of motion state data OD based on its changing pattern. For example, regarding the external force F detected by force sensor 22F, multiple identification codes SI2 can be assigned for forces exceeding a reference value β. F1 The reduced external force F1 is assigned the data identification code SI2: "DATA-F1". On the other hand, for forces exceeding the benchmark value β... F2 The added external force F2 assigns the data identification code SI2: "DATA-F2".

[0120] In this case, step PR3 (image data illustrating the separation and operation of robot 20) related to the anomaly AB3 of reduced external force can be associated with the data identification code SI2: "DATA-F1" and stored in the storage unit 64. Additionally, step PR4 (image data illustrating the steps for confirming whether a collision has occurred) related to the anomaly AB4 of increased external force can be associated with the data identification code SI2: "DATA-F2" and stored in the storage unit 64.

[0121] The processor 62 (or 42) functions as a data acquisition unit 78, acquiring the data identification code SI2 as an anomaly determination information SI, replacing the aforementioned anomaly identification code SI1 (or something else). For example, when the processor 62 (or 42) detects an anomaly AB2 where the voltage E decreases, it functions as a data acquisition unit 78 and acquires the data identification code SI2 assigned to the voltage E: "DATA-E" as an anomaly determination information SI.

[0122] Additionally, the anomaly determination information SI may also include a sensor identification code SI3 assigned individually to each of the various sensors 22 (e.g., rotation detection sensor 22A, current sensor 22B, torque sensor 22C, pressure sensor 22D, voltage sensor 22E, force sensor 22F, and vision sensor 22G). The storage unit 64 (or 44) stores multiple steps PR in association with the sensor identification code SI3.

[0123] For example, by assigning a sensor identification code SI3: "SENSOR-E" to the voltage sensor 22E, the step PR2 related to the abnormal voltage E detected by the voltage sensor 22E AB2 can be associated with the sensor identification code SI3: "SENSOR-E" and stored in the storage unit 64.

[0124] Processor 62 (or 42) functions as data acquisition unit 78, acquiring sensor identification code SI3 as an anomaly determination information SI, replacing the aforementioned anomaly identification code SI1 (or other equivalents). For example, when processor 62 (or 42) detects an anomaly AB2 of voltage E decreasing, it functions as data acquisition unit 78 and acquires the sensor identification code SI3 assigned to the voltage sensor 22E that detected voltage E: "SENSOR-E", as an anomaly determination information SI. Furthermore, the anomaly identification code SI1, data identification code SI2, and sensor identification code SI3 are not limited to strings; for example, they can be combinations of symbols (○, △, □, +, -, *, etc.). Additionally, step PR can also include multilingual text data.

[0125] In addition, the anomaly AB and step PR can be various other than those illustrated in the above embodiments. For example, anomaly AB can include an anomaly AB6 indicating a communication failure between sensor 22 or servo motor 40 and control device 24 (I / O interface 46). This anomaly AB6 can be detected, for example, by monitoring the detection values ​​of sensor 22 or servo motor 40. Step PR6 for responding to this anomaly AB6 may include, for example, image or audio data describing the steps for confirming the connection of the communication cable between sensor 22 or servo motor 40 and control device 24.

[0126] Furthermore, Robot 20 is not limited to Figure 2 The vertical multi-joint robot shown can also be any type of robot, such as a horizontal multi-joint robot, a parallel linkage robot, or a worktable device with multiple ball screw mechanisms. The present disclosure has been described above through embodiments, but these embodiments do not limit the scope of the invention covered by the patent.

[0127] Explanation of reference numerals in the attached figures

[0128] 10 Network Systems

[0129] 12 Robot Systems

[0130] 14. Preventive and maintenance devices

[0131] 16 External Devices

[0132] 18 Communication Networks

[0133] 20 robots

[0134] 22 sensors

[0135] 24 control devices

[0136] 42, 62 processors

[0137] 74 Anomaly Detection Department

[0138] 76 Input Receiving Unit

[0139] 78 Data Acquisition Department

[0140] 80 steps to obtain part

[0141] 82 Display Control Unit

[0142] 84 Can it be determined?

[0143] 86 Notification Generation Department

[0144] 88. Communications Control Department.

Claims

1. An anomaly handling apparatus, comprising steps for responding to anomalies arising in a robotic system, characterized in that, The anomaly handling device includes: The storage unit stores the multiple steps for responding to the various exceptions as well as the exception determination information for determining the exception. as well as processor, The processor detects the anomaly based on the robot system's motion state data. The processor acquires the anomaly determination information of the detected anomaly and the capability determination information for determining whether the anomaly can be handled. Based on the anomaly detection information, the processor determines whether the robot needs to be detached from the production line. Based on the aforementioned capability assessment information, the processor determines whether it is capable of handling the detected anomaly. When the processor determines, based on the first exception determination information, that the separation is not required, it retrieves the first step corresponding to the first exception determination information from the plurality of steps stored in the storage unit. When the processor determines, based on the second exception determination information, that the separation is necessary and that it is capable of handling the exception, it retrieves the second step corresponding to the second exception determination information from the plurality of steps stored in the storage unit.

2. The anomaly handling device according to claim 1, characterized in that, The processor accepts the input of the steps and the exception determination information. The storage unit stores the steps received by the processor and the exception determination information in association.

3. The anomaly handling device according to claim 1 or 2, characterized in that, The anomaly determination information includes multiple anomaly identification codes that are individually assigned to each anomaly. The processor determines whether separation is necessary by judging whether the anomaly identification code obtained as an anomaly determination information is equivalent to an identification code that has been pre-classified as requiring the robot to be separated from the work line.

4. The anomaly handling device according to claim 1 or 2, characterized in that, The processor causes the obtained steps to be displayed as an image on the display device.

5. The anomaly handling device according to claim 1 or 2, characterized in that, The validity determination information includes an identification code used to identify the robot or the task performed by the robot. The processor determines whether it can handle the detected anomaly by determining whether the identification code obtained as the capability determination information is equivalent to the identification code stored in the data table as a failure to handle the anomaly.

6. The anomaly handling device according to claim 1 or 2, characterized in that, When the processor determines that it cannot handle the exception, it generates notification data to indicate that it cannot handle the exception, and sends the generated notification data to an external device of the exception handling device.

7. A network system, characterized in that, have: A robotic system comprising a robot and a control device for controlling the robot; and The anomaly handling apparatus according to any one of claims 1 to 6.

8. The network system according to claim 7, characterized in that, The network system includes a preventive maintenance device, which is communicatively connected to the control device via a communication network and obtains the operational status data from the control device. The anomaly handling device is installed in the prevention and maintenance device.

9. The network system according to claim 7, characterized in that, The network system includes a preventive maintenance device, which is communicatively connected to the control device via a communication network and obtains the operational status data from the control device. The storage unit of the anomaly handling device, the first processor for performing the function of obtaining the anomaly determination information, and the function of obtaining the step are installed in the preventive maintenance device. On the other hand, the second processor for performing the function of detecting the anomaly is installed in the control device. The control device provides the anomaly determination information detected by the second processor to the prevention and maintenance device via the communication network.

10. A method for providing steps for handling anomalies generated in a robotic system, characterized in that, The multiple steps for handling the various anomalies are associated with anomaly determination information for determining the anomaly and stored in the storage unit. The anomaly is detected based on the motion state data of the robot system. Obtain the anomaly determination information of the detected anomaly and the capability determination information for determining whether the anomaly can be handled. Based on the anomaly detection information, determine whether the robot needs to be separated from the production line. Based on the aforementioned feasibility information, determine whether the detected anomaly can be addressed. When it is determined, based on the first anomaly determination information, that the separation is not required, the first step corresponding to the first anomaly determination information is obtained from the plurality of steps stored in the storage unit. When it is determined, based on the second anomaly determination information, that the separation is necessary and that the anomaly can be handled, the second step corresponding to the second anomaly determination information is obtained from the plurality of steps stored in the storage unit.

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