Control method and control device of intelligent factory

Abstract

The invention discloses a control method and a control device for an intelligent factory. The method comprises the following steps: determining and outputting a moving route of an intelligent logistics vehicle; the position of the intelligent logistics vehicle is checked, and a first control signal corresponding to the position is output; and checking the interlocking state while the intelligent logistics vehicle moves, and outputting or delaying a second control signal for stopping the intelligent logistics vehicle based on the interlocking state.

Description

Technical Field

[0001] The present disclosure relates to a control method and a control device for a smart factory that can effectively manage the processes of the smart factory. Background Art

[0002] In recent years, smart logistics vehicles have been introduced not only in general logistics warehouses and factories, but also in smart factories that use various components to manufacture products with different specifications.

[0003] Smart logistics vehicles are generally referred to as autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and unmanned forklifts, and these smart logistics vehicles can move and work under the control of a control system. In addition, the control system can control not only smart logistics vehicles, but also the operation of production facilities.

[0004] When such intelligent logistics vehicles and control systems are applied, the supply and delivery of parts, etc. can be handled flexibly and efficiently.

[0005] However, there are cases where the process is delayed depending on the control processing of the control system on the intelligent logistics vehicle, and therefore it is necessary to propose a method for improving process efficiency through rapid control processing.

[0006] The matters described above as background art are only intended to enhance the understanding of the background of the present disclosure and should not be regarded as an admission that they correspond to the prior art known to those skilled in the art. Summary of the invention

[0007] Technical issues

[0008] The purpose of the present disclosure is to provide a control method and a control device for a smart factory, which can effectively control smart logistics vehicles.

[0009] The technical tasks to be achieved by the present disclosure are not limited to the above-mentioned technical tasks, and those skilled in the art can clearly understand other technical tasks not mentioned from the following description.

[0010] Technical Solution

[0011] A control method for a smart factory for achieving the above-mentioned tasks according to an exemplary embodiment of the present disclosure includes the following steps: determining a moving route of a smart logistics vehicle to a specific area based on input production information and outputting the determined moving route; identifying a position of the smart logistics vehicle traveling along the moving route and outputting a first control signal corresponding to the identified position of the smart logistics vehicle to a process controller corresponding to the specific area; and identifying an interlock state corresponding to an entry requirement of a specific area from the process controller based on the first control signal output during the movement of the smart logistics vehicle, and outputting or delaying a second control signal capable of stopping the smart logistics vehicle based on the interlock state.

[0012] According to an exemplary embodiment of the present disclosure, a control device of a smart factory for realizing the above-mentioned tasks includes: a communication unit for communicating with at least one process controller; a task scheduling management unit for controlling the communication unit, determining a moving route of a smart logistics vehicle to a specific area based on input production information and outputting the determined moving route, identifying the position of the smart logistics vehicle traveling along the moving route, and outputting a first control signal corresponding to the identified position of the smart logistics vehicle to the process controller corresponding to the specific area; wherein the task scheduling management unit identifies an interlocking state corresponding to an entry requirement of a specific area from the process controller based on a first control signal output during the movement of the smart logistics vehicle, and outputs or delays a second control signal capable of stopping the smart logistics vehicle based on the interlocking state.

[0013] Beneficial Effects

[0014] Through the various exemplary embodiments of the present disclosure as described above, by controlling the process based on the position of the smart logistics vehicle while the smart logistics vehicle is traveling without separate control intervention, this can reduce the process delay generated when the smart logistics vehicle enters the process.

[0015] This can improve the control convenience of smart factories and improve process efficiency and productivity.

[0016] Effects obtained from the present disclosure are not limited to the above-mentioned effects, and other effects that are not mentioned may be clearly understood from the following description by those skilled in the art to which the present disclosure pertains. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a block diagram illustrating an example of a smart factory configuration applicable to an exemplary embodiment of the present disclosure.

[0018] Figure 2 : is a block diagram showing an example of a configuration of a control device applicable to an exemplary embodiment of the present invention.

[0019] Figure 3 is a block diagram showing an example of a smart logistics vehicle configuration applicable to an exemplary embodiment of the present disclosure.

[0020] Figure 4 is a perspective view showing an example of the exterior of a smart logistics vehicle applicable to an exemplary embodiment of the present disclosure.

[0021] Figure 5 The flowchart shows an example of the driving process of the intelligent logistics vehicle applicable to the exemplary embodiment of the present disclosure.

[0022] Figure 6 2 is a view for explaining the operation of the control device according to the exemplary embodiment of the present disclosure.

[0023] Figure 7 2 is a view for explaining a control process according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] Hereinafter, the exemplary embodiments disclosed in this specification will be described in detail with reference to the accompanying drawings, but the same or similar components will be assigned the same reference numbers regardless of the reference numbers, and their redundant descriptions will be omitted. The suffixes "module" and "unit" of the components used in the following description are assigned or used interchangeably only for the convenience of writing the specification, and do not have different meanings or functions in themselves. In addition, when describing the exemplary embodiments disclosed in this specification, when it is determined that the detailed description of the relevant known technology may make the subject of the exemplary embodiments disclosed in this specification unclear, its detailed description will be omitted. In addition, the accompanying drawings are merely intended to facilitate easy understanding of the exemplary embodiments disclosed in this specification, and the technical concepts disclosed in this specification are not limited by the accompanying drawings, and should be understood to include all modifications, equivalents or substitutes within the spirit and scope of the present disclosure.

[0025] Terms including ordinal numbers such as first and second may be used to describe various components, but the components are not limited by the above terms. These terms are used only for the purpose of distinguishing one component from another.

[0026] When referring to a component being "connected" or "linked" to another component, it should be understood that it can be directly connected or linked to the other component, but other components may exist in between. On the other hand, when referring to a component being "directly connected" or "directly connected" to another component, it should be understood that other components do not exist in between.

[0027] Unless the context clearly indicates otherwise, a singular expression includes a plural expression.

[0028] In this specification, terms such as "including" or "having" are intended to specify the existence of features, quantities, steps, operations, components, parts, or combinations thereof described in this specification, and it should be understood that the existence or addition of one or more other features, quantities, steps, operations, components, parts, or combinations thereof are not excluded.

[0029] In addition, the unit or control unit included in the internal configuration name of the intelligent logistics vehicle or control device is a term widely used to name a control device that controls a specific function, but does not mean a general functional unit. For example, each control device may include a modem / transceiver for communicating with other control devices or sensors to control the functions it is responsible for, a memory for storing operating systems or logic commands and input / output information, and one or more processors for performing determinations, calculations, and decisions necessary to control the functions it is responsible for. Depending on the embodiment, one processor may be responsible for the calculations of multiple control devices.

[0030] First, refer to Figure 1 A configuration of a smart factory that arranges and operates smart logistics vehicles according to an exemplary embodiment is described.

[0031] Figure 1 is a block diagram illustrating an example of a smart factory configuration applicable to an exemplary embodiment of the present disclosure.

[0032] Reference Figure 1 , the smart factory 100 may include a smart logistics vehicle 110, a production facility 120, a monitoring device 130 and a control device 140.

[0033] According to the production process and target production speed of the product, the smart factory 100 may be provided with a plurality of smart logistics vehicles 110, a plurality of production facilities 120, and a plurality of monitoring devices 130. Hereinafter, each component will be described.

[0034] First, the intelligent logistics vehicle 110 may include an autonomous mobile robot (hereinafter, referred to as "AMR" for convenience), an automated guided vehicle (hereinafter, referred to as "AGV" for convenience), and an unmanned forklift. According to the operation strategy of the intelligent logistics vehicle 110, only one type of AGV or AMR may be operated in the smart factory 100, or AGV and AMR may be operated together in a single smart factory 100.

[0035] The AGV can generally perform the required operations (movement, rotation, stop, etc.) within the smart factory 100 by identifying and following the guidance device set on the floor for the guidance of the AGV. Here, the guidance device may refer to an optically recognizable mark (spot, 2D code, etc.), a tag that can be identified in a close distance without contact (e.g., NFC tag, RFID tag, etc.), a magnetic strip, a wire, etc., but this may be merely an example and may not be limited to this. The guidance device may be arranged continuously on the floor or discontinuously spaced apart from each other. Since the AGV basically performs operations by identifying and following the guidance device, the AGV may need to pre-install the guidance device before operation, so that when the AGV needs to move to a new route or needs to modify an existing route, the installation or modification of the guidance device needs to be physically completed. In addition, since the AGV does not deviate from the route set by the guidance device, when an obstacle is detected on or near the route, the AGV can generally stop until the detected obstacle disappears or receives a separate control. In the operation of the AGV, the control device 140 should control the AGV based on the guidance device, so that commands such as "drive from the current position until the third mark is identified" and "switch the moving direction 90 degrees when the third mark is identified" can be sent to the AGV as a separate command unit or task unit including multiple commands (for example, recovery, supply, charging, patrol, etc.).

[0036] The AMR can determine the current position (i.e., positioning) by sensing its surroundings, and can perform its own path planning by using positioning and maps, which is the map that is most distinguished from the AGV. Therefore, when a map with coordinates compatible with the AMR and the control device 140 is shared, the control device 140 can control the AMR in a manner that instructs the AMR to take a route based on the coordinates. In addition, when an obstacle is detected while driving, the AMR can avoid the obstacle by setting its own avoidance route and then return to the original route. The function of the control device 140 to set the route of the AMR by using one or more intermediate coordinates can be referred to as global path planning, and the function of the AMR to set a moving route or avoidance route between intermediate coordinates according to the global path planning can be referred to as local path planning.

[0037] Respectively, a more detailed configuration of the intelligent logistics vehicle 110 will be referred to Figure 3 and Figure 4 Description, the AMR drive control process will be referred to later Figure 5 describe.

[0038] Next, the production facility 120 may refer to a device (e.g., a robotic arm, a conveyor belt, etc.) that performs a production process of a product in the smart factory 100, and in a broader sense, may refer to a device that is configured to assist in performing tasks (such as the entry and exit of the smart logistics vehicle 110) when a production process is performed by a person. The device configured to assist in performing a task may refer to a device for detecting the state of a specified location where a pallet carried by the smart logistics vehicle 110 can be dropped off or picked up in an area where a specific production process is performed, but is not necessarily limited thereto, and may refer to a device for determining the progress of a process and a tool for preventing entry into the area.

[0039] For example, the production facility 120 may be controlled by a programmable logic controller (PLC) and may be able to communicate with the control device 140 regarding process progress.

[0040] The monitoring device 130 may perform a function of obtaining information for determining a condition in the smart factory 100 and transmitting the information to the control device 140. For example, the monitoring device 130 may include a camera, a proximity sensor, etc., but may not necessarily be limited thereto.

[0041] By communicating with the above components 110, 120, 130, the control device 140 may be able to obtain information required for the operation of the smart factory 100 or control each component. For example, the control device 140 may perform deployment, route setting, task allocation, product process management, material management, etc. of the smart logistics vehicle 110.

[0042] In an embodiment, the control device 140 may include: a local control device (ACS: AMR / AGV control system) for controlling surrounding process facilities based on the position of the AGV / AMR and performing task-based control of the AGV / AMR; and an integrated control device (MoRIMS: mobile robot integrated monitoring system) for integrating and controlling more than two local control devices. The integrated control device can perform the status and route, logistics process setting, and traffic control of the entire intelligent logistics vehicle 110 in the smart factory 100 according to each of the multiple local control devices. For example, when the local control device (ACS) is set as a unit of intelligent logistics vehicles of the same manufacturer or model, the integrated control device can perform integrated control for preventing collisions, such as analysis of the narrowness in the intersection / overlapping area, drive acceleration / deceleration control, and reproduction of the avoidance route based on the information obtained through the multiple local control devices (ACS) through heterogeneous traffic logistics control.

[0043] Furthermore, the integrated control device may also have a Manufacturing Execution System (MES) as its higher control entity, and this Manufacturing Execution System (MES) may again be interlocked to an Automatic Scheduler (APS: Advanced Planning and Scheduling).

[0044] In addition to the above-mentioned configurations 110, 120, 130, 140 of the smart factory 100, devices for communicating with each other between each component (such as beacons, repeaters and APs (access points)), chargers for charging the smart logistics vehicles 110, loading spaces for storing or loading components, spaces for storing finished products or intermediate products, traffic lights, circuit breakers and waiting spaces for idle smart logistics vehicles 110 can be appropriately set within the smart factory 100.

[0045] In the following, reference will be made to Figure 2 The configuration of the control device 140 applicable to the exemplary embodiment of the present disclosure is described.

[0046] Figure 2 is a block diagram showing an example of a configuration of a control device applicable to an exemplary embodiment of the present invention. Figure 2 Each component shown in may primarily represent a component related to an exemplary embodiment of the present disclosure, and more or fewer components may be included in an actual embodiment of the control device 140 .

[0047] refer to Figure 2 The control device 140 may include a firmware management unit 141, a traffic control unit 142, a process management unit 143, a production / logistics management unit 144, an inventory management unit 145, a communication unit 146, a vehicle monitoring unit 147 and a map management unit 148.

[0048] The firmware management unit 141 can obtain the latest firmware of the smart logistics vehicle 110 through the communication unit 146 and send it to the smart logistics vehicle 110 to perform a firmware update, thereby maintaining the latest firmware of the smart logistics vehicle 110.

[0049] The traffic control unit 142 may control traffic lights and obstacles based on the route of the smart logistics vehicle 110 , and may recalculate the route of the smart logistics vehicle 110 depending on the traffic.

[0050] The process management unit 143 may define a process for each product, and may manage tasks such as a process progress and a process position.

[0051] The production / logistics management unit 144 may deploy the intelligent logistics vehicles 110 based on the tasks.

[0052] The inventory management unit 145 can manage the location and quantity of each material, and this information can be used for more efficient process operations, such as enabling the smart logistics vehicle 110 to depart for a destination for pallet pickup or recycling earlier than the time when the actual assembly / consumption of the material is detected.

[0053] The communication unit 146 can perform communications with internal components of the smart factory 100 (such as the smart logistics vehicle 110, the production facility 120, and the monitoring device 130) and external entities (such as a firmware update server).

[0054] The vehicle monitoring unit 147 can monitor the location, route, battery status, communication status, transmission status, etc. of each intelligent logistics vehicle 110. Here, the route can be a concept including a global route based on waypoints and a real-time local route. In addition, the battery status may include voltage, current, temperature, peak values ​​of voltage and current, state of charge (SOC), state of health (SOH), etc. The communication status may include information about the currently activated communication protocol (Wi-Fi, etc.), the connected AP, the distance to the AP, the channel in use, etc. Moreover, the transmission status may include the load, temperature, RPM, etc. of the drive system.

[0055] In addition, the vehicle monitoring unit 147 can identify the tasks, operating modes, firmware versions, etc. currently assigned to each smart logistics vehicle 110.

[0056] The map management unit 148 may obtain map data in the form of a grid map obtained when the AMR among the smart logistics vehicles 110 travels in the smart factory 100, and may provide the obtained map data to a tool edited by the factory manager. By editing the map data, an area, a virtual lane, an intersection, a prohibited entry area, etc., in which one or more preset operations are performed when the smart logistics vehicle 110 enters, may be set, but this may be exemplary and is not necessarily limited thereto. In addition, the map management unit 148 may distribute the corresponding map to the remaining smart logistics vehicles 110 other than the smart logistics vehicle 110 that obtains the initial grid map by actual driving through the communication unit 146.

[0057] Next, we will refer to Figure 3 and Figure 4 Describe the smart logistics vehicle.

[0058] Figure 3 is a block diagram showing an example of a smart logistics vehicle configuration applicable to an exemplary embodiment of the present disclosure.

[0059] Reference Figure 3, the smart logistics vehicle 110 may include a driving unit 111, a sensing unit 112, a loading unit 113, a communication unit 114, and a controller 115. Hereinafter, each component will be described.

[0060] The drive unit 111 may include a drive source, wheels, suspension, etc. involved in the movement, steering, and stopping of the intelligent logistics vehicle 110. The drive source may be an electric motor that receives power from a built-in battery (not shown). The wheels may include one or more drive wheels that receive a driving force from a drive source and a non-driven wheel that rotates by the movement of the vehicle body without receiving a driving force. According to an embodiment, when a plurality of drive wheels are provided, a drive source may be matched for each drive wheel so that the rotation of each drive wheel may be independently controlled. In this case, by changing the rotation direction of different drive wheels, steering can be achieved by rotating the vehicle body without a separate steering tool. At least some of the non-driven wheels may be configured as self-aligning wheels, but may be exemplary and not limited thereto.

[0061] The sensing unit 112 can be used to detect the surrounding environment of the intelligent logistics vehicle 100 or its own operating status, and can include at least one of a 2D laser scanner (e.g., LiDAR), a 3D vision (stereo) camera, a multi-axis gyroscope sensor, an acceleration sensor, a wheel encoder, and a proximity sensor.

[0062] The encoder may output information that can determine how much the wheel has rotated by using light emitted from a light emitting element (e.g., a photodiode). For example, the encoder may count the number of slits provided in a circumferential direction on a wheel or a disk that rotates with the wheel per unit time. The controller 115 is able to perform odometry by analyzing the amount of position change compared to time using data obtained from the encoder and the gyro sensor to estimate the displacement. However, the displacement estimated based on the encoder data may have an error with the actual displacement due to wheel slip or wear (change in the dynamic radius of the wheel). Therefore, when performing the odometry, the controller 115 may perform noise and error correction on the information collected from the wheel and the gyro sensor using a predetermined algorithm (e.g., EKF: Extended Kalman Filter), thereby outputting a result that tends to be close to the actual value. This odometry can be particularly useful when current position determination (positioning) using a 2D laser scanner (to be described later) is not possible.

[0063] A 2D laser scanner can scan an environment by irradiating the surrounding area with laser light via a rotating reflector and detecting the reflected signal. In this case, by analyzing the intensity of the reflected signal and the time difference between irradiation and reception, the detection result in the form of a point cloud can be output.

[0064] 3D vision cameras can calculate the distance to an object based on the parallax between two cameras separated by a certain distance (i.e., the pixel distance between the images captured by each camera). In this case, a texture projector can be set up to project a specific pattern of infrared light so that flat objects of the same color (e.g., a white wall) can be detected.

[0065] Typically, 2D laser scanners may be used for mapping, navigation, object recognition, etc., and 3D cameras may be particularly useful for avoiding obstacles during navigation, but these are examples and may not necessarily be limited thereto.

[0066] The loading unit 113 is a tool for loading the target product to be transferred, and may be in the form of a top plate itself located on the upper part of the vehicle body, a table set on the top plate, a lift, a turntable rotating along a vertical axis, a forklift, a conveyor belt, or a combination thereof. In the case of a forklift, similar to a forklift, telescopic and tilting functions may be supported.

[0067] The communication unit 114 can communicate with other components in the smart factory 100 (such as the production facility 120 and the control device 140), support communication between smart logistics vehicles 110, and communicate with the charger when performing charging tasks.

[0068] As an entity that performs overall control of each of the above-mentioned components 111, 112, 113, and 114, the controller 115 can perform current tasks, current position determination, destination determination, route planning, loading unit control, etc. based on information obtained from the control device 140 through the communication unit 114.

[0069] Figure 4 is a perspective view showing an example of the exterior of a smart logistics vehicle applicable to an exemplary embodiment of the present disclosure.

[0070] Reference Figure 4 , an example of AMR is shown as an intelligent logistics vehicle 110. The body may have a tracked plan shape having a long axis extending generally in the first axis direction. One drive wheel 111-1 may be disposed at a central portion of the body in the first axis direction, may be disposed on one side in the second axis direction, and another drive wheel (not shown) may be disposed on the other side to face the one drive wheel 111-1 in the second axis direction. This arrangement of drive wheels may be referred to as differential drive (DD). Although in Figure 4Not shown, more than two non-driven wheels may be provided at the lower portion of the vehicle body. In this case, when the two driving wheels rotate in the same direction at the same speed, they may rotate forward or backward along the first axis direction, and when rotating at the same speed in opposite directions, they may rotate along the third axis direction and based on a rotation axis extending along the center of the plane (C) passing through the vehicle body. In addition, the sensor unit 112 may be provided at the front surface of the vehicle body, and the loading unit 113 may be provided at the upper surface of the vehicle body. The loading unit 113 may be configured to rise and fall along the three-axis direction, and a rack, a pallet, etc. may be fixed to its upper surface by a guide 113-1.

[0071] However, the above Figure 4 The AMR forms may be exemplary, and it may be apparent that an AGV has a similar shape or an AMR has a different shape.

[0072] Next, we will refer to Figure 5 Describe the driving process of the intelligent logistics vehicle 110.

[0073] Figure 5 FIG. 1 is a flow chart showing an example of a driving process of an intelligent logistics vehicle applicable to an exemplary embodiment of the present disclosure. Figure 5 In the figure, for convenience, it can be assumed that the intelligent logistics vehicle 110 is an AMR capable of positioning and local route setting.

[0074] refer to Figure 5 ,First, the AMR can obtain a ground reality grid map through LiDAR and the ,other while driving inside the smart factory 100 (S501).

[0075] When the *AMR sends the obtained grid map to the control device 140, a grid map editing and matching process (S502) may be performed in the map management unit 148 of the control device 140. Here, the editing process may include a process of setting the above-mentioned various areas on the above-mentioned grid map, a process of assigning weights to each grid, etc. Here, the weight assignment may be performed in such a way that the closer the AMR is to an obstacle or a prohibited entry area, the higher the cost, so as to prevent the AMR from driving around obstacles or driving into an area it should not enter. This is because the AMR selects a cell set with the lowest weight among waypoints as the route when setting a local route.

[0076] In addition, the map matching process may refer to a process of matching coordinates between a CAD map used in the design of the smart factory 100, a ground truth grid map (LiDAR map), and a topological map of an edited process.

[0077] Thereafter, the control device 140 may share the topology map with all AMRs in the factory through the communication unit 146 ( S503 ).

[0078] Subsequent steps may be processes applied to individual AMRs.

[0079] The AMR may be able to determine the current position on the map through the sensor data of the sensing unit 112 and the obtained map (positioning) (S504). For example, the AMR may determine the current position by comparing the surrounding terrain obtained through LiDAR and the map based on feature points.

[0080] The control device 140 can select a specific AMR and assign a task, and the task can be assigned one or more waypoints that are usually determined by global path planning. Waypoints can be defined as coordinates on a map and can be accompanied by information about the direction in which the AMR should proceed at the corresponding coordinates (i.e., the direction of travel). According to the assignment of the task, the destination can be set in the AMR ("Yes" in S505), and the AMR can perform local path planning between waypoints based on the weights of the topological map (S506).

[0081] When the route is determined, the AMR may start driving (S507), and when an obstacle is detected by the sensing unit 112 during driving ("Yes" of S508), an evasive action may be performed by performing a local path search for bypassing the detected obstacle (S509). In some cases, the control device 140 may update the task of the corresponding AMR according to the evasive action or the failure of the evasive action.

[0082] Furthermore, the AMR may correct the position error during movement by the aforementioned odometry technique while traveling until reaching the destination ( S510 ).

[0083] Then, when arriving at the destination (S511), the AMR can perform task-based actions (S512). For example, the AMR can determine whether the conditions for entering a specific process area are clear, recycle an empty pallet from the destination, or put down a load loaded on the loading unit 113.

[0084] In an exemplary embodiment of the present disclosure, it may be proposed to improve the process efficiency of a smart factory and increase productivity by checking the possibility of entering a process in advance while a smart logistics vehicle is traveling and by controlling the process accordingly.

[0085] In the following, reference will be made to Figure 6 A smart logistics vehicle according to an exemplary embodiment is described.

[0086] Figure 6 2 is a view for explaining the operation of the control device according to the exemplary embodiment of the present disclosure.

[0087] refer to Figure 6According to the exemplary embodiment of the present disclosure, the control device 140 of the smart factory may include a communication unit 146 and a task scheduling management unit 149, and may take the location, production information, and interlocking status of smart logistics vehicles (such as AGVs and AMRs) as input information.

[0088] In addition, the control device 140 may output the movement route, the first control signal, and the second control signal as output information.

[0089] Here, production information and interlocking status may be obtained from process facilities such as the production facility 120 and the monitoring device 130 , and the location of the smart logistics vehicle may be obtained from the communication unit 114 of the smart logistics vehicle 110 .

[0090] At the same time, the control device 140 can determine the moving route based on the input information and send it to the intelligent logistics vehicle 110, and can control the process by outputting a first control signal for the process facility or outputting or delaying a second control signal for the intelligent logistics vehicle 110.

[0091] Hereinafter, detailed functions of the control device 140 according to the exemplary embodiment will be described.

[0092] First, the communication unit 146 may communicate with at least one process controller connected to the production facility 120. Here, the process controller may be implemented as, for example, the above-mentioned PLC.

[0093] The communication unit 146 can continuously exchange production information, interlocking status, first control signal, etc. with the process controller, and send it to the task scheduling management unit 149, so that the task scheduling management unit 149 can control the production facilities 120, intelligent logistics vehicles 110, etc.

[0094] In addition, the communication unit 146 can communicate with the communication unit 114 of the smart logistics vehicle 110 , so that the task scheduling management unit 149 can identify the location of the smart logistics vehicle 110 or control the smart logistics vehicle 110 .

[0095] At the same time, the task scheduling management unit 149 can control the communication unit 146 and can determine the moving route of the intelligent logistics vehicle 110 to a specific area based on the input production information.

[0096] Here, the production information may include at least one of operation information of a production robot for a specific area, production equipment information, and production equipment logistics release information.

[0097] The operation information of the production robot may include information on whether the robot is operating normally, information on the currently performed operation, etc., and the production equipment information may include the detection results obtained by the monitoring device 130, etc. In addition, the production equipment logistics release information may include the quantity, type and current location of the logistics.

[0098] At the same time, the task scheduling management unit 149 can determine whether to deploy the intelligent logistics vehicle 110 for at least one process based on the production information, and can determine the movement route of the intelligent logistics vehicle to the specific area corresponding to the process determined to be deployed. For example, the process that needs or requests to deploy the intelligent logistics vehicle 110 can be determined based on the production information, and the intelligent logistics vehicle 110 can be deployed to the corresponding process.

[0099] Furthermore, the task scheduling management unit 149 may determine whether to perform deployment by using a memory map pre-stored to correspond to production information.

[0100] In addition, the task scheduling management unit 149 can output the determined moving route so that the intelligent logistics vehicle 110 travels along the moving route.

[0101] In addition, the task scheduling management unit 149 can identify the position of the intelligent logistics vehicle 110 traveling along the moving route, and output a first control signal corresponding to the position of the identified intelligent logistics vehicle 110 to the process controller corresponding to the specific area. By receiving the first control signal, the process controller can obtain the position of the intelligent logistics vehicle 110 and reflect the position to determine production information, interlocking information, etc.

[0102] At the same time, the first control signal may correspond not only to the position of the intelligent logistics vehicle 110, but also to the operating state. Herein, the operating state of the intelligent logistics vehicle 110 may include whether the intelligent logistics vehicle 110 is parked, whether it is operating normally, what operation is currently being performed, or the expected end time.

[0103] Meanwhile, in an exemplary embodiment of the present disclosure, the intelligent logistics vehicle 110 may include at least one of an AMR and an AGV.

[0104] When the intelligent logistics vehicle 110 traveling along the moving route is an AMR, the location of the intelligent logistics vehicle 110 can be identified based on the detection results of surrounding objects by sensors connected to the robot.

[0105] In addition, when the intelligent logistics vehicle 110 traveling along the moving route is an automatic guided vehicle, the position of the intelligent logistics vehicle 110 can be identified based on whether it passes through nodes separately set at multiple points on the moving route.

[0106] In addition, the task scheduling management unit 149 can identify an interlocking state corresponding to a specific area entry requirement from the process controller based on the first control signal output during the movement of the smart logistics vehicle 110.

[0107] Here, the specific area may refer to an area where the process entered by the smart logistics vehicle 110 is performed, serving as the destination of the smart logistics vehicle 110 .

[0108] In addition, the interlocking state may correspond to the entry requirements of a specific area, that is, to the entry requirements of the target process, and may be determined by the work progress of the target process, the current work stage, whether it is operating normally, the quantity and type of logistics, etc. In addition, the position of the intelligent logistics vehicle 110 may be reflected in the interlocking state. For example, the current state may not allow the intelligent logistics vehicle 110 to enter the process, but the estimated arrival time according to the position of the intelligent logistics vehicle 110 may be reflected in the interlocking state, so that the process may be allowed to enter.

[0109] On the other hand, the interlocking state is determined by the process controller and sent to the task scheduling management unit 149 via the communication unit 146 .

[0110] At the same time, the task scheduling management unit 149 can output or delay the second control signal for stopping the intelligent logistics vehicle based on the interlocking state. For example, when it is determined according to the interlocking state that the process entry requirements are met, the intelligent logistics vehicle 110 can continue to travel along the moving route by delaying the second control signal, and when it is determined according to the interlocking state that the process entry requirements are not met, the intelligent logistics vehicle 110 can be stopped by outputting the second control signal.

[0111] At the same time, the task scheduling management unit 149 can set an interlocking area corresponding to a specific area on the moving route, and can output or delay a second control signal based on the interlocking state when the intelligent logistics vehicle enters the set interlocking area. The interlocking area can be understood as a space for checking whether the process entry is possible in advance before reaching the specific area, and by outputting or delaying the second control signal based on the interlocking state in the interlocking space, it can be ensured that the intelligent logistics vehicle 110 does not stop unnecessarily in the process of entering the process, and is allowed to stop when there is a reason such as not being able to enter the process.

[0112] At the same time, the task scheduling management unit 149 can determine and output the moving route again when the intelligent logistics vehicle reaches a specific area or stops according to the second control signal. That is, the production information, interlocking information, etc. can be initialized, and a new control process can be restarted.

[0113] In the following, reference will be made to Figure 7 A control process of a smart factory according to an exemplary embodiment is described.

[0114] Figure 7 is a view for explaining a control process according to an exemplary embodiment of the present disclosure.

[0115] refer to Figure 7 First, the communication unit 146 may receive production robot operation information, production equipment surrounding sensor information, production equipment logistics release information, etc. from the production facility 120 and the monitoring device 130. In addition, according to an exemplary embodiment, the production / logistics management unit 144 may receive production equipment logistics release information (S711-S713).

[0116] Thereafter, the communication unit 146 may send the production information to the task scheduling management unit 149 (S721-S723), and the task scheduling management unit 149 may determine and output the moving route of the intelligent logistics vehicle 110 based on the production information (S730).

[0117] The intelligent logistics vehicle 110 can travel along the output moving route, identify the current position through the controller 115 (S740), and send the information to the task scheduling management unit 149, so that the task scheduling management unit 149 can identify the position of the intelligent logistics vehicle 110 (S750).

[0118] The task scheduling management unit 149 can output a first control signal corresponding to the position of the intelligent logistics vehicle 110 to the process controller, so that the process controller can determine and control the interlocking information (S760), and identify the interlocking state from the process controller based on the first control signal (S770).

[0119] Thereafter, the task scheduling management unit 149 may output or delay a second control signal for stopping the intelligent logistics vehicle 110 based on the interlocking state and the position of the intelligent logistics vehicle. In this case, when the process cannot be entered, for example, when an abnormality in process control is identified according to the interlocking state, a second control signal may be output to control the intelligent logistics vehicle 110 to stop (S780).

[0120] Through the various exemplary embodiments of the present disclosure as described above, by controlling the process based on the position of the smart logistics vehicle while the smart logistics vehicle is traveling without separate control intervention, this can reduce the process delay generated when the smart logistics vehicle enters the process.

[0121] Through this, the control convenience of the smart factory can be increased and the process efficiency and productivity can be improved.

[0122] While the present disclosure has been shown and described in conjunction with the specific exemplary embodiments thereof as described above, it will be apparent to those skilled in the art that various modifications and changes may be made to the present disclosure without departing from the scope of the technical concept of the present disclosure provided by the appended claims.

[0123] [Explanation of Reference Numbers]

[0124] 100 Smart Factory

[0125] 110 Intelligent logistics vehicles

[0126] 120 Production equipment

[0127] 130 Monitoring Device

[0128] 140 Control device.

Claims

1. A control method for a smart factory, the method comprising: Determine a moving route for the intelligent logistics vehicle to a specific area based on the input production information and output the determined moving route; Identifying the position of the intelligent logistics vehicle traveling along the moving route, and outputting a first control signal corresponding to the identified position of the intelligent logistics vehicle to a process controller corresponding to the specific area; as well as Based on the first control signal output during the movement of the intelligent logistics vehicle, an interlock state corresponding to the entry requirement of the specific area is identified from the process controller, and a second control signal capable of stopping the intelligent logistics vehicle is output or delayed based on the interlock state.

2. The method according to claim 1, wherein: The production information includes: The production robot releases at least one of operation information, production equipment information and production equipment logistics information for the specific area.

3. The method according to claim 1, wherein: Outputting the moving route includes: Determine whether to deploy at least one process based on the production information; and Determine a movement route of the intelligent logistics vehicle to a specific area corresponding to the process determined to be deployed.

4. The method according to claim 3, wherein: Determining whether to deploy includes: Whether to perform deployment is determined by using a memory map pre-stored to correspond to the production information.

5. The method according to claim 1, wherein: The intelligent logistics vehicle comprises: At least one of an autonomous mobile robot (AMR, autonomous mobile robot) and an automatic guided vehicle (AGV, automatic guided vehicle).

6. The method according to claim 5, wherein: When the intelligent logistics vehicle traveling along the moving route is the autonomous mobile robot, the position of the intelligent logistics vehicle is identified based on the detection results of surrounding objects by sensors connected to the autonomous mobile robot.

7. The method according to claim 5, wherein: When the intelligent logistics vehicle traveling along the moving route is the automatic guided vehicle, the position of the intelligent logistics vehicle is identified based on whether the intelligent logistics vehicle passes through nodes arranged at intervals in the form of multiple points on the moving route.

8. The method according to claim 1, wherein: The first control signal corresponds to the operating state of the intelligent logistics vehicle.

9. The method according to claim 1, wherein: Outputting or delaying the second control signal includes: setting an interlocking area corresponding to the specific area on the moving route; and When the intelligent logistics vehicle enters the set interlocking area, the second control signal is output or delayed based on the interlocking state.

10. The method according to claim 1, wherein: When the intelligent logistics vehicle reaches the specific area or stops according to the second control signal, the process of the method returns to outputting the moving route.

11. A control device for a smart factory, the device comprising: a communication unit, communicating with at least one process controller; as well as a task scheduling management unit, which controls the communication unit, determines a moving route of the intelligent logistics vehicle to a specific area based on the input production information and outputs the determined moving route, identifies the position of the intelligent logistics vehicle traveling along the moving route, and outputs a first control signal corresponding to the identified position of the intelligent logistics vehicle to a process controller corresponding to the specific area, Among them, the task scheduling management unit identifies the interlocking state corresponding to the entry requirement of the specific area from the process controller based on the first control signal output during the movement of the intelligent logistics vehicle, and outputs or delays the second control signal capable of stopping the intelligent logistics vehicle based on the interlocking state.

12. The device according to claim 11, wherein The production information includes: The production robot releases at least one of operation information, production equipment information and production equipment logistics information for the specific area.

13. The device according to claim 11, wherein: The task scheduling management unit determines whether to deploy at least one process based on the production information, and determines a moving route of the intelligent logistics vehicle to a specific area corresponding to the process determined to be deployed.

14. The device according to claim 13, wherein: The task scheduling management unit determines whether to perform deployment by using a memory map pre-stored to correspond to the production information.

15. The device according to claim 11, wherein The intelligent logistics vehicle comprises: At least one of an autonomous mobile robot (AMR, autonomous mobile robot) and an automatic guided vehicle (AGV, automatic guided vehicle).

16. The device according to claim 15, wherein: When the intelligent logistics vehicle traveling along the moving route is the autonomous mobile robot, the position of the intelligent logistics vehicle is identified based on the detection results of surrounding objects by sensors connected to the autonomous mobile robot.

17. The device according to claim 15, wherein: When the intelligent logistics vehicle traveling along the moving route is the automatic guided vehicle, the position of the intelligent logistics vehicle is identified based on whether the intelligent logistics vehicle passes through nodes that are set at multiple points on the moving route.

18. The device according to claim 11, wherein The first control signal corresponds to the operating state of the intelligent logistics vehicle.

19. The device according to claim 11, wherein: The task scheduling management unit sets an interlocking area corresponding to the specific area on the moving route, and when the intelligent logistics vehicle enters the set interlocking area, the second control signal is output or delayed based on the interlocking state.

20. The device according to claim 11, wherein When the intelligent logistics vehicle reaches the specific area or stops according to the second control signal, the task scheduling management unit determines and outputs the moving route again.

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