Vehicle production system and control method of vehicle production system

Abstract

Introduced is a vehicle production system comprising: a path search unit which calculates multiple possible movement paths of a logistics robot on the basis of a departure point and a destination point of the logistics robot, and stores same; a path analysis unit which derives an alternative path of the logistics robot through movement distances according to the possible movement paths of the logistics robot, stored in the path search unit, or the degree of path overlapping between logistics robots, and stores same; and a path management unit which performs component transfer simulation according to the alternative path from the path analysis unit, and calculates a final path of the logistics robot in consideration of the time required for component transfer.

Description

Vehicle production system and vehicle production system control method

[0001] The present invention relates to a vehicle production system and a vehicle production system control method, and more particularly, to an invention applicable to a smart factory for producing vehicles.

[0002]

[0003] Smart logistics vehicles are being introduced not only in general logistics warehouses and factories, but also in smart factories that manufacture products with different specifications using various parts, to ensure flexible and efficient supply and transport of parts.

[0004] Smart logistics vehicles are a general term for autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and unmanned forklifts. These smart logistics vehicles can move and perform tasks under system control.

[0005] Meanwhile, smart logistics vehicles transport parts loaded on pallets to the location where the process is performed within the smart factory, and when parts are needed, smart logistics vehicles are called to the location where the process is performed within the smart factory.

[0006] When considering only one smart logistics vehicle, the most efficient route is to use the shortest route to the called location. However, when considering all smart logistics vehicles, if all smart logistics vehicles move along the shortest route, a bottleneck phenomenon occurs where smart logistics vehicles are simultaneously concentrated at a specific point, causing delays in logistics transport.

[0007] Therefore, there is a need for a system that can improve vehicle production efficiency by optimizing the movement path of all smart logistics vehicles.

[0008]

[0009] The matters described as background technology above are only intended to enhance understanding of the background of the present invention, and should not be taken as an admission that they correspond to prior art already known to those of ordinary skill in the art.

[0010]

[0011] The present invention has been proposed to solve these problems, and aims to provide a vehicle production system that can improve vehicle production efficiency by optimizing the movement path of the entire smart logistics vehicle.

[0012]

[0013] A vehicle production system for managing the movement path of a logistics robot transporting parts to each of multiple work spots in a smart factory, the system comprising: a path search unit for calculating and storing multiple possible movement paths of the logistics robot based on the starting point and the arrival point of the logistics robot transporting vehicle parts within the smart factory; a path analysis unit for deriving and storing an alternative path of the logistics robot through the movement distance according to the possible movement paths of the logistics robot stored in the path search unit or the degree of path overlap between the logistics robots; and a path management unit for performing a parts transport simulation according to the alternative path of the path analysis unit and calculating a final path of the logistics robot by considering the time required for transporting the parts.

[0014] The path search unit can implement a possible movement path of a logistics robot within a smart factory through connections between multiple nodes and a matrix.

[0015] The path search unit can select the starting point and destination point of the logistics robot and search and save the path from the starting point to the destination point using a depth search algorithm (DFS).

[0016] A production scheduling system further includes a work schedule for producing a vehicle, wherein information about the work schedule may include a work name, work time, and a starting point and an arrival point of a logistics robot for each work.

[0017] The path search unit receives a work schedule from the production scheduling system and can store multiple possible movement paths of the logistics robot corresponding to the work name.

[0018] A production scheduling system storing a work schedule for producing a vehicle; further comprising a path analysis unit receiving the work schedule from the production scheduling system, grouping tasks performed at the same time, and selecting one or more of the possible movement paths of logistics robots stored in the path search unit to calculate the degree of path overlap between logistics robots performing the grouped tasks.

[0019] The path analysis unit can calculate the degree of path overlap between logistics robots by mapping the work schedule received from the production scheduling system and the possible movement paths of logistics robots performing grouped tasks.

[0020] The path analysis unit determines alternative paths in the order of the minimum movement distance or degree of overlap of logistics robots performing grouped tasks, and can select and store alternative paths up to a standard number.

[0021] The path analysis unit stores multiple alternative paths for tasks performed at the same time, and the path management unit receives multiple alternative paths from the path analysis unit and performs a parts transport simulation for the multiple alternative paths to derive a final path that minimizes the time required for parts transport.

[0022]

[0023] A method for controlling a vehicle production system that manages a movement path of a logistics robot that transports parts to each of a plurality of work spots in a smart factory, the method comprising: a step in which a path search unit calculates and stores a plurality of possible movement paths of the logistics robot based on a starting point and an arrival point of the logistics robot that transports vehicle parts within the smart factory; a step in which a path analysis unit derives and stores an alternative path of the logistics robot based on a movement distance according to the possible movement paths of the logistics robot stored in the path search unit or a degree of path overlap between logistics robots; and a step in which a path management unit performs a simulation of movement of parts according to the alternative path of the path analysis unit and calculates a final path of the logistics robot by considering the time required to transport the parts.

[0024] The step of calculating and storing the possible movement path of the logistics robot can store the possible movement path of the logistics robot corresponding to the task name.

[0025] The step of deriving and storing an alternative route may include: a step of receiving a work schedule from a production scheduling system and grouping jobs to be performed at the same time; a step of selecting at least one of the possible movement paths of logistics robots stored in a path search unit and calculating the degree of path overlap between logistics robots performing the grouped tasks; a step of determining an alternative route in the order of the minimum movement distance of logistics robots performing the grouped tasks or the degree of path overlap between logistics robots by a path analysis unit; and a step of selecting and storing a number of alternative routes equal to or less than a standard number.

[0026] The step of calculating the degree of path overlap between logistics robots performing grouped tasks can calculate the degree of path overlap between logistics robots by mapping the work schedule transmitted from the production scheduling system and the possible movement paths of logistics robots performing grouped tasks.

[0027] In the step of deriving and storing an alternative path, multiple alternative paths for grouped tasks performed at the same time are stored, and the step of calculating the final path of the logistics robot may include a step of performing a parts transport simulation on the alternative paths stored in the path analysis unit; and a step of deriving a final path that minimizes the time required for parts transport as a result of the parts transport simulation.

[0028] By performing a part transfer simulation more than once, the final path that minimizes the average time required for part transfer can be derived from the part transfer simulation results.

[0029]

[0030] According to the vehicle production system and vehicle production system control method of the present invention, the movement path of the entire smart logistics vehicle can be optimized, thereby improving vehicle production efficiency.

[0031]

[0032] Figure 1 is a simplified illustration of part of the interior of a smart factory.

[0033] Figure 2 is intended to explain why the control method of conventional logistics robots causes inefficiency.

[0034] Figure 3 is a configuration diagram of a vehicle production system according to one embodiment of the present invention.

[0035] Figure 4 is for explaining the depth search algorithm.

[0036] Figure 5 is for explaining the work schedule of the production scheduling system.

[0037] Figure 6 is for explaining how the path search unit matches and stores the searched movable path with the work schedule.

[0038] Figures 7 and 8 illustrate overlapping nodes where parts transport paths and logistics robots for TE work and CM work performed at the same time overlap.

[0039] Figure 9 is for explaining the selection of an alternative route by the route analysis unit.

[0040] Figure 10 is for explaining the final route derivation of the route management unit.

[0041] Figures 11 to 13 are flowcharts of a vehicle production system control method according to one embodiment of the present invention.

[0042]

[0043] Hereinafter, embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Regardless of the drawing numbers, identical or similar components are given the same reference numbers and redundant descriptions thereof will be omitted.

[0044] In describing the embodiments disclosed in this specification, detailed descriptions of related known technologies will be omitted if it is determined that such detailed descriptions may obscure the gist of the embodiments disclosed in this specification. In addition, the attached drawings are provided solely to facilitate understanding of the embodiments disclosed in this specification, and the technical concepts disclosed in this specification are not limited by the attached drawings, and should be understood to include all modifications, equivalents, and substitutes included within the spirit and technical scope of the present invention.

[0045] Terms that include ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by these terms. These terms are used solely to distinguish one component from another.

[0046] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0047] In this specification, terms such as “include” or “have” are intended to specify the presence of a feature, number, step, operation, component, part or combination thereof described in the specification, but should be understood not to exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts or combinations thereof.

[0048] Hereinafter, among the configurations of the present invention to be described, a path search unit, a path analysis unit, a path management unit, and a production scheduling system may include a communication device for communicating with other controllers or sensors to control the functions in charge of the path search unit, the path analysis unit, the path management unit, and the production scheduling system, a memory for storing operating systems or logic commands and input / output information, and one or more processors for performing judgments, calculations, decisions, etc. necessary for controlling the functions in charge.

[0049] In addition, the following logistics robot is used as a general term for smart logistics vehicles such as autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and unmanned forklifts.

[0050]

[0051] Figure 1 is a simplified illustration of a portion of the interior of a smart factory. Referring to Figure 1, within the smart factory (100), there is a work spot (130) where processes necessary for vehicle production are performed. A logistics robot transports necessary parts to the work spot (130) depending on the type of process required for vehicle production.

[0052] To explain the specific parts transport procedure, the required parts are loaded onto a pallet, and the logistics robot can support and lift the lower part of the pallet loaded with parts to move the pallet to the work spot.

[0053] That is, when a logistics robot is called, it moves to the location where parts are loaded onto a pallet, lifts the pallet loaded with parts, and moves it back to the work spot (130).

[0054]

[0055] Figure 2 is intended to explain why the control method of conventional logistics robots causes inefficiency. Referring to Figure 2, logistics robots can transport parts to work spots where TE, CM, and FD tasks are performed. There can be five or more logistics robots for transporting parts required for TE, CM, and FD tasks, respectively, and each logistics robot is set to have a minimum movement distance. The logistics robot responsible for transporting parts required for TE tasks moves from location ①, the logistics robot responsible for transporting parts required for CM tasks moves from location ②, and the logistics robot responsible for transporting parts required for FD tasks moves from location ③ to each called location (as will be described later, the starting point and destination points of the logistics robots, and their movement paths, can be expressed as nodes). In addition, each of locations ①, ②, and ③ can be a location where a pallet loaded with parts required for each task is located.

[0056] Logistics robots transporting parts required for FD work do not overlap with other logistics robots, but logistics robots transporting parts required for TE and CM work do overlap with each other.

[0057] If logistics robots overlap, their movement speed may decrease, and if multiple logistics robots overlap at one point, managers may have to turn off the logistics robots and readjust their positions.

[0058] That is, even if each logistics robot is set to have a minimum movement distance, when considering the overall task, inefficiency in parts transport may occur due to multiple overlaps between logistics robots.

[0059]

[0060] The present invention can provide a vehicle production system that can minimize delays in transporting parts by calculating a movement path of a logistics robot that takes into account the movement of the entire logistics robot.

[0061] Figure 3 is a configuration diagram of a vehicle production system according to one embodiment of the present invention. Referring to Figure 3, the vehicle production system according to one embodiment of the present invention includes a path search unit (400), a path analysis unit (500), and a path management unit (600).

[0062] To explain the function of each configuration, the path search unit (400) calculates and stores multiple possible movement paths of the logistics robot based on the starting point and arrival point of the logistics robot transporting vehicle parts within the smart factory (100).

[0063] The path analysis unit (500) derives and stores an alternative path for the logistics robot through the movement distance according to the possible paths of the logistics robot stored in the path search unit (400) or the degree of path overlap between the logistics robots.

[0064] The path management unit (600) performs a simulation of parts transport according to the alternative path of the path analysis unit (500) and calculates the final path of the logistics robot by considering the time required for parts transport.

[0065] Specifically, the functions of each component are explained.

[0066] The path search unit (400) calculates and stores a possible path to move within the smart factory (100). Specifically, the path search unit (400) can implement the interior of the smart factory (100) in a simplified manner through connections between nodes by a plurality of nodes and a matrix, and the possible path to move can be expressed by the nodes.

[0067] When the starting point and destination point of the logistics robot are selected by the node implemented in this way, the path search unit (400) can search and store the path from the starting point to the destination point through a depth search algorithm (DFS).

[0068] The path search unit (400) performs path search based on a recursive function through a depth search algorithm, and can store all paths moving from the starting point to the destination point.

[0069] Referring to Fig. 4, this can be explained by saying that the smart factory (100) layout for searching a movable path can be implemented as a 1m X 1m grid structure, and a logistics robot can move around the node of each intersection.

[0070] For example, for a TE task, a logistics robot starts at Node 1, which becomes the starting point, and is called to Node 12, which becomes the destination. Some nodes between nodes may be unavailable due to unloaded items or other work sites. Therefore, these nodes are not assigned a serial number.

[0071] The method of searching for a possible path using a depth search algorithm is as follows.

[0072] First, we can define the priority of logistics robot movement. For example, if a logistics robot has the following movement priorities: north, east, south, and west, it will perform visit processing at the node it visits.

[0073] A logistics robot visits Node 1, the starting point, and performs processing. It can then move to Nodes 2 and 3, but based on movement priority, it visits Node 2 and performs processing there. From Node 2, the only node it can move to is Node 4, so it visits Node 4 and performs processing there. Similarly, from Node 4, the only node it can move to is Node 5, so it visits Node 5 and performs processing there. The process of moving from Node 5 to Nodes 7 and 10 is similar.

[0074] After visiting node 10, the remaining nodes available for movement are nodes 8 and 12. Node 8 is visited and processed based on movement priority. Since node 10 has already been visited, it moves to node 11. From node 11, it moves to node 12, processes the visit, and then performs the next path search.

[0075] In this way, using a recursive function, all cases of moving from node 1 to node 12 can be searched and stored. The path search unit (400) can store the movement path by node number, and in the above example, it is stored as 1, 2, 4, 5, 7, 10, 8, 11, 12, while the movement distance can be stored as 8.

[0076] The distance traveled can be stored in real time each time a node is visited, or it can be processed and stored in batches by searching the nodes passed when the destination is reached.

[0077] Furthermore, all paths starting from node n and arriving at node m can be explored and stored. By storing all paths in this way, node-based alternative path generation is possible, providing the advantage of flexible response even when the logistics robot's departure and arrival nodes change.

[0078]

[0079] Meanwhile, the vehicle production system according to the present invention may further include a production scheduling system (APS: Advanced Planning & Scheduling) (300) in which a work schedule for producing a vehicle is stored, and the path search unit (400) may receive information about the work schedule from the production scheduling system (300).

[0080] Specifically, referring to FIG. 5, information about the work schedule may include the work name, work time, and the starting point and arrival point of the logistics robot for each work.

[0081] The path search unit (400) can receive information about the work schedule from the production scheduling system (300) and store multiple possible movement paths of the logistics robot corresponding to the work name through the work name, work time, and starting point and arrival point.

[0082] Referring to FIG. 6, the path search unit (400) can match the received work schedule with the movable path and store the movable path corresponding to the work name.

[0083] For example, since the parts transport for the TE task starting at 09:00 starts from node 1 and arrives at node 15, the TE task can be matched and stored with the possible travel path starting from node 1 and arriving at node 15 among the searched paths.

[0084] In addition, since the parts transport for the CM task starting at 09:00 starts from node 3 and arrives at node 22, the CM task can be matched and saved by matching the possible movement path starting from node 3 and arriving at node 22 among the searched paths.

[0085] Accordingly, there are multiple possible movement paths for TE and CM operations.

[0086]

[0087] Meanwhile, the path analysis unit (500) is configured to produce an alternative path with a low degree of overlap through the degree of overlapping of nodes that may occur while logistics robots move among the possible paths searched and stored in the path search unit (400).

[0088] Here, overlap means that the starting order of the traversable path and the positions of two consecutive nodes are the same.

[0089] In order to analyze the path searched by the path search unit (400), the path search unit (400) can transmit the stored movable path to the path analysis unit (500).

[0090] Thereafter, the path search unit (400) can calculate the degree of overlap that may occur as logistics robots move, as illustrated in FIGS. 7 and 8. FIGS. 7 and 8 illustrate overlapping nodes where parts transport paths and logistics robots for TE and CM work performed at the same time overlap.

[0091] First, referring to Fig. 7, when explaining how the path search unit (400) determines the degree of overlap, by comparing the overlap of path a among the parts transport paths for TE work and path b among the parts transport paths for CM work, it can be determined that there are a total of 5 overlapping nodes.

[0092] That is, if path a is chosen for TE work and path b is chosen for CM work, the number of nodes where logistics robots overlap at the same time is 5. At this time, the travel distance of path a is 7, and the travel distance of path b is 8, for a total travel distance of 15.

[0093] Also, referring to Fig. 8, when comparing the overlap between path c among the parts transport paths for TE work and path d among the parts transport paths for CM work, it can be determined that there are a total of 0 overlapping nodes. In addition, it can be seen that the movement distance of path c is 5, and the movement distance of path d is 8, for a total movement distance of 13.

[0094] Comparing Figures 7 and 8, it can be seen that for transporting parts for TE and CM work performed at the same time, taking paths c and d rather than paths a and b is more efficient in terms of the degree of overlap and travel distance.

[0095] Referring to FIG. 9, the path analysis unit (500) can compare all parts transport paths for tasks to be performed through mapping to calculate the degree of overlap and movement distance, thereby deriving an alternative path.

[0096] Specifically, there are a total of 10 paths for performing TE tasks and a total of 20 paths for performing CM tasks, so by combining these, a total of 200 paths can be derived. The path analysis unit can derive alternative paths through the degree of overlap and travel distance for the 200 paths.

[0097]

[0098] Meanwhile, the route analysis unit (500) receives a work schedule from the production scheduling system (300), groups the work performed at the same time, and performs the above-described work. That is, referring to FIG. 5, the route analysis unit (500) groups parts transport for the TE work and the CM work for Car No. 1 that start at the same time (xx:xx). In addition, it groups parts transport for the FE work for Car No. 1 and the TE work for Car No. 2 that start at the same time (yy:yy). In addition, it groups parts transport for the CM work and the FE work for Car No. 2 that start at the same time (zz:zz).

[0099] For example, the path analysis unit (500) divides the work received from the production scheduling system (300) into 30-minute units, groups them, and calculates the degree of overlap in the work performed within the group.

[0100] As described above, through a path corresponding to a task name, the path analysis unit (500) can calculate the degree of path overlap and movement distance between logistics robots performing grouped tasks through mapping.

[0101] That is, the path analysis unit (500) can calculate the degree of path overlap between logistics robots by mapping the work schedule received from the production scheduling system (300) and the possible movement paths of logistics robots performing grouped tasks, and based on this, can derive an alternative path.

[0102] Meanwhile, the path analysis unit (500) determines alternative paths in the order of the minimum movement distance or degree of overlap of logistics robots performing grouped tasks. Alternative paths can be determined in the order of the lowest degree of overlap of logistics robots. If the degree of overlap of logistics robots is the same, alternative paths can be determined in the order of the lowest movement distance.

[0103] The path analysis unit (500) can select and store a number of alternative paths equal to or less than a standard number in order to select an alternative path to be transmitted to the path management unit (600) described later, and the standard number can be 20 or less.

[0104]

[0105] The path management unit (600) performs a parts transport simulation on the alternative paths stored in the path analysis unit (500). That is, the path management unit (600) evaluates the alternative paths through simulation and can derive the path resulting from the simulation, i.e., the path that minimizes the time required for parts transport, as the final path.

[0106] Specifically, referring to Fig. 10, when a simulation of parts transport is performed along the existing route, the time required is 3 hours and 49 minutes, and when a simulation of parts transport is performed for alternative route 1, the time required is 3 hours and 20 minutes. Since alternative route 1 takes the shortest time compared to alternative routes 2 to 20, the route management unit (600) can derive alternative route 1 as the final route.

[0107] At this time, the part transport simulation is performed at least once, and as a result of the part transport simulation, an alternative route that minimizes the average time required for part transport can be derived as the final route.

[0108] However, the user can arbitrarily change the final route by accessing the route management unit (600). That is, since there may be a difference between the results of the parts transport simulation and the results after actual application, the user can arbitrarily access the route management unit to have the parts transported via another alternative route.

[0109] When the final route is derived, the route management unit (600) can transmit the final route to the control system that controls and operates the logistics robot.

[0110]

[0111] Figures 11 to 13 are flowcharts of a vehicle production system control method according to one embodiment of the present invention. Referring to Figures 11 to 13, the vehicle production system control method of the present invention includes a step (S100) in which a path search unit (400) calculates and stores multiple possible movement paths of a logistics robot based on a starting point and an arrival point of a logistics robot transporting vehicle parts within a smart factory (100); a step (S200) in which a path analysis unit (500) derives and stores an alternative path of the logistics robot based on a movement distance according to the possible movement paths of the logistics robot stored in the path search unit (400) or the degree of path overlap between logistics robots; and a step (S300) in which a path management unit (600) performs a parts transport simulation according to the alternative path of the path analysis unit (500) and calculates a final path of the logistics robot by considering the time required to transport the parts.

[0112] In the step (S100) of calculating and storing the movement path of the logistics robot, the movement path of the logistics robot corresponding to the task name can be stored.

[0113] The step of deriving and storing an alternative route (S200) may include a step of receiving a work schedule from a production scheduling system (300) and grouping tasks to be performed at the same time (S210); a step of selecting one or more of the possible movement paths of logistics robots stored in a path search unit (400) and calculating the degree of path overlap between logistics robots performing the grouped tasks (S320); a step of determining an alternative route in the order of the minimum movement distance of logistics robots performing the grouped tasks or the degree of path overlap between logistics robots (S250) by a path analysis unit (500); and a step of selecting and storing alternative routes equal to or less than a standard number of routes (S270).

[0114] The step (S230) of calculating the degree of path overlap between logistics robots performing grouped tasks can calculate the degree of path overlap between logistics robots by mapping the work schedule transmitted from the production scheduling system (300) and the movable paths of logistics robots performing grouped tasks.

[0115] In the step of deriving and storing an alternative route (S250), multiple alternative routes for grouped tasks performed at the same time are stored, and the step of calculating the final route of the logistics robot (S300) may include a step of performing a parts transport simulation on the alternative route stored in the route analysis unit (500) (S310); and a step of deriving a final route that minimizes the time required for parts transport as a result of the parts transport simulation (S330).

[0116] Meanwhile, in the step of deriving the final path (S300), a part transfer simulation is performed at least once, and a final path can be derived that minimizes the average time required for part transfer as a result of the part transfer simulation.

[0117]

[0118] According to the present invention, in the case of some logistics robots, the movement distance may increase, but the parts transport path may be optimized in the overall movement of the logistics robot, so that the time required for parts transport may be reduced, and the occurrence of bottlenecks may be suppressed, thereby suppressing delays in logistics transport.

[0119] In addition, since the existing method writes the path of the logistics robot as a code used for programming, when the path of the logistics robot is changed, the change resource increases and the code must be modified by a professional programmer, but according to the present invention, even if there is a change in the departure node or arrival node, the path for all departure and arrival nodes is searched and stored, so there is an advantage in that it is possible to flexibly respond to node changes.

[0120]

[0121] Although the present invention has been illustrated and described with respect to specific embodiments thereof, it will be apparent to those skilled in the art that the present invention may be variously improved and modified without departing from the technical spirit of the present invention as defined by the following claims.

Claims

1. A vehicle production system that manages the movement path of logistics robots that transport parts to each of the multiple work spots in a smart factory. A path search unit that calculates and stores multiple possible movement paths of a logistics robot based on the starting point and destination point of the logistics robot transporting vehicle parts within a smart factory; A path analysis unit that derives and stores an alternative path for the logistics robot through the moving distance according to the possible paths of the logistics robots stored in the path search unit or the degree of path overlap between the logistics robots; and A vehicle production system including a path management unit that performs a parts transport simulation according to an alternative path of a path analysis unit and calculates a final path of a logistics robot by considering the time required to transport the parts.

2. In claim 1, A vehicle production system characterized in that the path search unit implements a possible movement path of a logistics robot within a smart factory through connections between nodes by a plurality of nodes and a matrix.

3. In claim 2, A vehicle production system characterized in that the path search unit selects the starting point and the destination point of the logistics robot and searches and stores the path from the starting point to the destination point using a depth search algorithm (DFS).

4. In claim 1, Further comprising a production scheduling system storing a work schedule for producing a vehicle; A vehicle production system characterized in that information about a work schedule includes a work name, work time, and a starting point and an arrival point of a logistics robot for each work.

5. In claim 4, A vehicle production system characterized in that the path search unit receives a work schedule from a production scheduling system and stores multiple possible movement paths of a logistics robot corresponding to the work name.

6. In claim 1, Further comprising a production scheduling system storing a work schedule for producing a vehicle; A vehicle production system characterized in that the path analysis unit receives a work schedule from a production scheduling system, groups tasks performed at the same time, selects one or more of the possible movement paths of the logistics robots stored in the path search unit, and calculates the degree of path overlap between the logistics robots performing the grouped tasks.

7. In claim 6, A vehicle production system characterized in that the path analysis unit calculates the degree of path overlap between logistics robots by mapping the work schedule transmitted from the production scheduling system and the possible movement paths of logistics robots performing grouped work.

8. In claim 6, A vehicle production system characterized in that the path analysis unit determines an alternative path in the order of the minimum movement distance or degree of overlap of logistics robots performing grouped tasks, and selects and stores a number of alternative paths equal to or less than a standard number.

9. In claim 1, A vehicle production system characterized in that the path analysis unit stores multiple alternative paths for work performed at the same time, and the path management unit receives multiple alternative paths from the path analysis unit and performs a parts transport simulation for the multiple alternative paths to derive a final path that minimizes the time required to transport the parts.

10. A method for controlling a vehicle production system that manages the movement path of a logistics robot that transports parts to each of multiple work spots in a smart factory, A step in which a path search unit calculates and stores multiple possible movement paths of a logistics robot based on the starting point and arrival point of the logistics robot transporting vehicle parts within a smart factory; A step in which a path analysis unit derives and stores an alternative path for a logistics robot through the moving distance according to the possible paths of the logistics robots stored in the path search unit or the degree of path overlap between logistics robots; A method for controlling a vehicle production system, comprising: a step of a path management unit performing a parts transport simulation according to an alternative path of a path analysis unit and calculating a final path of a logistics robot by considering the time required to transport the parts; 11. In claim 10, The step of calculating and saving the possible movement path of the logistics robot is: A vehicle production system control method characterized by storing a possible movement path of a logistics robot corresponding to a task name.

12. In claim 10, The steps for deriving and saving alternative paths are: A step of receiving a work schedule from a production scheduling system and grouping the work to be performed at the same time; A step of calculating the degree of path overlap between logistics robots performing grouped tasks by selecting one or more of the possible movement paths of logistics robots stored in the path search unit; The path analysis section determines an alternative path in the order of the minimum moving distance of the logistics robots performing the grouped task or the degree of path overlap between the logistics robots; and A vehicle production system control method, characterized by including a step of selecting and storing alternative routes in a number less than or equal to a standard number.

13. In claim 12, The step of calculating the degree of path overlap between logistics robots performing grouped tasks is A vehicle production system control method characterized by calculating the degree of path overlap between logistics robots by mapping the work schedule transmitted from a production scheduling system and the possible movement paths of logistics robots performing grouped work.

14. In claim 10, In the step of deriving and saving the alternative path, Multiple alternative paths for grouped tasks performed at the same time are stored, The step of calculating the final route of the logistics robot is: A step of performing a parts transport simulation for an alternative route stored in the route analysis unit; and A vehicle production system control method characterized by including a step of deriving a final path that minimizes the time required for transporting parts based on the results of a parts transport simulation.

15. In claim 14, A vehicle production system control method characterized by performing a parts transport simulation at least once and deriving a final path that minimizes the average time required for parts transport based on the parts transport simulation results.

Images