Multi-station collaborative steel plate cutting drawing distribution method and system

Abstract

The invention discloses a multi-station cooperative steel plate cutting drawing distribution method and system, and relates to the related field of steel plate cutting, and the method comprises the steps: connecting a steel plate cutting central control center to determine a plurality of cutting subtasks of a plurality of cutting stations; constructing a multi-station equipment fault prediction module for the plurality of cutting stations; steel plate cutting drawings are distributed once on the basis of a plurality of cutting subtasks and a plurality of cutting stations, a plurality of cutting equipment operation data of the plurality of cutting stations are collected and input into a multi-station equipment fault prediction module for analysis, and fault stations and non-fault stations are positioned; determining a redistribution sub-task and a redistribution cutting drawing corresponding to the fault station, and performing dual constraints of cutting quality and conversion load balance in a non-fault station to generate a redistribution scheme; and carrying out secondary distribution on the redistribution cutting drawing. The technical problem that existing drawing distribution is low in distribution efficiency and distribution accuracy is solved, and the technical effect of improving the drawing distribution efficiency and distribution accuracy is achieved.

Description

Technical Field

[0001] This application relates to the field related to steel plate cutting, and particularly to a method and system for distributing steel plate cutting drawings with multi-station collaboration. Background Art

[0002] With the rapid development of the manufacturing industry, steel plate cutting, as an important link in metal processing, has increasingly higher requirements for production efficiency and cutting quality. In order to achieve efficient and precise steel plate cutting, a multi-station collaborative operation mode has emerged. In this mode, multiple cutting stations work simultaneously to jointly complete complex cutting tasks. However, with the increase in the number of stations and the extension of equipment operation time, the risk of equipment failure also increases, which poses a severe challenge to the continuity and stability of the production line. In the existing multi-station collaborative steel plate cutting methods, manual monitoring and manual adjustment are usually adopted to deal with equipment failures. When a failure occurs at a certain station, the operator needs to discover it in time and manually transfer the task to other stations. This method cannot detect equipment failures in time, resulting in a long interruption time of production tasks and affecting production efficiency. Moreover, when manually adjusting task allocation, the actual situations of each station cannot be fully considered, resulting in unreasonable task allocation and affecting cutting quality and equipment utilization rate.

[0003] In the current related technologies, there are technical problems of low distribution efficiency and low distribution accuracy in the distribution of steel plate cutting drawings with multi-station collaboration. Summary of the Invention

[0004] By providing a method and system for distributing steel plate cutting drawings with multi-station collaboration, this application connects to the central control center of steel plate cutting, obtains the task information of each cutting station in real time, trains a multi-station equipment failure prediction module based on historical failure record data, distributes the steel plate cutting drawings once according to the cutting subtasks and station information, collects the equipment operation data of each cutting station, inputs it into the failure prediction module for analysis, locates the failure stations and non-failure stations, for the failure stations, determines the corresponding reallocated subtasks and reallocated cutting drawings, in the non-failure stations, considering the dual constraints of cutting quality and conversion load balance, generates a reallocation plan, and based on the reallocation plan, distributes the reallocated cutting drawings a second time and other technical means, achieving the technical effect of improving the drawing distribution efficiency and distribution accuracy.

[0005] The present application provides a method for distributing steel plate cutting drawings with multi-station collaboration, including: connecting to the central control center of steel plate cutting to determine multiple cutting subtasks of multiple cutting stations; constructing a multi-station equipment failure prediction module for the multiple cutting stations, and the multi-station equipment failure prediction module is trained based on historical failure record data; distributing the steel plate cutting drawings once based on the multiple cutting subtasks and the multiple cutting stations, collecting the operation data of multiple cutting devices at the multiple cutting stations, inputting the data into the multi-station equipment failure prediction module for analysis, and locating the failure stations and non-failure stations; determining the reallocation subtasks and reallocation cutting drawings corresponding to the failure stations, performing double constraints of cutting quality and conversion load balancing among the non-failure stations to generate a reallocation plan; and performing secondary distribution of the reallocation cutting drawings based on the reallocation plan.

[0006] In a possible implementation manner, to determine the reallocation subtasks and reallocation cutting drawings corresponding to the failure stations, perform double constraints of cutting quality and conversion load balancing among the non-failure stations to generate a reallocation plan, the following processing is executed: performing cutting complexity analysis on the reallocation subtasks based on the reallocation cutting drawings to generate a cutting complexity index; determining the task cutting precision requirements of the reallocation subtasks; performing cutting quality constraints among the non-failure stations based on the cutting complexity index and the task cutting precision requirements to generate a first constraint station set; and performing load balancing constraints after station conversion on the reallocation subtasks in the first constraint station set to generate the reallocation plan.

[0007] In a possible implementation manner, to perform cutting quality constraints among the non-failure stations based on the cutting complexity index and the task cutting precision requirements to generate a first constraint station set, the following processing is executed: collecting historical steel plate cutting record data of the non-failure stations; performing cutting precision statistics of different cutting path complexities based on the historical steel plate cutting record data to generate a complexity-precision mapping relationship; and screening the stations that simultaneously meet the cutting complexity index and the task cutting precision requirements among the non-failure stations based on the complexity-precision mapping relationship to form the first constraint station set.

[0008] In a possible implementation, perform the following processing for generating the reallocation plan by performing load balancing constraints on the reallocation subtasks after station conversion in the set of primary constraint stations: Determine the basic cutting equipment features of all stations in the set of primary constraint stations, compare them with the basic cutting equipment features of the faulty station, and obtain a set of secondary constraint stations whose basic cutting equipment features are the same as those of the faulty station; Obtain the current task load information corresponding to all secondary constraint stations in the set of secondary constraint stations; With the goal of minimizing the load balancing index, and using the set of secondary constraint stations as the balanced allocation space, perform balanced allocation of the reallocation subtasks based on the current task load information to generate the reallocation plan.

[0009] In a possible implementation, also perform the following processing: Obtain multiple compatible drawing formats corresponding to the multiple cutting stations; Construct a drawing distribution model with the multiple compatible drawing formats, where the drawing distribution model includes a format judgment channel and a format conversion channel; Embed the drawing distribution model into the central control center for steel plate cutting to perform the distribution processing of cutting drawings.

[0010] In a possible implementation, when determining the reallocation subtasks and reallocation cutting drawings corresponding to the faulty station, perform the following processing: Obtain the initial cutting subtasks and the tasks that have been executed at the faulty station; Extract the difference set between the initial cutting subtasks and the tasks that have been executed to generate the first reallocation subtask; Perform cutting quality verification on the tasks that have been executed, and generate the second reallocation subtask with the tasks whose verification results fail; Generate the reallocation subtasks with the first reallocation subtask and the second reallocation subtask, and extract the corresponding cutting drawings to generate the reallocation cutting drawings.

[0011] In a possible implementation, also perform the following processing: After locating the faulty station, generate a fault warning signal for the faulty station.

[0012] The present application also provides a steel plate cutting drawing distribution system with multi-station collaboration, including: a cutting subtask determination module for connecting to the central control center of steel plate cutting to determine multiple cutting subtasks for multiple cutting stations; a multi-station equipment failure prediction construction module for constructing a multi-station equipment failure prediction module for the multiple cutting stations, where the multi-station equipment failure prediction module is trained based on historical failure record data; a station equipment failure prediction module for distributing a steel plate cutting drawing once based on the multiple cutting subtasks and the multiple cutting stations, collecting the operation data of multiple cutting devices at the multiple cutting stations, and inputting the data into the multi-station equipment failure prediction module for analysis to locate the faulty stations and non-faulty stations; a reallocation plan generation module for determining the reallocation subtasks and reallocation cutting drawings corresponding to the faulty stations, performing double constraints on cutting quality and conversion load balance among the non-faulty stations, and generating a reallocation plan; and a drawing secondary distribution module for performing secondary distribution of the reallocation cutting drawings based on the reallocation plan.

[0013] It is intended to first connect to the central control center of steel plate cutting through the multi-station collaborative steel plate cutting drawing distribution method and system proposed in this application to determine multiple cutting subtasks for multiple cutting stations, then construct a multi-station equipment failure prediction module for the multiple cutting stations, where the multi-station equipment failure prediction module is trained based on historical failure record data, then distribute a steel plate cutting drawing once based on the multiple cutting subtasks and the multiple cutting stations, collect the operation data of multiple cutting devices at the multiple cutting stations, input the data into the multi-station equipment failure prediction module for analysis to locate the faulty stations and non-faulty stations, then determine the reallocation subtasks and reallocation cutting drawings corresponding to the faulty stations, perform double constraints on cutting quality and conversion load balance among the non-faulty stations to generate a reallocation plan, and finally perform secondary distribution of the reallocation cutting drawings based on the reallocation plan, achieving the technical effects of improving the drawing distribution efficiency and distribution accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments of the present invention will be briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the operations before or below do not necessarily need to be executed precisely in sequence. On the contrary, according to needs, they can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0015] Figure 1 It is a schematic flowchart of the multi-station collaborative steel plate cutting drawing distribution method provided by the embodiment of the present application.

[0016] Figure 2Schematic diagram of the structure of the steel plate cutting drawing distribution system with multi-station collaboration provided by the embodiments of the present application.

[0017] Explanation of reference numerals in the drawings: cutting sub-task determination module 10, multi-station equipment failure prediction construction module 20, station equipment failure prediction module 30, reallocation plan generation module 40, drawing secondary distribution module 50. Detailed implementation manners

[0018] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically gives the detailed implementation manners of the present application.

[0019] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings. The described embodiments should not be regarded as limitations of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0020] In the following description, "some embodiments" are involved, which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first" and "second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules not clearly listed or inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0021] The embodiments of the present application provide a method for distributing steel plate cutting drawings with multi-station collaboration, as Figure 1 shown. The method includes:

[0022] Step S100, connect to the steel plate cutting central control center to determine multiple cutting sub-tasks of multiple cutting stations.

[0023] Specifically, connect the steel plate cutting central control center through the network. The steel plate cutting central control center is a system that centrally manages and monitors all cutting stations. It can be a cloud-based platform or a local server, capable of receiving tasks from the production planning system and allocating these tasks to different cutting stations. The steel plate cutting central control center will split the overall cutting task into multiple sub-tasks (specific work units) according to the size, shape, material, and cutting requirements of the steel plate. Each sub-task corresponds to a cutting station or a group of stations. Among them, the cutting station refers to the specific location or equipment for steel plate cutting, and each station is equipped with different cutting tools and technologies.

[0024] Step S200, construct a multi-station equipment fault prediction module for the multiple cutting stations. The multi-station equipment fault prediction module is trained based on historical fault record data.

[0025] Specifically, collect the historical fault record data of each cutting station, including fault type, occurrence time, repair record, etc. Then, use this data to train a prediction model based on machine learning or deep learning techniques. This model can predict future faults based on the current equipment operation data.

[0026] Step S300, distribute a steel plate cutting drawing based on the multiple cutting sub-tasks and the multiple cutting stations, and collect the operation data of multiple cutting devices at the multiple cutting stations, and input them into the multi-station equipment fault prediction module for analysis to locate the fault stations and non-fault stations.

[0027] Specifically, according to the task allocation determined in step S100, distribute the cutting drawing (a drawing or file containing information such as the steel plate cutting path and dimensions) to the corresponding cutting stations. Use sensors or other monitoring devices to collect the operation data of the cutting devices in real time, such as current, voltage, temperature, vibration, etc. Input the collected operation data into the multi-station equipment fault prediction module constructed in step S200 to identify potential fault stations.

[0028] Step S400, determine the reallocated sub-tasks and reallocated cutting drawings corresponding to the fault stations, and perform double constraints on cutting quality and conversion load balancing among the non-fault stations to generate a reallocation plan.

[0029] Specifically, for the workstations where faults are predicted, it is necessary to reassign their tasks to other non-faulty workstations. Therefore, it is necessary to regenerate or adjust the cutting drawings. When reassigning tasks, an optimization algorithm is used to find the best task assignment plan (reassignment plan) to ensure that the cutting quality (accuracy, precision, and consistency of the cutting results) is not affected and to avoid overloading some workstations while other workstations are idle (i.e., achieve load balancing when distributing tasks among different workstations). Among them, the reassigned subtask refers to reassigning the tasks originally assigned to the faulty workstation to other workstations. The reassigned cutting drawing refers to the cutting drawing generated for the reassigned tasks.

[0030] In a possible implementation, to determine the reassigned subtasks and reassigned cutting drawings corresponding to the faulty workstation, step S400 further includes step S410 of obtaining the initial cutting subtasks and executed tasks of the faulty workstation. Specifically, by connecting to the central control center of steel plate cutting and performing a database query operation, retrieve the task records of a specific faulty workstation from the task management system, including information such as task ID, task description, drawing number, etc., to obtain the initial cutting subtasks (i.e., planned tasks) assigned to this workstation before the fault occurred and the partially executed tasks.

[0031] Step S420, extract the difference set between the initial cutting subtasks and the executed tasks to generate the first reassigned subtasks. Specifically, use set operations to calculate the difference set, traverse the initial task list and the executed task list, compare the task IDs or unique identifiers, identify the unfinished tasks, and output these tasks as the first reassigned subtasks.

[0032] Step S430, perform a cutting quality check on the executed tasks, and generate the second reassigned subtasks for the tasks that fail the check result. Specifically, for each executed task, use a quality detection sensor to perform a quality assessment, read the output data of the quality detection device, or query the quality detection report database. If the task fails the quality inspection (such as dimensional deviation, surface defects, etc.), then add this task to the second reassigned subtask list.

[0033] Step S440: Generate the reallocation subtasks using the first-level reallocation subtasks and the second-level reallocation subtasks, and extract the corresponding cutting drawings to generate the reallocation cutting drawings. Specifically, merge the first-level reallocation subtasks and the second-level reallocation subtasks to form a complete reallocation task list. Traverse this list, retrieve the corresponding cutting drawings from the drawing repository according to the drawing numbers or links in the tasks, and package or mark these drawings as reallocation cutting drawings to be redistributed. This implementation method distinguishes between unexecuted tasks and tasks that have been executed but do not meet the quality requirements, avoiding the omission of important tasks, and at the same time correcting quality problems in a timely manner, ensuring that the tasks on the faulty workstations are effectively reallocated.

[0034] In a possible implementation, perform dual constraints on cutting quality and conversion load balancing in the non-faulty workstations to generate a reallocation plan. Step S400 further includes step S450: Analyze the cutting complexity of the reallocation subtasks based on the reallocation cutting drawings to generate a cutting complexity index. Specifically, use a predefined algorithm or model to analyze each reallocation subtask (i.e., the task that needs to be transferred from the faulty workstation), evaluate the difficulty of its cutting, including considerations of various aspects such as the shape, size, material of the steel plate in the drawing, and the complexity of the required cutting path, and calculate the cutting complexity index for each task. The cutting complexity index is a quantitative value used to measure the difficulty of the cutting task.

[0035] Step S460: Determine the task cutting precision requirements for the reallocation subtasks. Specifically, refer to the original order information, customer requirements, or industry standards, etc., and determine the cutting precision requirements according to the specific requirements of each reallocation subtask, that is, the specific requirements for the cutting task in terms of dimensions, shape, surface quality, etc., including the flatness, perpendicularity, dimension accuracy, etc. of the cutting edge.

[0036] Step S470: Perform cutting quality constraints in the non-faulty workstations based on the cutting complexity index and the task cutting precision requirements to generate a first-level constrained workstation set. Specifically, use the cutting complexity index and the task cutting precision requirements as screening conditions, and comprehensively consider factors such as the equipment capabilities of the workstations and the historical cutting quality records to evaluate the non-faulty workstations, and select the workstations that can meet these conditions to form the first-level constrained workstation set.

[0037] Step S480: Perform load balancing constraints on the reassigned subtasks after station conversion in the set of primary constraint stations to generate the reassignment plan. Specifically, on the basis of ensuring cutting quality and accuracy, further consider the load balance between stations, including evaluating factors such as the current workload, task queue length, and estimated completion time of each station, to ensure that the workloads of each station are relatively balanced after reassignment and avoid situations where some stations are overloaded while others are idle. Generate the final reassignment plan through an optimization algorithm. This implementation method comprehensively considers cutting complexity, cutting accuracy requirements, and load balance between stations, ensuring that the reassigned tasks can be efficiently completed while guaranteeing quality, thereby minimizing the impact of equipment failures on production.

[0038] In a possible implementation, perform cutting quality constraints on the non-faulty stations based on the cutting complexity index and the task cutting accuracy requirements to generate a set of primary constraint stations. Step S470 further includes step S471: Collect historical steel plate cutting record data for the non-faulty stations. Specifically, obtain the historical cutting records of the non-faulty stations from the steel plate cutting central control center or relevant data storage systems through methods such as database query or file system access, including detailed information such as the cutting tasks executed by each station in the past, cutting path complexity, and cutting results (including accuracy measurement data).

[0039] Step S472: Perform cutting accuracy statistics for different cutting path complexities based on the historical steel plate cutting record data to generate a complexity-accuracy mapping relationship. Specifically, after collecting sufficient historical data, classify the historical data according to cutting path complexity, and then calculate the average cutting accuracy or accuracy distribution characteristics in each category, thereby establishing a mapping relationship between complexity and accuracy.

[0040] Step S473: Based on the complexity-accuracy mapping relationship, screen the non-faulty stations that simultaneously meet the cutting complexity index and the task cutting accuracy requirements in the non-faulty stations to form the set of primary constraint stations. Specifically, according to the cutting complexity index and task cutting accuracy requirements generated in steps S450 and S460, use the complexity-accuracy mapping relationship established in step S472 to evaluate each non-faulty station, screen out those stations whose historical data shows that they can achieve the required accuracy within the specified complexity range, and form these stations into a set of primary constraint stations. This implementation method accurately evaluates the capabilities of non-faulty stations by deeply analyzing historical data and establishing a mapping relationship between complexity and accuracy, thereby ensuring that the reassigned tasks can be efficiently completed while meeting quality requirements.

[0041] In a possible implementation, after performing station conversion on the reallocation subtasks in the set of primary constraint stations to generate the reallocation plan, step S480 further includes step S481 of determining the basic characteristics of the cutting equipment of all stations in the set of primary constraint stations, comparing them with the basic characteristics of the cutting equipment of the faulty station, and obtaining a set of secondary constraint stations whose basic characteristics of the cutting equipment are consistent with those of the faulty station. Specifically, collect the basic characteristic information of the cutting equipment of each station in the set of primary constraint stations, that is, the inherent basic attributes of the cutting equipment that affect its cutting ability and efficiency. These basic characteristics include but are not limited to key parameters such as the type of cutting equipment (such as laser cutting machine, plasma cutting machine, etc.), the power of the equipment, the cutting speed, and the range of material thickness that can be processed. Compare these characteristics with the basic characteristics of the cutting equipment of the faulty station one by one, and find the stations whose equipment characteristics are consistent with those of the faulty station to form a set of secondary constraint stations. These stations are closer to the faulty station in terms of equipment capabilities, facilitating seamless task conversion.

[0042] Step S482, obtain the current task load information corresponding to all secondary constraint stations in the set of secondary constraint stations. Specifically, through a real-time data acquisition mechanism, obtain the current task load information of each station in the set of secondary constraint stations, including the number of tasks being executed, the estimated completion time of the tasks, the task priorities, etc.

[0043] Step S483, with the goal of minimizing the load balancing index, using the set of secondary constraint stations as the balanced allocation space, based on the current task load information, perform balanced allocation of the reallocation subtasks to generate the reallocation plan. Specifically, adopt an optimization algorithm, with the goal of minimizing the load balancing index (a quantitative index to measure whether the task allocation among stations in the system is uniform, such as the standard deviation of the task loads of each station, the ratio of the maximum task load to the average task load, etc.), perform balanced allocation of the reallocation subtasks. During the allocation process, consider factors such as the current task load information, task priorities, and requirements of the tasks for the cutting equipment of each station in the set of secondary constraint stations to ensure that the task allocation not only meets the quality requirements but also achieves load balancing. This implementation method ensures the compatibility of the equipment and the stability of the cutting quality during task conversion by screening out stations similar to the faulty station (the set of secondary constraint stations) according to the basic characteristics of the cutting equipment. By considering the current task load information and the load balancing index for task allocation, the production process is further optimized, improving the overall production efficiency and resource utilization rate.

[0044] Step S500, based on the reallocation plan, perform secondary distribution of the reallocated cutting drawings.

[0045] Specifically, update the task assignment records in the central control center for steel plate cutting. According to the generated reallocation plan, distribute the newly generated cutting drawings to the corresponding non-fault workstations, enabling the relevant workstations to start new cutting tasks. In the embodiment of the present application, by connecting to the central control center for steel plate cutting, the task information of each cutting workstation is obtained in real time. A multi-workstation equipment fault prediction module is trained based on historical fault record data. According to the cutting subtasks and workstation information, the steel plate cutting drawings are distributed once. The equipment operation data of each cutting workstation is collected and input into the fault prediction module for analysis to locate the fault workstations and non-fault workstations. For the fault workstations, determine their corresponding reallocation subtasks and reallocation cutting drawings. Among the non-fault workstations, considering the dual constraints of cutting quality and conversion load balance, generate a reallocation plan. Based on the reallocation plan, perform a secondary distribution of the reallocation cutting drawings and other technical means, achieving the technical effect of improving the drawing distribution efficiency and distribution accuracy.

[0046] In a possible implementation manner, the method further includes step S600 of obtaining a plurality of compatible drawing formats corresponding to the plurality of cutting workstations. Specifically, communicate with the equipment manufacturers or operators of each cutting workstation, collect and record the drawing formats that each cutting workstation can receive and process. The information collected includes but is not limited to AutoCAD files (.dwg or.dxf), PDF, JPEG, PNG, etc. Among them, the compatible drawing format refers to the drawing file format that can be correctly read and processed by a specific cutting device or software.

[0047] Step S700 of constructing a drawing distribution model with the plurality of compatible drawing formats, where the drawing distribution model includes a format judgment channel and a format conversion channel. Specifically, based on the information collected in step S600, construct a drawing distribution model. This model includes two main channels. Among them, the format judgment channel is used to identify the format of the drawing to be distributed. When the drawing is uploaded to the central control center for steel plate cutting, this channel will check the file extension or content of the drawing to determine its format. For those drawing formats that are incompatible with the target cutting workstation, the format conversion channel converts them into a compatible format by calling specific conversion software or services, such as the conversion tool of AutoCAD, the online PDF to DWG service, etc.

[0048] Step S800: Embed the drawing distribution model into the central control center for steel plate cutting to perform the distribution process of cutting drawings. Specifically, integrate the drawing distribution model constructed in step S700 into the central control center for steel plate cutting. When the central control center for steel plate cutting receives a cutting drawing, first check the drawing format through the format judgment channel. If the drawing format is compatible with the target cutting station, directly distribute it; if not, convert it through the format conversion channel and then distribute it. This implementation method can automatically handle the compatibility problem of drawing formats by constructing a drawing distribution model and integrating it into the central control center for steel plate cutting, ensuring that each cutting station can receive the drawing in the correct format, thereby improving the cutting efficiency and accuracy.

[0049] In a possible implementation, the method further includes step S900: After locating the faulty station, generate a fault warning signal for the faulty station. Specifically, once the faulty station is located through the multi-station equipment fault prediction module, immediately trigger a fault warning mechanism. The fault warning signal can be sent in various ways, such as by email, text message, instant message notification (such as Slack, Teams, etc.), or directly display a warning message on the interface of the central control center for steel plate cutting. The warning signal contains key information such as the specific location of the faulty station, the predicted fault type, the possible cause of the fault, and the recommended countermeasures. This implementation method can ensure that maintenance personnel can quickly learn about the fault situation by sending the fault warning signal in real time, thereby shortening the fault response time and reducing production interruptions.

[0050] In the above text, reference is made to Figure 1 The method for distributing steel plate cutting drawings with multi-station collaboration according to an embodiment of the present invention is described in detail. Next, reference will be made to Figure 2 Describe the system for distributing steel plate cutting drawings with multi-station collaboration according to an embodiment of the present invention.

[0051] The system for distributing steel plate cutting drawings with multi-station collaboration according to an embodiment of the present invention is used to solve the technical problems of low distribution efficiency and low distribution accuracy existing in the existing distribution of steel plate cutting drawings with multi-station collaboration, and achieve the technical effect of improving the drawing distribution efficiency and distribution accuracy. The system for distributing steel plate cutting drawings with multi-station collaboration includes: a cutting sub-task determination module 10, a multi-station equipment fault prediction construction module 20, a station equipment fault prediction module 30, a reallocation plan generation module 40, and a drawing secondary distribution module 50.

[0052] The cutting subtask determination module 10 is used to connect to the central control center of steel plate cutting to determine multiple cutting subtasks for multiple cutting stations; the multi-station equipment fault prediction construction module 20 is used to construct a multi-station equipment fault prediction module for the multiple cutting stations, and the multi-station equipment fault prediction module is trained based on historical fault record data; the station equipment fault prediction module 30 is used to distribute a steel plate cutting drawing once based on the multiple cutting subtasks and the multiple cutting stations, collect the operation data of multiple cutting devices at the multiple cutting stations, and input the data into the multi-station equipment fault prediction module for analysis to locate the fault stations and non-fault stations; the reallocation plan generation module 40 is used to determine the reallocation subtasks and reallocation cutting drawings corresponding to the fault stations, perform double constraints on cutting quality and conversion load balance among the non-fault stations, and generate a reallocation plan; the drawing secondary distribution module 50 is used to perform secondary distribution of the reallocation cutting drawings based on the reallocation plan.

[0053] Next, the specific configuration of the reallocation plan generation module 40 will be described in detail. As described above, to determine the reallocation subtasks and reallocation cutting drawings corresponding to the fault stations, perform double constraints on cutting quality and conversion load balance among the non-fault stations, and generate a reallocation plan, the reallocation plan generation module 40 may further include: a cutting complexity analysis unit for performing cutting complexity analysis on the reallocation subtasks based on the reallocation cutting drawings to generate a cutting complexity index; a task cutting precision requirement determination unit for determining the task cutting precision requirements of the reallocation subtasks; a cutting quality constraint unit for performing cutting quality constraints among the non-fault stations based on the cutting complexity index and the task cutting precision requirements to generate a first constraint station set; a load balance constraint unit for performing load balance constraints after station conversion on the reallocation subtasks in the first constraint station set to generate the reallocation plan.

[0054] Among them, to perform cutting quality constraints among the non-fault stations based on the cutting complexity index and the task cutting precision requirements to generate a first constraint station set, the cutting quality constraint unit may further include: a historical steel plate cutting record data collection sub-unit for collecting historical steel plate cutting record data of the non-fault stations; a cutting precision statistics sub-unit for performing cutting precision statistics of different cutting path complexities based on the historical steel plate cutting record data to generate a complexity-precision mapping relationship; a first constraint station set construction sub-unit for screening stations that simultaneously meet the cutting complexity index and the task cutting precision requirements among the non-fault stations based on the complexity-precision mapping relationship to construct the first constraint station set.

[0055] Among them, for the load balancing constraint after the station conversion of the reallocation subtask in the primary constraint station set, the reallocation scheme is generated. The load balancing constraint unit may further include: a secondary constraint station set acquisition subunit for determining the basic cutting equipment features of all stations in the primary constraint station set, comparing them with the basic cutting equipment features of the faulty station, and acquiring a secondary constraint station set that is consistent with the basic cutting equipment features of the faulty station; a current task load information acquisition subunit for acquiring the current task load information corresponding to all secondary constraint stations in the secondary constraint station set; and an equal distribution subunit for taking the minimization of the load balancing index as the goal, using the secondary constraint station set as the equal distribution space, and performing equal distribution of the reallocation subtask based on the current task load information to generate the reallocation scheme.

[0056] Among them, the system may further include: a compatible drawing format acquisition module for acquiring a plurality of compatible drawing formats corresponding to the plurality of cutting stations; a drawing distribution model construction module for constructing a drawing distribution model with the plurality of compatible drawing formats, where the drawing distribution model includes a format judgment channel and a format conversion channel; and a model embedding module for embedding the drawing distribution model into the steel plate cutting central control center for distribution processing of cutting drawings.

[0057] Among them, for determining the reallocation subtask and the reallocation cutting drawing corresponding to the faulty station, the reallocation scheme generation module 40 may further include: a task information acquisition unit for acquiring the initial cutting subtask and the executed task of the faulty station; a first reallocation subtask generation unit for extracting the difference set between the initial cutting subtask and the executed task to generate a first reallocation subtask; a second reallocation subtask generation unit for performing cutting quality verification on the executed task and generating a second reallocation subtask for the tasks with unqualified verification results; and a reallocation subtask and cutting drawing generation unit for generating the reallocation subtask with the first reallocation subtask and the second reallocation subtask, and extracting the corresponding cutting drawing to generate the reallocation cutting drawing.

[0058] Among them, the system may further include: a fault warning module for generating a fault warning signal for the faulty station after locating the faulty station.

[0059] The multi-station collaborative steel plate cutting drawing distribution system provided by the embodiments of the present invention can execute the multi-station collaborative steel plate cutting drawing distribution method provided by any embodiment of the present invention, and has the corresponding function modules and beneficial effects for executing the method.

[0060] Although this application makes various references to certain modules in the system according to embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and do not limit the protection scope of the present invention.

[0061] The above specific implementation manners do not constitute a limitation on the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of this application shall be included within the protection scope of this application. In some cases, the actions or steps recorded in this application can be executed in a different order from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A multi-station collaborative steel plate cutting drawing distribution method, characterized in that: include: Connect to the steel plate cutting central control center to determine multiple cutting subtasks of multiple cutting stations; Constructing a multi-station equipment fault prediction module for the multiple cutting stations, wherein the multi-station equipment fault prediction module is trained based on historical fault record data; Distribute a steel plate cutting drawing based on the multiple cutting subtasks and the multiple cutting stations, collect multiple cutting equipment operation data of the multiple cutting stations, input the data into the multi-station equipment fault prediction module for analysis, and locate the faulty station and the non-faulty station; Determine the reallocation subtasks and reallocation cutting drawings corresponding to the faulty workstation, perform dual constraints of cutting quality and conversion load balance in the non-faulty workstation, and generate a reallocation plan; The reallocated cutting drawings are redistributed based on the reallocation scheme.

2. The method for distributing steel plate cutting drawings with multi-station collaboration as claimed in claim 1, characterized in that: Determine the reallocation subtasks and reallocation cutting drawings corresponding to the faulty workstation, perform dual constraints of cutting quality and conversion load balancing in the non-faulty workstation, and generate a reallocation plan, including: Performing a cutting complexity analysis on the reallocated subtask based on the reallocated cutting drawing to generate a cutting complexity index; Determining the task cutting accuracy requirement of the reallocated subtask; Based on the cutting complexity index and the task cutting accuracy requirement, cutting quality constraints are performed in the non-faulty workstations to generate a constrained workstation set; The load balancing constraint after the workstation conversion is performed on the reallocated subtask in the primary constrained workstation set to generate the reallocation plan.

3. The method for distributing steel plate cutting drawings in a multi-station collaborative manner as claimed in claim 2, characterized in that: Based on the cutting complexity index and the task cutting accuracy requirement, cutting quality constraints are performed in the non-faulty workstations, and a constrained workstation set is generated, including: Collecting historical steel plate cutting record data for the non-faulty workstation; Based on the historical steel plate cutting record data, cutting accuracy statistics of different cutting path complexities are performed to generate a complexity-accuracy mapping relationship; Based on the complexity-precision mapping relationship, workstations that meet both the cutting complexity index and the task cutting precision requirement are screened from the non-fault workstations to form the primary constraint workstation set.

4. The method for distributing steel plate cutting drawings in a multi-station collaborative manner as claimed in claim 2, characterized in that: The load balancing constraint after the workstation conversion is performed on the reallocated subtask in the primary constrained workstation set to generate the reallocation plan, including: Determine the basic characteristics of cutting equipment of all workstations in the primary constraint workstation set, and compare them with the basic characteristics of cutting equipment of the faulty workstation to obtain a secondary constraint workstation set consistent with the basic characteristics of cutting equipment of the faulty workstation; Obtaining current task load information corresponding to all quadratic constraint workstations in the quadratic constraint workstation set; With the goal of minimizing the load balancing index and the quadratic constraint workstation set as the balanced allocation space, the reallocated subtasks are evenly allocated based on the current task load information to generate the reallocation plan.

5. The method for distributing steel plate cutting drawings in a multi-station collaborative manner as claimed in claim 1, characterized in that: Also includes: Acquire multiple compatible drawing formats corresponding to the multiple cutting stations; Constructing a drawing distribution model with the multiple compatible drawing formats, wherein the drawing distribution model includes a format determination channel and a format conversion channel; The drawing distribution model is embedded in the steel plate cutting central control center to perform distribution processing of cutting drawings.

6. The method for distributing steel plate cutting drawings in a multi-station collaborative manner as claimed in claim 2, characterized in that: Determining the reassignment subtask and the reassignment cutting drawing corresponding to the faulty workstation includes: Obtaining the initial cutting subtask and executed tasks of the faulty workstation; Extracting a difference between the initial cutting subtask and the executed task to generate a first reallocated subtask; Performing cutting quality verification on the executed tasks, and generating second redistributed subtasks for the tasks that fail the verification; The reallocation subtask is generated by using the first reallocation subtask and the second reallocation subtask, and the corresponding cutting drawings are extracted to generate the reallocation cutting drawings.

7. The method for distributing steel plate cutting drawings in a multi-station collaborative manner as claimed in claim 1, characterized in that: After locating the faulty workstation, a fault warning signal is generated for the faulty workstation.

8. The multi-station collaborative steel plate cutting drawing distribution system is characterized by: The system is used to implement the multi-station collaborative steel plate cutting drawing distribution method according to any one of claims 1 to 7, and the system comprises: A cutting subtask determination module is used to connect to the steel plate cutting central control center to determine multiple cutting subtasks for multiple cutting stations; A multi-station equipment fault prediction construction module is used to construct a multi-station equipment fault prediction module for the multiple cutting stations, wherein the multi-station equipment fault prediction module is trained based on historical fault record data; A station equipment fault prediction module is used to distribute a steel plate cutting drawing based on the multiple cutting subtasks and the multiple cutting stations, collect multiple cutting equipment operation data of the multiple cutting stations, input the data into the multi-station equipment fault prediction module for analysis, and locate the faulty station and the non-faulty station; A reallocation plan generating module, used to determine the reallocation subtasks and reallocation cutting drawings corresponding to the faulty workstation, perform dual constraints of cutting quality and conversion load balancing in the non-faulty workstation, and generate a reallocation plan; The drawing secondary distribution module is used for secondary distribution of the reallocated cutting drawings based on the reallocation scheme.

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