Traceability supervision method and system for smart park

Abstract

The invention discloses a traceability supervision method and system for a smart park, and relates to the technical field of traceability supervision. The method comprises the following steps: acquiring a plurality of production lines for target products in a smart park; constructing a product production graph model according to the plurality of production lines; setting a process data structure on each process point, configuring a process data collector, setting a circulation data structure on each process connection edge and production conversion edge, and configuring a circulation data collector; obtaining first process execution data based on the process data collector, and obtaining first circulation execution data based on the circulation data collector; performing structure storage to obtain a first product production drawing, and adding the first product production drawing to a production drawing database of the target product; and performing traceability supervision on the target product based on the production drawing database. The technical problem that products produced in a smart park are difficult to trace precisely in the prior art is solved, and the technical effect of improving the product traceability accuracy is achieved by constructing the product production model diagram.

Description

Technical Field

[0001] The present invention relates to the technical field of traceability supervision, and in particular to a traceability supervision method and system for a smart park. Background Art

[0002] In today's rapidly developing technological era, smart parks, as new industrial clusters that integrate informatization, intelligence, and greening, are gradually becoming an important engine for promoting the transformation and upgrading of urban economies. In smart parks, the production processes of enterprises are highly automated and information-based, with a wide variety of products and complex production processes. However, this efficient production model also poses new challenges to product quality traceability and supervision. Traditional supervision methods often make it difficult to accurately track the entire life cycle of a product, making it difficult to quickly locate the source of the problem when product quality problems arise, thereby increasing recall costs. Summary of the invention

[0003] The present application provides a traceability supervision method and system for a smart park, which solves the technical problem in the prior art that it is difficult to accurately trace the products produced in the smart park.

[0004] In view of the above problems, the present application provides a traceability supervision method and system for a smart park.

[0005] In a first aspect of the present application, a traceability supervision method for a smart park is provided, the method comprising:

[0006] For target products in the smart park, multiple production lines are obtained, including a packaging production line, a product production line and an integrated production line, wherein the packaging production line is parallel to the product production line, and the integrated production line is located after the packaging production line and the product production line; based on the multiple production lines, a product production graph model is constructed, including multiple production graphs, namely, a packaging production graph, a product production graph and an integrated production graph, wherein any production graph includes multiple process layers for executing different processes, and any process layer includes multiple process points for executing the same process; in the product production graph model, there are process connection edges between adjacent process layers in each production graph, and there are production conversion edges between adjacent production graphs, wherein the packaging production graph and the integrated production graph have production conversion edges, and there is a production conversion edge between the product production line and the integrated production line; set A process data structure is provided, and a process data collector is configured, a flow data structure is set on each process connection edge and production conversion edge, and a flow data collector is configured; in the production process of the target product, the first process execution data of the process point passed by the first product is obtained based on the process data collector, and the first flow execution data on the corresponding first process connection edge and the first production conversion edge is obtained based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production schedule; according to the product production graph model, the first process execution data and the first flow execution data of the first product are combined with the first process connection edge and the first production conversion edge for structural storage, the first product production graph is obtained, and added to the production graph database of the target product; the target product is traced and supervised based on the production graph database.

[0007] The second aspect of the present application provides a traceability supervision system for a smart park, the system comprising:

[0008] A production line acquisition module, the production line acquisition module is used to acquire multiple production lines for target products in the smart park, including a packaging production line, a product production line and an integrated production line, the packaging production line is parallel to the product production line, and the integrated production line is located after the packaging production line and the product production line; a production map model construction module, the production map model construction module is used to construct a product production map model according to the multiple production lines, including multiple production maps, namely a packaging production map, a product production map and an integrated production map, wherein any production map includes multiple process layers for executing different processes, and any process layer includes multiple process points for executing the same process; a connection edge definition module, the connection edge definition module is used to, in the product production map model, have process connection edges between adjacent process layers in each production map, and have production conversion edges between adjacent production maps, wherein the packaging production map and the integrated production map have production conversion edges, and the product production line and the integrated production line have production conversion edges; a collector configuration module, the collector The collector configuration module is used to set the process data structure at each process point and configure the process data collector, set the flow data structure on each process connection edge and production conversion edge, and configure the flow data collector; the data collection module is used to obtain the first process execution data of the process point passed by the first product based on the process data collector during the production process of the target product, and obtain the first flow execution data on the corresponding first process connection edge and the first production conversion edge based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production progress; the storage module is used to store the first process execution data and the first flow execution data of the first product according to the product production graph model, in combination with the first process connection edge and the first production conversion edge, obtain the first product production graph, and add it to the production graph database of the target product; the traceability supervision module is used to perform traceability supervision on the target product based on the production graph database.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, for the target products in the smart park, multiple production lines are obtained, including packaging production lines, product production lines and integrated production lines. The packaging production line is parallel to the product production line, and the integrated production line is located after the packaging production line and the product production line. Then, according to the multiple production lines, a product production graph model is constructed, including multiple production graphs, namely packaging production graphs, product production graphs and integrated production graphs, wherein any production graph includes multiple process layers that perform different processes, and any process layer includes multiple process points that perform the same process; in the product production graph model, there are process connection edges between adjacent process layers in each production graph, and there are production conversion edges between adjacent production graphs, wherein the packaging production graph and the integrated production graph have production conversion edges, and there are production conversion edges between the product production line and the integrated production line. Next, a process data structure is set at each process point, and a process data collector is configured, and a flow data structure is set on each process connection edge and production conversion edge, and a flow data collector is configured. During the production process of the target product, the first process execution data of the process point passed by the first product is obtained based on the process data collector, and the first flow execution data on the corresponding first process connection edge and the first production conversion edge is obtained based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production progress. Then, according to the product production graph model, the first process execution data and the first flow execution data of the first product are structurally stored in combination with the first process connection edge and the first production conversion edge, and the production graph of the first product is obtained and added to the production graph database of the target product. Finally, the target product is traced and supervised based on the production graph database. The technical problem that it is difficult to accurately trace the products produced in the smart park in the prior art is solved, and the technical effect of improving the accuracy of product traceability is achieved by constructing a product production model graph. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic diagram of a traceability supervision method for a smart park provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of a traceability supervision system for a smart park provided in an embodiment of the present application.

[0014] Explanation of the accompanying drawings: production line acquisition module 11, production graph model construction module 12, connection edge definition module 13, collector configuration module 14, data collection module 15, storage module 16, traceability supervision module 17. DETAILED DESCRIPTION

[0015] This application solves the technical problem in the prior art that it is difficult to accurately trace the products produced in smart parks by providing a traceability supervision method and system for smart parks.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0018] Embodiment 1, as Figure 1 As shown, the present application provides a traceability supervision method for a smart park, wherein the method includes:

[0019] For target products in the smart park, multiple production lines are obtained, including a packaging production line, a product production line and an integrated production line. The packaging production line is parallel to the product production line, and the integrated production line is located after the packaging production line and the product production line.

[0020] In the smart park, for specific target products, multiple production lines related to product production are obtained, including packaging production lines, product production lines and integrated production lines. Among them, the packaging production line is the production line used for product packaging; the product production line refers to the manufacturing process of the target product; the packaging production line and the product production line run in parallel, that is, the packaging process and the product production process are independent of each other but related; the integrated production line is located after the packaging production line and the product production line, and plays the role of integrating the two production lines, and is responsible for combining the packaging and product production processes.

[0021] According to the multiple production lines, a product production map model is constructed, including multiple production maps, namely a packaging production map, a product production map and an integrated production map, wherein any production map includes multiple process layers for executing different processes, and any process layer includes multiple process points for executing the same process.

[0022] Through the analysis and data collection of multiple production lines, a product production map model is constructed, which can fully display the operation status of each production line during the product production process. The product production map model includes packaging production map, product production map and integrated production map. The packaging production map reflects the process and flow of the packaging production line, the product production map reflects the process and flow of the product production line, and the integrated production map reflects the process and flow of the integrated production line. Each production map includes multiple process layers that perform different processes. Each layer represents a specific process (such as assembly, testing, packaging, etc.), showing the position and role of the process in the production process; in any process layer, there are multiple process points, each process point represents multiple operation nodes that actually perform tasks in the same process. By summarizing multiple process points, the actual operation status of the process layer can be reflected.

[0023] In the product production graph model, there are process connection edges between adjacent process layers in each production graph, and production conversion edges between adjacent production graphs, wherein the packaging production graph and the integrated production graph have production conversion edges, and there is a production conversion edge between the product production line and the integrated production line.

[0024] In the product production graph model, different connection edges are constructed to represent the connection between each process layer and the production graph. In each production graph, adjacent process layers are connected by process connection edges. The process connection edges not only represent the physical flow path of the product between different processes, but also imply the logical relationship and time sequence between the processes; between adjacent production graphs, production conversion edges are used to represent the flow and conversion process of products between different production lines (such as packaging production lines, product production lines, and integration production lines). For example, the products completed in the product production graph will flow along the production conversion edges to the integration production graph for further packaging and integration operations; similarly, the packaged products may also enter other production lines or storage areas for subsequent processing through the production conversion edges.

[0025] A process data structure is set at each process point, and a process data collector is configured; a flow data structure is set at each process connection edge and production conversion edge, and a flow data collector is configured.

[0026] At each process point, a process data structure is set up. The process data structure is used to describe the execution information of each process point, including the start time, end time, operator, equipment status, production materials, quality inspection results, etc. of the process. A process data collector (such as a sensor, barcode scanner) is configured at each process point to collect the execution data of the process point in real time. On the process connection edge and production conversion edge, a flow data structure is set up. The flow data structure is used to record the movement and conversion of materials or products in the production process, reflecting the flow status from one process layer to the next process layer, as well as the conversion process between different production diagrams. The flow data may include the material number, timestamp, flow status and other information of the flow; a flow data collector is configured at the entrance and exit of each process connection edge and production conversion edge. The flow data collector automatically collects the flow data by reading the RFID tag and QR code on the product to ensure the accurate record of each flow step. By setting these data structures and collectors, the whole production process can be monitored and recorded, thus providing a solid data foundation for product quality traceability and production supervision.

[0027] During the production process of the target product, the first process execution data of the process point passed by the first product is obtained based on the process data collector, and the first flow execution data on the corresponding first process connection edge and the first production conversion edge is obtained based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production progress.

[0028] In the production process of the target product, when the first product (any product in production) passes through each process point, the process data collector at the process point will automatically start and obtain the first process execution data of the product in real time, including but not limited to the execution start time, end time, execution status, parameters of the operating equipment, operator records, product processing status, quality inspection results, etc. of the process; as the first product continues to move forward on the production line, it will pass through different process connection edges and production conversion edges. At these key positions, the flow data collector will capture the first flow execution data of the product when it flows between process layers or production lines, including the movement time, flow status, flow path of the product from one process point to the next process point, and the flow information on the process connection edge and production conversion edge, such as material number, batch number, flow timestamp, etc. In the production process, the first process connection edge and the first production conversion edge will be dynamically allocated according to the production progress, that is, the process point where the current product is located will be identified, and the next process connection edge or production conversion edge will be dynamically adjusted to ensure that the product's flow path can be smoothly connected and seamlessly converted between different production lines.

[0029] Furthermore, the first process connection edge is dynamically allocated according to the production schedule, including:

[0030] For any production line, obtain the corresponding target production map, identify the first process point in the first process layer, wherein the target production map is a packaging production map, a product production map or an integrated production map; identify the next process layer adjacent to the first process layer as the second process layer, and obtain all process points in the second process layer to generate a second process point set; perform task statistics on all process points in the second process point set, and dynamically determine the second process point based on the statistical results of the task execution; connect the first process point and the second process point to generate a first sub-process connection edge, and add it to the first process connection edge.

[0031] Specifically, for any production line where the target product is located, the corresponding target production map is obtained, which can be a packaging production map, a product production map or an integrated production map, depending on the production stage of the current product; in the target production map, the first process layer where the current product is located is identified, and the first process point in the process layer is further determined. The first process point is the location where the current product is executing the process and is the starting point of the next process flow; the next process layer adjacent to the first process layer is taken as the second process layer, and all process points in the layer are obtained to form a second process point set; all process points in the second process point set are counted for execution tasks, and the second process point suitable for receiving product flow is dynamically determined based on the execution task statistics results; the first process point and the dynamically determined second process point are connected to generate a first sub-process connection edge, which is used to describe the flow path of the product from the first process point to the second process point; the generated first sub-process connection edge will be added to the first process connection edge to form a complete dynamic process connection path. According to the needs of actual production, the same method for generating the first sub-process connection edge can be used to generate the second sub-process connection edge, the third sub-process connection edge, and so on, to meet actual needs.

[0032] Furthermore, performing task statistics on all process points in the second process point set, and dynamically determining the second process point based on the task statistics result, includes:

[0033] Read the process execution efficiencies of all process points in the second process point set respectively to obtain multiple process execution efficiencies; read the amount of tasks to be executed of all process points in the second process point set respectively to obtain multiple amounts of tasks to be executed; based on the multiple process execution efficiencies and the multiple amounts of tasks to be executed, obtain multiple execution task durations of all process points in the second process point set as the statistical results of the execution tasks; sort the multiple execution task durations from small to large, and select the process point with the smallest execution task duration as the second process point.

[0034] Specifically, the process execution efficiency of each process point in the second process point set is read respectively to obtain multiple process execution efficiencies, which refers to the average time required for the process point to complete a certain amount of tasks; at the same time, the amount of tasks to be executed at each process point is read to obtain multiple amounts of tasks to be executed, which refers to the number of tasks or task loads that the process point currently needs to handle; based on the process execution efficiency and the amount of tasks to be executed at each process point, the execution time of each process point is calculated, which can be expressed as the estimated time required for the process point to complete the current task load, and the execution time = the amount of tasks to be executed / process execution efficiency; the multiple calculated execution times are sorted in order from small to large, and the smaller the execution time, the lighter the task load of the process point and the shorter the time required to complete the task; the process point with the smallest execution time is selected from the sorting results as the second process point of the target. Through this dynamic allocation mechanism, the optimal second process point can be intelligently selected to ensure that the resources of each process point in the production line are used evenly, and to avoid the situation where a process point is overloaded and affects the production progress.

[0035] Furthermore, the first production conversion edge is dynamically allocated according to the production schedule, including:

[0036] When the first packaging product of the first product executes to the termination process layer of the packaging production diagram, obtain the final packaging process point of the first packaging product; identify the starting process layer of the integrated production diagram, and obtain all process points in the starting process layer to generate a starting process point set; perform integration task statistics on all process points in the starting process layer, and dynamically determine the integration starting process point based on the integration task statistics results; connect the packaging final process point and the integration starting process point to generate a packaging integration connection edge; synchronously generate a product integration connection edge, and combine the packaging integration connection edge to obtain the first production conversion edge.

[0037] Specifically, when the packaging production of the first product has been executed to the terminal process layer of the packaging production diagram, the final packaging process point of the product in the packaging production process is read, that is, the last process point where the product completes packaging; the starting process layer in the integrated production diagram is identified, which is the first process layer executed after the product enters the integrated production line from the packaging production line, indicating the beginning of the integration process, and all process points in the starting process layer are obtained to form a starting process point set; task statistics are performed on the starting process point set of the integrated production diagram, and the statistical content includes the task load of each process point, the current task execution status, the available equipment status, etc.; based on these statistical results, the integration starting process point is dynamically selected, that is, which process point is determined to be most suitable for receiving the product from the packaging production line; the packaging final process point is connected with the selected integration starting process point to generate a packaging integration connection edge, which represents the path of the product successfully transferred from the packaging production line to the integration production line; while completing the packaging integration connection, a product integration connection edge is also generated synchronously to process the flow between the product production line and the integration production line; the packaging integration connection edge is combined with the product integration connection edge to generate the final first production conversion edge to represent the complete conversion process of the product from packaging, product production line to integration production line.

[0038] Furthermore, performing integration task statistics on all process points in the starting process layer, and dynamically determining the integration starting process point based on the integration task statistics result, includes:

[0039] The process execution efficiency and the amount of tasks to be integrated of all process points in the starting process point set are read respectively to obtain multiple execution task durations; the packaging product matching degrees of the amount of tasks to be integrated of all process points in the starting process point set are read respectively to obtain multiple packaging product matching degrees; the multiple execution task durations and the multiple packaging product matching degrees are used as the statistical results of the integration task to determine the integration starting process point.

[0040] Specifically, the process execution efficiency of each process point in the starting process point set is read respectively; at the same time, the amount of tasks to be integrated at each process point is read, that is, the process point currently waiting to be processed; based on these data, the execution task duration of each process point is calculated, that is, the number of tasks or workload required to complete the current task to be integrated, and the execution task duration = the amount of tasks to be integrated / process execution efficiency; for each process point in the starting process point set, the current packaging product matching degree of the process point is evaluated based on product characteristics, production requirements and the configuration of the process point. The packaging product matching degree refers to whether the process point is suitable for processing the packaging products currently waiting to enter. For example, some processes already have a lot of packaging, but the number of products is small, resulting in inability to match during integration; the obtained execution task duration and packaging product matching degree are combined as the statistical results of the integration task of each process point. According to the statistical results of the integration task, the process point with a shorter execution task duration and a higher packaging product matching degree is selected as the integration starting process point. When determining the integration starting process point, the task load of the process point and the adaptability of the packaging product are comprehensively considered, so as to maximize the matching and stability of production while ensuring efficient execution of tasks.

[0041] Furthermore, taking the plurality of execution task durations and the plurality of packaging product matching degrees as the statistical results of the integration task and determining the integration starting process point includes:

[0042] Traverse all process points in the starting process point set, and for each process point, obtain the corresponding execution task duration and packaging product matching degree; determine whether multiple packaging product matching degrees meet multiple preset matching degree thresholds, and screen out alternative process points that are lower than the preset matching degree thresholds; extract multiple alternative point task durations of the alternative process points from the multiple execution task durations, and sort the multiple alternative point task durations from small to large, and select the alternative process point with the smallest alternative point task duration as the integration starting process point; when the multiple packaging product matching degrees of all process points in the starting process point set meet the preset matching degree threshold, select the process point with the smallest execution task duration as the integration starting process point.

[0043] Specifically, all process points in the starting process point set are traversed, and for each process point, the execution task duration and packaging product matching degree of the point are obtained respectively. The execution task duration is used to evaluate the time for the current process point to complete the existing task, and the packaging product matching degree is used to evaluate the degree of adaptability between the process point and the packaging product to be integrated; it is determined whether the packaging product matching degree of each process point meets the preset matching degree threshold. If the packaging product matching degree of a process point is lower than the preset threshold, the process point will be screened out as an alternative process point; for the screened alternative process points, the execution task duration corresponding to these alternative process points is extracted, that is, the estimated time to complete the current task; Sort multiple task durations of candidate process points in ascending order, and select the candidate process point with the shortest task duration as the starting process point for integration, to ensure that the selected process point not only has a high packaging product matching degree, but also can efficiently complete the current task and reduce waiting time; if after traversing all process points, it is found that the packaging product matching degrees of all process points meet the preset matching degree threshold, then directly select the process point with the shortest task execution time as the starting process point for integration. In this case, all process points are suitable for processing the packaging products to be integrated, so the task duration becomes the only basis for judgment, and the process point that can process the task fastest is selected to improve integration efficiency.

[0044] According to the product production graph model, the first process execution data and the first flow execution data of the first product are structurally stored in combination with the first process connection edge and the first production conversion edge to obtain the first product production graph and add it to the production graph database of the target product.

[0045] During the production process of the product, the process data collector and the flow data collector are used to obtain the first process execution data and the first flow execution data of the first product in real time, and structurally store them in combination with the first process connection edge and the first production conversion edge, that is, according to the established data structure model, the process execution data and the flow execution data are orderly stored under the framework of the process connection edge and the production conversion edge; based on the stored data, a first product production map is generated, which comprehensively reflects each link of the product in the production process, the execution status of each process, and the flow status between processes; the first product production map is added to the production map database of the target product.

[0046] The target product is traced and supervised based on the production map database.

[0047] When it is necessary to trace the target product, the corresponding product production map is queried from the production map database to obtain detailed records of the product in each process link; based on the process execution data in the product production map, the production situation of the target product at each process point is traced and analyzed.

[0048] Furthermore, the target product is traced and supervised based on the production map database, including:

[0049] Receiving a traceability request for a specific product among target products, the traceability request including a unique identifier of the specific product and a traceability production stage, the traceability production stage being a packaging production stage, a product production stage, an integrated production stage, or a full production stage;

[0050] According to the unique identifier and the traceable production stage, the corresponding specific production map is retrieved from the production map database and fed back.

[0051] Specifically, a traceability request for a specific product among target products is received, and the traceability request contains a unique identifier and a traceability production stage of the specific product; wherein the unique identifier of a specific product means that each product has a unique identifier, such as a product number, batch number or QR code; the traceability production stage is the packaging production stage, the product production stage, the integrated production stage or the full production stage; using the unique identifier in the traceability request, the production map related to the specific product is retrieved from the production map database, and the production map records the detailed execution data and flow data of the product at different production stages; according to the traceability production stage in the traceability request, the production data of the corresponding stage is filtered out from the retrieved production map, for example, if the request is for the packaging production stage, only the execution data and flow data of the packaging-related processes of the product will be fed back; the retrieved specific production map and the corresponding traceability production stage information are fed back. The traceability mechanism based on the production map database can quickly retrieve and feedback detailed data in the production process for specific products and specific production stages, ensuring the accuracy and traceability of the traceability information.

[0052] In summary, the embodiments of the present application have at least the following technical effects:

[0053] First, for the target products in the smart park, multiple production lines are obtained, including packaging production lines, product production lines and integrated production lines. The packaging production line is parallel to the product production line, and the integrated production line is located after the packaging production line and the product production line. Then, according to the multiple production lines, a product production graph model is constructed, including multiple production graphs, namely packaging production graphs, product production graphs and integrated production graphs, wherein any production graph includes multiple process layers that perform different processes, and any process layer includes multiple process points that perform the same process; in the product production graph model, there are process connection edges between adjacent process layers in each production graph, and there are production conversion edges between adjacent production graphs, wherein the packaging production graph and the integrated production graph have production conversion edges, and there are production conversion edges between the product production line and the integrated production line. Next, a process data structure is set at each process point, and a process data collector is configured, and a flow data structure is set on each process connection edge and production conversion edge, and a flow data collector is configured. During the production process of the target product, the first process execution data of the process point passed by the first product is obtained based on the process data collector, and the first flow execution data on the corresponding first process connection edge and the first production conversion edge is obtained based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production progress. Then, according to the product production graph model, the first process execution data and the first flow execution data of the first product are structurally stored in combination with the first process connection edge and the first production conversion edge, and the production graph of the first product is obtained and added to the production graph database of the target product. Finally, the target product is traced and supervised based on the production graph database. The technical problem that it is difficult to accurately trace the products produced in the smart park in the prior art is solved, and the technical effect of improving the accuracy of product traceability is achieved by constructing a product production model graph.

[0054] Embodiment 2 is based on the same inventive concept as the traceability supervision method of a smart park in the above embodiment. Figure 2 As shown, the present application provides a traceability supervision system for a smart park, wherein the system includes:

[0055] A production line acquisition module 11, the production line acquisition module 11 is used to acquire multiple production lines for target products in the smart park, including a packaging production line, a product production line and an integrated production line, wherein the packaging production line is parallel to the product production line, and the integrated production line is located after the packaging production line and the product production line; a production map model construction module 12, the production map model construction module 12 is used to construct a product production map model according to the multiple production lines, including multiple production maps, namely a packaging production map, a product production map and an integrated production map, wherein any production map includes multiple process layers for executing different processes, and any process layer includes multiple process points for executing the same process; a connection edge definition module 13, the connection edge definition module 13 is used in the product production map model, wherein each adjacent process layer in each production map has a process connection edge, and there is a production conversion edge between adjacent production maps, wherein the packaging production map and the integrated production map have a production conversion edge, and the product production line and the integrated production line have a production conversion edge; a collector configuration module 14, the collector The collector configuration module 14 is used to set the process data structure at each process point and configure the process data collector, set the flow data structure on each process connection edge and production conversion edge, and configure the flow data collector; the data collection module 15, the data collection module 15 is used to obtain the first process execution data of the process point passed by the first product based on the process data collector during the production process of the target product, and obtain the first flow execution data on the corresponding first process connection edge and the first production conversion edge based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production progress; the storage module 16, the storage module 16 is used to store the first process execution data and the first flow execution data of the first product in combination with the first process connection edge and the first production conversion edge according to the product production graph model, obtain the first product production graph, and add it to the production graph database of the target product; the traceability supervision module 17, the traceability supervision module 17 is used to perform traceability supervision on the target product based on the production graph database.

[0056] Furthermore, the data acquisition module 15 is used to perform the following method:

[0057] For any production line, obtain the corresponding target production map, identify the first process point in the first process layer, wherein the target production map is a packaging production map, a product production map or an integrated production map; identify the next process layer adjacent to the first process layer as the second process layer, and obtain all process points in the second process layer to generate a second process point set; perform task statistics on all process points in the second process point set, and dynamically determine the second process point based on the statistical results of the task execution; connect the first process point and the second process point to generate a first sub-process connection edge, and add it to the first process connection edge.

[0058] Furthermore, the data acquisition module 15 is used to perform the following method:

[0059] Read the process execution efficiencies of all process points in the second process point set respectively to obtain multiple process execution efficiencies; read the amount of tasks to be executed of all process points in the second process point set respectively to obtain multiple amounts of tasks to be executed; based on the multiple process execution efficiencies and the multiple amounts of tasks to be executed, obtain multiple execution task durations of all process points in the second process point set as the statistical results of the execution tasks; sort the multiple execution task durations from small to large, and select the process point with the smallest execution task duration as the second process point.

[0060] Furthermore, the data acquisition module 15 is used to perform the following method:

[0061] When the first packaging product of the first product executes to the termination process layer of the packaging production diagram, obtain the final packaging process point of the first packaging product; identify the starting process layer of the integrated production diagram, and obtain all process points in the starting process layer to generate a starting process point set; perform integration task statistics on all process points in the starting process layer, and dynamically determine the integration starting process point based on the integration task statistics results; connect the packaging final process point and the integration starting process point to generate a packaging integration connection edge; synchronously generate a product integration connection edge, and combine the packaging integration connection edge to obtain the first production conversion edge.

[0062] Furthermore, the data acquisition module 15 is used to perform the following method:

[0063] The process execution efficiency and the amount of tasks to be integrated of all process points in the starting process point set are read respectively to obtain multiple execution task durations; the packaging product matching degrees of the amount of tasks to be integrated of all process points in the starting process point set are read respectively to obtain multiple packaging product matching degrees; the multiple execution task durations and the multiple packaging product matching degrees are used as the statistical results of the integration task to determine the integration starting process point.

[0064] Furthermore, the data acquisition module 15 is used to perform the following method:

[0065] Traverse all process points in the starting process point set, and for each process point, obtain the corresponding execution task duration and packaging product matching degree; determine whether multiple packaging product matching degrees meet multiple preset matching degree thresholds, and screen out alternative process points that are lower than the preset matching degree thresholds; extract multiple alternative point task durations of the alternative process points from the multiple execution task durations, and sort the multiple alternative point task durations from small to large, and select the alternative process point with the smallest alternative point task duration as the integration starting process point; when the multiple packaging product matching degrees of all process points in the starting process point set meet the preset matching degree threshold, select the process point with the smallest execution task duration as the integration starting process point.

[0066] Furthermore, the traceability supervision module 17 is used to perform the following method:

[0067] A traceability request for a specific product among target products is received, wherein the traceability request includes a unique identifier and a traceability production stage of the specific product, wherein the traceability production stage is a packaging production stage, a product production stage, an integrated production stage, or a full production stage; and according to the unique identifier and the traceability production stage, a corresponding specific production map is retrieved from the production map database and fed back.

[0068] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0070] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A traceability supervision method for a smart park, characterized in that: The method comprises: For target products in the smart park, multiple production lines are obtained, including a packaging production line, a product production line, and an integration production line, wherein the packaging production line is parallel to the product production line, and the integration production line is located after the packaging production line and the product production line; According to the multiple production lines, a product production map model is constructed, including multiple production maps, namely, a packaging production map, a product production map, and an integrated production map, wherein any production map includes multiple process layers for executing different processes, and any process layer includes multiple process points for executing the same process; In the product production graph model, there are process connection edges between adjacent process layers in each production graph, and there are production conversion edges between adjacent production graphs, wherein the packaging production graph and the integrated production graph have production conversion edges, and there is a production conversion edge between the product production line and the integrated production line; Set up a process data structure at each process point and configure a process data collector, set up a flow data structure at each process connection edge and production conversion edge and configure a flow data collector; In the production process of the target product, first process execution data of a process point passed by the first product is obtained based on the process data collector, and first flow execution data on the corresponding first process connection edge and the first production conversion edge is obtained based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production schedule; According to the product production graph model, the first process execution data and the first flow execution data of the first product are combined with the first process connection edge and the first production conversion edge for structural storage, the first product production graph is obtained, and added to the production graph database of the target product; The target product is traced and supervised based on the production map database.

2. According to claim 1, a traceability supervision method for a smart park is characterized in that: The first process connection edges are dynamically allocated according to the production schedule, including: For any production line, a corresponding target production map is obtained, and a first process point in a first process layer is identified, wherein the target production map is a packaging production map, a product production map, or an integrated production map; Identify the next process layer adjacent to the first process layer as the second process layer, and obtain all process points in the second process layer to generate a second process point set; Performing task statistics on all process points in the second process point set, and dynamically determining the second process point based on the task execution statistics result; The first process point and the second process point are connected to generate a first sub-process connection edge, which is added to the first process connection edge.

3. The traceability supervision method of a smart park according to claim 2 is characterized in that: Performing task statistics on all process points in the second process point set, and dynamically determining the second process point based on the task statistics results, including: Read the process execution efficiencies of all process points in the second process point set respectively to obtain multiple process execution efficiencies; Read the to-be-executed task quantities of all process points in the second process point set respectively to obtain multiple to-be-executed task quantities; Based on the multiple process execution efficiencies and the multiple to-be-executed task amounts, obtaining multiple task execution durations of all process points in the second process point set as task execution statistical results; The multiple task execution times are sorted from small to large, and the process point with the shortest task execution time is selected as the second process point.

4. The traceability supervision method for a smart park according to claim 1 is characterized in that: The first production conversion side is dynamically allocated according to the production schedule, including: When the first packaging product of the first product reaches the final process layer of the packaging production diagram, the final packaging process point of the first packaging product is obtained; Identify the starting process layer of the integrated production graph, obtain all process points in the starting process layer, and generate a starting process point set; Performing integration task statistics on all process points in the starting process layer, and dynamically determining the integration starting process point based on the integration task statistics result; Connecting the final process point of packaging and the starting process point of integration to generate a packaging integration connection edge; A product integration connection edge is generated synchronously, and combined with the packaging integration connection edge to obtain the first production conversion edge.

5. The traceability supervision method of a smart park according to claim 4 is characterized in that: Performing integration task statistics on all process points in the starting process layer, and dynamically determining the integration starting process point based on the integration task statistics results, including: Read the process execution efficiency and the amount of tasks to be integrated of all process points in the starting process point set respectively, and obtain the duration of multiple execution tasks; Read the matching degrees of packaging products of the task quantities to be integrated in all process points in the starting process point set respectively, and obtain the matching degrees of multiple packaging products; The multiple execution task durations and the multiple packaging product matching degrees are used as the statistical results of the integration task to determine the integration starting process point.

6. The traceability supervision method of a smart park according to claim 5 is characterized in that: The plurality of execution task durations and the plurality of matching degrees of the packaged products are used as statistical results of the integration task to determine the integration starting process point, including: Traversing all process points in the starting process point set, and obtaining the corresponding execution task duration and packaging product matching degree for each process point; Determine whether the matching degree of multiple packaging products meets multiple preset matching degree thresholds, and select candidate process points whose matching degree is lower than the preset matching degree thresholds; Extracting multiple candidate point task durations of the candidate process points from the multiple execution task durations, and sorting the multiple candidate point task durations from small to large, and selecting the candidate process point with the smallest candidate point task duration as the integration starting process point; When the matching degrees of multiple packaged products of all process points in the starting process point set meet the preset matching degree threshold, the process point with the shortest task execution time is selected as the integrated starting process point.

7. The traceability supervision method of a smart park according to claim 1 is characterized in that: The target product is traced and supervised based on the production map database, including: Receiving a traceability request for a specific product among target products, the traceability request including a unique identifier of the specific product and a traceability production stage, the traceability production stage being a packaging production stage, a product production stage, an integrated production stage, or a full production stage; According to the unique identifier and the traceable production stage, the corresponding specific production map is retrieved from the production map database and fed back.

8. A traceability supervision system for a smart park, characterized in that: A method for tracing and supervising a smart park according to any one of claims 1 to 7, the system comprising: A production line acquisition module, wherein the production line acquisition module is used to acquire multiple production lines for a target product in the smart park, including a packaging production line, a product production line, and an integrated production line, wherein the packaging production line is parallel to the product production line, and the integrated production line is located after the packaging production line and the product production line; A production map model building module, the production map model building module is used to build a product production map model according to the multiple production lines, including multiple production maps, namely, a packaging production map, a product production map and an integrated production map, wherein any production map includes multiple process layers for executing different processes, and any process layer includes multiple process points for executing the same process; A connection edge definition module, wherein in the product production graph model, each production graph has a process connection edge between adjacent process layers, and adjacent production graphs have a production conversion edge, wherein the packaging production graph and the integrated production graph have a production conversion edge, and the product production line and the integrated production line have a production conversion edge; A collector configuration module, the collector configuration module is used to set a process data structure at each process point and configure a process data collector, set a flow data structure at each process connection edge and production conversion edge, and configure a flow data collector; A data collection module, wherein the data collection module is used to obtain, during the production process of the target product, first process execution data of a process point passed by the first product based on the process data collector, and to obtain first flow execution data on a corresponding first process connection edge and a first production conversion edge based on the flow data collector, wherein the first process connection edge and the first production conversion edge are dynamically allocated according to the production schedule; a storage module, the storage module being used to structurally store the first process execution data and the first flow execution data of the first product in combination with the first process connection edge and the first production conversion edge according to the product production graph model, obtain the first product production graph, and add the data to the production graph database of the target product; A traceability supervision module is used to perform traceability supervision on the target product based on the production map database.

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