Batch lifecycle traceability system, usage methods and computer equipment

Abstract

This application discloses a batch lifecycle traceability system, its usage method, and a computer device, belonging to the field of low-code workflow orchestration technology. It includes: a batch lifecycle acquisition module, which collects event data for each batch throughout its entire lifecycle, with each batch corresponding to a batch code; a lifecycle graph construction module, which constructs a lifecycle graph corresponding to each batch based on the event data; an abnormal state centralized management module, including: an anomaly identification unit, which identifies anomalies in each event data; an abnormal lifecycle construction unit, which constructs an abnormal batch lifecycle graph in response to determining the presence of abnormal events in each event data; and a lifecycle query and traceability module, which displays the lifecycle graph corresponding to the index information. The technical solution of this application provides intuitive visualization of batch flow, improves query efficiency, enables clearer and more intuitive viewing of batch quality issues, and improves management efficiency.

Description

Technical Field

[0001] This application relates to the field of low-code workflow orchestration technology, and in particular to a batch full lifecycle traceability system, its usage method, and computer equipment. Background Technology

[0002] In the lithium battery manufacturing industry, due to the complexity of production processes and the numerous steps involved, massive amounts of work report data are generated daily. A database is needed to store this massive amount of work report data. Currently, the main methods for storing massive amounts of work report data include: traditional relational database full storage: complete recording of all process data for all batches; time-series database solutions: storing collected data based on time series data; and hybrid storage architecture: separating hot and cold data for storage.

[0003] In the context of large-scale production reporting data in the battery industry, the above-mentioned main methods of storing massive production reporting data have the following drawbacks: slow traceability response: full data query results in batch lifecycle traceability taking minutes, affecting the rapid response to quality issues; and overwhelmed key information: important abnormal batch information is overwhelmed by massive qualified data, making it difficult to quickly locate quality issues. Summary of the Invention

[0004] To address the problems of slow traceability response and loss of critical information in existing technologies, this application mainly provides a batch full lifecycle traceability system, a method for using the batch full lifecycle traceability system, and computer equipment.

[0005] To achieve the above objectives, the first technical solution adopted in this application is: a batch full lifecycle traceability system for large-scale manufacturing production data, comprising: a batch lifecycle acquisition module, which collects event data for each batch throughout its entire lifecycle, wherein each batch corresponds to a batch code; a lifecycle graph construction module, which constructs a lifecycle graph corresponding to each batch based on the event data and using the batch code as the primary key; and an abnormal status centralized management module, comprising: an anomaly identification unit, which performs anomaly identification on each event data to determine whether there are abnormal events in each event data; an abnormal lifecycle construction unit, which constructs an abnormal batch lifecycle graph in response to determining that there are abnormal events in each event data; and a lifecycle query and traceability module, which displays the lifecycle graph corresponding to the index information based on the index information.

[0006] Optionally, the batch lifecycle acquisition module includes: a process flow acquisition unit, which collects equipment acquisition data for each process in the batch, wherein the equipment acquisition data includes process code, equipment identifier and acquisition time; an equipment data acquisition unit, which collects various extended attribute information of each equipment running in each process of the batch; and an association code binding unit, which collects the binding time points at which the batch establishes an association relationship with each association code.

[0007] Optionally, the batch lifecycle acquisition module further includes: a quality status acquisition unit, which collects quality status information of each process in the batch; a quality status anomaly detection unit, which performs anomaly detection on each quality status information to determine whether there is any abnormal quality status information in each quality status information; and an anomaly change event generation unit, which generates a batch anomaly change event based on the anomaly quality status information in response to determining that there is abnormal quality status information in each quality status information.

[0008] Optionally, the centralized management module for abnormal states may also include: an abnormal state tracking unit, which determines whether there are abnormal events in each event data and obtains the subsequent event data corresponding to the abnormal event; and an abnormal cause analysis unit, which generates the cause of the abnormal event based on the extended attribute information of the device operation corresponding to the abnormal event.

[0009] Optionally, the lifecycle mapping construction module includes: a timeline construction unit, which establishes a batch lifecycle timeline based on the batch code as the primary key according to the data of each event; a node relationship construction unit, which establishes a lifecycle chain on the batch lifecycle timeline based on the collection points of each process as nodes of the lifecycle and the flow relationship between process nodes; and a status labeling unit, which labels the quality status at each node in the lifecycle chain based on the quality status information.

[0010] Optionally, the lifecycle query and traceability module further includes: a query unit, which, in response to detecting an input operation corresponding to the index information, displays any event data of the lifecycle graph, wherein the index information includes at least one of the following: batch code, device identifier, and collection time; and an association traceability unit, which, in response to detecting an input operation corresponding to the association code, displays the batch code corresponding to the association code and the lifecycle graph corresponding to the batch code.

[0011] Optionally, the lifecycle query and tracing module also includes a trajectory visualization unit, which graphically processes and displays the lifecycle map.

[0012] Optionally, the batch lifecycle traceability system also includes a data storage optimization module, which includes: a partitioned storage unit, which partitions and stores each event data according to the collection time; and an abnormal batch caching unit, which caches the lifecycle map corresponding to the abnormal batch in response to the determination that there are abnormal events in each event data corresponding to the batch.

[0013] The second technical solution adopted in this application is: a method for using a batch full lifecycle traceability system, including: an event data collection step, collecting event data for each batch throughout its entire lifecycle, wherein each batch corresponds to a batch code; a lifecycle map construction step, constructing a lifecycle map corresponding to each batch based on the event data and using the batch code as the primary key; and an abnormal state centralized management step, including: an abnormal identification sub-step, performing abnormal identification on each event data to determine whether there are abnormal events in each event data; an abnormal lifecycle construction sub-step, constructing an abnormal batch lifecycle map in response to determining whether there are abnormal events in each event data; and a lifecycle query and traceability step, displaying the lifecycle map corresponding to the index information based on the index information.

[0014] The third technical solution adopted in this application is: a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method of using the batch full life cycle traceability system in Solution 2.

[0015] The beneficial effects that the technical solution of this application can achieve are as follows: When applied, the technical solution of this application constructs a lifecycle map corresponding to the batch, provides intuitive visualization of batch flow, and directly displays the corresponding lifecycle map by inputting index information, which can improve query efficiency. In addition, constructing a separate abnormal batch lifecycle map can more clearly and intuitively view batch quality problems and improve management efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of a specific embodiment of a batch full lifecycle traceability system according to this application; Figure 2 This is a flowchart of a specific embodiment of a batch full lifecycle traceability system according to this application.

[0018] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0019] The preferred embodiments of this application will now be described in detail with reference to the accompanying drawings, so that the advantages and features of this application can be more easily understood by those skilled in the art, thereby providing a clearer and more definite definition of the scope of protection of this application.

[0020] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0021] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. The specific embodiments described below can be combined with each other to form new embodiments. The same or similar ideas or processes described in one embodiment may not be repeated in other embodiments.

[0022] Figure 1 This is a schematic diagram of a specific embodiment of a batch full lifecycle traceability system according to this application; Figure 1 The batch lifecycle traceability system shown includes: a batch lifecycle acquisition module 101, which collects event data for each batch throughout its entire lifecycle. Each batch has a corresponding batch code. A batch can be a group of products produced in the same production cycle or under the same conditions. Each batch code uniquely identifies a batch. The event data can include equipment parameters generated during product processing by various devices and quality parameters generated during product testing by various testing devices.

[0023] In one specific embodiment of this application, the batch lifecycle acquisition module 101 includes: The process flow data acquisition unit collects equipment data for each process within a batch. This equipment data includes a process code, equipment identifier, and acquisition time. The process code identifies the specific process in the product manufacturing process. For example, the process code could be: front-end processes: feeding 101, homogenizing 102, coating 103, rolling 104; mid-stage processes: winding 201, leveling 202, welding 203, cell baking 204, electrolyte injection 205; and post-sealing processes: formation 301, capacity grading 302, testing 303, packaging 304. The equipment identifier uniquely identifies the equipment. Specifically, different processes can use different equipment, and different equipment can be used to process the same batch. Each piece of equipment has a different identifier. The acquisition time includes the entry time of the batch into any given process and the exit time from that process. One process can correspond to one piece of equipment data. One piece of equipment data can include a process code, one or more equipment identifiers, and an acquisition time.

[0024] The equipment data acquisition unit collects extended attribute information of each piece of equipment during each process of a batch. This extended attribute information can be various parameters of the equipment during operation. For example, extended attribute information may include at least one of the following: operating power, operating temperature, operating speed, and operating pressure.

[0025] The association code binding unit collects the binding time points at which each batch establishes an association with each association code. The association code can be the code of the material used in the production process. For example, the association code can be a winding code, steel shell code, cell code, or PACK (Pack Code). The binding time point can be the time when the material is used in production. Specifically, when materials are used in the production process, the material code (i.e., each association code) can be bound to the batch code. As an example, the associated association codes, the time when the material corresponding to the association code is used in product production, and the corresponding batch code can be stored together.

[0026] This allows for the effective management of the battery's unique multi-level associated codes (winding code, steel shell code, cell code, PACK code) traceability relationships, establishing a complete, multi-dimensional quality traceability chain, and supporting full-process quality traceability of battery batches from raw materials to finished products.

[0027] In one specific embodiment of this application, the batch lifecycle acquisition module 101 may further include: The quality status acquisition unit collects quality status information for each process within a batch. This quality status information can be product quality parameters during the production process. For example, it can include appearance parameters, cell parameters, consistency, and safety parameters. Specifically, it can obtain quality status information for each process within a batch from associated testing equipment. This testing equipment can include visual inspection equipment, infrared spectrometers, thermal analyzers, chromatographs and mass spectrometers, and gas chromatographs. The quality status anomaly detection unit performs anomaly detection on each quality status information to determine whether any abnormal quality status information exists. Abnormal quality status information can represent information indicating a quality problem in the batch. Specifically, it can determine whether each quality status information falls within the normal quality status information range to identify any abnormal quality status information. For example, during the slitting process, the batch size is inspected to determine whether the detected batch size is within the normal batch size range, thus identifying any abnormal quality status information within the batch size.

[0028] The abnormal change event generation unit, in response to determining the presence of abnormal quality status information among various quality status information, generates a batch abnormal change event based on the abnormal quality status information. A batch abnormal change event can characterize an error event that occurred in the batch, meaning an error occurred in the batch during that process.

[0029] This application Figure 1 The batch lifecycle traceability system shown includes a lifecycle graph construction module 102, which constructs a lifecycle graph corresponding to each batch based on the batch code as the primary key, using various event data. The lifecycle graph can be a visualization tool for displaying the event data throughout the entire production process of that batch. For example, the lifecycle graph can be a coordinate axis with time as the horizontal axis and various event data as the vertical axis.

[0030] In one specific embodiment of this application, the lifecycle mapping construction module 102 may include: The timeline construction unit establishes a batch lifecycle timeline based on each event data point, using the batch code as the primary key. Specifically, for each batch code, a batch lifecycle timeline is built for the corresponding batch with time as the horizontal axis and each event data point as the vertical axis.

[0031] The node relationship construction unit uses the collection points of each process as nodes in the life cycle, and establishes a life cycle chain on the batch life cycle time axis according to the flow relationship between process nodes.

[0032] The status labeling unit marks the quality status at each node in the lifecycle chain based on various quality status information. Therefore, by marking the quality status at each node in the lifecycle chain, a more complete quality traceability chain can be established, providing intuitive visualization of the quality status at each node.

[0033] Figure 1 The batch lifecycle traceability system shown includes: a centralized management module 103 for abnormal states, which includes: The anomaly identification unit 1031 performs anomaly identification on each event data in each event data set to determine whether any abnormal events exist in the event data. Specifically, it can determine whether the quality status information in each event data set is within the normal quality status information range parameter to determine whether any abnormal events exist in the event data.

[0034] The abnormal lifecycle construction unit 1032, in response to determining the existence of abnormal events in each event data, constructs an abnormal batch lifecycle map. Specifically, the abnormal batch lifecycle map can be constructed with time as the horizontal axis and each event data in which an abnormal event occurs as the vertical axis.

[0035] In one specific embodiment of this application, the lifecycle mapping construction module 103 may further include: The abnormal state tracking unit, in response to determining whether an abnormal event exists in each event data set, retrieves the subsequent event data corresponding to the abnormal event. Specifically, in response to determining whether an abnormal event exists in each event data set, it retrieves the subsequent event data corresponding to the abnormal event from the lifecycle graph based on the time corresponding to the abnormal event.

[0036] The anomaly cause analysis unit generates the cause of the anomaly based on the extended attribute information of the equipment operation corresponding to the anomaly event. Specifically, it can determine whether a malfunction has occurred in the equipment operation based on the extended attribute information of the equipment operation corresponding to the anomaly event, thereby generating the cause of the anomaly event. As an example, if the anomaly event is that the batch size is smaller than the normal batch size range in the slitting process, it determines whether the speed of the corresponding cutting equipment is greater than the normal cutting speed. In response to determining that the cutting speed of the cutting equipment is greater than the normal cutting speed, the abnormal cutting speed is identified as the cause of the anomaly event. This allows for the rapid location of quality anomalies in the battery production process and the determination of the root cause of problems that occur during battery production.

[0037] Figure 1The batch lifecycle traceability system shown includes a lifecycle query and traceability module 104, which displays a lifecycle map corresponding to the index information based on the index information. Specifically, in response to detecting user input information for any batch, the lifecycle map of the corresponding batch can be displayed.

[0038] In one specific embodiment of this application, the lifecycle query and tracing module 104 includes: The query unit, in response to an input operation corresponding to the detected index information, displays any event data from the lifecycle graph. The index information includes at least one of the following: batch code, device identifier, and acquisition time. Specifically, in response to an input operation corresponding to the detected index information, event data with the corresponding batch code, device identifier, and acquisition time can be filtered from the lifecycle graph for display.

[0039] The associated traceability unit, in response to an input operation corresponding to an associated code, displays the batch code corresponding to the associated code and its corresponding lifecycle graph. Specifically, in response to an input operation corresponding to an associated code, it can filter and display the batch code corresponding to the associated code and its corresponding lifecycle graph from the lifecycle graph. As an example, in response to determining that any steel shell code has a quality problem, the corresponding batch code can be queried through the associated code table to trace the complete lifecycle of that batch code. Then, the specific process and time point where the quality problem occurred can be determined based on the association time between the associated code and the batch code. Finally, the scope of impact and other related material codes are analyzed. Therefore, by establishing a multi-code associated network traceability relationship, batches can be queried and traced by batch code, equipment identifier and collection time, or by multi-level associated codes. This provides cross-process and cross-equipment associated traceability, supports reverse lookup of batch lifecycle from any associated code, realizes one-stop query of the entire batch trajectory, supports full-process quality traceability of battery batches from raw materials to finished products, and improves query and traceability efficiency.

[0040] In one specific embodiment of this application, the lifecycle query and tracing module 104 may further include: The trajectory visualization unit graphically processes and displays the lifecycle graph. Furthermore, in response to a user's click on any node in the graphical lifecycle graph, it can display the event data for that node. This provides a more intuitive view of the various processes within a batch, making it easier for users to understand.

[0041] In one specific embodiment of this application, the batch lifecycle traceability system further includes a data storage optimization module, which includes: The partitioned storage unit stores event data in partitions based on the acquisition time. Different storage areas correspond to different acquisition times. Specifically, event data can be partitioned based on the production time of each node in a batch. For example, it can be differentiated into front-end, mid-end, and back-end processes. For instance, front-end processes may include feeding, homogenizing, coating, and rolling; mid-end processes may include winding, leveling, welding, cell baking, electrolyte injection, and sealing; and back-end processes may include formation, capacity testing, and packaging. Therefore, by partitioning and storing the event data of a batch, storage pressure is reduced, and it is easier for users to view the data later.

[0042] The exception batch caching unit, in response to the determination that an exception event exists in each event data corresponding to a batch, caches the lifecycle graph of the exception batch. This accelerates access to exception events and reduces backend storage pressure.

[0043] The beneficial effects that the technical solution of this application can achieve are as follows: When applied, the technical solution of this application constructs a lifecycle map corresponding to the batch, provides intuitive visualization of batch flow, and directly displays the corresponding lifecycle map by inputting index information, which can improve query efficiency. In addition, constructing a separate abnormal batch lifecycle map can more clearly and intuitively view batch quality problems and improve management efficiency.

[0044] Figure 2 This is a flowchart of a specific embodiment of a batch full lifecycle traceability system according to this application.

[0045] Figure 2 This paper illustrates a specific implementation of a batch lifecycle traceability system according to this application.

[0046] exist Figure 2 In the specific implementation shown, the method of using the batch full lifecycle traceability system includes: an event data acquisition step S201, collecting event data for each batch throughout its entire lifecycle, wherein each batch corresponds to a batch code; a lifecycle graph construction step S202, constructing a lifecycle graph corresponding to each batch based on the event data and using the batch code as the primary key; and an abnormal state centralized management step S203, including: an anomaly identification sub-step S2031, performing anomaly identification on each event data to determine whether there are any abnormal events in each event data; an abnormal lifecycle construction sub-step S2032, constructing an abnormal batch lifecycle graph in response to determining whether there are any abnormal events in each event data; and a lifecycle query and traceability step S204, displaying the lifecycle graph corresponding to the index information based on the index information.

[0047] The method of using the batch full life cycle traceability system provided in this application can be used to execute the batch full life cycle traceability system described in any of the above embodiments. Its implementation principle and technical effect are similar, and will not be repeated here.

[0048] In one specific embodiment of this application, a computer device includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the method of using the batch lifecycle traceability system described in the above embodiments.

[0049] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0050] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0051] The above are merely embodiments of this application and do not limit the scope of this patent application. Any equivalent structural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of this application.

Claims

1. A batch-based full lifecycle traceability system for manufacturing industries with large volumes of production data, characterized in that: include: The batch lifecycle acquisition module collects event data for each batch throughout its entire lifecycle, wherein each batch corresponds to a batch code. The lifecycle graph construction module constructs a lifecycle graph corresponding to each batch based on the event data and using the batch code as the primary key. The centralized management module for abnormal states includes: An anomaly identification unit performs anomaly identification on each event data in the event data to determine whether there are any abnormal events in the event data; An abnormal lifecycle construction unit, in response to determining that there are abnormal events in each of the event data, constructs an abnormal batch lifecycle map; The lifecycle query and tracing module displays a lifecycle map corresponding to the index information based on the index information.

2. The batch full lifecycle traceability system according to claim 1, characterized in that, The batch lifecycle acquisition module includes: The process flow acquisition unit collects equipment acquisition data for each process in a batch, wherein the equipment acquisition data includes process code, equipment identifier and acquisition time; The equipment data acquisition unit collects extended attribute information of each piece of equipment during each process in each batch; The association code binding unit refers to the binding time points at which the collection batch establishes an association relationship with each association code.

3. The batch full lifecycle traceability system according to claim 2, characterized in that, The batch lifecycle acquisition module also includes: The quality status acquisition unit collects quality status information for each process in a batch. A quality status anomaly detection unit performs anomaly detection on each quality status information to determine whether there is any abnormal quality status information among the various quality status information. An abnormal change event generation unit, in response to determining that there is abnormal quality status information among the various quality status information, generates a batch abnormal change event based on the abnormal quality status information.

4. The batch full lifecycle traceability system according to claim 2, characterized in that, The centralized management module for abnormal states also includes: An abnormal state tracking unit, in response to determining whether there is an abnormal event in the various event data, obtains the subsequent event data corresponding to the abnormal event; The anomaly cause analysis unit generates the cause of the anomaly corresponding to the anomaly event based on the extended attribute information of the device operation corresponding to the anomaly event.

5. The batch full lifecycle traceability system according to claim 3, characterized in that, The lifecycle mapping construction module includes: The timeline construction unit establishes a batch lifecycle timeline based on the various event data, using the batch code as the primary key. The node relationship construction unit uses the collection points of each process as nodes in the life cycle, and establishes a life cycle chain on the batch life cycle time axis according to the flow relationship between process nodes. The status labeling unit labels the quality status at each node in the lifecycle chain based on the various quality status information.

6. The batch full lifecycle traceability system according to claim 2, characterized in that, The lifecycle query and tracing module also includes: The query unit, in response to an input operation corresponding to the detected index information, displays any event data of the lifecycle map, wherein the index information includes at least one of the following: batch code, device identifier, and collection time; The associated traceability unit, in response to the detection of an input operation corresponding to the associated code, displays the batch code corresponding to the associated code and the lifecycle map corresponding to the batch code.

7. The batch full lifecycle traceability system according to claim 5, characterized in that, The lifecycle query and tracing module also includes: The trajectory visualization unit graphically processes and displays the lifecycle map.

8. The batch full lifecycle traceability system according to claim 2, characterized in that, The batch full lifecycle traceability system also includes a data storage optimization module, which includes: A partitioned storage unit, which partitions and stores the event data according to the acquisition time; The abnormal batch caching unit, in response to determining that there are abnormal events in the event data corresponding to each batch, caches the lifecycle graph corresponding to the abnormal batch.

9. A method for using a batch full lifecycle traceability system, characterized in that, include: The event data collection steps involve collecting event data for each batch throughout its entire lifecycle, wherein each batch corresponds to a batch code. The lifecycle graph construction steps involve constructing a lifecycle graph corresponding to a batch based on the event data and using the batch code as the primary key. The centralized management steps for abnormal states include: The anomaly identification sub-step involves identifying anomalies in each event data set to determine whether any anomalous events exist within the event data set. The abnormal lifecycle construction sub-step, in response to determining that there are abnormal events in each of the event data, constructs an abnormal batch lifecycle map; The lifecycle query and tracing step displays the lifecycle map corresponding to the index information based on the index information.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the method of using the batch full lifecycle traceability system as described in claim 9.

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