Graph theory-based industrial internet identification system whole-process tracing method

Abstract

The invention discloses a graph theory-based industrial internet identification system full-process tracing method, which realizes full-process tracing in a supply chain by introducing identifier fields into metadata and constructing a directed graph structure. The identifier fields include fields with similar representations for representing associations of the product upstream and downstream of the supply chain. The system queries across enterprises through a graph traversal algorithm (such as depth-first search (DFS) or breadth-first search (BFS)), and tracks the full life cycle of a product. The method supports attribute pointing code management, is used for tracing multi-attribute information (such as allocation weight, time and the like) of a product, solves cross-enterprise and cross-system coding differences through an alias mechanism, and simplifies a tracing process. The method has a flexible traceability path setting capability, can monitor the product circulation process in real time, gives out an early warning when an abnormality is found, and improves the transparency and safety of a supply chain.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial Internet, and particularly relates to a full-process traceability method for industrial Internet identification and resolution based on graph theory, which is applicable to the traceability and management of products, materials, processes, and other entity or non-entity elements in cross-enterprise and cross-industry supply chains. Background Art

[0002] The industrial Internet identification and resolution system, as the core infrastructure for promoting the development of the industrial Internet in the country, ensures the circulation and traceability of each item, device, process, etc. in the supply chain by assigning a unique identification code to them. In complex supply chain management, the problem of re-coding of identifiers mainly stems from the differences in the identification management of items, devices, processes, etc. among enterprises. Since different enterprises adopt different internal coding rules, even if the same item circulates in the supply chain, its identifier may be re-assigned at different links. For example, the identification coding system used by raw material suppliers may be incompatible with those of manufacturers, distributors, and retailers, resulting in the need to re-assign internal codes when the item enters downstream enterprises. This re-coding may be due to various reasons, such as the internal management requirements of the enterprise, the limitations of the ERP system, data format requirements, or the non-uniformity of industry standards. This phenomenon leads to the inability to directly map cross-enterprise data, making supply chain traceability complex and error-prone. During the cross-enterprise traceability process, without an effective parsing mechanism, the identifiers of upstream enterprises may not be recognized or associated by downstream enterprises, thereby affecting the integrity and traceability of data, increasing query costs, and possibly leading to information silos. Therefore, establishing a method based on graph theory, through identification resolution and alias management, can establish dynamic mapping relationships between different enterprises, ensure the traceability of identification conversion, and thus improve the transparency and management efficiency of the entire supply chain process. Summary of the Invention

[0003] Object of the Invention: The object of the present invention is to provide a full-process traceability method for the industrial Internet identification system based on graph theory. By generating unique identifiers for entity or non-entity elements such as products, materials, and processes, defining the upstream and downstream relationships of materials through metadata fields, and then implementing full-process traceability and query across enterprises and industries through graph theory modeling and graph traversal algorithms.

[0004] Technical Solution: The full-process traceability method for the industrial Internet identification system based on graph theory of the present invention includes the following steps:

[0005] Step 1, Identification Generation and Assignment: Generate unique identifiers for enterprise elements, and define their upstream and downstream associations in the supply chain through the identifier fields in the metadata to form a directed graph structure;

[0006] Step 2, Graph Theory Modeling: Represent the identifier fields and their pointing relationships as a directed graph, where nodes represent product identifier fields and edges represent the upstream and downstream relationships in the supply chain. Multiple identifier fields are not unique, allowing multiple fields to point to the same node or different nodes;

[0007] Step 3, Graph Traversal Query: Use graph traversal algorithms to perform cross-enterprise traceability queries in the directed graph, tracking the entire life cycle of products or materials;

[0008] Step 4, Attribute Pointing Code Management: For multiple key attributes of products or materials, define attribute pointing codes through metadata extension to achieve precise traceability of multi-dimensional attributes. The attribute pointing codes allow non-unique names;

[0009] Step 5, Alias Management: When upstream products enter downstream enterprises, the system converts the upstream identification codes into the internal codes of downstream enterprises through the alias management mechanism, ensuring the coherence and consistency of the traceability path in a cross-enterprise environment. The alias fields are not unique and allow multiple names to correspond to the same identifier, simplifying the traceability process;

[0010] Step 6, Data Collection and Upload: Collect relevant data on production, transportation, and process flow links through Internet of Things devices or related systems, associate them with the identifiers and pointing codes in the metadata, and upload them to the traceability system for management;

[0011] Step 7, Abnormality Monitoring and Warning: Monitor the supply chain or process flow data in real time. If an abnormality is detected, the system automatically issues a warning and notifies relevant enterprises or personnel for handling.

[0012] Furthermore, in Step 1, the enterprise elements include products, materials, people, processes, drawings, and equipment; the identifier fields include "next1", "next2", "previous1", and "previous2".

[0013] Furthermore, in Step 3, the graph traversal algorithms include Depth-First Search (DFS) and Breadth-First Search (BFS).

[0014] Furthermore, the specific Depth-First Search (DFS) algorithm is as follows:

[0015] DFS algorithm formula:

[0016] Input: Graph G = (V, E), starting node v0;

[0017] Output: The traversal order of the nodes in the graph, in depth-first;

[0018] The recursive process is:

[0019] DFS(v):

[0020] Among them, v0 represents the starting node, the starting position of the graph, V represents the set of nodes, E represents the set of edges, indicating the connections between nodes in the graph, and u represents the adjacent node of the current node;

[0021] Access flag: used to record whether each node has been visited;

[0022] Steps of the DFS algorithm:

[0023] Start from the starting node, visit the node and mark it as visited;

[0024] Recursively visit all its unvisited adjacent nodes until all nodes are visited.

[0025] Furthermore, the specific breadth-first search BFS algorithm is as follows:

[0026] BFS algorithm formula:

[0027] Input: Graph G=(V, E), starting node v0;

[0028] Output: The traversal order of nodes in the graph, in breadth-first;

[0029] Iteration process:

[0030] BFS(v0):

[0031] Among them, v0 represents the starting node, the starting position of the graph, V represents the set of nodes, E represents the set of edges, indicating the connections between nodes in the graph, u represents the adjacent node of the current node, dequeue() represents removing and returning the front element of the queue, and the queue queue represents the queue used to store nodes to be visited.

[0032] Steps of the BFS algorithm:

[0033] Enqueue from the starting node;

[0034] When the queue is not empty, dequeue nodes in turn, visit unvisited adjacent nodes and enqueue them;

[0035] Continue until the queue is empty and all reachable nodes in the graph are visited.

[0036] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of the method of the present invention.

[0037] The present invention also discloses a computer-readable storage medium, on which a computer program / instructions are stored, and when the computer program / instructions are executed by a processor, the steps of the method of the present invention are implemented.

[0038] The present invention also discloses a computer program product, including computer programs / instructions, which, when executed by a processor, implement the steps of the method of the present invention.

[0039] Advantages: Compared with the prior art, the present invention has the following remarkable advantages:

[0040] The present invention not only realizes the full - life - cycle traceability of materials, products and processes in the cross - enterprise supply chain, but also has many remarkable advantages. First, through identifier generation and metadata field management, the uniqueness and scalability of the identification system are ensured, enabling the system to adapt to the coding rules and management requirements of different enterprises. Second, by using graph - theory modeling and path - query technology, the construction of the traceability path is more flexible, which can efficiently support multi - level and multi - dimensional dynamic queries, improving the relevance and accessibility of data. In addition, the system introduces efficient graph - traversal algorithms (DFS, BFS), ensuring a fast response during the traceability process. At the same time, combined with an optimized index mechanism, the query latency and computational overhead are significantly reduced. Especially the application of the alias management mechanism not only solves the problem of inconsistent identifiers across enterprises, but also enhances the data mapping ability, making the information exchange between enterprises smoother and avoiding information gaps caused by identifier conversion. Finally, this method has good scalability and compatibility, can be seamlessly integrated into the existing industrial Internet architecture, supports the efficient management of large - scale supply - chain networks, and improves the transparency of the supply chain, data reliability and the intelligent level of enterprise collaboration. Brief Description of the Drawings

[0041] Figure 1 Schematic diagram of the present invention. Detailed Embodiments

[0042] The technical solutions of the present invention will be further described below with reference to the drawings.

[0043] 1. Identifier Generation and Allocation:

[0044] The system generates a unique identifier for each product, material, process or other entity, and defines its upstream and downstream relationships through fields such as PREVIOUS1 and NEXT1 in the metadata, forming a traceability chain.

[0045] Advantages: The generation of unique identifiers and the definition of upstream and downstream relationships ensure the traceability of each node in the supply chain.

[0046] 2. Cross - enterprise Resolution and Alias Management:

[0047] When materials or processes in the upstream enterprise flow to the downstream enterprise, the system uses the ALIAS field to convert the identifiers of the upstream enterprise to adapt to the internal coding system of the downstream enterprise, thus realizing cross - enterprise identifier conversion and seamless traceability.

[0048] Advantages: Through the alias management mechanism, it ensures the accurate conversion of identifiers during the cross-enterprise traceability process.

[0049] 3. Graph Theory Modeling and Path Query:

[0050] In the present invention, through the graph theory method, the relationship between the identifier and its flow in the supply chain is represented as a directed graph, where the nodes represent the identifiers and the edges represent the upstream and downstream relationships. The system realizes the dynamic tracking of the whole process through graph traversal algorithms such as depth-first search (DFS) or breadth-first search (BFS).

[0051] Furthermore, the specific DFS algorithm is as follows:

[0052] DFS algorithm formula:

[0053] Input: Graph G = (V, E), starting node v0;

[0054] Output: The traversal order of the nodes in the graph, in depth-first;

[0055] The recursive process is:

[0056] DFS(v):

[0057] Among them, v0 represents the starting node, the starting position of the graph, V represents the set of nodes, E is the set of edges, representing the connection between the nodes in the graph, and u represents the adjacent node of the current node;

[0058] Access flag: Used to record whether each node has been visited;

[0059] Steps of the DFS algorithm:

[0060] Start from the starting node, visit the node and mark it as visited;

[0061] Recursively visit all its unvisited adjacent nodes until all nodes have been visited.

[0062] Furthermore, the specific BFS algorithm is as follows:

[0063] BFS algorithm formula:

[0064] Input: Graph G = (V, E), starting node v0;

[0065] Output: The traversal order of the nodes in the graph, in breadth-first;

[0066] Iterative process:

[0067] BFS(v0):

[0068] Among them, v0 represents the starting node, the starting position of the graph, V represents the set of nodes, E is the set of edges, representing the connections between nodes in the graph, u represents the adjacent node of the current node, dequeue() represents removing and returning the front element of the queue, and the queue queue represents the queue used to store nodes to be visited.

[0069] Steps of the BFS algorithm:

[0070] Enqueue the starting node;

[0071] When the queue is not empty, dequeue nodes in sequence, visit unvisited adjacent nodes and enqueue them;

[0072] Continue until the queue is empty and all reachable nodes in the graph are visited.

[0073] Advantages: Through the graph traversal algorithm, the upstream and downstream paths of each material can be efficiently queried, which is especially suitable for complex supply chain environments.

[0074] 4. Attribute tracking and management:

[0075] Each identifier can be associated with specific attributes (such as time, consumption, price, operator, etc.) through metadata fields to record the detailed status of each product or process. These attributes can be used for the specific management and tracking of supply chain nodes.

[0076] Advantages: It can accurately track the status and attribute changes of materials in the supply chain, ensuring that the information in all links is controllable and transparent. For some information involving trade secrets (such as formulas), a separate pointing method is used to ensure that the data does not leak.

[0077] 5. Management of metadata fields and traceability paths:

[0078] The system manages the upstream and downstream relationships of each material or process in the supply chain through metadata fields such as PREVIOUS1 and NEXT1. For example, after the process of material 1 is processed within enterprise A, a new material is generated, and the identifiers of its previous process and subsequent process are recorded through metadata fields.

[0079] During the cross-enterprise transfer process, the identifier of the upstream enterprise can be converted into the internal code of the downstream enterprise through the ALIAS field to ensure the consistency of the traceability path.

[0080] 6. Abnormality monitoring and warning:

[0081] The system monitors the status of each node in the supply chain in real time. If abnormal situations are detected, such as the breakage of the identifier chain or the over-time retention of materials, the system will issue a warning and notify the relevant responsible person for handling.

[0082] Advantages: Real-time exception monitoring ensures the safety and continuity of each link in the supply chain, preventing production problems caused by unexpected interruptions.

[0083] In practical applications, the materials of Enterprise A are marked with unique identifiers and undergo process treatment within the enterprise to generate new materials. Each material defines its upstream and downstream identifiers through metadata fields to ensure the traceability of internal processes. When the materials are transferred to downstream Enterprise B, Enterprise B converts the identifiers of Enterprise A into its internal codes through an alias management mechanism and continues to track the status and transfer path of the materials. Through graph theory modeling and graph traversal algorithms, the system can query the full process path of products or materials in real time, achieving efficient tracking across enterprises and industries.

Claims

1. A full-process traceability method for industrial Internet identification system based on graph theory, characterized in that: The steps include: Step 1: Identifier generation and allocation: Generate a unique identifier for the enterprise element, and define its upstream and downstream associations in the supply chain through the identifier field in the metadata to form a directed graph structure; Step 2: Graph theory modeling: The identifier fields and their pointing relationships are represented as directed graphs. Nodes represent product identifier fields, and edges represent upstream and downstream relationships in the supply chain. Multiple identifier fields are not unique, and multiple fields are allowed to point to the same node or different nodes. Step 3: Graph traversal query: Use graph traversal algorithms to perform cross-enterprise traceability queries in directed graphs to track the entire life cycle of products or materials. Step 4: Attribute pointing code management: For multiple key attributes of products or materials, attribute pointing codes are defined through metadata extension to achieve accurate traceability of multi-dimensional attributes. Attribute pointing codes are allowed to have non-unique names. Step 5: Alias ​​management: When upstream products enter downstream enterprises, the system converts the upstream identification code into the internal code of the downstream enterprise through the alias management mechanism, so that the traceability path in the cross-enterprise environment remains coherent and consistent. The alias field is not unique and allows multiple names to correspond to the same identifier, simplifying the traceability process; Step 6: Data collection and upload: Collect relevant data on production, transportation, and process flow through IoT devices or related systems, associate them with the identifiers and pointing codes in the metadata, and upload them to the traceability system for management; Step 7: Abnormal monitoring and early warning: Real-time monitoring of supply chain or process flow data. If an abnormality is detected, the system automatically issues an early warning and notifies relevant companies or personnel to handle it.

2. According to the graph-theory-based full-process tracing method of the industrial Internet identification system according to claim 1, it is characterized in that: In step 1, the enterprise elements include products, materials, people, processes, drawings, and equipment; the identifier fields include "next1", "next2", "previous1", and "previous2".

3. According to the graph-theory-based full-process tracing method of the industrial Internet identification system according to claim 1, it is characterized in that: In step 3, the graph traversal algorithm includes a depth-first search DFS algorithm and a breadth-first search BFS algorithm.

4. According to the graph-theory-based full-process tracing method of the industrial Internet identification system according to claim 3, it is characterized in that: The depth-first search DFS algorithm is specifically: DFS algorithm formula: Input: graph G = (V, E), starting node v0; Output: The traversal order of the nodes in the graph, depth-first; The recursive process is: Among them, v0 represents the starting node, the starting position of the graph, V represents the node set, E is the edge set, representing the connection between nodes in the graph, and u represents the adjacent node of the current node; Access mark: used to record whether each node has been visited; DFS algorithm steps: Starting from the starting node, visit the node and mark it as visited; Recursively visit all its unvisited adjacent nodes until all nodes have been visited.

5. According to the graph-theory-based full-process tracing method of the industrial Internet identification system of claim 3, it is characterized in that: The breadth-first search BFS algorithm is specifically: BFS algorithm formula: Input: graph G = (V, E), starting node v0; Output: The order of traversal of nodes in the graph, in breadth-first order; Iteration process: Among them, v0 represents the starting node, the starting position of the graph, V represents the node set, E is the edge set, representing the connection between the nodes in the graph, u represents the adjacent node of the current node, dequeue() represents removing and returning the front element of the queue, and queue queue represents the queue used to store the nodes to be visited. BFS algorithm steps: Join the queue from the starting node; When the queue is not empty, dequeue nodes one by one, visit unvisited adjacent nodes and add them to the queue; This continues until the queue is empty and all reachable nodes in the graph have been visited.

6. According to the graph-theory-based full-process tracing method of the industrial Internet identification system according to claim 1, it is characterized in that: In step 4, the key attributes include weight and time.

7. According to the graph-theory-based full-process tracing method of the industrial Internet identification system according to claim 1, it is characterized in that: In step 7, the anomaly includes a broken identification chain or a timeout.

8. 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 steps of the method of claim 1.

9. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to claim 1 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to claim 1 are implemented.

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