Industrial manufacturing traceability method based on tree-ring architecture sharded blockchain

Abstract

The application discloses an industrial manufacturing traceability method based on a tree-ring architecture sharded block chain, and comprises the following steps: when abnormal data of an industrial product is detected, a tree-shaped path from a root quality inspection node to a target leaf quality inspection node is determined; according to a root aggregation data packet, inclusion verification is performed layer by layer along the tree-shaped path until the target leaf quality inspection node is reached; legality verification is performed in a shard corresponding to the target leaf quality inspection node; after the legality verification passes, chain integrity verification and quality parameter compliance verification are sequentially performed on each production and processing node based on a ring link; a production and processing node in which the first chain integrity verification fails or the quality parameter compliance verification fails is taken as a responsibility positioning node, and a traceability result corresponding to the responsibility positioning node is output. Through the precise traceability of layer-by-layer positioning along the tree-shaped path and process-by-process reconstruction verification along the ring link, precise fault positioning from the whole vehicle level anomaly to the specific process level is realized.

Description

Technical Field

[0001] This invention relates to an industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain, belonging to the field of sharded blockchain technology. Background Technology

[0002] As the global automotive industry transforms towards intelligent, electric, and high-end products, product quality and safety, as well as full lifecycle traceability, have become core concerns for the industry. As a complex system engineering project, a single vehicle typically consists of tens of thousands of parts. These parts span multiple tiers of suppliers and production plants, undergoing numerous precision processes before final assembly. In the event of a product quality incident or recall, it is crucial to be able to quickly and accurately trace the supplier, production batch, manufacturing station, process parameters, operator, and inspection records of specific parts to achieve liability determination, defect location, and efficient recall.

[0003] Blockchain technology, due to its decentralized, immutable, and collectively maintained characteristics, is considered an effective means of solving product traceability issues. In recent years, it has been widely applied both domestically and internationally in areas such as agricultural product traceability, pharmaceutical traceability, and luxury goods traceability. However, existing blockchain traceability technologies are mostly designed for linear chain scenarios, making it difficult to effectively adapt to the complex tree-like hierarchical structures and time-series manufacturing requirements of the industrial sector, resulting in significant technical bottlenecks in industrial scenarios such as automotive parts manufacturing.

[0004] Existing blockchain traceability technologies primarily use linear chain structures or horizontal sharding to record product flow information. Due to the inherent tree-like bill of materials hierarchy and strong time-series constraints of circular production lines in industrial products, directly applying such linear blockchain technologies to industrial scenarios results in the following technical drawbacks: First, high query latency and high computational complexity in reconstructing traceability paths. Existing technologies, using linear chains or flat storage, cannot directly map the tree-like hierarchical relationships of industrial product parts, components, assemblies, and complete vehicles. Traceability requires extensive cross-chain queries or multi-table joins to reconstruct the hierarchical path, causing the query path length to increase exponentially with the hierarchy depth. This leads to excessively long traceability response times, making it difficult to meet the real-time requirements of OEMs for second-level location and rapid recall in industry. Second, weak time-sequence preservation capabilities and low credibility of the evidence chain. Existing technologies mainly rely on block timestamps and simple hash chains to maintain the order of events. However, in industrial manufacturing, the time interval between data generation at each workstation is extremely short and must be strictly executed according to the process sequence. This can easily lead to problems such as legitimate but out-of-order data being uploaded to the chain, subsequent data overwriting previous data, or replay attacks. As a result, the evidence chain formed cannot strictly prove the irreversibility of causal sequence, and the credibility of the evidence chain is significantly reduced when determining product quality liability. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide an industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain. By locating the source layer by layer along the tree path and reconstructing and verifying the source process step by step along the ring link, the response time is significantly shortened, and accurate fault location from vehicle-level anomalies to specific process-level faults is achieved.

[0006] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0007] This invention discloses an industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain. The method is characterized by its application to a sharded blockchain for industrial products. The sharded blockchain includes leaf quality inspection nodes, intermediate quality inspection nodes, root quality inspection nodes, and production / processing nodes. Each quality inspection node forms a tree-like hierarchical structure based on the industrial product's bill of materials. Each leaf quality inspection node and its associated production / processing node constitute a shard and are sequentially connected in a ring link with the leaf quality inspection node as the first and last node, according to the manufacturing process sequence.

[0008] The industrial manufacturing traceability method includes:

[0009] In the manufacturing process of industrial products, the manufacturing transaction data of industrial products is anchored, generated, and aggregated and solidified layer by layer based on sharded blockchain to obtain the root aggregated data package.

[0010] When abnormal data of industrial products is detected, a tree path is determined from the root quality inspection node to the target leaf quality inspection node.

[0011] Based on the root aggregated data packet, inclusion verification is performed layer by layer along the tree path until the target leaf quality inspection node is reached.

[0012] Legality verification is performed within the segment corresponding to the target leaf quality inspection node; after the legality verification is passed, chain integrity verification and quality parameter compliance verification are performed on each production and processing node in sequence based on the ring link;

[0013] The first production and processing node that fails to verify chain integrity or quality parameter compliance is designated as the responsible location node, and the traceability result corresponding to the responsible location node is output to complete the industrial manufacturing traceability based on the tree-ring architecture sharded blockchain.

[0014] Furthermore, the construction steps of the tree-ring architecture sharded blockchain for the industrial products include:

[0015] Obtain the bill of materials for the industrial product; the bill of materials includes root materials, intermediate materials, and leaf materials.

[0016] Map each material in the bill of materials to a quality inspection node; construct a tree-like structure between the quality inspection nodes based on the bill of materials; wherein, the root material corresponds to the root quality inspection node, the intermediate material corresponds to the intermediate quality inspection node, and the leaf material corresponds to the leaf quality inspection node; the root quality inspection node, the intermediate quality inspection node, and the leaf quality inspection node form a tree-like hierarchical structure;

[0017] Each production and processing step corresponding to each leaf material is mapped to a production and processing node, and the attribution relationship between each production and processing node and the corresponding leaf quality inspection node is established.

[0018] Each leaf quality inspection node and all the production and processing nodes to which it belongs are grouped into a segment, and a unique segment identifier is generated for each segment.

[0019] For each shard, based on the order of each production and processing step corresponding to the shard, the leaf quality inspection node is used as the first and last node, and each production and processing node is connected in sequence to form a directed circular link, so as to form a sharded blockchain with a tree-ring architecture for industrial products.

[0020] Furthermore, the anchoring, generation, and layer-by-layer aggregation and solidification of manufacturing transaction data for industrial products based on sharded blockchain includes:

[0021] For any leaf quality inspection node corresponding to a fragment, cumulative hash recursion is performed based on the ring link to encapsulate the fragmented data packet, which is then submitted to the next higher intermediate quality inspection node along the tree hierarchy.

[0022] For any intermediate quality inspection node, based on the fragmented data packets or intermediate aggregated data packets of the next-level quality inspection node, aggregate hash recursion is performed based on the tree hierarchy to encapsulate the intermediate aggregated data packet corresponding to the current intermediate quality inspection node, and it is submitted to the next-level quality inspection node along the tree hierarchy until it is submitted to the root quality inspection node.

[0023] For the root quality inspection node, based on the intermediate aggregated data packets of the next-level intermediate quality inspection node, aggregate hashing is performed on a tree-like hierarchical structure to encapsulate the root aggregated data packet, thus completing the anchor data aggregation and solidification of the entire manufacturing process.

[0024] Furthermore, obtaining the fragmented data packets includes:

[0025] For any leaf quality inspection node, obtain the current node chain height and the number of production and processing nodes, obtain the batch identifier and shard identifier to generate an initial hash and perform a startup signature; use the initial hash and startup signature as the initial anchor data packet and pass it to the first production and processing node along the ring link;

[0026] For any production and processing node, the anchor data packet of the previous node is signed and verified; after the signature verification is successful, the transaction data generated by the production process corresponding to the production and processing node is collected.

[0027] Based on the initial hash or cumulative hash in the anchor data packet of the previous level, the current transaction data and the corresponding timestamp, and the pre-acquired auxiliary data, the current cumulative hash is generated and a production signature is generated.

[0028] The current accumulated hash and production signature are used as the current anchor data packet and passed along the ring link to the next node until they are returned to the leaf quality inspection node.

[0029] The leaf quality inspection node uses the cumulative hash returned at the end as the shard hash and performs a final state signature on the shard hash; it then encapsulates the batch identifier, shard identifier, shard hash, start signature, final state signature, node chain height, and number of production and processing nodes into a shard data packet.

[0030] Furthermore, the encapsulation to obtain the intermediate aggregated data packet corresponding to the current intermediate quality inspection node includes:

[0031] For any intermediate quality inspection node, obtain the batch identifier, the current node chain height, and the number of the corresponding next-level quality inspection nodes, and receive the fragmented data packets or intermediate aggregated data packets submitted by all next-level quality inspection nodes.

[0032] Signature verification is performed on the fragmented data packets or intermediate aggregated data packets submitted by each quality inspection node; after the signature verification is passed, the fragment hash or aggregated hash in each data packet is extracted as leaf data.

[0033] A Merkle tree is constructed based on all leaf data. The root hash value of the Merkle tree is used as the aggregate hash and aggregated signature is performed. A Merkle proof path from the corresponding leaf data to the aggregate hash is generated for each lower-level quality inspection node.

[0034] The aggregate hash, aggregate signature, batch identifier, current node chain height, and the corresponding number of next-level quality inspection nodes are encapsulated into an intermediate aggregate data packet corresponding to the current intermediate quality inspection node.

[0035] Furthermore, determining the tree path from the root quality inspection node to the target leaf quality inspection node includes:

[0036] Based on the abnormal data of the industrial products, identify the corresponding abnormal leaf materials; based on the abnormal leaf materials, match the corresponding target leaf quality inspection nodes.

[0037] Based on the tree-like hierarchical structure of the sharded blockchain, starting from the root quality inspection node and ending at the target leaf quality inspection node, the tree path from the root quality inspection node to the target leaf quality inspection node is obtained by traversing all intermediate quality inspection nodes.

[0038] Furthermore, the inclusion verification performed layer by layer along the tree path includes:

[0039] Starting from the root quality inspection node, the verification operation is performed layer by layer from top to bottom along the tree path according to the root aggregated data packet until the current level is the level above the target leaf quality inspection node and the verification is successful.

[0040] The verification operation includes:

[0041] For the quality inspection node at the current level on the tree path, obtain the corresponding root aggregated data packet or intermediate aggregated data packet;

[0042] Extract the aggregate hash from the root aggregate data packet or intermediate aggregate data packet as the aggregate hash of the current level, and query to obtain the leaf data of the next level, as well as the Merkle proof path from the leaf data of the next level to the aggregate hash of the current level.

[0043] Based on the aggregate hash of the current level, the leaf data of the next level, and the Merkle proof path, perform a Merkle verification operation. If the Merkle verification passes, proceed to the next level to continue verification; otherwise, terminate the tracing and output an aggregation anomaly alarm.

[0044] Furthermore, the legality verification includes:

[0045] Obtain the public key of the target leaf quality inspection node and the fragmented data packets generated during the manufacturing process;

[0046] The batch identifier, fragment identifier, fragment hash, and startup signature are extracted from the fragmented data packets.

[0047] Based on the fragmented hash, the initial hash is extracted;

[0048] The legitimacy of the target leaf quality inspection node is verified based on its public key, initial hash, batch identifier, shard identifier, and startup signature.

[0049] If the legality verification passes, then chain integrity verification and quality parameter compliance verification are performed sequentially on each production and processing node based on the ring link.

[0050] If the signature verification fails, the legitimacy verification is deemed to have failed, the tracing process is terminated, and a legitimacy anomaly alarm is output.

[0051] Furthermore, the chained integrity verification includes:

[0052] For each production and processing node within the slice corresponding to the target leaf quality inspection node, arranged in the order of manufacturing processes, the following verification operations are performed sequentially:

[0053] Obtain the anchor data packet and public key generated by the current production and processing node during the manufacturing stage, and extract the current cumulative hash, transaction data, timestamp, auxiliary data and production signature from the anchor data packet;

[0054] Based on the current transaction data, timestamps, and auxiliary data, the current reconstructed cumulative hash is recalculated based on the cumulative hash of the previous node that was previously acquired.

[0055] The extracted current cumulative hash is compared with the reconstructed cumulative hash, and the production signature is verified based on the public key of the production processing node.

[0056] If the comparison matches and the signature verification passes, it is determined that the transaction data of the production and processing node has not been tampered with, and the chain integrity verification passes; if the comparison does not match or the signature verification fails, it is determined that the chain integrity verification fails, and the production and processing node is identified as the responsible location node.

[0057] Furthermore, the compliance verification of the quality parameters includes:

[0058] For any production and processing node within the segment corresponding to the target leaf quality inspection node, obtain the anchor data packet generated by the production and processing node during the manufacturing stage, and extract the current transaction data from the anchor data packet;

[0059] Compare the current transaction data with the preset parameter standard specifications;

[0060] If the current transaction data meets the preset parameter standard specifications, the quality parameter compliance verification is passed; otherwise, the quality parameter compliance verification is determined to have failed, and the production and processing node is identified as the responsibility location node.

[0061] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0062] The present invention provides an industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain. First, it directly maps the hierarchical structure of the industrial product bill of materials to the tree-like hierarchical structure of blockchain nodes. Within each shard, a ring link carries the temporal dependencies of manufacturing processes. This allows for direct tracing by locating the target shard layer by layer along the tree path, and then reconstructing and verifying each process along the ring link. This avoids the exponential increase in query complexity caused by cross-chain queries or multi-table associations to reconstruct hierarchical paths in existing linear blockchain technologies, significantly shortening the traceability response time and meeting the requirements of second-level location and rapid retrieval in industrial scenarios.

[0063] Secondly, based on sharded blockchain, the manufacturing transaction data of industrial products is anchored, generated, and aggregated and solidified layer by layer. The on-chain solidification of manufacturing transaction data is completed simultaneously with the manufacturing process, forming a complete chain of evidence that is anchored layer by layer from bottom to top and cannot be tampered with. Any tampering, reversal of order, or absence of transaction data will lead to the failure of comparison of cumulative hash or aggregated hash, providing a reliable data foundation for subsequent traceability verification.

[0064] Finally, the legitimacy verification confirms the credibility of the data fragments, the chain integrity verification confirms that the transaction data has not been tampered with, and the quality parameter compliance verification confirms that the measured parameters of each process meet the standard specifications. This triple verification is progressive and screens each process step by step. When any production and processing node fails verification, the specific manufacturing process, operation time, process parameters, and operator signature corresponding to that node can be accurately located, achieving precise fault location from vehicle-level anomalies to specific process-level anomalies. Attached Figure Description

[0065] Figure 1 This is a flowchart of the industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain provided in Embodiment 1 of the present invention;

[0066] Figure 2 This is a schematic diagram illustrating an application scenario of the industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain provided in Embodiment 2 of the present invention. Detailed Implementation

[0067] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0068] Example 1

[0069] This embodiment 1 provides an industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain, which is applied to the sharded blockchain of industrial products. The sharded blockchain includes leaf quality inspection nodes, intermediate quality inspection nodes, root quality inspection nodes, and production and processing nodes. Each quality inspection node forms a tree-like hierarchical structure based on the bill of materials of the industrial product. The leaf quality inspection nodes and their respective production and processing nodes constitute shards and are connected sequentially according to the manufacturing process to form a ring link with the leaf quality inspection nodes as the beginning and end.

[0070] Industrial manufacturing traceability methods, such as Figure 1 As shown, it includes:

[0071] In the manufacturing process of industrial products, the manufacturing transaction data of industrial products is anchored, generated, and aggregated and solidified layer by layer based on sharded blockchain to obtain the root aggregated data package.

[0072] When abnormal data of industrial products is detected, a tree path is determined from the root quality inspection node to the target leaf quality inspection node.

[0073] Based on the root aggregate data packet, inclusion verification is performed layer by layer along the tree path until the target leaf quality inspection node is reached.

[0074] Legality verification is performed within the segment corresponding to the target leaf quality inspection node; after the legality verification is passed, chain integrity verification and quality parameter compliance verification are performed sequentially for each production and processing node based on the ring link;

[0075] The first production and processing node that fails to verify chain integrity or quality parameter compliance is designated as the responsible location node, and the traceability result corresponding to the responsible location node is output to complete the industrial manufacturing traceability based on the tree-ring architecture sharded blockchain.

[0076] The technical concept of this invention is as follows:

[0077] First, by directly mapping the hierarchical structure of the industrial product bill of materials to the tree-like hierarchical structure of blockchain nodes, and using a circular link within each shard to carry the temporal dependencies of manufacturing processes, traceability can be achieved by directly locating the target shard layer by layer along the tree path, and then reconstructing and verifying it process by process along the circular link. This avoids the problem of exponential growth in query complexity caused by cross-chain queries or multi-table associations to reconstruct hierarchical paths in existing linear blockchain technologies, significantly shortening the traceability response time and meeting the requirements of second-level location and rapid recall in industrial scenarios.

[0078] Secondly, based on sharded blockchain, the manufacturing transaction data of industrial products is anchored, generated, and aggregated and solidified layer by layer. The on-chain solidification of manufacturing transaction data is completed simultaneously with the manufacturing process, forming a complete chain of evidence that is anchored layer by layer from bottom to top and cannot be tampered with. Any tampering, reversal of order, or absence of transaction data will lead to the failure of comparison of cumulative hash or aggregated hash, providing a reliable data foundation for subsequent traceability verification.

[0079] Finally, the legitimacy verification confirms the credibility of the data fragments, the chain integrity verification confirms that the transaction data has not been tampered with, and the quality parameter compliance verification confirms that the measured parameters of each process meet the standard specifications. This triple verification is progressive and screens each process step by step. When any production and processing node fails verification, the specific manufacturing process, operation time, process parameters, and operator signature corresponding to that node can be accurately located, achieving precise fault location from vehicle-level anomalies to specific process-level anomalies.

[0080] The specific steps are as follows:

[0081] Step 1: In the manufacturing process of industrial products, the manufacturing transaction data of industrial products is anchored, generated, and aggregated and solidified layer by layer based on the sharded blockchain to obtain the root aggregated data package;

[0082] 1.1 The construction steps of a tree-ring architecture sharded blockchain for industrial products include:

[0083] Obtain the bill of materials (BOM) for industrial products; the BOM includes root materials, intermediate materials, and leaf materials.

[0084] Map each material in the bill of materials to a quality inspection node; construct a tree-like structure between the quality inspection nodes based on the bill of materials; where the root material corresponds to the root quality inspection node, the intermediate materials correspond to the intermediate quality inspection nodes, and the leaf materials correspond to the leaf quality inspection nodes; the root quality inspection node, the intermediate quality inspection nodes, and the leaf quality inspection nodes form a tree-like hierarchical structure.

[0085] Each production and processing step corresponding to each leaf material is mapped to a production and processing node, and the attribution relationship between each production and processing node and the corresponding leaf quality inspection node is established.

[0086] Each leaf quality inspection node and all the production and processing nodes to which it belongs are grouped into a segment, and a unique segment identifier is generated for each segment.

[0087] For each shard, based on the order of each production and processing step corresponding to the shard, the leaf quality inspection node is used as the first and last node, and then connected to each production and processing node in sequence to form a directed circular link, thus forming a tree-ring architecture sharded blockchain for industrial products.

[0088] 1.1.1 The expression for sharded blockchain is:

[0089]

[0090] In the formula, Indicates a sharded blockchain;

[0091] To avoid coupling conflicts between processing and aggregation operations when an intermediate quality control node manages multiple shards, nodes are used to represent nodes. Divided into production and processing nodes With quality inspection nodes Two categories, .

[0092] Represents a tree-like edge, connecting only quality inspection nodes, indicating that data from the next level of quality inspection nodes is aggregated and reported to the next level of quality inspection nodes;

[0093] A circular edge represents a connection between a quality inspection node and a production processing node within the same segment, indicating a process time dependency.

[0094] 1.1.2 Node Type Definition:

[0095] Production Processing Nodes: Production processing nodes are operational nodes responsible for executing specific manufacturing processes. They do not participate in the tree hierarchy and do not have a parent node in a tree sense. Production processing nodes are associated with a unique leaf quality inspection node through a ring-shaped hierarchy, not a tree-like parent-child relationship. The responsibilities of a production processing node are strictly limited to: executing specific production processing processes, such as forging, turning, welding, and painting; generating transaction data containing process parameters, timestamps, and equipment information; calculating the current cumulative hash based on the previous cumulative hash and the current transaction data and performing a production signature; and passing the anchor data packet containing the current cumulative hash and production signature along the ring link to the next node. Production processing nodes do not broadcast information to outside the shard and do not communicate directly with upper-level quality inspection nodes in the tree hierarchy.

[0096] Quality Inspection Nodes: Quality inspection nodes are the constituent nodes of a tree-like hierarchical structure, divided into three categories: root quality inspection nodes, intermediate quality inspection nodes, and leaf quality inspection nodes. Leaf quality inspection nodes serve as the managers and external interfaces for shards, with one and only one leaf quality inspection node per shard. Leaf quality inspection nodes undertake the following responsibilities: acting as the start and end point of the ring link, generating the initial hash and receiving the final accumulated hash; broadcasting the current accumulated hash to all production and processing nodes within the shard to ensure chain state synchronization; submitting the encapsulated shard data packets to higher-level quality inspection nodes along the tree edges; accepting traceability requests from upper layers and initiating the ring link problem location process; performing a start signature on the initial anchor data and a final state signature on the shard hash. Intermediate and root quality inspection nodes undertake aggregation responsibilities, receiving data packets submitted from lower levels, performing aggregation hash recursion based on the Merkle tree, generating aggregate data packets, and submitting them layer by layer upwards.

[0097] 1.1.3 Definition of Nodes and Hierarchies:

[0098] The hierarchical relationship is defined only between quality inspection nodes. Based on the tree-like hierarchical structure formed by the bill of materials for industrial products, the root quality inspection node corresponds to the root material and is located at the top level of the tree structure; the intermediate quality inspection nodes correspond to the intermediate materials and are located in the middle layer of the tree structure; the leaf quality inspection nodes correspond to the leaf materials and are located in the leaf layer of the tree structure, directly managing the production and processing nodes.

[0099] For any quality inspection node Define the hierarchy depth:

[0100]

[0101] In the formula, Indicates quality inspection node The depth of the hierarchy Indicates the root quality inspection node; Indicates quality inspection node The parent node.

[0102] Define the set of nodes at level d. :

[0103]

[0104] in, This indicates the maximum level depth, which is determined by the specific business bill of materials; the system does not preset an upper limit.

[0105] The set of child quality inspection nodes of quality inspection node q: }, This indicates that u must be a quality inspection node, excluding production and processing nodes; This indicates that the direct parent quality inspection node of quality inspection node u is quality inspection node q; therefore... } represents selecting quality inspection nodes whose parent node is q from all quality inspection nodes, forming a set of child quality inspection nodes of q.

[0106] Parent node of quality inspection node q: ,

[0107] Leaf quality inspection nodes meet the following requirements: Leaf-level quality inspection nodes directly manage production and processing nodes, forming the lowest-level segment.

[0108] Tree edges only exist between quality inspection nodes that have a direct hierarchical relationship:

[0109]

[0110] Indicates quality inspection node The parent node;

[0111] Indicates quality inspection node With parent node The formed edge;

[0112] Let q represent any quality inspection node, where q is not the root node;

[0113] Production and processing nodes do not participate in the definition of hierarchical depth, nor are they connected to quality inspection nodes through tree edges. Instead, their respective shards are clearly defined through a ring-shaped affiliation relationship.

[0114] 1.1.4 Definition and Attribution Relationship of Circular Edges:

[0115] Production and processing nodes are associated through a ring-shaped hierarchy. Clearly define the segment to which the production and processing node belongs. Belonging to the leaf quality inspection node The areas under its jurisdiction yes Managers within a segment.

[0116] Leaf quality inspection nodes The set of production and processing nodes under its jurisdiction is denoted as Workers( ),

[0117]

[0118] Leaf quality inspection nodes The production and processing nodes under its jurisdiction are arranged in the order of manufacturing processes as follows: , , …, , Indicates leaf quality inspection node The number of production and processing nodes under its jurisdiction. Leaf quality inspection nodes. Corresponding Shards The ring-shaped edge inside is formed by the leaf quality inspection node. Together with the production and processing nodes under its jurisdiction, it constitutes:

[0119]

[0120] In the formula, Indicates leaf quality inspection node and its managed production and processing nodes The ring-shaped edge;

[0121] Indicates production and processing nodes The ring edge and the production and processing node The ring-shaped edge;

[0122] Indicates production and processing nodes Leaf quality inspection node The ring-shaped edge.

[0123] Leaf quality inspection node Starting from this point, connect the first production and processing node sequentially. Then connect each production and processing node in sequence according to the process flow until the last node. Ultimately by Connect the leaf quality inspection node This forms a directed ring link with the leaf quality inspection node at the beginning and end.

[0124] All loop edges are defined as follows: , Indicates all leaf quality inspection nodes The union of the formed ring links;

[0125] like This indicates that the quality inspection node only undertakes aggregation responsibilities and has no directly subordinate processing procedures. .

[0126] It should be noted that the ring edge It is a directed chain, not a closed loop. The starting point is the leaf quality control node. Output initial anchoring data, and return to the leaf quality inspection node. The system receives the final accumulated hash, passing through each production and processing node in sequence. The circular name originates from the visual appearance of the local loop formed by the ring and tree edges in the BOM diagram. Essentially, it is a time-series directed chain with the quality inspection node as the beginning and end.

[0127] 1.1.5 Definition of Fragmentation:

[0128] A segment consists of a leaf quality inspection node and all the production and processing nodes under its jurisdiction:

[0129]

[0130] in, For the leaf quality inspection node corresponding to this partition, Workers( This is a set of production and processing nodes arranged in the order of manufacturing processes.

[0131] The segment identifier is: ,in, Leaf quality inspection node Business identifiers, such as crankshaft quality inspection station; Leaf quality inspection node Tree-like paths, such as root, engine, crankshaft; Leaf quality inspection node The node identifier of the parent quality inspection node.

[0132] The shard identifier is generated based on the business identifier of the leaf quality inspection node, its path in the tree hierarchy, and the identifier of the parent quality inspection node, and is used to uniquely identify the shard. Production and processing nodes belong to shards, and their identity is jointly identified by their affiliation relationship and the shard identifier of their respective shards.

[0133] Processing all transactions on a single chain would create a performance bottleneck; sharding distributes transactions across multiple sub-chains for parallel processing. Each shard... Each component maintains its own ring link, allowing manufacturing data from different segments to be processed in parallel, thus achieving horizontal scaling.

[0134] 1.1.6 Definition of Asymmetric Key Pairs:

[0135] Each node holds a pair of asymmetric keys: a private key. and public key The private key is held only by the node itself and is used to sign the anchored data or aggregate hash; the public key is published to all nodes in the network and is used to verify the legitimacy of the corresponding node's signature. Successful signature verification proves that the signed data was indeed issued by the corresponding node and has not been tampered with.

[0136] 1.2. Based on sharded blockchain, the manufacturing transaction data of industrial products is anchored, generated, and aggregated and solidified layer by layer, including:

[0137] For any leaf quality inspection node corresponding to a fragment, cumulative hash recursion is performed based on the ring link to encapsulate the fragmented data packet, which is then submitted to the next higher intermediate quality inspection node along the tree hierarchy.

[0138] For any intermediate quality inspection node, based on the fragmented data packets or intermediate aggregated data packets of the next-level quality inspection node, aggregate hash recursion is performed based on the tree hierarchy to encapsulate the intermediate aggregated data packet corresponding to the current intermediate quality inspection node, and it is submitted to the next-level quality inspection node along the tree hierarchy until it is submitted to the root quality inspection node.

[0139] For the root quality inspection node, based on the intermediate aggregated data packets of the next-level intermediate quality inspection node, aggregate hashing is performed on a tree-like hierarchical structure to encapsulate the root aggregated data packet, thus completing the anchor data aggregation and solidification of the entire manufacturing process.

[0140] Directed time-series chains are not P2P networks and have the following vulnerabilities: Nodes The inability to obtain preceding data caused the entire loop to break.

[0141] The cumulative hash signature chain solution works as follows: Each node not only transmits its own transaction but also carries the cumulative hash of all preceding transactions. The quality control node q, acting as the sole broadcast source for the shard, synchronizes the latest cumulative hash to all production and processing nodes in real time, enabling any node within the shard to verify the complete history.

[0142] 1.2.1 For any leaf quality inspection node corresponding to a fragment, cumulative hash recursion is performed based on the ring link to encapsulate the fragmented data packet, which is then submitted to the next higher intermediate quality inspection node along the tree hierarchy.

[0143] The fragmented data packets are obtained, including:

[0144] For any leaf quality inspection node, obtain the current node chain height and the number of production and processing nodes, and obtain the batch identifier and shard identifier to generate an initial hash and perform a startup signature;

[0145] The initial hash and startup signature are used as the initial anchor data packet and transmitted along the ring link to the first production and processing node;

[0146] For any production and processing node, the anchor data packet of the previous node is signed and verified; after the signature verification is successful, the transaction data generated by the production process corresponding to the production and processing node is collected.

[0147] Based on the initial hash or cumulative hash in the anchor data packet of the previous level, the current transaction data and the corresponding timestamp, and the pre-acquired auxiliary data, the current cumulative hash is generated and a production signature is generated.

[0148] The current accumulated hash and production signature are used as the current anchor data packet and passed to the next node along the ring link until they are returned to the leaf quality inspection node.

[0149] The leaf quality inspection node uses the cumulative hash returned at the end as the shard hash and performs a final state signature on the shard hash; it encapsulates the batch identifier, shard identifier, shard hash, start signature, final state signature, node chain height, and number of production and processing nodes into a shard data packet.

[0150] Specifically, the expression for the initial hash is:

[0151]

[0152] In the formula, Indicates leaf quality inspection node The initial hash; A hash function is a cryptographic one-way function that maps an input of arbitrary length to an output of fixed length. Indicates leaf quality inspection node Fragment identifier; This identifies which production cycle this shard chain started in. , Indicates the production batch number; Indicates the production date; Indicates the global block height of the root chain at startup;

[0153] Leaf quality inspection nodes right Perform startup signing:

[0154]

[0155] In the formula, Indicates leaf quality inspection node Startup signature; Indicates leaf quality inspection node Use your own private key to perform startup signing.

[0156] For fragmentation Production and processing node of the i-th process The cumulative hash is:

[0157]

[0158] In the formula, This represents the cumulative hash of the i-th production / processing node; This represents the cumulative hash of the (i-1)th production and processing node, linking all preceding transactions; This represents the transaction data for the i-th production and processing node, including process data, timestamps, and sensor readings. This represents the timestamp of the i-th production / processing node; This represents the auxiliary data for the i-th production and processing node, including equipment ID, process code, quality inspection results, etc.

[0159] To ensure The on-chain data is consistent with the direct data. Data is automatically collected by sensors / IoT devices and uploaded directly to the chain, reducing manual intervention and not relying on nodes to "manually fill in".

[0160] node For hash value Sign:

[0161] ,

[0162] After signing, the production and processing node The accumulated hash value after signing continues to be passed along the ring edge.

[0163] Production and processing nodes Receive the previous node of the ring. The transmitted hash value Then, first utilize the nodes public key For hash value Verification required:

[0164]

[0165] In the formula, Represents the i-th production and processing node The production signature proves the authenticity of the data;

[0166] Represents the i-th production and processing node The private key;

[0167] Represents the i-th production and processing node The cumulative hash;

[0168] Represents the i-th production and processing node The public key;

[0169] Indicates a node hash value Verification results.

[0170] After verification, the production and processing nodes... The cumulative hash of the generated node is:

[0171]

[0172] And the current cumulative hash signature:

[0173] ,

[0174] After signing, the production and processing node The accumulated hash value after signing continues to be passed along the ring edge.

[0175] The leaf quality inspection node uses the final returned cumulative hash as the shard hash and performs a final state signature on the shard hash:

[0176]

[0177] In the formula, Indicates leaf quality inspection node The final state signature; Indicates leaf quality inspection node Use your own private key to perform startup signing; Indicates leaf quality inspection node The fragmented hash.

[0178] Leaf quality inspection nodes After the circular chain completes its execution, it sends a message to the Workers. Each node in the process broadcasts the cumulative hash of the current signature. .

[0179] Production and processing nodes Upon receiving the broadcast, verify its validity. For leaf quality inspection nodes... All production and processing nodes All Then Shard( All transaction sequences within the range have not been tampered with.

[0180] After receiving acceptance confirmations from all production and processing nodes, the quality inspection node uses the final accumulated hash as the shard hash and performs a final state signature on the shard hash. The batch identifier, shard identifier, shard hash, startup signature, final state signature, node chain height, and number of production and processing nodes are then encapsulated into a shard data packet.

[0181]

[0182] In the formula, Indicates leaf quality inspection node Fragment identifier; Indicates batch identifier; Indicates leaf quality inspection node Startup signature; Indicates leaf quality inspection node The final state signature; Indicates leaf quality inspection node Fragment hash; Indicates leaf quality inspection node The node chain height is used to detect broken chains or skipped blocks; This indicates the number of production and processing nodes within this segment.

[0183] To ensure that the process sequence is irreversible, the system mandates the following:

[0184]

[0185]

[0186] In the formula, Indicates production and processing nodes timestamp; Indicates production and processing nodes timestamp;

[0187] This indicates the timeout threshold for the process; exceeding the timeout triggers the leaf quality inspection node. Early warning mechanism.

[0188] When production and processing nodes Waiting for production and processing nodes When the anchor data packet times out, the leaf quality inspection node Trigger fault detection:

[0189]

[0190] In the formula, Represents a node The returned error signal;

[0191] Indicates timeout;

[0192] express ,Right now and The difference between the timestamps of the hash values ​​generated by the nodes;

[0193] This indicates that the signature verification failed, meaning the data is at risk of being tampered with.

[0194] Backup processing nodes From the leaf quality inspection point Obtain the cumulative hash of the (i-1)th production / processing node. The quality inspection node holds all broadcast records, naturally becoming a reliable source for state recovery. Continue the calculation:

[0195]

[0196] In the formula, Indicates backup processing node The cumulative hash; Indicates backup processing node The auxiliary data; RecoveryFlag indicates that this is a fault recovery, ensuring on-chain auditability.

[0197] 1.2.2 For any intermediate quality inspection node, based on the fragmented data packets or intermediate aggregated data packets of the next-level quality inspection node, perform aggregate hash recursion based on the tree hierarchy to encapsulate the intermediate aggregated data packet corresponding to the current intermediate quality inspection node, and submit it to the next-level quality inspection node along the tree hierarchy until it is submitted to the root quality inspection node.

[0198] The intermediate aggregated data packet corresponding to the current intermediate quality inspection node is encapsulated, including:

[0199] For any intermediate quality inspection node, obtain the batch identifier, the current node chain height, and the number of the corresponding next-level quality inspection nodes, and receive the fragmented data packets or intermediate aggregated data packets submitted by all next-level quality inspection nodes.

[0200] Signature verification is performed on the fragmented data packets or intermediate aggregated data packets submitted by each quality inspection node; after the signature verification is passed, the fragment hash or aggregated hash in each data packet is extracted as leaf data.

[0201] A Merkle tree is constructed based on all leaf data. The root hash value of the Merkle tree is used as the aggregate hash and aggregated signature is performed. A Merkle proof path from the corresponding leaf data to the aggregate hash is generated for each lower-level quality inspection node.

[0202] The aggregate hash, aggregate signature, batch identifier, current node chain height, and the number of quality inspection nodes at the next level are encapsulated into an intermediate aggregate data packet corresponding to the current intermediate quality inspection node.

[0203] Specifically, the expression for the Merkle aggregation tree is as follows:

[0204]

[0205] In the formula, Indicates intermediate quality inspection nodes The aggregate hash, i.e. the root hash value of the Merkle tree; This indicates the construction of a Merkle tree; Indicates intermediate quality inspection nodes The sharding hash or aggregate hash of the first next-level quality inspection node; Intermediate quality inspection nodes The corresponding fragment hash or aggregate hash of the m-th next-level quality inspection node; Indicates intermediate quality inspection nodes The number of the next-level quality inspection nodes.

[0206] The expression for the intermediate aggregated data packet is:

[0207]

[0208] In the formula, Indicates intermediate quality inspection nodes intermediate aggregated data packets; Indicates intermediate quality inspection nodes Aggregate signature; Indicates intermediate quality inspection nodes The height of the node chain; Indicates batch identifier; Indicates intermediate quality inspection nodes The number of the next-level quality inspection nodes.

[0209] 1.2.3 For the root quality inspection node, based on the intermediate aggregated data packet of the next level intermediate quality inspection node, aggregate hashing is performed based on the tree hierarchical structure to encapsulate the root aggregated data packet, thus completing the anchor data aggregation and solidification of the entire manufacturing process.

[0210] Step 2: When abnormal data of industrial products is detected, determine the tree path from the root quality inspection node to the target leaf quality inspection node;

[0211] Determine the tree path from the root quality inspection node to the target leaf quality inspection node, including:

[0212] Based on the abnormal data of industrial products, identify the corresponding abnormal leaf materials; based on the abnormal leaf materials, match the corresponding target leaf quality inspection nodes.

[0213] Based on the tree-like hierarchical structure of sharded blockchain, starting from the root quality inspection node and ending at the target leaf quality inspection node, the tree path from the root quality inspection node to the target leaf quality inspection node is obtained by traversing all intermediate quality inspection nodes.

[0214] Specifically, when a quality issue occurs, the system initiates a source tracing query to the root quality inspection node:

[0215]

[0216] In the formula, Indicates a source tracing query;

[0217] The ID of the industrial product that has a quality problem;

[0218] Components of industrial products that have quality problems;

[0219] Represents a tree-like path;

[0220] This represents a node sequence that starts at the root quality inspection node and ends at the target leaf quality inspection node, traversing all intermediate quality inspection nodes.

[0221] in, This indicates the 0th layer quality inspection node, i.e., the root quality inspection node; This represents the l-th layer quality inspection node, i.e., the target leaf quality inspection node, along the path. Extending downwards, satisfying:

[0222]

[0223] In the formula, This indicates that on the tree-structured traceability path, the parent node of the (l+1)th level quality inspection node is the lth level quality inspection node.

[0224] Step 3: Based on the root aggregated data packet, perform inclusion verification layer by layer along the tree path until the target leaf quality inspection node is reached;

[0225] Inclusion validation is performed layer by layer along the tree path, including:

[0226] Starting from the root quality inspection node, the verification operation is performed layer by layer from top to bottom along the tree path according to the root aggregated data packet, until the current level is the level above the target leaf quality inspection node and the verification is successful.

[0227] The verification process includes:

[0228] For the quality inspection node at the current level on the tree path, obtain the corresponding root aggregated data packet or intermediate aggregated data packet;

[0229] Extract the aggregate hash from the root aggregate data packet or intermediate aggregate data packet as the aggregate hash of the current level, and query to obtain the leaf data of the next level, as well as the Merkle proof path from the leaf data of the next level to the aggregate hash of the current level.

[0230] Based on the aggregate hash of the current level, the leaf data of the next level, and the Merkle proof path, perform the Merkle verification operation. If the Merkle verification passes, proceed to the next level to continue verification; otherwise, terminate the tracing and output an aggregation anomaly alarm.

[0231] The expression for the Merkle validation operation is:

[0232]

[0233] In the formula, This represents the validation function, used to verify whether the leaf data of the next level is correctly included in the aggregation based on the Merkle path;

[0234] This represents the aggregate hash of the quality inspection node at level l on the tree path;

[0235] This represents the leaf data of the quality inspection node at level l+1 on the tree path;

[0236] This represents the Merkle proof path from the leaf data of the (l+1)th level quality check node in the tree path to the aggregate hash of the lth level quality check node.

[0237] Step 4: Perform legality verification within the segment corresponding to the target leaf quality inspection node; after the legality verification is passed, perform chain integrity verification and quality parameter compliance verification on each production and processing node in sequence based on the ring link;

[0238] 4.1. Legality verification includes:

[0239] Obtain the public key of the target leaf quality inspection node and the fragmented data packets generated during the manufacturing process;

[0240] The batch identifier, fragment identifier, fragment hash, and startup signature are extracted from the fragmented data packets.

[0241] The initial hash is obtained by extracting the hash from the fragment hash;

[0242] The legitimacy is verified based on the public key, initial hash, batch identifier, shard identifier, and startup signature of the target leaf quality inspection node;

[0243] If the legality verification passes, then chain integrity verification and quality parameter compliance verification are performed sequentially on each production and processing node based on the ring link;

[0244] If the signature verification fails, the legitimacy verification is deemed to have failed, the tracing process is terminated, and a legitimacy anomaly alarm is output.

[0245] 4.2 Chain integrity verification includes:

[0246] For each production and processing node within the segment corresponding to the target leaf quality inspection node, arranged in the order of manufacturing processes, perform the following verification operations sequentially:

[0247] Obtain the anchor data packet and public key generated by the current production and processing node during the manufacturing stage, and extract the current cumulative hash, transaction data, timestamp, auxiliary data and production signature from the anchor data packet;

[0248] Based on the current transaction data, timestamps, and auxiliary data, the current reconstructed cumulative hash is recalculated based on the cumulative hash of the previous node that was previously acquired.

[0249] The extracted current cumulative hash is compared with the reconstructed cumulative hash, and the production signature is verified based on the public key of the production processing node.

[0250] If the comparison matches and the signature verification passes, the transaction data of the production and processing node is determined to have not been tampered with, and the chain integrity verification passes; if the comparison does not match or the signature verification fails, the chain integrity verification fails, and the production and processing node is identified as the responsible location node.

[0251] 4.3 Quality parameter compliance verification includes:

[0252] For any production and processing node within the shard corresponding to the target leaf quality inspection node, obtain the anchor data packet generated by the production and processing node during the manufacturing stage, and extract the current transaction data from the anchor data packet;

[0253] Compare the current transaction data with the preset parameter standard specifications;

[0254] If the current transaction data meets the preset parameter standards, the quality parameter compliance verification is passed; otherwise, the quality parameter compliance verification is deemed to have failed, and the production and processing node is identified as the responsible location node.

[0255] Step 5: Take the first production and processing node that fails the chain integrity verification or the quality parameter compliance verification as the responsibility location node, and output the traceability result corresponding to the responsibility location node to complete the industrial manufacturing traceability based on the tree-ring architecture sharded blockchain.

[0256] The expression for the source tracing result is:

[0257]

[0258] In the formula, Indicates the source tracing results;

[0259] This represents the traceability path, i.e. the sequence of quality inspection nodes from the root quality inspection node to the target leaf quality inspection node;

[0260] This indicates the segment identifier corresponding to the target leaf quality inspection node;

[0261] This indicates the production / processing node within the segment that caused the anomaly;

[0262] This represents the transaction data generated by the problematic process. This includes parameters, timestamps, sensor data, etc. for the process.

[0263] A chain of evidence, used for tracing and proving evidence, typically includes: : A Merkle proof path segment from the current level to the next higher level; : Startup signature of the leaf quality inspection node; : The final state signature of the leaf quality inspection node; The production signature corresponding to FaultStation is used to prove the authenticity of the data in this process; there may also be signatures / proofs of other intermediate data generated along the path to fully express the traceability evidence chain.

[0264] Example 2

[0265] This embodiment 2 provides an industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain. Taking the production traceability of engine crankshafts as an example, it fully demonstrates the entire process from system initialization to fault traceability.

[0266] Business Background: A car factory produces a batch of crankshafts, batch number B-2024-001. The crankshafts require three processes: forging, turning, and grinding. Finally, they are inspected by the quality inspection station and reported to the engine assembly department. The engine assembly department also oversees piston assembly, and both piston assembly and piston assembly report jointly to the root quality inspection node. Figure 2 As shown.

[0267] The list of nodes is as follows:

[0268] Quality inspection nodes : Root quality inspection point, Engine quality inspection checkpoints Crankshaft quality inspection points Piston quality inspection checkpoints. Among them, Crankshaft quality inspection points and The piston quality inspection point is the blade quality inspection point. The engine quality inspection node is an intermediate quality inspection node.

[0269] Production and processing nodes : Forging Station , Turning station ; Grinding station .

[0270] Step 1: Tree partitioning initialization

[0271] The system constructs a tree-structured sharded topology based on the industrial bill of materials. All nodes are authenticated using digital certificates issued by the industrial CA. Each shard is assigned a unique shard ID.

[0272] Step 2: Quality inspection nodes generate initial anchor values

[0273] Crankshaft quality inspection points Calculate the initial hash And obtain the startup signature by signing it. Crankshaft quality inspection points Signing will be initiated. Send it to the first processing node within the segment.

[0274] Step 3: Circular chain propulsion – Production and processing nodes execute processes sequentially.

[0275] First process: Forging station

[0276] Forging Station Verify startup signature After the authenticity is verified, the forging station... Generate process transaction data And calculate the cumulative hash This ensures the legality of the chain-like process. Forging Station Use private key For cumulative hash Signature, forming a production signature And generate the first anchor data packet and pass it to the turning station. .

[0277] Second process: Turning station

[0278] Turning station Received the first anchor data packet and verified the production signature. Verify timing constraints After verification, the turning station... Generate process transaction data And calculate the cumulative hash Turning station Use private key For cumulative hash Signature, forming a production signature And generate a second anchor data packet and pass it to the grinding station. .

[0279] The third process: Grinding station

[0280] Grinding station Received the second anchor data packet, verify the production signature. Verify timing constraints After verification, the grinding station... Generate process transaction data And calculate the cumulative hash Grinding station Use private key For cumulative hash Signature, forming a production signature And generate a third anchored data packet and send it back to the quality inspection node. .

[0281] Step 4: The crankshaft quality inspection node encapsulates the fragmented data packet and submits it upwards.

[0282] Crankshaft quality inspection points Use your own private key Perform a final state signature on the fragment hash:

[0283] .

[0284] In the formula, Indicates crankshaft quality inspection node The final state signature; Indicates crankshaft quality inspection node Sign using your own private key; Indicates crankshaft quality inspection node Fragment hash; .

[0285] Crankshaft quality inspection points The final state signature is broadcast. Upon receiving the broadcast, the production / processing node verifies its validity. For the crankshaft quality inspection node... All production and processing nodes All Then Shard( All transaction sequences within the range have not been tampered with.

[0286] Crankshaft quality inspection points After receiving confirmation from all nodes, encapsulate the complete output of this fragment into a fragmented data packet:

[0287]

[0288] In the formula, Indicates crankshaft quality inspection node Fragment identifier; Indicates batch identifier; Indicates crankshaft quality inspection node Startup signature; Indicates crankshaft quality inspection node The final state signature; Indicates crankshaft quality inspection node Fragment hash; Indicates crankshaft quality inspection node The node chain height is used to detect broken chains or skipped blocks; 3 indicates the number of production and processing nodes within this segment.

[0289] Crankshaft quality inspection points The fragmented data packets are submitted to the engine quality inspection node via tree edges. .

[0290] Step 5: Bottom-up aggregation.

[0291] (1) Constructing the Merkle tree

[0292] Engine quality inspection nodes Received fragment data packets from all next-level quality inspection nodes, namely crankshaft and piston segments. and Then, based on the shard hash of each shard... Construct a Merkle aggregate tree for the leaves:

[0293]

[0294] In the formula, Indicates engine quality inspection nodes The aggregate hash, i.e. the root hash value of the Merkle tree; This indicates the construction of a Merkle tree; Indicates crankshaft quality inspection node Fragment hash; Indicates piston quality inspection node The fragmented hash.

[0295] (2) Encapsulate the aggregated summary and submit it upwards.

[0296] Engine quality inspection nodes Encapsulate intermediate aggregated data packets:

[0297] ,

[0298] In the formula, Indicates engine quality inspection nodes intermediate aggregated data packets; Indicates engine quality inspection nodes Aggregate signature; Indicates engine quality inspection nodes The height of the node chain; Indicates batch identifier; Indicates engine quality inspection nodes The corresponding number of quality inspection nodes at the next level is used by the verification party to confirm whether the Merkle tree leaf count is complete.

[0299] Engine quality inspection nodes Submit intermediate aggregated data packets to the root quality inspection node.

[0300] (3) The root quality inspection node completes the final aggregation.

[0301] MerkleRoot( =MerkleTree( )

[0302] In the formula, MerkleRoot( ) represents the aggregate hash of the root quality check node.

[0303] Step 6: Trace the source from top to bottom.

[0304] Triggering scenario: If after the vehicle rolls off the production line, VH-2024-008819 discovers abnormal wear of the crankshaft bearing during durability testing, it is suspected that the crankshaft surface roughness does not meet the standards.

[0305] (1) Initiate source tracing query

[0306]

[0307] In the formula, Indicates a source tracing query;

[0308] Indicates the part number;

[0309] This describes the quality issues of the part.

[0310] Represents a tree-like path;

[0311] This represents the node sequence starting from the root quality inspection node, ending at the crankshaft quality inspection node, and passing through the engine quality inspection node.

[0312] (2) First-level verification: root node → engine quality inspection node

[0313] from verify Was it correctly included?

[0314]

[0315] In the formula, Indicates root quality inspection node Aggregate hash;

[0316] Indicates engine quality inspection nodes Leaf data, i.e., engine quality inspection nodes Aggregate hash;

[0317] (3) Second-level verification: Engine quality inspection node → Crankshaft quality inspection node

[0318] from verify Was it correctly included?

[0319]

[0320] In the formula, Indicates engine quality inspection nodes Aggregate hash; Indicates crankshaft quality inspection node Leaf data, i.e., crankshaft quality inspection nodes The fragmented hash.

[0321] (4) Reaching the target segment: Unfolding the circular chain

[0322] Arrival at the crankshaft quality inspection point Extract the complete circular chain data and reconstruct it step by step:

[0323]

[0324] Indicates crankshaft quality inspection node The set of production and processing nodes under its jurisdiction.

[0325] Reconstruction steps:

[0326]

[0327] First, verify the validity of the initial hash:

[0328]

[0329] In the formula, Indicates crankshaft quality inspection node The public key; Indicates crankshaft quality inspection node The initial hash; Indicates crankshaft quality inspection node Fragment identifier; Indicates batch identifier; Indicates crankshaft quality inspection node Startup signature;

[0330] Then, each process was verified step by step. For example, the forging station at the production and processing node. First, perform chain-based integrity verification to prevent tampering:

[0331]

[0332]

[0333] In the formula, Indicates forging station Reconstructing the cumulative hash; Indicates hash calculation; Indicates crankshaft quality inspection node The initial hash; Indicates forging station Transaction data; Indicates forging station timestamp; Indicates forging station Auxiliary data; Indicates forging station The signature; Indicates forging station The public key.

[0334] After successful verification, compliance verification of quality parameters will be conducted. From Extract the measured parameters and compare them with the standard specifications. If they are qualified, continue to the next process for verification; if they are not qualified, output the responsibility location.

[0335] Suppose the following conclusions are true:

[0336] Signature chain integrity: All signatures passed, indicating that the data has not been tampered with.

[0337] Quality compliance inspection: Grinding station fail

[0338] Responsibility Location Node: Grinding Station

[0339] Problematic process record:

[0340] Reason for failure: Shaft diameter of 49.91 mm is lower than the lower limit of specification of 49.95 mm.

[0341] Timestamp:

[0342] Operator signature: It's locked, and there's no denying it.

[0343] (5) Output of traceability results

[0344]

[0345] In the formula, Indicates the source tracing results;

[0346] This represents the traceability path, i.e. the sequence of quality inspection nodes from the root quality inspection node to the target leaf quality inspection node;

[0347] This indicates the segment identifier corresponding to the target leaf quality inspection node;

[0348] This indicates the production / processing node within the segment that caused the anomaly;

[0349] This represents the transaction data generated by the problematic process. This includes parameters, timestamps, sensor data, etc. for the process.

[0350] A chain of evidence, used for tracing and proving evidence, typically includes: : A Merkle proof path segment from the current level to the next higher level; : Startup signature of the leaf quality inspection node; : The final state signature of the leaf quality inspection node; The production signature corresponding to FaultStation is used to prove the authenticity of the data for that process.

[0351] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0352] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0353] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0354] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0355] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain, characterized by: A sharded blockchain applied to industrial products; the sharded blockchain includes leaf quality inspection nodes, intermediate quality inspection nodes, root quality inspection nodes, and production and processing nodes; each quality inspection node forms a tree-like hierarchical structure based on the bill of materials of the industrial product; the leaf quality inspection node and its corresponding production and processing node constitute a shard, and are connected sequentially according to the manufacturing process to form a ring link with the leaf quality inspection node as the first and last node; The industrial manufacturing traceability method includes: In the manufacturing process of industrial products, the manufacturing transaction data of industrial products is anchored, generated, and aggregated and solidified layer by layer based on sharded blockchain to obtain the root aggregated data package. When abnormal data of industrial products is detected, a tree path is determined from the root quality inspection node to the target leaf quality inspection node. Based on the root aggregated data packet, inclusion verification is performed layer by layer along the tree path until the target leaf quality inspection node is reached. Legality verification is performed within the segment corresponding to the target leaf quality inspection node; after the legality verification is passed, chain integrity verification and quality parameter compliance verification are performed on each production and processing node in sequence based on the ring link; The first production and processing node that fails to verify chain integrity or quality parameter compliance is designated as the responsible location node, and the traceability result corresponding to the responsible location node is output to complete the industrial manufacturing traceability based on the tree-ring architecture sharded blockchain.

2. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 1, characterized in that, The steps for constructing the tree-ring architecture sharded blockchain for the industrial products include: Obtain the bill of materials for the industrial product; the bill of materials includes root materials, intermediate materials, and leaf materials. Map each material in the bill of materials to a quality inspection node; construct a tree-like structure between the quality inspection nodes based on the bill of materials; wherein, the root material corresponds to the root quality inspection node, the intermediate material corresponds to the intermediate quality inspection node, and the leaf material corresponds to the leaf quality inspection node; the root quality inspection node, the intermediate quality inspection node, and the leaf quality inspection node form a tree-like hierarchical structure; Each production and processing step corresponding to each leaf material is mapped to a production and processing node, and the attribution relationship between each production and processing node and the corresponding leaf quality inspection node is established. Each leaf quality inspection node and all the production and processing nodes to which it belongs are grouped into a segment, and a unique segment identifier is generated for each segment. For each shard, based on the order of each production and processing step corresponding to the shard, the leaf quality inspection node is used as the first and last node, and each production and processing node is connected in sequence to form a directed circular link, so as to form a sharded blockchain with a tree-ring architecture for industrial products.

3. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 2, characterized in that, The process of anchoring, generating, and aggregating industrial product manufacturing transaction data based on sharded blockchain includes: For any leaf quality inspection node corresponding to a fragment, cumulative hash recursion is performed based on the ring link to encapsulate the fragmented data packet, which is then submitted to the next higher intermediate quality inspection node along the tree hierarchy. For any intermediate quality inspection node, based on the fragmented data packets or intermediate aggregated data packets of the next-level quality inspection node, aggregate hash recursion is performed based on the tree hierarchy to encapsulate the intermediate aggregated data packet corresponding to the current intermediate quality inspection node, and it is submitted to the next-level quality inspection node along the tree hierarchy until it is submitted to the root quality inspection node. For the root quality inspection node, based on the intermediate aggregated data packets of the next-level intermediate quality inspection node, aggregate hashing is performed on a tree-like hierarchical structure to encapsulate the root aggregated data packet, thus completing the anchor data aggregation and solidification of the entire manufacturing process.

4. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 3, characterized in that, The process of obtaining fragmented data packets includes: For any leaf quality inspection node, obtain the current node chain height and the number of production and processing nodes, obtain the batch identifier and shard identifier to generate an initial hash and perform a startup signature; use the initial hash and startup signature as the initial anchor data packet and pass it to the first production and processing node along the ring link; For any production and processing node, the anchor data packet of the previous node is signed and verified; after the signature verification is successful, the transaction data generated by the production process corresponding to the production and processing node is collected. Based on the initial hash or cumulative hash in the anchor data packet of the previous level, the current transaction data and the corresponding timestamp, and the pre-acquired auxiliary data, the current cumulative hash is generated and a production signature is generated. The current accumulated hash and production signature are used as the initial anchor data packet and passed along the ring link to the next node until they are returned to the leaf quality inspection node. The leaf quality inspection node uses the cumulative hash returned at the end as the shard hash and performs a final state signature on the shard hash; it then encapsulates the batch identifier, shard identifier, shard hash, start signature, final state signature, node chain height, and number of production and processing nodes into a shard data packet.

5. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 3, characterized in that, The encapsulation process yields the intermediate aggregated data packet corresponding to the current intermediate quality inspection node, including: For any intermediate quality inspection node, obtain the batch identifier, the current node chain height, and the number of the corresponding next-level quality inspection nodes, and receive the fragmented data packets or intermediate aggregated data packets submitted by all next-level quality inspection nodes. Signature verification is performed on the fragmented data packets or intermediate aggregated data packets submitted by each quality inspection node; after the signature verification is passed, the fragment hash or aggregated hash in each data packet is extracted as leaf data. A Merkle tree is constructed based on all leaf data. The root hash value of the Merkle tree is used as the aggregate hash and aggregated signature is performed. A Merkle proof path from the corresponding leaf data to the aggregate hash is generated for each lower-level quality inspection node. The aggregate hash, aggregate signature, batch identifier, current node chain height, and the corresponding number of next-level quality inspection nodes are encapsulated into an intermediate aggregate data packet corresponding to the current intermediate quality inspection node.

6. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 1, characterized in that, Determining the tree path from the root quality inspection node to the target leaf quality inspection node includes: Based on the abnormal data of the industrial products, identify the corresponding abnormal leaf materials; based on the abnormal leaf materials, match the corresponding target leaf quality inspection nodes. Based on the tree-like hierarchical structure of the sharded blockchain, starting from the root quality inspection node and ending at the target leaf quality inspection node, the tree path from the root quality inspection node to the target leaf quality inspection node is obtained by traversing all intermediate quality inspection nodes.

7. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 1, characterized in that, The inclusion verification performed layer by layer along the tree path includes: Starting from the root quality inspection node, the verification operation is performed layer by layer from top to bottom along the tree path according to the root aggregated data packet until the current level is the level above the target leaf quality inspection node and the verification is successful. The verification operation includes: For the quality inspection node at the current level on the tree path, obtain the corresponding root aggregated data packet or intermediate aggregated data packet; Extract the aggregate hash from the root aggregate data packet or intermediate aggregate data packet as the aggregate hash of the current level, and query to obtain the leaf data of the next level, as well as the Merkle proof path from the leaf data of the next level to the aggregate hash of the current level. Based on the aggregate hash of the current level, the leaf data of the next level, and the Merkle proof path, perform a Merkle verification operation. If the Merkle verification passes, proceed to the next level to continue verification; otherwise, terminate the tracing and output an aggregation anomaly alarm.

8. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 1, characterized in that, The legality verification includes: Obtain the public key of the target leaf quality inspection node and the fragmented data packets generated during the manufacturing process; The batch identifier, fragment identifier, fragment hash, and startup signature are extracted from the fragmented data packets. Based on the fragmented hash, the initial hash is extracted; The legitimacy of the target leaf quality inspection node is verified based on its public key, initial hash, batch identifier, shard identifier, and startup signature. If the legality verification passes, then chain integrity verification and quality parameter compliance verification are performed sequentially on each production and processing node based on the ring link. If the signature verification fails, the legitimacy verification is deemed to have failed, the tracing process is terminated, and a legitimacy anomaly alarm is output.

9. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 1, characterized in that, The chained integrity verification includes: For each production and processing node within the slice corresponding to the target leaf quality inspection node, arranged in the order of manufacturing processes, the following verification operations are performed sequentially: Obtain the anchor data packet and public key generated by the current production and processing node during the manufacturing stage, and extract the current cumulative hash, transaction data, timestamp, auxiliary data and production signature from the anchor data packet; Based on the current transaction data, timestamps, and auxiliary data, the current reconstructed cumulative hash is recalculated based on the cumulative hash of the previous node that was previously acquired. The extracted current cumulative hash is compared with the reconstructed cumulative hash, and the production signature is verified based on the public key of the production processing node. If the comparison matches and the signature verification passes, it is determined that the transaction data of the production and processing node has not been tampered with, and the chain integrity verification passes; if the comparison does not match or the signature verification fails, it is determined that the chain integrity verification fails, and the production and processing node is identified as the responsible location node.

10. The industrial manufacturing traceability method based on a tree-ring architecture sharded blockchain according to claim 1, characterized in that, The compliance verification of the quality parameters includes: For any production and processing node within the segment corresponding to the target leaf quality inspection node, obtain the anchor data packet generated by the production and processing node during the manufacturing stage, and extract the current transaction data from the anchor data packet; Compare the current transaction data with the preset parameter standard specifications; If the current transaction data meets the preset parameter standard specifications, the quality parameter compliance verification is passed; otherwise, the quality parameter compliance verification is determined to have failed, and the production and processing node is identified as the responsibility location node.

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