Equipment manufacturing quality tracing method based on block chain

Abstract

The invention provides an equipment manufacturing quality tracing method based on a block chain, and the method comprises the steps: carrying out the encryption processing of equipment manufacturing data, guaranteeing the confidentiality and integrity of the data, uploading the encrypted data to a distributed file system, and storing the encrypted data, and generating unique identity identification data for positioning and verifying the authenticity of the data. By receiving and using the identity identification data, transaction data is generated and uploaded to the block chain, and non-tampering and traceability of the data are realized. The distributed account book technology of the block chain ensures the transparency and non-tampering of all transaction data, and the use of the distributed file system provides an efficient and reliable storage solution. The method not only improves the safety and reliability of equipment manufacturing data, but also improves the controllability and traceability of equipment quality management through a systematic recording and tracking mechanism, thereby guaranteeing the quality control of the whole process of equipment manufacturing.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment quality tracing technology, and in particular to a blockchain-based equipment manufacturing quality tracing method. Background Art

[0002] Equipment quality traceability refers to the recording, storage, analysis and tracking of quality information throughout the entire manufacturing process of equipment (such as mechanical equipment, electronic equipment, etc.) through systematic methods and technical means to ensure the reliability, controllability and traceability of equipment quality.

[0003] In related technologies, in the technical field of equipment quality traceability, there is a technical problem of high risk of data tampering. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned technical deficiencies and provide a blockchain-based equipment manufacturing quality traceability method to solve the technical problem of high risk of data tampering in related technologies.

[0005] In order to achieve the above technical objectives, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a blockchain-based equipment manufacturing quality traceability method, the method comprising: Receive equipment manufacturing data; Performing encryption processing on the equipment manufacturing data based on a preset encryption method to obtain encrypted equipment manufacturing data; Uploading the encrypted equipment manufacturing data to a distributed file system to store the encrypted equipment manufacturing data, and triggering the distributed file system to generate identity data for the encrypted equipment manufacturing data; wherein the identity data is data indicating an address of the encrypted equipment manufacturing data in the distributed file system; Receiving identity data sent by the distributed file system; generating transaction data based at least on the identity data; The transaction data is uploaded to the blockchain.

[0006] In a second aspect, the present invention provides a blockchain-based equipment manufacturing quality traceability device, the device comprising: A first receiving module, configured to receive equipment manufacturing data; an encryption module, configured to perform encryption processing on the equipment manufacturing data based on a preset encryption method to obtain encrypted equipment manufacturing data; a first uploading module, configured to upload the encrypted equipment manufacturing data to a distributed file system to store the encrypted equipment manufacturing data, and trigger the distributed file system to generate identification data for the encrypted equipment manufacturing data; wherein the identification data is data indicating an address of the encrypted equipment manufacturing data in the distributed file system; A second receiving module, configured to receive identity data sent by the distributed file system; a generating module configured to generate transaction data based at least on the identity identification data; The second uploading module is used to upload the transaction data to the blockchain.

[0007] In a third aspect, the present invention proposes an electronic device comprising: a memory, and one or more processors communicatively connected to the memory; the memory stores instructions that can be executed by the one or more processors, and the instructions are executed by the one or more processors so that the one or more processors implement the above-mentioned method.

[0008] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer program is stored in the computer-readable storage medium, and the computer program implements the above method when executed by a processor.

[0009] Beneficial effects: The present invention effectively solves the problem of high risk of data tampering during the storage and transmission of equipment manufacturing data by introducing a combination of blockchain and distributed file system. Specifically, the method first encrypts the equipment manufacturing data to ensure the confidentiality and integrity of the data, and then uploads the encrypted data to the distributed file system for storage, and generates unique identity data for locating and verifying the authenticity of the data. By receiving and using the identity data, generating transaction data and uploading it to the blockchain, the data is tamper-proof and traceable. The distributed ledger technology of the blockchain ensures the transparency and tamper-proofness of all transaction data, while the use of a distributed file system provides an efficient and reliable storage solution. This method not only improves the security and reliability of equipment manufacturing data, but also enhances the controllability and traceability of equipment quality management through a systematic recording and tracking mechanism, thereby ensuring quality control of the entire equipment manufacturing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 is a schematic diagram of a scenario example provided by an embodiment of the present invention; Figure 2 This is a flowchart of a blockchain-based equipment manufacturing quality traceability method provided by an embodiment of the present invention; Figure 3is a schematic diagram of a consensus algorithm provided by an embodiment of the present invention; Figure 4 This is a flowchart of a blockchain-based equipment manufacturing quality traceability method provided by an embodiment of the present invention; Figure 5 This is a flowchart of a blockchain-based equipment manufacturing quality traceability method provided by an embodiment of the present invention; Figure 6 This is a block diagram of a blockchain-based equipment manufacturing quality traceability device used in an embodiment of the present invention; Figure 7 This is a block diagram of an electronic device used in an embodiment of the present invention. DETAILED DESCRIPTION

[0011] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0012] Overview: In related technologies, with the rapid development of the equipment manufacturing industry and the increasing complexity of production processes, product quality traceability has become a significant issue. The equipment manufacturing industry involves multiple stages, including raw material procurement, production and processing, assembly and testing, and final delivery, each of which can affect the quality of the final product. Therefore, establishing an efficient, transparent, and reliable quality traceability system is crucial to ensuring product quality and enhancing corporate competitiveness.

[0013] Some technical solutions can use technologies such as barcodes and RFID, batch and serial number tracking, and integration with ERP systems to assign unique identifiers to each component and product, enabling tracking of products from raw material procurement to final delivery. These methods provide records of production and distribution information, helping to address product recalls and quality issues, and enhance overall process management capabilities through integration with enterprise resource planning systems. While these technical solutions have achieved some success in improving quality management, they carry a high risk of data tampering. For example, while traditional barcode and RFID technologies can record information, their data is easily tampered with, making it difficult to ensure the authenticity and integrity of the information.

[0014] Therefore, in the related technologies, in the technical field of equipment quality traceability, there is a technical problem of high risk of data tampering.

[0015] In response to this technical problem, the present invention effectively solves the problem of high risk of data tampering during the storage and transmission of equipment manufacturing data by introducing a combination of blockchain and distributed file system. Specifically, the method first encrypts the equipment manufacturing data to ensure the confidentiality and integrity of the data, and then uploads the encrypted data to the distributed file system for storage, and generates unique identity data for locating and verifying the authenticity of the data. By receiving and using the identity data, generating transaction data and uploading it to the blockchain, the data is tamper-proof and traceable. The distributed ledger technology of the blockchain ensures the transparency and tamper-proofness of all transaction data, while the use of a distributed file system provides an efficient and reliable storage solution. This method not only improves the security and reliability of equipment manufacturing data, but also improves the controllability and traceability of equipment quality management through a systematic recording and tracking mechanism, thereby ensuring quality control of the entire equipment manufacturing process.

[0016] Example scenario: like Figure 1 As shown, before describing the embodiments of the present invention in detail, a specific scenario example is used to disclose a scenario in which the technical solution of the present invention can be used. In this scenario example, it can include an intelligent device layer, an edge gateway layer, a data storage layer, and a platform application layer.

[0017] Smart device layer: This layer includes multiple smart devices. Specifically, it includes key components such as device sensors, surveillance cameras, and device monitors. These smart devices play a crucial role in capturing and recording equipment manufacturing data in real time during the manufacturing process.

[0018] Edge gateway layer: responsible for receiving and processing equipment manufacturing data from the smart device layer. The edge gateway layer uses efficient data processing programs to conduct in-depth analysis and conversion of the raw data generated by smart devices, and generates structured data processing result records. Specifically, the edge gateway layer is composed of edge gateway devices, which undertake the key functions of data collection, standardization, uploading and processing. Among them, the data collection function refers to the edge gateway connecting to the smart device through the network, and then obtaining its relevant data through the corresponding data acquisition interface of the smart device; the data acquisition interface can allow external users or systems to access device data safely and efficiently; the data standardization function refers to the face of diversified data generated by smart devices from different manufacturers and different models. The edge gateway can convert it into standardized data in a unified format to ensure data consistency and interoperability; the data upload function refers to the edge gateway uploading the processed standardized data to the data storage layer; the data processing function refers to the edge gateway using its built-in computing and storage resources to execute the executable data processing program provided by the system administrator to perform in-depth processing on the collected smart device data; Data storage layer: After the structured data processing results are recorded and uploaded to the blockchain of the data storage layer, the blockchain uses the PBFT consensus mechanism to reach consensus on the structured information record and then generates a block for storage. The device data of the smart devices is then retrieved from the blockchain through smart contracts for management and analysis. Specifically, the data storage layer includes a blockchain, a cloud server, and an edge server, with the blockchain system deployed on the cloud server and edge server devices to store data and operational information collected by smart devices. The blockchain refers to the Hyperledger Fabric consortium blockchain platform; the blockchain storage of smart device data refers to the edge gateway uploading collected smart device data to the blockchain via a smart contract, and then storing it in the blockchain after consensus sorting via the PBFT consensus mechanism. The consensus sorting refers to each node sorting and authenticating multiple pieces of data uploaded to the blockchain to ensure data consistency across nodes.

[0019] The platform application layer has management functions, visualization functions, data analysis functions, and equipment quality traceability functions. The management functions refer to equipment management functions such as intelligent device linkage management, intelligent device ledger management, and intelligent device alarm management. The basic functions refer to basic functions such as user registration, equipment operation monitoring, and equipment fault repair. The visualization function refers to the visualization of data collected by intelligent devices in charts and graphs, as well as the visualization of the real-time operating status of intelligent devices. The data analysis functions include statistical analysis, trend analysis, and correlation analysis. Specifically, statistical analysis refers to the use of descriptive statistical methods to calculate basic statistical indicators such as the mean, median, and standard deviation of data to understand the overall distribution of the data. Trend analysis refers to the use of time series analysis to identify the changing trends of production and quality data and predict future quality conditions. Correlation analysis refers to the use of association rule mining methods to identify the correlation between different production parameters and quality results and discover potential quality influencing factors. The equipment quality traceability function refers to the comprehensive analysis and optimization of product quality through in-depth mining of trusted equipment manufacturing process data recorded on the blockchain, combined with data analysis tools in the platform application layer, to guide equipment manufacturing companies to improve production processes and quality control measures.

[0020] Example method: like Figure 2 The present embodiment provides a blockchain-based equipment manufacturing quality traceability method, which may include: Step S102: receiving equipment manufacturing data.

[0021] In this embodiment, the receiving action can be represented as an edge gateway node acquiring equipment manufacturing data from a smart device. The smart device can be deployed in a smart device layer, and it is understood that multiple smart devices can be deployed in the smart device layer to collect equipment manufacturing data. The edge gateway node can be configured in the edge gateway layer, and it is understood that multiple edge gateway nodes can be configured in the edge gateway layer to acquire equipment manufacturing data from the smart device layer.

[0022] Specifically, the smart devices can be deployed at equipment manufacturing sites to collect equipment manufacturing data. These smart devices can include equipment sensors, surveillance cameras, or equipment monitors. Smart devices can capture and record data from the equipment manufacturing process in real time, including data generated at every stage of the process, from raw material procurement, production and processing, assembly and testing, to final delivery.

[0023] More specifically, during the raw material procurement phase, the equipment manufacturing data may include supplier information, raw material batch numbers, material specifications and descriptions, and material testing reports. During the production and processing phase, the equipment manufacturing data may include equipment operating parameters, production batch numbers, and operation records. These equipment operating parameters may further include operating parameters such as temperature, pressure, speed, and power. During the assembly and testing phase, the equipment manufacturing data may include assembly sequence and process information, component information, and functional test data. During the final delivery phase, the equipment manufacturing data may include product serial numbers and factory inspection reports.

[0024] The edge gateway node can be an edge computing device with certain data acquisition, data processing, and data transmission capabilities. The edge gateway node is connected to the smart device. The edge gateway node can be an industrial computer, edge server, or industrial gateway. It can also be an embedded system or Internet of Things (IoT) gateway.

[0025] Step S104: encrypting the equipment manufacturing data based on a preset encryption method to obtain encrypted equipment manufacturing data.

[0026] In this embodiment, multiple encryption methods can be preset in the edge gateway node, and the edge gateway node can use one of the encryption methods to encrypt the equipment manufacturing data. Alternatively, the edge gateway node can use multiple encryption methods to encrypt the equipment manufacturing data. The encryption method can be an encryption rule or an encryption algorithm. The encryption method can be the Advanced Encryption Standard (AES) encryption algorithm, the Triple DES encryption algorithm, or the Rivest-Shamir-Adleman encryption algorithm.

[0027] Step S106: Upload the encrypted equipment manufacturing data to the distributed file system to store the encrypted equipment manufacturing data, and trigger the distributed file system to generate identity data of the encrypted equipment manufacturing data; wherein the identity data is data representing the address of the encrypted equipment manufacturing data in the distributed file system.

[0028] In this embodiment, the distributed file system can be configured in a data storage layer. The data storage layer can be composed of at least one server. The server can be a cloud server or an edge server, etc. The distributed file system and blockchain can be deployed in the server to store the corresponding data.

[0029] The distributed file system may be an IPFS system (InterPlanetary File System), an HDFS system (Hadoop Distributed File System), an Amazon S3 system (Simple Storage Service), or the like.

[0030] The data storage layer can be configured to monitor upload events. Specifically, this mechanism is automatically triggered when new data is uploaded. The server can be configured to monitor uploads using event listeners or triggers. Once the trigger mechanism is activated, the server performs a hashing operation on the uploaded data to generate identification data for the encrypted equipment manufacturing data. This identification data can be a hash value.

[0031] In this embodiment, multiple hash algorithms may be used to perform hash processing, for example, the SHA-256 (Secure Hash Algorithm 256-bit) algorithm, the SHA-3 (Secure Hash Algorithm 3) algorithm, or the MD5 (Message Digest Algorithm 5) algorithm.

[0032] Step S108: Receive identity data sent by the distributed file system.

[0033] In this embodiment, the distributed file system performs a hash operation on the encrypted equipment manufacturing data by calling a preset hash algorithm to obtain the identity data, and then returns the identity data to the edge gateway node.

[0034] Step S110: Generate transaction data based at least on the identity identification data.

[0035] In this embodiment, upon receiving the identity data, corresponding transaction data can be generated. This transaction data needs to be uploaded to the blockchain for storage. The transaction data can be represented as a structured information record that can be stored on the blockchain. In addition to the identity data field, the transaction data can also include other fields, such as a timestamp, gateway number, upload time, data file type, administrator signature, and previous transaction hash. The timestamp can record the time the transaction was created, which is used to record the specific time of the transaction and facilitate traceability and sequencing. The gateway number can be the edge gateway node number, which is used to track the data source and ensure data reliability. The upload time records the time the data was uploaded, helping to verify the data's timeliness. The data file type describes the data file type and helps to classify and manage different types of data. The administrator signature can be a digital signature of the transaction information using the administrator's private key, which verifies the authenticity and integrity of the transaction information and prevents tampering. The previous transaction hash can be used to link previous and subsequent transaction records, forming a chain structure to ensure data continuity and traceability.

[0036] Step S112: Upload the transaction data to the blockchain.

[0037] In this embodiment, the transaction data can be uploaded to the blockchain via a data upload contract. This data upload contract is a smart contract deployed on the blockchain that automatically executes data upload and recording operations. It ensures that data is correctly processed and stored during the upload process and records transaction information. The blockchain can be a Hyperledger Fabric consortium blockchain platform. In addition to the Hyperledger Fabric consortium blockchain platform, the Ethereum platform can also be used. The Ethereum platform is an open-source, global decentralized computing platform that supports smart contracts and decentralized applications.

[0038] After being uploaded to the blockchain, the transaction data can be stored on the blockchain after reaching consensus.

[0039] like Figure 3 As shown, in this embodiment, a consensus algorithm can be used to perform consensus on the transaction data. For example, a PoW consensus algorithm (Proof of Work) or a BFT consensus algorithm (Byzantine Fault Tolerance) can be used.

[0040] In this embodiment, the PBFT consensus algorithm (Practical Byzantine Fault Tolerance) can also be used. Specifically, it can include: System initialization: The system is set to contain n nodes, of which a maximum of f nodes are allowed to be malicious. The requirement is that n ≥ 3f + 1. Nodes are divided into primary and backup nodes. A node is selected as the primary node through rotation or a random algorithm. As long as the primary node remains unchanged, this is called a view.

[0041] Masternode broadcast: In a certain view, the client will request<REQUEST, operation, timestamp,client> Sent to the master node (if the client sends it to a slave node, the slave node will forward it to the master node), and the master node is responsible for broadcasting the request to all other replica nodes and completing consensus.

[0042] Response processing: All nodes complete the processing request and process the results<REPLLY, view, timestamp,client, id_node, response> Return to the client. The client checks whether it has received at least f+1 identical results from different nodes as the final result.

[0043] The master node's broadcast process consists of three phases: pre-prepare, prepare, and commit. The pre-prepare and prepare phases ensure that requests are sent in the correct order within the same view; the prepare and commit phases ensure that confirmation requests between different views are in order.

[0044] Pre-prepare phase: The master node assigns a proposal number to the request received from the client and then sends a pre-prepare message <<PRE-PREPARE, view, n, digest> , message> is sent to each replica node. The master node needs to sign the prepared message. Where n is the sequence number assigned by the master node for this request, message is the client's request message, and digest is the message digest. The purpose of this step is to assign a sequence number to the client request.

[0045] Preparation phase: After receiving the pre-prepare message, the replica node checks the message (including checking the signature, view, and number). If the message is legal, it sends the preparation message to other nodes.<PREPARE, view, n, digest, id> , including its own ID information and adding a signature. Nodes receiving the prepare message also check the legitimacy of the message. If a node collects at least 2f+1 verified messages, it is considered verified and the prepare message is written to the local commit message log. This step confirms that a majority of nodes have reached consensus on the sequence number.

[0046] Commit phase: broadcast commit message<COMMIT, v, n, d, id> And add your own signature to tell other nodes that a proposal numbered n has been submitted in view v. If at least 2f+1 verified commit messages are collected, it means that the proposal has been accepted by the entire system.

[0047] The definitions of the terms appearing in the above steps are as follows: Replica: A node in the system. Each replica stores a copy of the system's data and participates in the consensus process.

[0048] Master node: The node responsible for coordinating the consensus process, receiving client requests and forwarding them to backup nodes; Backup nodes: All nodes except the master node, which receive and verify the messages from the master node and participate in the consensus process.

[0049] Client: An entity that sends requests to a distributed system, expecting the system to reach consensus and execute its requests.

[0050] Pre-prepare message: A message sent by the master node to the backup node, containing the sequence number and operation content requested by the client, used to initiate the consensus process.

[0051] Prepare message: A message generated by a backup node after verifying the pre-prepare message, indicating that it has received and verified the request.

[0052] Commit message: A message generated by a node after receiving enough prepare messages, indicating that it believes the request has reached consensus and is ready to be executed.

[0053] Sequence number: A unique number used to identify client requests and ensure the orderly execution of requests.

[0054] Malicious nodes: Nodes that attempt to disrupt the consensus process or the normal operation of the system. PBFT allows a maximum of f malicious nodes in the system.

[0055] Signature verification: When verifying a message, a node checks the digital signature of the message to ensure the authenticity of its source and the integrity of its content; In the above-mentioned implementation, by introducing a combination of blockchain and distributed file systems, the problem of high risk of data tampering during the storage and transmission of equipment manufacturing data is effectively solved. Specifically, the method first encrypts the equipment manufacturing data to ensure the confidentiality and integrity of the data, and then uploads the encrypted data to the distributed file system for storage, and generates unique identification data for locating and verifying the authenticity of the data. By receiving and using the identification data, generating transaction data and uploading it to the blockchain, the data is tamper-proof and traceable. The distributed ledger technology of the blockchain ensures the transparency and tamper-proofness of all transaction data, while the use of a distributed file system provides an efficient and reliable storage solution. This method not only improves the security and reliability of equipment manufacturing data, but also improves the controllability and traceability of equipment quality management through a systematic recording and tracking mechanism, thereby ensuring quality control of the entire equipment manufacturing process.

[0056] like Figure 4 As shown, in some embodiments, the step of receiving equipment manufacturing data may include: Step S1022: Sending a request for acquiring equipment manufacturing data to a target smart device at a preset time frequency; wherein the smart device is a device for collecting equipment manufacturing data.

[0057] In this embodiment, the preset time frequency can be one hour, two hours, one day, etc. The target smart device can be one or more smart devices in the smart device layer. Specifically, the timer task can be configured in the edge gateway node through a timer or scheduler. The timer task can call a function or method to send a request, thereby sending a request to the target smart device to obtain equipment manufacturing data. The request can carry the identifier of the smart device, which can be a device number, which can be a number that uniquely identifies the smart device. The request can also carry a request type, which can specify the type or mode of the request, such as "real-time data" or "historical data". It can also carry a data range, that is, specifying the data time range of the request, such as the start time and end time. The request can also carry a data format, which specifies the expected data format, such as JSON, XML, etc. The edge gateway node can send a request to the target smart device via HTTP, MQTT or other communication protocols.

[0058] Step S1024: receiving equipment manufacturing data returned in response to the request from the target smart device.

[0059] In this embodiment, after receiving the returned equipment manufacturing data, the edge gateway node may also perform analysis and preprocessing.

[0060] The above implementation achieves scheduled data collection and real-time monitoring of equipment manufacturing processes by sending requests for equipment manufacturing data to target smart devices at a preset frequency and receiving the equipment manufacturing data returned in response to the requests. This solution ensures the timeliness and continuity of data collection, effectively avoiding omissions and delays in data collection, and enhancing data integrity and accuracy. Furthermore, through a preset frequency request mechanism, the data collection frequency can be flexibly adjusted according to specific needs to meet the requirements of different application scenarios, thereby improving the availability of equipment manufacturing data and the reliability of quality traceability.

[0061] In some embodiments, the step of receiving equipment manufacturing data may also be passive reception. Accordingly, when passive reception is adopted, a timer or scheduling library may be used on the smart device to set a scheduled task.

[0062] like Figure 5 As shown, in some embodiments, the step of performing encryption processing on the equipment manufacturing data based on a preset encryption method includes: Step S1042: Call the preset elliptic curve encryption algorithm to generate a public-private key pair.

[0063] Step S1044: encrypting the equipment manufacturing data based on the public key in the public-private key pair.

[0064] In this embodiment, the public key in the public-private key pair can perform encryption processing on the equipment manufacturing data, and correspondingly, the private key can perform decryption processing on the encrypted equipment manufacturing data.

[0065] In the above implementation, the public-private key pair generated using Elliptic Curve Cryptography (ECC) provides higher security than traditional encryption algorithms (such as RSA) with the same key length. Furthermore, ECC's high computational efficiency enables efficient encryption processing with limited computing resources, making it suitable for resource-constrained devices (such as edge devices or IoT devices). While maintaining the same security as traditional encryption algorithms, it requires shorter keys, reducing computing resource consumption and enhancing attack resistance.

[0066] In some embodiments, the identity data is obtained by: The distributed file system performs hash processing on the encrypted equipment manufacturing data based on a preset hash algorithm to obtain a first hash value.

[0067] In this embodiment, the preset hash algorithm may be the SHA-256 hash function. SHA-256 is a highly cryptographically strong hash function that generates a 256-bit hash value with high uniqueness and collision resistance, ensuring data integrity. By hashing data, it is possible to verify that the data has not been tampered with during transmission and storage, thereby ensuring data reliability.

[0068] The distributed file system performs a first encoding process on the first hash value to obtain a second hash value; wherein the second hash value has at least hash algorithm identification information and length information relative to the first hash value.

[0069] In this embodiment, the first encoding process may be a Multihash encoding process. Multihash encoding adds algorithm identification information before the hash value, making the hash value self-descriptive, and clearly indicating which hash algorithm was used to generate it. Multihash encoding also includes the length of the hash value, further enhancing the self-descriptive nature of the hash value and facilitating the system's identification and processing of hash values ​​of different lengths.

[0070] The distributed file system performs a second encoding process on the second Hash value to obtain a third Hash value; wherein the third Hash value is easier to input than the second Hash value, and the third Hash value is the identity identification data.

[0071] In this embodiment, the second encoding process may be Base58 encoding. Base58 encoding removes easily confused characters (such as 0, 0, 1, and 1), resulting in an encoded string that is more suitable for human reading and input, reducing the possibility of human input errors. Compared to other encoding methods, Base58 encoding generates shorter strings, making them easier to display and transmit, and is suitable for resource-constrained environments.

[0072] In the above-mentioned implementation, through multi-level hashing and encoding processing, each encrypted equipment manufacturing data generates unique identification data, thereby ensuring the uniqueness and traceability of the data.

[0073] In some embodiments, the step of generating transaction data based at least on the identity data includes: Extract the gateway number, the first timestamp, the second timestamp, the data type of the encrypted equipment manufacturing data and the administrator signature; wherein the first timestamp is the timestamp for recording the generation of transaction data, and the second timestamp is the timestamp for receiving equipment manufacturing data.

[0074] In this embodiment, the action of extracting the gateway number can be expressed as reading the unique gateway number directly from the configuration or management system of the edge gateway node. The action of extracting the first timestamp can be expressed as calling the time function to obtain the current timestamp when generating transaction data, and recording the time when the transaction was created. The action of extracting the second timestamp can be expressed as reading directly from the configuration or management system of the edge gateway node. It can be understood that after the edge gateway node receives the equipment manufacturing data, it can generate the corresponding timestamp. The action of extracting the data type can be expressed as reading the data type field from the encrypted equipment manufacturing data or its metadata. The administrator signature is the administrator using his private key to digitally sign the transaction data, so the digital signature can be extracted from the corresponding system.

[0075] The gateway number, the first timestamp, the second timestamp, the data type of the encrypted equipment manufacturing data, the administrator signature and the transaction data are assembled into transaction data.

[0076] In this embodiment, the assembling action can be expressed as integrating the above data into a structured JSON object.

[0077] In the above implementation plan, by extracting the gateway number, first timestamp, second timestamp, data type of encrypted equipment manufacturing data and administrator signature, these key information and identity identification data are assembled into transaction data, ensuring the integrity, timeliness and security of the data, helping to achieve accurate traceability and verification of transaction data, enhancing the transparency and credibility of the system, and effectively preventing the risk of data tampering.

[0078] In some embodiments, the step of uploading the transaction data to the blockchain includes: The transaction data is uploaded to the blockchain through a preset data upload contract.

[0079] In this embodiment, a smart contract can be deployed on the blockchain, which is responsible for receiving and storing transaction data.

[0080] When the event notification of transaction data being uploaded to the blockchain is monitored, the transaction data is obtained from the blockchain through the preset data acquisition contract.

[0081] In this implementation, smart contracts deployed on the blockchain can trigger events. Blockchain clients or applications need to listen for these events to be notified when transaction data is uploaded. The pre-defined data acquisition contract is another smart contract that retrieves stored transaction data from the blockchain. When a transaction data upload event is detected, the data acquisition contract's methods are called to retrieve the transaction data.

[0082] At least the gateway number in the transaction data is verified to prevent the transaction data from being modified during the upload process.

[0083] In this embodiment, in addition to verifying the gateway number in the transaction data, the administrator signature can also be verified.

[0084] In this embodiment, transaction data is uploaded to the blockchain through a preset data upload contract, and when an upload event notification is monitored, the transaction data is obtained from the blockchain through a preset data acquisition contract and the gateway number therein is verified, thereby ensuring that the transaction data is not tampered with during the upload process, enhancing the security and integrity of data transmission, and at the same time improving the system's real-time monitoring and verification capabilities of transaction data, ensuring the transparency and traceability of the equipment manufacturing process.

[0085] In some embodiments, the method further comprises: Obtaining transaction data from the blockchain; In this embodiment, the acquisition action can be represented as the platform application layer obtaining transaction data from the data storage layer, that is, from the blockchain. The platform application layer can be composed of a server, workstation, desktop computer, laptop computer, or intelligent mobile terminal, such as a smartphone. Specifically, the device in the platform application layer can call the data query contract on the blockchain to first obtain the transaction data and then extract the identity data from the transaction data.

[0086] Based on the transaction data, corresponding encrypted equipment manufacturing data is extracted from the distributed file system.

[0087] In this embodiment, the identity identification data is also the IPFS address of the encrypted equipment manufacturing data, and then the encrypted equipment manufacturing data can be obtained from IPFS.

[0088] Decryption processing is performed on the encrypted equipment manufacturing data to obtain decrypted equipment manufacturing data.

[0089] In this embodiment, the encrypted equipment manufacturing data can be decrypted using a private key to obtain the decrypted equipment manufacturing data. The decrypted data can be standardized to enable comparison and analysis of data from different data sources and formats on the same platform. This includes unit conversion, numerical normalization, and text data structured processing.

[0090] Data modeling of at least one dimension is performed on the decrypted equipment manufacturing data to obtain a data model.

[0091] In this implementation, the dimensions required for analysis are determined, such as time, geography, production batches, equipment, and quality indicators. Based on these dimensions, a data cube is constructed, enabling data to be sliced ​​and aggregated according to different dimensions and levels, supporting flexible data pivot analysis.

[0092] At least one data analysis and mining method is executed on the data model to obtain a mining result.

[0093] In this embodiment, the data analysis and mining methods described can specifically include statistical analysis, trend analysis, and association analysis. Statistical analysis: Descriptive statistical methods are used to calculate basic statistical indicators such as the mean, median, and standard deviation of the data to understand the overall distribution of the data. Trend analysis: Time series analysis is used to identify changing trends in production and quality data and predict future quality conditions. Association analysis: Association rule mining methods are used to identify the correlations between different production parameters and quality results, discovering potential factors affecting quality.

[0094] The mining results are presented.

[0095] In this implementation, an interactive dashboard and automated reporting system can be configured on the platform's application layer devices to display key quality indicators, trend charts, and correlation diagrams, helping managers quickly understand quality status. Multi-dimensional perspective analysis: Leveraging data cube technology, managers can freely select dimensions for data perspective analysis by dragging and dropping, allowing them to deeply explore the underlying causes and patterns in the data.

[0096] In some implementations, decision support models, such as quality warning models and production optimization models, can be constructed based on the analysis results to provide managers with data-driven decision-making recommendations. Incorporating smart contract technology can automate parts of the decision-making process. For example, if a quality issue is discovered in a production batch, a recall process can be automatically triggered or the responsible personnel can be notified.

[0097] In some embodiments, the data analysis results can be fed back to the production and quality management departments to guide them in improving production processes and quality control measures.

[0098] According to an embodiment of the present invention, a blockchain-based equipment manufacturing quality traceability device is provided. Figure 6 , the device may include: The first receiving module is used to receive equipment manufacturing data.

[0099] The encryption module is used to perform encryption processing on the equipment manufacturing data based on a preset encryption method to obtain encrypted equipment manufacturing data.

[0100] A first uploading module is used to upload the encrypted equipment manufacturing data to a distributed file system to store the encrypted equipment manufacturing data, and trigger the distributed file system to generate identity identification data of the encrypted equipment manufacturing data; wherein the identity identification data is data representing the address of the encrypted equipment manufacturing data in the distributed file system.

[0101] The second receiving module is configured to receive identity data sent by the distributed file system.

[0102] A generating module is used to generate transaction data based at least on the identity identification data.

[0103] The second uploading module is used to upload the transaction data to the blockchain.

[0104] According to an embodiment of the present invention, an electronic device is provided. Figure 7 The electronic device in this embodiment may include one or more of the following components: a processor, a network interface, a memory, a non-volatile memory, and one or more applications, wherein the one or more applications may be stored in the non-volatile memory and configured to be executed by one or more processors, and the one or more programs are configured to execute the method described in the aforementioned method embodiment.

[0105] According to an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a computer, the computer executes the method described in any one of the above embodiments.

[0106] According to an embodiment of the present invention, a computer program product comprising instructions is further provided. When the instructions are executed by a computer, the computer is enabled to perform the method in any one of the above embodiments.

[0107] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0108] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0109] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0110] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0111] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A blockchain-based equipment manufacturing quality traceability method, characterized in that: The method comprises: Receive equipment manufacturing data; Performing encryption processing on the equipment manufacturing data based on a preset encryption method to obtain encrypted equipment manufacturing data; Uploading the encrypted equipment manufacturing data to a distributed file system to store the encrypted equipment manufacturing data, and triggering the distributed file system to generate identity data of the encrypted equipment manufacturing data; wherein the identity data is data indicating an address of the encrypted equipment manufacturing data in the distributed file system; Receiving identity data sent by the distributed file system; generating transaction data based at least on the identification data; The transaction data is uploaded to the blockchain.

2. The method according to claim 1, characterized in that The step of receiving equipment manufacturing data comprises: Sending a request for acquiring equipment manufacturing data to a target smart device at a preset time frequency; wherein the smart device is a device for collecting equipment manufacturing data; Receive equipment manufacturing data returned in response to the request from the target smart device.

3. The method according to claim 1, characterized in that The step of performing encryption processing on the equipment manufacturing data based on a preset encryption method includes: Call the preset elliptic curve encryption algorithm to generate a public and private key pair; The equipment manufacturing data is encrypted based on the public key in the public-private key pair.

4. The method according to claim 1, characterized in that: The identity data is obtained by the following method: The distributed file system performs hash processing on the encrypted equipment manufacturing data based on a preset hash algorithm to obtain a first hash value; The distributed file system performs a first encoding process on the first hash value to obtain a second hash value; wherein the second hash value has at least hash algorithm identification information and length information relative to the first hash value; The distributed file system performs a second encoding process on the second Hash value to obtain a third Hash value; wherein the third Hash value is easier to input than the second Hash value, and the third Hash value is the identity identification data.

5. The method according to claim 1, characterized in that The step of generating transaction data based at least on the identity data comprises: Extract the gateway number, the first timestamp, the second timestamp, the data type of the encrypted equipment manufacturing data, and the administrator signature; wherein the first timestamp is the timestamp for recording the generation of transaction data, and the second timestamp is the timestamp for receiving equipment manufacturing data; The gateway number, the first timestamp, the second timestamp, the data type of the encrypted equipment manufacturing data, the administrator signature and the transaction data are assembled into transaction data.

6. The method according to claim 5, characterized in that The step of uploading the transaction data to the blockchain includes: Upload the transaction data to the blockchain through a preset data upload contract; When the event notification of transaction data being uploaded to the blockchain is monitored, the transaction data is obtained from the blockchain through a preset data acquisition contract; At least the gateway number in the transaction data is verified to prevent the transaction data from being modified during the upload process.

7. The method according to claim 1, characterized in that The method further comprises: Obtaining transaction data from the blockchain; Based on the transaction data, extracting corresponding encrypted equipment manufacturing data from the distributed file system; Performing decryption processing on the encrypted equipment manufacturing data to obtain decrypted equipment manufacturing data; Performing data modeling of at least one dimension on the decrypted equipment manufacturing data to obtain a data model; Executing at least one data analysis and mining method on the data model to obtain a mining result; The mining results are presented.

8. A blockchain-based equipment manufacturing quality traceability device, characterized in that: The device comprises: A first receiving module, which is used to receive equipment manufacturing data; An encryption module, which is used to perform encryption processing on the equipment manufacturing data based on a preset encryption method to obtain encrypted equipment manufacturing data; a first uploading module, which is used to upload the encrypted equipment manufacturing data to a distributed file system to store the encrypted equipment manufacturing data, and trigger the distributed file system to generate identity data of the encrypted equipment manufacturing data; wherein the identity data is data indicating an address of the encrypted equipment manufacturing data in the distributed file system; A second receiving module, which is used to receive identity data sent by the distributed file system; A generating module, configured to generate transaction data based at least on the identity identification data; The second uploading module is used to upload the transaction data to the blockchain.

9. An electronic device, characterized in that: include: a memory, and one or more processors communicatively coupled to the memory; The memory stores instructions that can be executed by the one or more processors. The instructions are executed by the one or more processors to enable the one or more processors to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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