Block chain and digital twinning fused production whole process credible tracing method

Abstract

The invention discloses a block chain and digital twinborn integrated production whole process credible tracing method, and belongs to the technical field of intelligent manufacturing and digital tracing. The system comprises a digital twin construction module, a block chain evidence storage module, a tracing verification module and a data acquisition module. The method comprises the following steps: creating a digital twinborn body for each product instance, and mapping material, process, equipment and quality data of the whole manufacturing process in real time; recording the twinborn key state hash value to a block chain in real time through an intelligent contract; credible tracing verification is provided based on block chain evidence storage and digital twin data; industrial Internet of Things equipment is used for collecting manufacturing data in real time to drive twin updating. According to the method, millisecond-level slice tracing in the manufacturing process is realized, the deep description capability of digital twinning and credible guarantee of the block chain are fused, the problems of insufficient data depth and low credibility of a traditional tracing system are solved, and judicial-level evidence support is provided for quality disputes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent manufacturing and digital traceability, and particularly relates to a production whole-process credible traceability method fusing blockchain and digital twin. BACKGROUND

[0002] With the in-depth development of intelligent manufacturing and Industry 4.0, manufacturing enterprises are facing the urgent demand for credible traceability of the whole life cycle of products. However, the existing traceability system has the following outstanding problems: first, the traditional traceability system is mostly limited to the recording of logistics information and key nodes, and cannot provide deep traceability covering the whole manufacturing process. When complex quality problems occur, it is difficult to accurately locate the responsible link and the root cause.

[0003] Secondly, the existing traceability data are mostly stored in centralized systems, which have the risk of being tampered with, and are difficult to serve as effective legal evidence in quality disputes. The authenticity and integrity of the data cannot be effectively guaranteed.

[0004] In addition, digital twin technology is widely used in manufacturing industry and can create a virtual mirror image of the product, but the twin data itself also has credibility problems. How to ensure the authenticity and tamper resistance of digital twin data is a technical problem to be solved.

[0005] Although there are some attempts to use blockchain for product traceability, most of the schemes only record result data and lack deep description of the manufacturing process, which cannot meet the demand of modern manufacturing industry for fine traceability of the whole process.

[0006] The information disclosed in this BACKGROUND section is only intended to increase an understanding of the general context in which the application can be practiced. It will be apparent that the information in this BACKGROUND section can not be prior art to the claimed application, and it should not be construed as suggesting that any of the approaches described in this BACKGROUND section are known prior art in the United States or any other jurisdiction. SUMMARY

[0007] The technical problem to be solved by the present application is to overcome the above technical defects, and to provide a production whole-process credible traceability method fusing blockchain and digital twin, to solve the problem of insufficient data depth and low credibility in the existing traceability system, and to build a credible traceability system for the whole manufacturing process of products by fusing blockchain and digital twin technology, to realize full-dimensional, tamper-proof and verifiable accurate traceability from raw materials to finished products.

[0008] In order to solve the above problems, the technical scheme of the present application is a production whole-process credible traceability system combined with blockchain and digital twin, comprising: a digital twin construction module, which is used to create a corresponding digital twin for each product instance, and to map the full-dimensional data of the product in the manufacturing process in real time; a blockchain storage module, which records the key state change hash value of the digital twin in real time to the blockchain through a smart contract; a traceability verification module, which provides complete and credible traceability verification services based on blockchain storage and digital twin data; and a data acquisition module, which acquires manufacturing site data in real time through industrial Internet of Things devices, and drives the digital twin to update.

[0009] Preferably, the digital twin construction module comprises: a geometric modeling unit, which constructs a three-dimensional geometric model of the product, supports parameterized design and dynamic update; a data association unit, which associates material batches, process parameters, equipment states, and environmental data with the twin; a state management unit, which manages the state evolution of the twin from raw materials to finished products throughout the manufacturing process; and a version control unit, which records the state versions of the twin at different time points.

[0010] Preferably, the blockchain storage module comprises: a hash calculation unit, which calculates the hash value of the twin state data, supports incremental hash and full hash; a smart contract unit, which implements storage logic, verification logic, and permission control logic; a timestamp service unit, which provides a trusted timestamp for each storage record; and a storage strategy unit, which configures storage frequency, data type, and storage strategy.

[0011] Preferably, the traceability verification module comprises: a query processing unit, which supports multi-dimensional queries based on product identification, time range, and process type; a verification execution unit, which compares the consistency of the blockchain storage hash and the twin data hash; a report generation unit, which generates a traceability report containing a timestamp, a verification result, and a digital signature; and a visualization display unit, which provides visual reproduction and data analysis of the manufacturing process.

[0012] Preferably, the data acquisition module comprises: a sensor network unit, which deploys temperature, vibration, pressure, and visual sensors; a device interface unit, which interfaces with PLC, CNC, and robot control systems; a data preprocessing unit, which performs data cleaning, format conversion, and quality checking; and a real-time transmission unit, which ensures low-latency and high-reliability data transmission.

[0013] The present application also discloses a production whole-process credible traceability method combined with blockchain and digital twin, which is applied to the above-mentioned system and comprises the following steps: Step one, create a digital twin for each product instance, and establish real-time mapping between the physical entity and the virtual model; Step two, real-time collection of manufacturing process data through industrial internet of things, driving digital twin state update; Step three, calculating twin state hash value at key manufacturing nodes, and storing the same in block chain through smart contract; Step four, providing trusted full-process traceability verification service based on block chain storage and digital twin data.

[0014] As preferred, the digital twin creation comprises assigning a unique digital identity to the product, establishing twin life cycle management, constructing a multi-dimensional model comprising geometric features, physical properties and process parameters, establishing an association with manufacturing resources, process flow and quality standards, and realizing real-time data synchronization and state consistency maintenance with the physical entity.

[0015] As preferred, the data collection and processing comprises configuring a sensor network covering key processes and quality control points, collecting material information, process parameters, equipment status and environmental data in real time, performing data quality evaluation, identifying and repairing abnormal data, and establishing data blood relationship to record data sources and transformation process.

[0016] As preferred, the block chain storage comprises defining storage strategy, including storage time, data range and storage format, calculating twin state hash to ensure data integrity, realizing storage logic through smart contract to record timestamp and transaction hash, and establishing storage index to support efficient query and verification.

[0017] As preferred, the traceability verification comprises receiving traceability request, verifying query authority and range, obtaining storage records from block chain to verify data integrity, obtaining detailed process data from digital twin system, performing consistency verification to generate a trusted traceability report, and supporting quality root cause analysis and process optimization suggestions.

[0018] Compared with the prior art, the present application has the following advantages: 1. The present application realizes "millisecond-level slicing" traceability of the manufacturing process, which can accurately reproduce the complete state at any manufacturing moment.

[0019] 2. The present application ensures the non-tamperability of traceability data through block chain technology, providing judicial-level evidence for quality disputes.

[0020] 3. The present application combines the deep description capability of digital twin and the trusted guarantee of block chain to realize truly meaningful full-process trusted traceability.

[0021] 4. The present application supports rapid root cause analysis, significantly improving the efficiency and accuracy of quality problem investigation. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1is a schematic diagram of the architecture of the system of the present application; Figure 2 is a flowchart of digital twin data notarization of the system of the present application; Figure 3 is a flowchart of whole-process traceability verification of the system of the present application; Figure 4 is a flowchart of quality root cause analysis of the system of the present application DETAILED DESCRIPTION

[0023] In order to make the content of the present application easier to be clearly understood, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application.

[0024] A production whole-process credible traceability system fusing blockchain and digital twin includes: 1. A digital twin construction module, which is used to create a corresponding digital twin for each product instance, and to map the full-dimension data of the product in the manufacturing process in real time; The digital twin construction module includes: A geometric modeling unit, which constructs a three-dimensional geometric model of the product, supports parameterized design and dynamic update; A data association unit, which associates the material batch, process parameters, equipment state, and environmental data with the twin; A state management unit, which manages the state evolution of the twin from raw materials to finished products in the whole manufacturing process; A version control unit, which records the state versions of the twin at different time points.

[0025] 2. A blockchain notarization module, which records the key state change hash value of the digital twin to the blockchain in real time through a smart contract; The blockchain notarization module includes: A hash calculation unit, which calculates the hash value of the state data of the twin, supports incremental hash and full hash; A smart contract unit, which implements notarization logic, verification logic, and permission control logic; A timestamp service unit, which provides a trusted timestamp for each notarization record; A notarization strategy unit, which configures the notarization frequency, data type, and storage strategy.

[0026] 3. A traceability verification module, which provides complete and credible traceability verification services based on blockchain notarization and digital twin data; The traceability verification module includes: A query processing unit, which supports multi-dimensional queries based on product identification, time range, and process type; A verification execution unit compares the blockchain storage hash with the twin data hash for consistency; A report generation unit generates a traceability report containing a timestamp, verification result, and digital signature; A visual display unit provides a visual reproduction and data analysis of the manufacturing process.

[0027] 4. A data acquisition module that acquires real-time manufacturing site data through industrial Internet of Things devices to drive digital twin updates.

[0028] The data acquisition module includes: A sensor network unit that deploys temperature, vibration, pressure, and visual sensors; A device interface unit that interfaces with PLCs, CNCs, and robot control systems; A data preprocessing unit that performs data cleaning, format conversion, and quality checking; A real-time transmission unit that ensures low-latency, high-reliability data transmission.

[0029] A production full-process trusted traceability method that combines blockchain and digital twin, applied to the above system, including the following steps: Step 1: Create a digital twin for each product instance to establish real-time mapping between physical entities and virtual models; Step 2: Collect real-time manufacturing process data through industrial Internet of Things to drive digital twin state updates; Step 3: Calculate the twin state hash value at key manufacturing nodes and store it in the blockchain through a smart contract; Step 4: Based on blockchain storage and digital twin data, provide trusted full-process traceability verification services.

[0030] Digital twin creation includes assigning a unique digital identifier to the product, establishing twin lifecycle management, building a multi-dimensional model containing geometric features, physical properties, and process parameters, establishing associations with manufacturing resources, process flow, and quality standards, and achieving real-time data synchronization and state consistency maintenance with physical entities.

[0031] Data acquisition and processing include: configuring a sensor network to cover key processes and quality control points; collecting real-time material information, process parameters, equipment status, and environmental data; performing data quality assessment, identifying and repairing abnormal data; establishing data blood relationship, recording data source and transformation process.

[0032] Blockchain storage includes: defining storage strategies, including storage timing, data range, and storage format; calculating twin state hash to ensure data integrity; implementing storage logic through a smart contract to record timestamps and transaction hashes; establishing a storage index to support efficient querying and verification.

[0033] Traceability verification includes: receiving traceability requests, verifying query permissions and scope; obtaining records from the blockchain, verifying data integrity; obtaining detailed process data from the digital twin system; performing consistency verification to generate a trusted traceability report; supporting quality root cause analysis and process optimization recommendations. Embodiments

[0034] I. System architecture implementation Reference Figure 1 The implementation of the system includes the following core components: 1. Physical manufacturing layer Deploy high-precision sensors and Internet of Things devices; Configure data collection gateways and edge computing nodes; Establish a workshop-level industrial network.

[0035] 2. Digital twin layer Build a product digital twin model library; Deploy twin data management and computing engines; Real-time synchronization of physical entities and virtual twins.

[0036] 3. Blockchain evidence layer Establish a manufacturing traceability alliance chain; Deploy evidence and verification smart contracts; Configure a distributed storage system.

[0037] 4. Application service layer Provide traceability query and verification services; Support quality analysis and root cause positioning; Generate a trusted traceability report.

[0038] II. Digital twin data evidence process Reference Figure 2 The specific implementation of digital twin data evidence: S201: Create a unique digital twin for each product instance; S202: Real-time collection of materials, processes, equipment, environment, etc. during manufacturing; S203: Update the digital twin state and record complete process data; S204: Calculate the twin state hash value at key process nodes; S205: Store the hash value in the blockchain through the smart contract; S206: Verify the success of the evidence and update the evidence status.

[0039] III. Whole-process traceability verification implementation, Reference Figure 3, the specific implementation process of traceability verification: 1. Traceability request processing Receive the product traceability request of the user; Verify user permissions and query scope; Locate the target product and related data.

[0040] 2. Data verification execution Obtain the record hash from the blockchain; Obtain detailed process data from the digital twin system; Verify data integrity and consistency.

[0041] 3. Traceability report generation Reconstruct the entire product manufacturing process; Generate a visual traceability report; Provide proof of data authenticity verification.

[0042] Four, quality root cause analysis implementation Reference Figure 4 , the specific implementation of quality root cause analysis: 1. Problem positioning Identify quality defect phenomena; Locate the manufacturing link where the defect occurs; Determine the time range and data type for analysis.

[0043] 2. In-depth analysis Compare the twin data of normal products and defective products; Analyze process parameter differences and equipment state changes; Identify key influencing factors and root causes.

[0044] 3. Improvement suggestions Based on the analysis results, propose process optimization suggestions; Generate a quality improvement report; Update quality control standards.

[0045] Five, typical application scenarios Scenario One: Quality Traceability of Precision Parts Record the entire manufacturing process data of each part; Accurately trace the specific process where defects occur; Analyze the impact of process parameters on quality.

[0046] Scenario Two: Food and Pharmaceutical Safety Traceability Track raw material batches and processing processes; Monitor environmental parameters and process conditions; Ensure compliance and safety.

[0047] Scenario 3: Major equipment manufacturing traceability Record the assembly process of complex products; Track the source of parts and assembly quality; Support quality control throughout the life cycle.

[0048] Through the above implementation, the application can provide manufacturing enterprises with deep and reliable full-process traceability capability, significantly improving the quality control level and problem solving efficiency.

[0049] The above describes the application and its implementation, which is not limited, and the drawings shown are only one of the embodiments of the application. In general, if a person skilled in the art is inspired, without departing from the purpose of the application, without creative design, similar structural methods and examples to the technical solution should belong to the protection scope of the application.

Claims

1. A trusted traceability system for the entire production process integrating blockchain and digital twins, characterized in that, include: The system includes a digital twin construction module, which creates a corresponding digital twin for each product instance and maps the full-dimensional data of the product during the manufacturing process in real time; a blockchain evidence storage module, which records the hash values ​​of key state changes of the digital twin to the blockchain in real time through smart contracts; and a traceability verification module, which provides complete and reliable traceability verification services based on blockchain evidence storage and digital twin data. The data acquisition module collects manufacturing site data in real time through industrial IoT devices, driving the digital twin to update.

2. The trusted traceability system for the entire production process integrating blockchain and digital twins as described in claim 1, characterized in that: The digital twin construction module includes: a geometric modeling unit, which constructs a three-dimensional geometric model of the product and supports parametric design and dynamic updates; a data association unit, which associates material batches, process parameters, equipment status, environmental data and the twin; a status management unit, which manages the status evolution of the twin from raw materials to finished products throughout the entire manufacturing process; and a version control unit, which records the status versions of the twin at different points in time.

3. The trusted traceability system for the entire production process integrating blockchain and digital twins as described in claim 1, characterized in that: The blockchain evidence storage module includes: a hash calculation unit, which calculates the hash value of the twin state data and supports incremental hashing and full hashing; a smart contract unit, which implements evidence storage logic, verification logic, and access control logic; a timestamp service unit, which provides a trusted timestamp for each evidence storage record; and an evidence storage strategy unit, which configures the evidence storage frequency, data type, and storage strategy.

4. A trusted traceability system for the entire production process integrating blockchain and digital twins as described in claim 1, characterized in that: The traceability verification module includes: a query processing unit that supports multi-dimensional queries based on product identifier, time range, and process type; a verification execution unit that compares the consistency between the blockchain evidence hash and the twin data hash; a report generation unit that generates a traceability report containing timestamps, verification results, and digital signatures; and a visualization display unit that provides a visual reproduction and data analysis of the manufacturing process.

5. A trusted traceability system for the entire production process integrating blockchain and digital twins as described in claim 1, characterized in that: The data acquisition module includes: a sensor network unit, which deploys temperature, vibration, pressure, and vision sensors; an equipment interface unit, which interfaces with PLC, CNC, and robot control systems; a data preprocessing unit, which performs data cleaning, format conversion, and quality verification; and a real-time transmission unit, which ensures low-latency and highly reliable data transmission.

6. A trusted traceability method for the entire production process integrating blockchain and digital twins, applied to the system described in claims 1-5, characterized in that: Includes the following steps: Step 1: Create a digital twin for each product instance to establish a real-time mapping between the physical entity and the virtual model; Step 2: Collect data from the entire manufacturing process in real time through the Industrial Internet of Things (IIoT) to drive the status update of the digital twin; Step 3: Calculate the twin state hash value at key manufacturing nodes and store it on the blockchain via a smart contract; Step 4: Based on blockchain-based evidence storage and digital twin data, provide a reliable end-to-end traceability and verification service.

7. The method for trusted traceability of the entire production process integrating blockchain and digital twins as described in claim 6, characterized in that: The creation of the digital twin includes assigning a unique digital identifier to the product and establishing a lifecycle management system for the twin; constructing a multi-dimensional model that includes geometric features, physical attributes, and process parameters; establishing associations with manufacturing resources, process flows, and quality standards; and achieving real-time data synchronization and status consistency maintenance with the physical entity.

8. A trusted traceability method for the entire production process integrating blockchain and digital twins as described in claim 6, characterized in that: The data acquisition and processing includes: configuring a sensor network to cover key processes and quality control points; collecting material information, process parameters, equipment status, and environmental data in real time; conducting data quality assessments, identifying and repairing abnormal data; and establishing data lineage, recording data sources and transformation processes.

9. A trusted traceability method for the entire production process integrating blockchain and digital twins as described in claim 6, characterized in that: The blockchain-based evidence storage includes: defining an evidence storage strategy, including the timing, data scope, and storage format; calculating the twin state hash to ensure data integrity; implementing the evidence storage logic through smart contracts, recording timestamps and transaction hashes; and establishing an evidence storage index to support efficient querying and verification.

10. A trusted traceability method for the entire production process integrating blockchain and digital twins as described in claim 6, characterized in that: The traceability verification includes: receiving traceability requests and verifying query permissions and scope; obtaining evidence records from the blockchain and verifying data integrity; obtaining detailed process data from the digital twin system; performing consistency verification and generating a reliable traceability report; and supporting quality root cause analysis and process optimization suggestions.

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