Product manufacturing process full-link traceability method and device and storage medium

Abstract

The embodiment of the invention provides a product manufacturing process full-link traceability method and device and a storage medium, and belongs to the technical field of traceability. The method comprises the steps that raw material information uploaded by a raw material supply end is received, a server sends the raw material information and product information to a product manufacturing end, after the product manufacturing end confirms that the raw material information and the product information are correct, product processing and manufacturing are conducted, product processing link information and processing image encryption data are uploaded to the server, and the server sends the product processing link information and the processing image encryption data to the server. And receiving a product detection result fed back by the product detection end according to the product information. And the server stores the raw material information, the product processing link information, the processing image encryption data and the product detection result into the preset block chain, so that all data of the complete product manufacturing process are stored in the preset block chain, and when the product detection is not passed and the source is traced on the preset block chain according to the product detection result, the data of the product manufacturing process are stored in the preset block chain. According to the method, a specific error link can be accurately positioned, the supervision is improved, the image data in the processing link is encrypted, and the safety is improved.

Description

Technical Field

[0001] This application relates to the field of traceability technology, and in particular to a full-link traceability method, device and storage medium for the product manufacturing process. Background Art

[0002] Traceability technology is mainly applied to trace the whole process of product manufacturing to find out the reasons when problems occur in products. For example, in the traceability process of jewelry products, since the manufacturing process of jewelry products includes links such as raw material procurement, model making, casting and forging, shaping and carving, polishing and grinding, and quality inspection, each of these links requires strict supervision and management. Due to the high value and scarcity of jewelry products, the manufacturing process needs to ensure the safety and traceability of products in the whole link to ensure the authenticity and quality of products. At the same time, due to the confidentiality of design and processing technology, while supervising the manufacturing process, it is also necessary to ensure the protection of the confidential information of manufacturers. Therefore, it is of great significance to improve the traceability and supervisability of all stages of the full link of the jewelry product manufacturing process while protecting the confidential information of manufacturers.

[0003] In related technologies, using blockchain technology, the information related to the jewelry product manufacturing process is stored on the blockchain, and the product is labeled, and the traceability of the jewelry product manufacturing process is realized by scanning and reading the label information. However, due to the transparency of the blockchain, currently mainly the summary data of the manufacturing process is stored on the blockchain. Only storing the summary data on the blockchain cannot accurately locate the specific error link when defects occur. Since the manufacturing process cannot be completely recorded, the inspection agency can only inspect the finished products and cannot control the manufacturing process. Therefore, how to improve the security and supervisability of the full-link information of the product manufacturing process has become an urgent technical problem to be solved. Summary of the Invention

[0004] The main purpose of the embodiments of this application is to propose a full-link traceability method, device and storage medium for the product manufacturing process, aiming to improve the security and supervisability of the full-link information of the product manufacturing process.

[0005] To achieve the above object, a first aspect of the embodiments of this application proposes a full-link traceability method for the product manufacturing process, which is applied to a server, and the method includes:

[0006] Obtain the product information of the target product;

[0007] Select a target processing team item from the preset candidate processing team items according to the product information; wherein, the target processing team item includes: a raw material supply end, a product manufacturing end, and a product inspection end;

[0008] Send the product information to the raw material supply end and receive the raw material information uploaded by the raw material supply end;

[0009] Send the raw material information and the product information to the product manufacturing end, and receive the product processing link information and the encrypted processing image data fed back by the product manufacturing end;

[0010] Send the product information to the product inspection end, and receive the product inspection result fed back by the product inspection end according to the product information;

[0011] Store the raw material information, the product processing link information, the encrypted processing image data and the product inspection result into a preset blockchain;

[0012] When the product inspection result indicates non - passing, conduct traceability on the preset blockchain according to the product inspection result.

[0013] In some embodiments, before screening out the target processing team item from the preset candidate processing team items according to the product information, the method further includes: constructing the candidate processing team items, specifically including:

[0014] Obtain the identity registration information of each candidate participating end; wherein, the identity registration information includes key information and role information;

[0015] Authenticate the identity of the candidate participating end according to the key information to obtain the identity authentication result of the candidate participating end;

[0016] If the identity authentication result indicates passing authentication, determine the candidate participating end as the target participating end;

[0017] Set the role name of the target participating end according to the role information;

[0018] Combine the target participating ends into the candidate processing team items according to the preset product processing participating end information and the role name.

[0019] In some embodiments, the step of sending the raw material information and the product information to the product manufacturing end, and receiving the product processing link information and the encrypted processing image data fed back by the product manufacturing end includes:

[0020] Send the raw material information and the product information to the product manufacturing end, so that the product manufacturing end constructs a product manufacturing strategy according to the product information and the raw material information; wherein, the product manufacturing strategy includes product processing link information;

[0021] Receive the product processing link information and the encrypted data of the processing image fed back by the product manufacturing end; wherein, the encrypted data of the processing image is obtained by the product manufacturing end encrypting the processing link image data collected in the product processing link.

[0022] To achieve the above object, a second aspect of the embodiments of the present application proposes a full-link traceability method for the product manufacturing process, which is applied to the product manufacturing end. The method includes:

[0023] Receive the product information and raw material information of the target product sent by the server; wherein, the raw material information is the material information fed back by the raw material supply end received by the server according to the product information.

[0024] The product manufacturing end constructs a product manufacturing strategy according to the product information and the raw material information; wherein, the product manufacturing strategy includes product processing link information.

[0025] Collect processing link image data according to the product processing link.

[0026] Perform encryption processing on the processing link image data to obtain encrypted data of the processing image.

[0027] Send the product processing link information and the encrypted data of the processing image to the server, so that the server receives the product detection result fed back by the product detection end according to the product information, and stores the raw material information, the product processing link information, the encrypted data of the processing image, and the product detection result in a preset blockchain. When the product detection result indicates that the detection fails, perform problem traceability on the preset blockchain according to the product detection result.

[0028] In some embodiments, the performing encryption processing on the processing link image data to obtain encrypted data of the processing image includes:

[0029] Perform preprocessing on the processing link image data according to a preset preprocessing operation to obtain image processing data; wherein, the preprocessing operation includes: mean filtering processing, threshold segmentation processing, feature enhancement processing, image segmentation processing, and feature screening processing.

[0030] Obtain a digital image, and use the pixel value sequence of the digital image as the encryption key.

[0031] Perform an exclusive OR operation at the pixel level between the image processing data and the encryption key to obtain the encrypted data of the processing image.

[0032] In some embodiments, if the preprocessing operation is the feature enhancement process, the preprocessing of the image data of the processing link according to the preset preprocessing operation to obtain the image processing data includes:

[0033] Screening the image data of the processing link according to a preset screening operation to obtain screened image data; wherein, the preset screening operation includes: rectangularity screening, hole area screening, and hole number screening;

[0034] Performing convexity screening on the screened image data to obtain the image processing data.

[0035] In some embodiments, the encrypted data of the processed image is the image ciphertext. After performing the exclusive OR operation at the pixel level on the image processing data and the encryption key to obtain the encrypted data of the processed image, the method further includes:

[0036] Using the pixel value sequence of the digital image as the decryption key;

[0037] Performing the exclusive OR operation at the pixel level on the image ciphertext and the decryption key to obtain the pixel value sequence of the image;

[0038] Constructing the image data of the processing link according to the pixel value sequence of the image.

[0039] To achieve the above object, a third aspect of the embodiments of the present application proposes a full-link traceability device for the product manufacturing process, which is applied to a server. The device includes:

[0040] An acquisition module, configured to acquire the product information of the target product;

[0041] A screening module, configured to screen out a target processing team item from the preset candidate processing team items according to the product information; wherein, the target processing team item includes: a raw material supply end, a product manufacturing end, and a product detection end;

[0042] A first sending module, configured to send the product information to the raw material supply end and receive the raw material information uploaded by the raw material supply end;

[0043] A second sending module, configured to send the raw material information and the product information to the product manufacturing end and receive the product processing link information and the encrypted data of the processed image fed back by the product manufacturing end;

[0044] A third sending module, configured to send the product information to the product detection end and receive the product detection result fed back by the product detection end according to the product information;

[0045] A storage module, configured to store the raw material information, the product processing link information, the encrypted data of the processing image, and the product detection result into a preset blockchain;

[0046] A traceability module, configured to perform problem traceability on the preset blockchain according to the product detection result when the product detection result indicates a failed detection.

[0047] To achieve the above object, a fourth aspect of the embodiments of the present application proposes a full-link traceability device for the product manufacturing process, which is applied to the product manufacturing end. The device includes:

[0048] A receiving module, configured to receive the product information and the raw material information of the target product sent by the server; wherein, the raw material information is the material information fed back by the raw material supply end received by the server according to the product information;

[0049] A construction strategy module, configured to construct a product manufacturing strategy by the product manufacturing end according to the product information and the raw material information; wherein, the product manufacturing strategy includes product processing link information;

[0050] A collection module, configured to collect image data of the processing link according to the product processing link;

[0051] An encryption module, configured to encrypt the image data of the processing link to obtain encrypted data of the processing image;

[0052] A sending module, configured to send the product processing link information and the encrypted data of the processing image to the server, so that the server receives the product detection result fed back by the product detection end according to the product information, and stores the raw material information, the product processing link information, the encrypted data of the processing image, and the product detection result into a preset blockchain, and when the product detection result indicates a failed detection, perform problem traceability on the preset blockchain according to the product detection result.

[0053] To achieve the above object, a fifth aspect of the embodiments of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the methods described in the first aspect and the second aspect above are implemented.

[0054] The full-link traceability method, device and storage medium for product manufacturing process proposed in this application receive the raw material information uploaded by the raw material supply end, and the server then sends the raw material information and product information to the product manufacturing end. After the product manufacturing end confirms that it is correct, the product is processed and manufactured, and the product processing link information and encrypted processing image data are uploaded to the server, and the product detection result feedback by the product detection end according to the product information is received. After each link is completed, the next link confirms the previous link, reducing the defect rate in the product manufacturing process. The server stores the raw material information, product processing link information, encrypted processing image data and product detection results in a preset blockchain, so that the preset blockchain stores all the data of the complete product manufacturing process. When the product detection fails, when tracing back on the preset blockchain according to the product detection result, the specific error link can be accurately located, improving the supervision ability, and because the image data of the processing link is encrypted, the security is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a flowchart of the full-link traceability method for product manufacturing process provided by an embodiment of this application;

[0056] Figure 2 is a flowchart of the full-link traceability method for product manufacturing process provided by another embodiment of this application;

[0057] Figure 3 is Figure 1 a flowchart of step S104 in

[0058] Figure 4 is a flowchart of the full-link traceability method for product manufacturing process provided by a third embodiment of this application;

[0059] Figure 5 is Figure 4 a flowchart of step S404 in

[0060] Figure 6 is a flowchart of the full-link traceability method for product manufacturing process provided by a fourth embodiment of this application;

[0061] Figure 7 is a full-link schematic diagram of the product processing and manufacturing process provided by an embodiment of this application;

[0062] Figure 8 is a schematic structural diagram of the full-link traceability device for product manufacturing process provided by an embodiment of this application;

[0063] Figure 9 is a schematic structural diagram of the full-link traceability device for product manufacturing process provided by another embodiment of this application;

[0064] Figure 10It is a schematic diagram of the hardware structure of the electronic device provided by the embodiments of the present application. Detailed implementation manners

[0065] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0066] It should be noted that although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different module division in the device or a different order in the flowchart. Terms such as "first" and "second" in the description, claims and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application.

[0068] First, several nouns involved in the present application are analyzed:

[0069] Blockchain: It is a chain-like data structure formed by combining data blocks in sequence according to the time sequence, and is a new distributed infrastructure and computing method that uses smart contracts composed of automated script codes to program and operate data.

[0070] Smart contract: It is a program code that automates business logic and embeds it in the blockchain. When the conditions of the contract are met, the smart contract can automatically execute the program code.

[0071] Consortium blockchain: It is a cluster composed of multiple private blockchains, a blockchain jointly managed by multiple institutions, and each institution manages one or more nodes. Each node of the consortium blockchain usually has a corresponding entity organization, and can only join and exit the network after authorization. Each institution organization forms an alliance of interested parties to jointly maintain the healthy operation of the blockchain.

[0072] Traceability technology is mainly applied to trace the whole process of product manufacturing to find out the reasons when problems occur in the product. Blockchain traceability uses blockchain technology to make the source, production process, quality management and other links of the product transparent, facilitating users to query the process and the generated information records. However, due to the transparency of the blockchain, in order to ensure the protection of the confidential information of manufacturers, only the summary data of the manufacturing process is currently uploaded to the blockchain, and the manufacturing process cannot be completely recorded, resulting in the inability to accurately locate the specific error link when the product is defective.

[0073] Based on this, the embodiments of this application provide a full-link traceability method, device and storage medium for product manufacturing processes, aiming to enable product manufacturers to carry out product processing after determining that the product information and the raw material information provided by the raw material suppliers are accurate through traceability queries, and upload the information of the product processing links and the encrypted data of the processing images to the blockchain. So that the preset blockchain stores all the data of the complete product manufacturing process. When the product fails the inspection and traceability is performed on the preset blockchain according to the product inspection results, the specific error link can be accurately located, improving the supervision ability, and the image data of the processing link is encrypted, improving the security.

[0074] The embodiments of this application can obtain and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0075] Artificial intelligence basic technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation / interaction systems, and mechatronics. Artificial intelligence software technologies mainly include several major directions such as computer vision technology, robotics, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0076] The full-link traceability method for product manufacturing process provided by the embodiments of the present application can be applied to terminals, can also be applied to the server side, or can be software running on the terminal or the server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, can also be configured as a server cluster or a distributed system composed of multiple physical servers, or can also be configured as a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the full-link traceability method for product manufacturing process, etc., but is not limited to the above forms.

[0077] The present application can be used in many general or specific computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet-type devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in a distributed computing environment, where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0078] The full-link traceability method, device, and storage medium for product manufacturing process provided by the embodiments of the present application will be specifically described through the following embodiments. First, the full-link traceability method for product manufacturing process in the embodiments of the present application will be described.

[0079] Please refer to Figure 1 , Figure 1 which is an optional flowchart of the full-link traceability method for product manufacturing process provided by the embodiments of the present application. The full-link traceability method for product manufacturing process is applied to the server. Figure 1 The method in

[0080] Step S101, obtain the product information of the target product;

[0081] Step S102, screen out the target processing team item from the preset candidate processing team items according to the product information; wherein, the target processing team item includes: raw material supply end, product manufacturing end, and product inspection end;

[0082] Step S103: Send the product information to the raw material supply side and receive the raw material information uploaded by the raw material supply side;

[0083] Step S104: Send the raw material information and the product information to the product manufacturing side and receive the product processing link information and the encrypted processing image data fed back by the product manufacturing side;

[0084] Step S105: Send the product information to the product inspection side and receive the product inspection result fed back by the product inspection side according to the product information;

[0085] Step S106: Store the raw material information, the product processing link information, the encrypted processing image data and the product inspection result into a preset blockchain;

[0086] Step S107: When the product inspection result indicates non - passing, conduct traceability on the preset blockchain according to the product inspection result.

[0087] In steps S101 to S102 of some embodiments, since different products require different raw materials, manufacturing processes and inspection processes, the corresponding raw material suppliers, product manufacturers and product inspection providers for different products may be different, and it is necessary to screen out the target processing team items from the preset candidate processing team items according to the product information. For example, the product information carries the information of the required target processing team items, and the preset candidate processing team items include raw material supply side A, raw material supply side B, product manufacturing side A, product manufacturing side B, product manufacturing side C, product inspection side A and product inspection side B. The product information of target product A carries the information of raw material supply side A, product manufacturing side B and product inspection side B, then select raw material supply side A, product manufacturing side B and product inspection side B from the preset candidate processing team items.

[0088] In an example, it is also possible to establish the correspondence between the product information and the information of the target processing team items. After obtaining the product information of the target product, obtain the information of the target processing team items corresponding to the product information from the correspondence, and screen out the target processing team items from the preset candidate processing team items according to the information of the target processing team items.

[0089] In steps S103 to S105 of some embodiments, after screening out the target processing team items, send the product information to the raw material supply side, so that the corresponding raw material supplier of the raw material supply side purchases the corresponding raw materials according to the product information and uploads the raw material information to the server, so that the server stores the raw material information on the preset blockchain. Among them, the raw material information includes raw material procurement information and raw material quality inspection information.

[0090] The server then sends the raw material information and product information to the product manufacturing end. After the corresponding product manufacturer at the product manufacturing end confirms the raw material information and product information without errors, product processing and manufacturing are carried out. By further confirming the raw material information and product information by the product manufacturer, the processing of problematic raw materials is prevented, and the defect rate during product manufacturing is reduced. During the product processing and manufacturing process, the product processing link information and the image data of the processing link are retained, and then the image data of the processing link is encrypted to obtain encrypted processing image data. The product manufacturing end uploads the product processing link information and the encrypted processing image data to the server, so that the server saves the product processing link information and the encrypted processing image data on a preset blockchain. By encrypting the image data of the processing link, the confidential information of the product manufacturer is protected.

[0091] In one example, when more than one product manufacturer is required to complete the product manufacturing, the server sends the raw material information and product information to the first product manufacturer. After the first product manufacturer confirms the raw material information and product information without errors, product processing and manufacturing are carried out to obtain semi-finished products. The product processing link information and the encrypted processing image data of the semi-finished product are uploaded to the server, and the server then sends the product processing link information and the encrypted processing image data of the semi-finished product to the second product manufacturer for confirmation. After confirmation without errors, the semi-finished product is further processed and manufactured, and the corresponding product processing link information and the encrypted processing image data are sent to the server, and so on until the product manufacturing is completed. The server then sends the product information to the product inspection end, and the product inspection end inspects the product according to the product information to obtain a product inspection result, and the product inspection end uploads the product inspection result to the server.

[0092] In steps S106 to S107 of some embodiments, the server can record the raw material information, the product processing link information, the encrypted processing image data, and the product inspection result on the preset blockchain respectively when receiving them. When all the product inspection results pass, it indicates that the target product meets the requirements. If the inspection fails, it indicates that there are quality problems with the target product, and traceability is carried out on the preset blockchain according to the product inspection result. For example, when the product is a jewelry item, the traceability solution based on blockchain and image encryption technology can trace the jewelry item, improving the security and regulatory nature of the full-link information of jewelry item manufacturing.

[0093] Steps S101 to S107 shown in the embodiments of the present application quickly screen out a target processing team item from a preset candidate processing team item according to product information. The target processing team item includes a raw material supply end, a product manufacturing end, and a product inspection end. The product information is sent to the raw material supply end, so that the corresponding raw material supplier at the raw material supply end purchases raw materials according to the product information and uploads the raw material information to the server. The server then sends the raw material information and the product information to the product manufacturing end. After the corresponding product manufacturer at the product manufacturing end confirms the raw material information and the product information without error, product processing and manufacturing are carried out. After the product processing is completed, the product processing link information and the encrypted data of the processing image are uploaded to the server, and then the product information is sent to the product inspection end and the product inspection result feedback by the product inspection end according to the product information is received. After each link is completed, the next link confirms the previous link. Only after the confirmation is correct can it proceed downward, reducing the defect rate in the product manufacturing process. The server stores the raw material information, the product processing link information, the encrypted data of the processing image, and the product inspection result in a preset blockchain, so that the preset blockchain stores all the data of the complete product manufacturing process. When the product inspection fails and traceability is carried out on the preset blockchain according to the product inspection result, the specific error link can be accurately located, improving the regulatory ability. And because the image data of the processing link is encrypted, the security is improved.

[0094] In an example, after storing the raw material information, the product processing link information, the encrypted data of the processing image, and the product inspection result in the preset blockchain, in combination with the traceability requirement, a smart contract is formulated. The process of formulating the smart contract is as follows:

[0095] Define fields: In the smart contract, fields related to the traceability requirement are defined. Each field corresponds to a specific piece of information. These fields include key data in the product manufacturing process, such as the raw material delivery time, the raw material material, the supplier name, the manufacturing process name, the manufacturing process image, the product delivery time, the raw material deliverer, the product deliverer, and the quality inspector.

[0096] Privacy rule formulation: Since some information may involve privacy, such as the personal information of the deliverer and the quality inspector, corresponding desensitization rules need to be formulated. It is stipulated in the smart contract the desensitization means adopted for these sensitive information, such as using the hash algorithm to encrypt and store sensitive information such as names and ID numbers.

[0097] Smart contract writing: According to the above requirements, the defined fields and privacy rules, the team writes the code of the smart contract. The contract code will include the logic of data storage, update, query, etc.

[0098] Smart contract deployment: The completed smart contract is deployed to a preset blockchain and becomes part of the chain. Once deployed, the rules of the smart contract will be automatically executed to ensure the reliability and privacy security of the traceability information.

[0099] Testing and optimization: After the smart contract is deployed, sufficient testing is carried out to ensure its stability and reliability in actual applications. Necessary optimizations and adjustments are made according to the test results to improve the performance and adaptability of the smart contract.

[0100] Please refer to Figure 2 , in some embodiments, before step S102, the full-chain traceability method for the product manufacturing process may further include: constructing a candidate processing team item, specifically including but not limited to steps S201 to S205:

[0101] Step S201, obtain the identity registration information of each candidate participating end; wherein, the identity registration information includes key information and role information;

[0102] Step S202, authenticate the candidate participating end according to the key information to obtain the identity authentication result of the candidate participating end;

[0103] Step S203, if the identity authentication result indicates that the authentication is passed, determine the candidate participating end as the target participating end;

[0104] Step S204, set the role name of the target participating end according to the role information;

[0105] Step S205, combine the target participating ends into a candidate processing team item according to the preset product processing participating end information and role name.

[0106] In steps S201 to S203 of some embodiments, the candidate participating ends include at least one raw material supply end, at least one product manufacturing end, and at least one product inspection end. When the identity registration information of the candidate participating end exists in the identity registration table of the preset blockchain, the identity authentication of the candidate participating end is passed, and the candidate participating end that passes the authentication is determined as the target participating end.

[0107] In step S204 of some embodiments, each target participating end has a specific role. For example, an administrator, a validator, and a participant. The participant can be a raw material supplier and a product manufacturer, the validator can be a product inspector, and the administrator can assign corresponding permissions and responsibilities to the validator and the participant. After obtaining the role corresponding to the target participating end according to the role information, set the corresponding role name for the corresponding target participating end. When both target participating ends are participants, the corresponding role names can be participant 1 and participant 2 respectively, so that each role name uniquely corresponds to a target participant.

[0108] In step S205 of some embodiments, the preset product processing participation end information is the target participation end information required for the product processing and manufacturing process. For example, the target participation ends required for the processing and manufacturing process of product A are target participation ends A-C. All target participation ends form a candidate processing team item, and each target participation end stores the product type and role name being manufactured. For example, if the product types manufactured by target participation end A are product A and product B, then when screening the target processing team item according to the product information of product A, the target processing team item includes target participation end A, or the product information of product A carries the role name of target participation end A, and target participation end A is screened out from the candidate processing team item according to the role name of target participation end A.

[0109] In steps S201 to S205 illustrated in this embodiment, by creating a candidate processing team item, when product processing and manufacturing are to be carried out, the target processing team item can be quickly selected according to the product information, and then the product information is sent to the target participation ends in the target processing team item, thereby promoting the product manufacturing process.

[0110] Please refer to Figure 3 , in some embodiments, step S104 may include but is not limited to steps S301 to S302:

[0111] Step S301, sending the raw material information and product information to the product manufacturing end, so that the product manufacturing end constructs a product manufacturing strategy according to the product information and raw material information; wherein, the product manufacturing strategy includes product processing link information;

[0112] Step S302, receiving the product processing link information and processed image encryption data fed back by the product manufacturing end; wherein, the processed image encryption data is obtained by the product manufacturing end encrypting the processed link image data collected according to the product processing link.

[0113] In steps S301 and S302 of some embodiments, different product information and raw material information correspond to different product manufacturing strategies. Therefore, the product manufacturer corresponding to the product manufacturing end constructs a product manufacturing strategy according to the received product information and raw material information, processes and manufactures the product according to the product manufacturing strategy, and then collects the product processing link information and processed link image data in the product processing and manufacturing process. The processed link image data is encrypted to obtain the processed image encryption data, and the server receives the product processing link information and processed image encryption data fed back by the product manufacturing end.

[0114] Please refer to Figure 4 , Figure 4 is the flowchart of the full-link traceability method for the product manufacturing process provided by the third embodiment of the present application. The full-link traceability method for the product manufacturing process is applied to the product manufacturing end.Figure 4 The method in

[0115] Step S401 may include but is not limited to steps S401 to S405. Receive the product information and raw material information of the target product sent by the server; wherein, the raw material information is the material information fed back by the raw material supply end received by the server according to the product information;

[0116] Step S402, the product manufacturing end constructs a product manufacturing strategy according to the product information and raw material information; wherein, the product manufacturing strategy includes product processing link information;

[0117] Step S403, collect processing link image data according to the product processing link;

[0118] Step S404, encrypt the processing link image data to obtain encrypted processing image data;

[0119] Step S405, send the product processing link information and the encrypted processing image data to the server, so that the server receives the product detection result fed back by the product detection end according to the product information, and stores the raw material information, the product processing link information, the encrypted processing image data and the product detection result into a preset blockchain. When the product detection result indicates that the detection fails, trace the problem on the preset blockchain according to the product detection result.

[0120] In steps S401 to S405 shown in this embodiment, after the product manufacturing end receives the product information and raw material information of the target product sent by the server, it constructs a product manufacturing strategy according to the product information and raw material information. Process and manufacture the product according to the product manufacturing strategy, retain the product processing link information, collect the processing link image data in the product processing link, and encrypt the processing link image data to obtain encrypted processing image data. The product manufacturing end sends the product processing link information and the encrypted processing image data to the server, so that the server receives the product detection result fed back by the product detection end according to the product information, and stores the raw material information, the product processing link information, the encrypted processing image data and the product detection result into a preset blockchain. When the product detection result indicates that the detection fails, trace the problem on the preset blockchain according to the product detection result. By saving all the data in the product manufacturing process to the preset blockchain, when the product detection fails and the problem is traced on the preset blockchain according to the product detection result, the specific error link can be accurately located, improving the supervision ability, and since the processing link image data is encrypted, the security is improved.

[0121] It should be noted that when the product is a jewelry item, since the shape and color characteristics of jewelry items are particularly important compared to other products, that is, when tracing the origin, it is desired to obtain the shape and color characteristics of the jewelry item, but at the same time, the shape and color characteristics of the jewelry item need to be kept confidential. Therefore, it is necessary to encrypt the image data of the processing link of the jewelry item, and then store the encrypted data of the processing image in a preset blockchain. When tracing the origin of the jewelry item, decrypt the encrypted data of the processing image to obtain the image data of the processing link, and trace the origin based on the image data of the processing link and the relevant information of the jewelry item, which improves the security and supervision of the full-link information of jewelry manufacturing.

[0122] Please refer to Figure 5 , in some embodiments, step S404 includes but is not limited to steps S501 to S503:

[0123] Step S501, preprocess the image data of the processing link according to a preset preprocessing operation to obtain image processing data; wherein, the preprocessing operation includes: mean filtering processing, threshold segmentation processing, feature enhancement processing, image segmentation processing, and feature screening processing;

[0124] Step S502, obtain a digital image, and use the pixel value sequence of the digital image as the encryption key;

[0125] Step S503, perform an exclusive OR operation at the pixel level between the image processing data and the encryption key to obtain the encrypted data of the processing image.

[0126] In step S501 of some embodiments, by preprocessing the image data of the processing link, the interfering objects in the image data of the processing link are removed, and only the product in the image is retained. For example, when the product is jewelry, the processing link image contains the jewelry and the tools required for processing the jewelry. Then, the tools in the processing link image need to be removed so that the processing link image only contains the jewelry image.

[0127] Specifically, the interference caused by image noise can be removed through mean filtering processing. For the special pixel value distribution of the jewelry image, threshold segmentation processing is adopted, and all the connected domains in the image after threshold segmentation are calculated, and the non-connected regions are segmented into separate regions to obtain the jewelry image features.

[0128] Enhance the features of the extracted jewelry images: First, perform rectangularity screening, hole area screening, and hole number screening to filter out features with low rectangularity and remove redundant holes in the features. Then, perform convexity screening to eliminate redundant circular features and crop the ROI region containing the jewelry image. Here, ROI (region of interest) refers to the region of interest. In machine vision and image processing, the region to be processed outlined in the form of a square, circle, ellipse, irregular polygon, etc. from the processed image is called the region of interest.

[0129] Rectangularity is a parameter reflecting the similarity degree of an object to a rectangle. Since the rectangularity of jewelry images is relatively high, when the rectangularity of an object is less than the threshold, it indicates that the object is not jewelry. Therefore, screening by rectangularity can effectively filter out the influence of some interferences. The calculation formula for rectangularity is shown in Formula 1 below:

[0130]

[0131] where S obj is the area of the object, and S NEO is the area of the minimum bounding rectangle of the object. Re reflects the degree of filling of an object. For a rectangular object, Re reaches the maximum value of 1. For slender and curved objects, the value of Re becomes smaller. The range of the Re value is 0 to 1.

[0132] Screening by convexity can remove redundant circular features. The calculation formula for convexity is shown in Formula 2 below:

[0133]

[0134] where R o is the area of the region, and R T is the area of the minimum convex hull enclosing the region area.

[0135] For the gray-scale edge features of jewelry images, use the Canny operator to perform image segmentation processing and crop the jewelry images containing edges in the ROI region.

[0136] Perform feature screening on the extracted jewelry contours, screen out the contours with a larger circumradius in the features and connect all the contours with close endpoints, convert the closed contours into regions, and finally output the extracted jewelry features. According to the finally output jewelry features, obtain the image processing data.

[0137] In steps S502 to S503 of some embodiments, select a custom digital image, use the pixel value sequence of the digital image as the encryption key, and perform an exclusive OR operation at the pixel level between the image processing data and the encryption key to obtain the encrypted data of the processed image.

[0138] In steps S501 to S503 illustrated in this embodiment, by preprocessing the image data of the processing link, other items in the image except the product are screened out to obtain image processing data, preventing unnecessary information from being saved and reducing the use of storage space. Then, the image processing data is encrypted to obtain encrypted processing image data, and the encrypted processing image data is uploaded to improve the security of the full-link information.

[0139] Please refer to Figure 6 , in some embodiments, the encrypted processing image data is image ciphertext. After step S503, the full-link traceability method for the product manufacturing process may include but is not limited to steps S601 to S603:

[0140] Step S601, using the pixel value sequence of the digital image as the decryption key;

[0141] Step S602, performing an exclusive OR operation at the pixel level on the image ciphertext and the decryption key to obtain the pixel value sequence of the image;

[0142] Step S603, constructing the image data of the processing link according to the pixel value sequence of the image.

[0143] In steps S601 to S603 illustrated in this embodiment, when tracing problems on the preset blockchain according to the product detection results, it is necessary to view the encrypted processing image data. At this time, the encrypted processing image data needs to be decrypted to be viewed. Similarly, the pixel value sequence of a custom digital image is used as the decryption key, and an exclusive OR operation at the pixel level is performed on the image ciphertext and the decryption key to obtain the pixel value sequence of the image, and the image data of the processing link is constructed according to the pixel value sequence of the image to complete the decryption.

[0144] In an example, Figure 7 is the full-link schematic diagram of the product processing and manufacturing process of this application embodiment. As Figure 7 shown, the preset blockchain is a consortium blockchain. A smart contract is formulated and deployed to the consortium blockchain. The raw material supplier uploads the raw material information to the consortium blockchain. Manufacturer A queries the raw material information and product information. After confirming that it is correct, product processing and manufacturing are carried out, and the product processing link information and encrypted processing image data are uploaded to the consortium blockchain. It is passed to Manufacturer B for manufacturing. Manufacturer B queries the information uploaded by Manufacturer A. After confirming that it is correct, product processing and manufacturing are carried out, and the product processing link information and encrypted processing image data are uploaded to the consortium blockchain. And so on. After all manufacturers complete product manufacturing, the product is detected by the inspection agency and the detection results are uploaded to the consortium blockchain. When the detection results are unqualified, tracing is performed on the consortium blockchain based on the detection results.

[0145] Please refer to Figure 8, an embodiment of the present application further provides a full-link traceability device for the product manufacturing process, which is applied to a server and can implement the above full-link traceability method for the product manufacturing process. The device includes:

[0146] An acquisition module 801, configured to acquire product information of a target product;

[0147] A screening module 802, configured to screen out a target processing team item from a preset candidate processing team items according to the product information; wherein, the target processing team item includes: a raw material supply end, a product manufacturing end, and a product detection end;

[0148] A first sending module 803, configured to send the product information to the raw material supply end and receive the raw material information uploaded by the raw material supply end;

[0149] A second sending module 804, configured to send the raw material information and the product information to the product manufacturing end and receive the product processing link information and the encrypted processing image data fed back by the product manufacturing end;

[0150] A third sending module 805, configured to send the product information to the product detection end and receive the product detection result fed back by the product detection end according to the product information;

[0151] A saving module 806, configured to store the raw material information, the product processing link information, the encrypted processing image data, and the product detection result into a preset blockchain;

[0152] A traceability module 807, configured to perform problem traceability on the preset blockchain according to the product detection result when the product detection result indicates non-passing.

[0153] The specific implementation manner of the full-link traceability device for the product manufacturing process is basically the same as the specific embodiment of the full-link traceability method for the product manufacturing process executed by the above server, and will not be elaborated herein.

[0154] Please refer to Figure 9 , another embodiment of the present application further provides a full-link traceability device for the product manufacturing process, which is applied to the product manufacturing end and can implement the above full-link traceability method for the product manufacturing process. The device includes:

[0155] A receiving module 901, configured to receive the product information and the raw material information of the target product sent by the server; wherein, the raw material information is the material information fed back by the raw material supply end according to the product information received by the server;

[0156] A construction strategy module 902, configured to construct a product manufacturing strategy by the product manufacturing end according to the product information and the raw material information; wherein, the product manufacturing strategy includes product processing link information;

[0157] The acquisition module 903 is used to acquire image data of the processing link according to the product processing link;

[0158] The encryption module 904 is used to encrypt the image data of the processing link to obtain encrypted processing image data;

[0159] The sending module 905 is used to send the product processing link information and the encrypted processing image data to the server, so that the server receives the product detection result feedback by the product detection end according to the product information, and stores the raw material information, the product processing link information, the encrypted processing image data and the product detection result into a preset blockchain. When the product detection result indicates that the detection fails, problem tracing is performed on the preset blockchain according to the product detection result.

[0160] The specific implementation manner of the full-link traceability device for the product manufacturing process is basically the same as the specific embodiment of the full-link traceability method for the product manufacturing process executed by the above product manufacturing end, and will not be elaborated here.

[0161] The embodiment of the present application further provides an electronic device. The electronic device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the full-link traceability method for the product manufacturing process is implemented. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0162] Please refer to Figure 10 , Figure 10 which schematically shows the hardware structure of an electronic device in another embodiment. The electronic device includes:

[0163] The processor 301 can be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided by the embodiments of the present application;

[0164] The memory 302 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The memory 302 can store an operating system and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 302, and the processor 301 is used to call and execute the full-link traceability method for the product manufacturing process executed by the server and the full-link traceability method for the product manufacturing process executed by the product manufacturing end in the embodiments of the present application;

[0165] An input / output interface 303 for implementing information input and output;

[0166] A communication interface 304 for implementing communication interaction between this device and other devices, which can achieve communication through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.);

[0167] A bus 305 for transmitting information between various components of the device (such as a processor 301, a memory 302, an input / output interface 303, and a communication interface 304);

[0168] Among them, the processor 301, the memory 302, the input / output interface 303, and the communication interface 304 are communicatively connected to each other inside the device through the bus 305.

[0169] The embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the full-link traceability method of the product manufacturing process executed by the above server and the full-link traceability method of the product manufacturing process executed by the product manufacturing end.

[0170] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0171] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0172] Those skilled in the art can understand that the technical solutions shown in the figure do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than those shown in the figure, or combine certain steps, or different steps.

[0173] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0174] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and their appropriate combinations.

[0175] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of this application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0176] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or a similar expression means any combination of these items, including any combination of single items (ones) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0177] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0178] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0179] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0180] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store programs.

[0181] The preferred embodiments of the embodiments of the present application have been described above with reference to the drawings, but this does not limit the scope of rights of the embodiments of the present application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of rights of the embodiments of the present application.

Claims

1. A full-link traceability method for the product manufacturing process, characterized in that, applied to a server, the method includes: Obtain the product information of the target product; Screen out the target processing team item from the preset candidate processing team items according to the product information; wherein, the target processing team item includes: a raw material supply end, a product manufacturing end, and a product inspection end; Send the product information to the raw material supply end and receive the raw material information uploaded by the raw material supply end; Send the raw material information and the product information to the product manufacturing end and receive the product processing link information and the encrypted processing image data fed back by the product manufacturing end; Send the product information to the product inspection end and receive the product inspection result fed back by the product inspection end according to the product information; Store the raw material information, the product processing link information, the encrypted processing image data, and the product inspection result in a preset blockchain; When the product inspection result indicates that the inspection fails, trace back on the preset blockchain according to the product inspection result.

2. The method according to claim 1, characterized in that, Before screening out the target processing team item from the preset candidate processing team items according to the product information, the method further includes: constructing the candidate processing team item, specifically including: Obtain the identity registration information of each candidate participating end; wherein, the identity registration information includes key information and role information; Authenticate the identity of the candidate participating end according to the key information to obtain the identity authentication result of the candidate participating end; If the identity authentication result indicates that the authentication is passed, determine that the candidate participating end is the target participating end; Set the role name of the target participating end according to the role information; Combine the target participating ends into the candidate processing team item according to the preset product processing participating end information and the role name.

3. The method according to claim 1, characterized in that, The sending the raw material information and the product information to the product manufacturing end and receiving the product processing link information and the encrypted processing image data fed back by the product manufacturing end includes: Send the raw material information and the product information to the product manufacturing end so that the product manufacturing end constructs a product manufacturing strategy according to the product information and the raw material information; wherein, the product manufacturing strategy includes product processing link information; Receive the product processing link information and the encrypted processing image data fed back by the product manufacturing end; wherein, the encrypted processing image data is obtained by the product manufacturing end encrypting the processing link image data collected according to the product processing link.

4. A full-link traceability method for the product manufacturing process, characterized in that, applied to the product manufacturing end, the method includes: Receive the product information and the raw material information of the target product sent by the server; wherein, the raw material information is the material information fed back by the raw material supply end received by the server according to the product information; The product manufacturing end constructs a product manufacturing strategy based on the product information and the raw material information; wherein, the product manufacturing strategy includes product processing link information; Collect processing link image data according to the product processing link; Perform encryption processing on the processing link image data to obtain encrypted processing image data; Send the product processing link information and the encrypted processing image data to the server, so that the server receives the product detection result feedback by the product detection end according to the product information, and stores the raw material information, the product processing link information, the encrypted processing image data and the product detection result in a preset blockchain. When the product detection result indicates a failed detection, perform problem tracing on the preset blockchain according to the product detection result.

5. The method according to claim 4, wherein, The performing encryption processing on the processing link image data to obtain encrypted processing image data includes: Performing preprocessing on the processing link image data according to a preset preprocessing operation to obtain image processing data; wherein, the preprocessing operation includes: mean filtering processing, threshold segmentation processing, feature enhancement processing, image segmentation processing and feature screening processing; Obtain a digital image, and use the pixel value sequence of the digital image as an encryption key; Perform an exclusive OR operation at the pixel level between the image processing data and the encryption key to obtain the encrypted processing image data.

6. The method according to claim 5, wherein, If the preprocessing operation is the feature enhancement processing, the performing preprocessing on the processing link image data according to a preset preprocessing operation to obtain image processing data includes: Performing screening on the processing link image data according to a preset screening operation to obtain screened image data; wherein, the preset screening operation includes: rectangularity screening, hole area screening and hole number screening; Performing convexity screening on the screened image data to obtain image processing data.

7. The method according to claim 5, wherein, The encrypted processing image data is an image ciphertext. After performing the exclusive OR operation at the pixel level between the image processing data and the encryption key to obtain the encrypted processing image data, the method further includes: Use the pixel value sequence of the digital image as a decryption key; Perform an exclusive OR operation at the pixel level between the image ciphertext and the decryption key to obtain an image pixel value sequence; Construct processing link image data according to the image pixel value sequence.

8. A full-link traceability device for the product manufacturing process, wherein, Applied to a server, the device includes: An acquisition module, configured to acquire product information of a target product; A screening module, configured to screen out a target processing team item from preset candidate processing team items according to the product information; wherein, the target processing team item includes: a raw material supply end, a product manufacturing end and a product detection end; A first sending module, configured to send the product information to the raw material supply end and receive the raw material information uploaded by the raw material supply end; A second sending module, configured to send the raw material information and the product information to the product manufacturing end, and receive the product processing link information and the encrypted processing image data fed back by the product manufacturing end; A third sending module, configured to send the product information to the product detection end, and receive the product detection result fed back by the product detection end according to the product information; A storage module, configured to store the raw material information, the product processing link information, the encrypted processing image data, and the product detection result into a preset blockchain; A traceability module, configured to perform problem traceability on the preset blockchain according to the product detection result when the product detection result indicates a failed detection; 9. A full-link traceability device for the product manufacturing process, characterized in that, applied to the product manufacturing end, the device includes: A receiving module, configured to receive the product information and the raw material information of the target product sent by the server; wherein, the raw material information is the material information fed back by the raw material supply end received by the server according to the product information; A construction strategy module, configured to construct a product manufacturing strategy according to the product information and the raw material information at the product manufacturing end; wherein, the product manufacturing strategy includes product processing link information; An acquisition module, configured to acquire processing link image data according to the product processing link; An encryption module, configured to perform encryption processing on the processing link image data to obtain encrypted processing image data; A sending module, configured to send the product processing link information and the encrypted processing image data to the server, so that the server receives the product detection result fed back by the product detection end according to the product information, and stores the raw material information, the product processing link information, the encrypted processing image data, and the product detection result into a preset blockchain, and perform problem traceability on the preset blockchain according to the product detection result when the product detection result indicates a failed detection.

10. A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, it implements the full-link traceability method for the product manufacturing process according to any one of claims 1 to 3 and the full-link traceability method for the product manufacturing process according to any one of claims 4 to 7.

Images