A process technology data package packaging method for supply chain rapid collaboration

Abstract

The present application relates to a kind of process technical data package packaging methods for supply chain rapid cooperation, comprising the following steps: using pre-defined structured analysis template, outside cooperation outsourcing task sheet information is parsed into the standardized task description model containing multiple core data group elements;Based on the standardized task description model established, core data group elements are associated with microservice, and by the parallel operation of multiple search microservices, the required process file data is retrieved, matched and captured from the relevant information system, to form process technical data set;According to the obtained process file data set, based on the retrieval path and data version label backtracking, consistency judgment and data automatic synchronization are realized;Using the process technical data set after synchronization, corresponding encryption algorithm is selected according to the different format characteristics of file, and the original format is retained, to form the data package embedded with security packaging index file, to complete the packaging and encryption process.

Description

Technical Field

[0001] This invention relates to the field of process technology data encapsulation and processing for rapid mission collaboration in the upstream and downstream of the aerospace supply chain, specifically a process technology data package encapsulation method for rapid supply chain collaboration. Background Technology

[0002] Under the socialized collaborative model of equipment manufacturing, a trend of cross-entity, cross-regional, and cross-temporal collaborative development is emerging, involving "OEMs / final assembly plants + suppliers." OEMs / final assembly plants, based on information platforms, structurally package data packages of process technologies required for outsourced components or processes, including digital models, drawings, process documents, quality specifications, and contracts, according to specific organizational structures and standards. Supply chain collaborating companies download and parse the required data packages, import them into their own business systems, and use this data to organize production, provide progress feedback, and complete delivery.

[0003] However, traditional semi-automatic packaging methods based primarily on manual labor have the following challenges and difficulties: 1) Manually traversing, matching, searching, and mounting data is inefficient and prone to errors; 2) Dynamic updates of data files after version changes are difficult to synchronize; 3) Lightweight data packaging methods are prone to causing the loss of product topology, making it impossible for supply chain partners to use professional software for direct reading and further operations; 4) Traditional full-file encryption modes have long latency and consume a lot of resources, making them unsuitable for industrial scenarios. At the same time, the lack of cross-system verification mechanisms means that suppliers cannot prove that the received data has not been tampered with, relying on manual verification.

[0004] Therefore, given the multiple constraints faced by industrial chain and supply chain collaboration, such as high data exchange frequency, high data fidelity requirements, strong consistency, and a moderate balance of security control, existing research cannot comprehensively and completely provide an integrated strategy for high-fidelity and rapid encapsulation and control of process technology data. It still cannot effectively solve the current problems of efficient data preparation, conversion, and exchange in the field of equipment research and development and production supply chain collaboration, and the collaborative capability is difficult to improve rapidly. Summary of the Invention

[0005] The technical problem solved by this invention is to provide a process technology data package encapsulation method for rapid collaboration in the supply chain, which addresses the above-mentioned shortcomings of the existing technology. This method solves the bottlenecks of traditional semi-automatic methods based on manual labor, such as low data matching efficiency, difficulty in synchronizing data version updates, easy information distortion due to lightweight encapsulation methods, and low level of secure and reliable transmission.

[0006] This invention is achieved through the following technical solution: a method for encapsulating process technology data packets for rapid collaboration in the supply chain, comprising:

[0007] Using a predefined structured parsing template, outsourcing task information is parsed into a standardized task description model containing multiple core data elements;

[0008] Based on the established standardized task description model, core data elements are associated with microservices. Through the parallel operation of multiple retrieval microservices, the required process document data is retrieved, matched, and captured from relevant information systems to form a process technology dataset.

[0009] Based on the obtained process document dataset, consistency judgment and automatic data synchronization are achieved by backtracking through the retrieval path and data version tags.

[0010] Using the synchronized process technology dataset, encryption algorithms are selected according to the different format characteristics of the files, while preserving the original format, forming a data packet with a nested secure encapsulation index file, thus completing the encapsulation and encryption process.

[0011] The predefined structured parsing template includes predefined structured parsing templates for five core data elements: product drawing number, stage attributes, material handover requirements, process requirements, and technical agreements.

[0012] The outsourcing task information is parsed into a standardized task description model containing multiple core data elements, including:

[0013] Obtain the outsourcing task list and determine the entity value of each data element based on the predefined structured parsing template;

[0014] Each data element and its entity value is structured to generate a standardized task description model, including product drawing number, stage attributes, material handover requirements, process requirements, and technical agreements.

[0015] The established standardized task description model associates core data elements with microservices. Through the parallel operation of multiple retrieval microservices, the required process document data is retrieved, matched, and extracted from relevant information systems to form a process technology dataset, including:

[0016] Based on the established task description model, core data elements are associated with microservices to obtain multiple process technology data retrieval microservices, and the corresponding data retrieval and crawling microservices are given targeting.

[0017] By running multiple process technology data retrieval microservices in parallel, process technology data corresponding to outsourced tasks are obtained from the databases of relevant information systems, forming a process technology dataset, and the process technology dataset is assigned the current retrieval path and data version label.

[0018] The aforementioned multi-process technology data retrieval microservices, and the corresponding data retrieval and crawling microservices are given targeted features, including:

[0019] The product data retrieval microservice is targeted at product image number and stage attribute.

[0020] The process document retrieval microservice targets product drawing number, stage attribute, and process requirements.

[0021] The technical document retrieval microservice is targeted at product drawing numbers and material handover requirements.

[0022] The technical protocol retrieval microservice is targeted by product drawing number and technical protocol.

[0023] The process technology dataset includes three-dimensional process models, process documents, technical documents, and technical agreements.

[0024] The process of backtracking based on the obtained process document dataset, using the retrieval path and data version tags, to achieve consistency judgment and automatic data synchronization includes:

[0025] Based on the file retrieval path in the process technology dataset, backtrack and compare whether the data version in the existing dataset is consistent with the data version in each current information system; if inconsistent, start the data synchronization process and update the corresponding version tags in the dataset; if consistent, pass the entire dataset to the data transformation and packaging stage.

[0026] The process involves utilizing the synchronized process technology dataset to select encryption algorithms based on different file format characteristics, while preserving the original format, to form a data packet containing a nested secure encapsulation index file, thus completing the encapsulation and encryption process. This includes:

[0027] Perform multi-source data feature labeling and metadata extraction on the transmitted dataset;

[0028] Build a format preservation container to maintain the original format and extension of various files in the dataset, and embed container-level digital fingerprints;

[0029] Adaptively select encryption algorithms based on the different format characteristics of 3D models, document fields, and process diagrams to generate hierarchical fingerprint trees;

[0030] Create a process technology data package for supply chain collaboration, including 3D models, process specifications, technical documents and technical agreements, configure the corresponding security index list for this data package, and complete the entire encapsulation and encryption process.

[0031] The method of adaptively selecting encryption algorithms based on different format features of 3D models, document fields, and process diagrams to generate a hierarchical fingerprint tree includes:

[0032] For the 3D model, a binary positioning offset algorithm is used to perform AES-CTR stream encryption on key feature regions to generate the first hierarchical fingerprint tree;

[0033] A format-preserving encryption algorithm is used for Excel files, key characters are replaced with encrypted strings, and a second-level fingerprint tree is generated.

[0034] The Word terms employ an attribute-based encryption algorithm, binding digital fingerprints to supplier roles to generate a third-layer fingerprint tree;

[0035] A dynamic invisible watermarking strategy is adopted for sensitive areas in PDF process specifications to achieve local sensitive encryption of native process technology documents and generate a fourth-layer fingerprint tree.

[0036] The beneficial effects of this invention are:

[0037] (1) This invention utilizes a generalized outsourcing task parsing model based on predefined templates to parse outsourcing task information into a standardized task description model containing 5 core data elements, thereby eliminating the personalized differences in outsourcing information of aerospace equipment manufacturing enterprises.

[0038] (2) This invention introduces a fast and parallel heterogeneous process technology data retrieval method, which associates data components in the description model with microservices. Through the parallel operation of the corresponding retrieval microservices, it solves the problem of low efficiency caused by traditional manual serial traversal matching and data mounting.

[0039] (3) This invention achieves accurate consistency verification of process technology data packages. Based on the "path + version" backtracking mechanism, it solves the problem of difficulty in synchronizing dynamic updates after data file version changes, and ensures the accuracy of data based on a single source.

[0040] (4) By using the “cross-format processing + dynamic policy encryption” method, a balance between the direct operability of data and data security is achieved. A high-fidelity encapsulation structure that separates metadata from the original file but is related is constructed, and the encryption policy based on format features is adaptive, which effectively improves the efficiency, operability and secure and reliable transmission level of data encapsulation. Attached Figure Description

[0041] Figure 1 This is a flowchart of the four core steps in the process technology data package encapsulation process;

[0042] Figure 2 This is a schematic diagram of the process technology data packet encapsulation and dynamic encryption technology. Detailed Implementation

[0043] like Figure 1As shown, the present invention provides a method for encapsulating process technology data packets for rapid collaboration in the supply chain, comprising the following steps:

[0044] Table 1. Endframe Outsourcing Task Information

[0045]

[0046] S1: Based on the information of the outsourcing tasks in Table 1, establish a parsing template, and use the parsing template to perform parsing, forming a standardized task description model M containing 5 core data elements. 前端框 This includes product drawing number DK1020-01, stage attribute as research and development, material handover requirement as titanium alloy TA15, self-supplied by the institute, process requirements, and technical agreement.

[0047] S2: Task description model M formed based on step S1 前端框 By associating core data components with microservices, and through the parallel operation of product data retrieval microservices, process document retrieval microservices, technical document retrieval microservices, and technical protocol retrieval microservices, the required process document data is quickly retrieved, matched, and extracted from relevant information systems. The data is then assigned the current retrieval path and data version tags, forming a process technology dataset D. 前端框 This includes a 3D process model (file path: path 1, data version: a.2); a process document (process procedure for this operation, file path: path 2, data version: a.3); a technical document (file path: path 3, data version: b.1); and a technical agreement (file path: path 4, data version: b.2).

[0048] S3: Based on the retrieval path and data version tag backtracking, consistency judgment and automatic data synchronization are achieved. If updates are found in the product 3D model and technical protocol, they are automatically updated to the process technology dataset D. 前端框 This includes a 3D process model (file path: path 1, data version updated to a.3); a process document (process procedure for this operation, file path: path 2, data version a.3); a technical document (path: path 3, data version b.1); and a technical agreement (file path: path 4, data version updated to b.3).

[0049] S4: Adaptively selects encryption algorithms based on different file format characteristics, while preserving the original format, forming a data packet with a nested secure encapsulation index file, completing the encapsulation and encryption process, as detailed below:

[0050] S41: Perform multi-source data feature labeling and metadata extraction on the dataset passed from step S3;

[0051] S42: Construct a format preservation container (NSP) to maintain the original format and extension of various files in the dataset, such as 3D model .prt, process specification .pdf, technical document .xls, and technical agreement .doc;

[0052] S43: Adaptively selects encryption algorithms based on different format characteristics of 3D models, document fields, and process drawings, such as... Figure 2 As shown, the details are as follows:

[0053] For the 3D model, a binary positioning offset algorithm is used to perform AES-CTR stream encryption on key feature regions to generate the first hierarchical fingerprint tree;

[0054] For Excel files, the Format Preservation Encryption (FPE) algorithm is used, key characters are replaced with encrypted strings, and a second-level fingerprint tree is generated;

[0055] The Attribute-Based Encryption (ABE) algorithm is used for Word terms, and digital fingerprints are bound to supplier roles to generate a third-level fingerprint tree;

[0056] A dynamic invisible watermarking strategy is adopted for sensitive areas in PDF process specifications to achieve local sensitive encryption of native process technology documents and generate a fourth-layer fingerprint tree.

[0057] S44: Aggregate the various hierarchical fingerprint trees to form a digital fingerprint and security index list for the entire data packet, ultimately forming a process technology data packet (DP) for supply chain collaboration. 前端框 .

[0058] Supply chain collaboration enables the rapid and secure use of process technology collaboration data through steps such as opening the secure encapsulation list, unlocking the digital fingerprint of the entire data packet, opening the hierarchical fingerprint tree of each file type, and parsing and restoring the data files within the data packet.

[0059] This invention is not limited to the specific embodiments described above. Those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of this invention. Unless otherwise specified, the embodiments and features described in these embodiments can be arbitrarily combined with each other.

Claims

1. A method for encapsulating process technology data packets for rapid collaboration in the supply chain, characterized in that, include: Using a predefined structured parsing template, outsourcing task information is parsed into a standardized task description model containing multiple core data elements; Based on the established standardized task description model, core data elements are associated with microservices. Through the parallel operation of multiple retrieval microservices, the required process document data is retrieved, matched, and captured from relevant information systems to form a process technology dataset. Based on the obtained process document dataset, consistency judgment and automatic data synchronization are achieved by backtracking through the retrieval path and data version tags. Using the synchronized process technology dataset, encryption algorithms are selected according to the different format characteristics of the files, while preserving the original format, forming a data packet with a nested secure encapsulation index file, thus completing the encapsulation and encryption process; The predefined structured parsing template includes a predefined structured parsing template for five core data elements: product drawing number, stage attribute, material handover requirements, process requirements, and technical protocol. The outsourcing task information is parsed into a standardized task description model containing multiple core data elements, including: Obtain the outsourcing task list and determine the entity value of each data element based on the predefined structured parsing template; Each data element and its entity value is structured to generate a standardized task description model, including product drawing number, stage attributes, material handover requirements, process requirements, and technical agreements. The established standardized task description model associates core data elements with microservices. Through the parallel operation of multiple retrieval microservices, the required process document data is retrieved, matched, and extracted from relevant information systems to form a process technology dataset, including: Based on the established standardized task description model, core data elements are associated with microservices to obtain multiple process technology data retrieval microservices, and the corresponding data retrieval and crawling microservices are given targeting. By running multiple process technology data retrieval microservices in parallel, process technology data corresponding to outsourced tasks are obtained from the databases of relevant information systems, forming a process technology dataset, and the process technology dataset is assigned the current retrieval path and data version label. The aforementioned multi-process technology data retrieval microservices, and the corresponding data retrieval and crawling microservices are given targeted features, including: The product data retrieval microservice is targeted at product image number and stage attribute. The process document retrieval microservice targets product drawing number, stage attribute, and process requirements. The technical document retrieval microservice is targeted at product drawing numbers and material handover requirements. The microservice for retrieving technical protocols is targeted by product drawing number and technical protocol. The process technology dataset includes three-dimensional process models, process documents, technical documents, and technical agreements; The process of backtracking based on the obtained process document dataset, using the retrieval path and data version tags, to achieve consistency judgment and automatic data synchronization includes: Based on the file retrieval path in the process technology dataset, backtrack and compare the data version in the existing dataset with the data version in each current information system; if they are inconsistent, start the data synchronization process and update the corresponding version tags in the dataset; if they are consistent, pass the entire dataset to the data transformation and packaging stage. The process involves utilizing the synchronized process technology dataset to select encryption algorithms based on different file format characteristics, while preserving the original format, to form a data packet containing a nested secure encapsulation index file, thus completing the encapsulation and encryption process. This includes: Perform multi-source data feature labeling and metadata extraction on the transmitted dataset; Build a format preservation container to maintain the original format and extension of various files in the dataset, and embed container-level digital fingerprints; Adaptively select encryption algorithms based on the different format characteristics of 3D models, document fields, and process diagrams to generate hierarchical fingerprint trees; Create a process technology data package for supply chain collaboration, including 3D models, process specifications, technical documents and technical agreements, configure the security index list corresponding to this data package, and complete the entire encapsulation and encryption process; The method of adaptively selecting encryption algorithms based on different format features of 3D models, document fields, and process diagrams to generate a hierarchical fingerprint tree includes: For the 3D model, a binary positioning offset algorithm is used to perform AES-CTR stream encryption on key feature regions to generate the first hierarchical fingerprint tree; A format-preserving encryption algorithm is used for Excel files, key characters are replaced with encrypted strings, and a second-level fingerprint tree is generated. The Word terms employ an attribute-based encryption algorithm, binding digital fingerprints to supplier roles to generate a third-layer fingerprint tree; A dynamic invisible watermarking strategy for sensitive areas is adopted for PDF process specifications to achieve local sensitive encryption of native process technology documents and generate a fourth-layer fingerprint tree.

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