Electronic equipment design, manufacturing, test integration collaborative method and system

Abstract

The present application relates to the technical field of digital design and manufacturing test integration of precision electronic equipment, and particularly relates to an electronic equipment design, manufacturing and test integration collaborative method and system. The method comprises the following steps: obtaining multidisciplinary data of the electronic equipment, and establishing an integrated fusion model; performing design change analysis and data consistency check, and generating collaborative design data and change requirement data; performing assembly unit planning, sequence optimization and merging, and obtaining assembly sequence, assembly process card, quality control point and manufacturing process parameters; performing digital assembly and manufacturing process automatic generation, and performing data comparison processing and change impact evaluation processing, and obtaining digital archives, parameter range suggestion, performance prediction and potential risk early warning. The present application realizes two-way closed-loop collaboration of design and manufacturing by front positioning of manufacturing feasibility analysis and fusion and evaluation of manufacturing deviation and design change information, and significantly improves the collaborative design efficiency and manufacturing quality consistency of the electronic equipment.

Description

Technical Field

[0001] This invention relates to the field of integrated digital design, manufacturing and testing technology for precision electronic equipment, and in particular to a collaborative method and system for integrated design, manufacturing and testing of electronic equipment. Background Technology

[0002] In the field of collaborative technology for digital design and manufacturing of electronic equipment, existing solutions typically revolve around digital product models, integrated fusion models, model files, manufacturing process files, assembly process information, and version management. They complete the design and manufacturing process through multidisciplinary data access, collaborative design data generation, multidisciplinary collaborative optimization, digital assembly, and digital archive management. However, these solutions suffer from limitations such as insufficient connection between collaborative design data and change request data, delayed intervention in manufacturing feasibility analysis and assembly evaluation analysis, and fragmented processing of real-time monitoring data and design change information.

[0003] Existing methods often rely on a typical path of first modeling, then collaborative solving, and finally outputting manufacturing process documents and assembly process cards. In the context of collaborative design and manufacturing of electronic equipment, it is easy for design change information to be difficult to be synchronously entered into manufacturing feasibility analysis and processing, and for real-time monitoring data to be difficult to enter into change impact assessment and processing, making it difficult to meet the stable implementation of verification data package generation.

[0004] Furthermore, in existing solutions, the design model, manufacturing process model, and test verification model are independent of each other, and parameters cannot be automatically transferred and synchronized. Design changes are unlikely to drive automatic updates to manufacturing processes and test cases; conversely, manufacturing deviations and test feedback are difficult to trace back to the design source. This fragmented 'design-manufacturing-testing' model leads to a prominent data silo problem throughout the entire lifecycle of electronic equipment, severely restricting the rapid iteration and quality consistency improvement of precision electronic equipment.

[0005] For the joint processing of collaborative design data, real-time monitoring data, manufacturing feasibility analysis, and change impact assessment, existing technologies generally suffer from the common shortcoming of scattered links between data format conversion processing, multi-disciplinary mapping processing, real-time synchronization processing, data comparison processing, and structured storage. This makes it difficult to form a consistent process of collection, alignment, judgment, and recording in the collaborative scenario of multidisciplinary design and manufacturing of electronic equipment, resulting in a lack of continuous correlation between deviation data, verification data packages, digital archives, parameter range suggestions, performance predictions, and potential risk warnings. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides an integrated collaborative method for the design, manufacturing, and testing of electronic equipment, comprising:

[0007] S100. Acquire multidisciplinary data of electronic equipment, perform integrated multi-level model fusion and parameter integration processing to obtain an integrated fusion model; the multidisciplinary data includes shape features, topology information, material type, geometric parameters, material properties, structural parameters, assembly model, model file, historical manufacturing data and test case data;

[0008] S200. Based on the integrated fusion model, perform design change analysis and data consistency check to obtain collaborative design data and change requirement data;

[0009] S300. Based on the collaborative design data and change requirement data, conduct manufacturing feasibility analysis and assembly evaluation analysis to obtain assembly sequence, assembly process card, quality control points and manufacturing process parameters.

[0010] S400: Based on the assembly sequence, assembly process card, quality control points and manufacturing process parameters, perform automatic generation of digital assembly and manufacturing process, and perform data comparison processing and change impact assessment processing to obtain digital archives, parameter range suggestions, performance predictions and potential risk warnings.

[0011] Furthermore, the process of integrating multi-level models includes:

[0012] A product structure tree is established, generating a product structure tree containing a structural layer, an assembly layer, and a process layer, and a test layer is added; the test layer is used to define test items, test sequences, performance indicators, test coverage, and fault criteria;

[0013] Assembly semantics are established to generate assembly semantics that include fixed relationships, plug-in relationships, fitting relationships, limit relationships, detection reachability relationships, and disassembly / assembly sequence relationships;

[0014] Establish assembly constraint relationships, generating assembly constraint relationships that include assembly position, assembly direction, assembly gap, assembly sequence, assembly interference information, and detection position constraints.

[0015] Furthermore, the parameter integration process includes:

[0016] Assign globally unique identifiers to key geometric parameters, material properties, and structural parameters in the design model layer, and establish bidirectional links and transfer rules between them and process parameters in the manufacturing model layer and test thresholds in the test model layer;

[0017] When design parameters change, the manufacturing process parameters and test thresholds are automatically updated. Conversely, manufacturing deviations or test feedback can also correct the tolerance range of the design parameters.

[0018] Furthermore, the process of design change analysis and data consistency check includes:

[0019] Spatial analysis is performed to extract shape features, topological information, geometric parameters, and structural parameters from real-time updated professional data. The installation boundaries, connection positions, assembly sequence candidate relationships, and detection reachability relationships of adjacent objects are compared item by item to generate conflict detection results that include conflict object identifiers, conflict location records, conflict source models, corresponding assembly semantics, corresponding assembly constraint relationships, and current version management records.

[0020] Design change analysis is performed, and objects that have undergone version changes, location changes, assembly semantic changes, assembly constraint relationship changes, and manufacturing process document changes are associated with conflict detection results. The impact propagation path of the change in the test model layer is analyzed, and design change information is generated, including the changed object, change source, pre-change record, post-change record, corresponding conflict detection results, corresponding assembly semantics, corresponding assembly constraint relationship, and affected test items and test thresholds.

[0021] Perform data consistency checks to examine the correspondence of the same object in digital product models, integrated fusion models, model files, manufacturing process files, assembly process information, and version management records, and generate collaborative design data and change request data.

[0022] Furthermore, the manufacturing feasibility analysis process includes:

[0023] By calling upon the process knowledge graph of associated design features, manufacturing processes, and historical defects, targeted analysis is performed on objects in the change request data that contain conflict detection result markers to generate manufacturability data.

[0024] Furthermore, the manufacturability data includes:

[0025] The manufacturability data includes records of the correspondence between structural parameters and manufacturing process documents, records of the correspondence between material types and manufacturing process parameters, records of the correspondence between assembly constraints and assembly process information, and reserved locations for quality control points.

[0026] Furthermore, the assembly evaluation and analysis process includes:

[0027] According to the structural, assembly, and process layers of the product structure tree, spatial analysis is performed layer by layer at the part level, sub-assembly level, and product level. The consistency between the installation boundary, connection position, detection position and assembly semantics is checked, and assembly modification suggestions are generated. The assembly modification suggestions include the assembly sequence to be adjusted, the assembly constraint relationship to be adjusted, the location of the assembly process information to be supplemented, and the location of the quality control point to be reattached.

[0028] Furthermore, the data comparison and processing steps include:

[0029] Based on the product structure tree, real-time monitoring data and performance evaluation results generated during the automatic generation process of digital assembly and manufacturing are compared with assembly process cards, quality control points, and manufacturing process parameters at the object level. Furthermore, the performance evaluation results are compared with the performance indicators and test thresholds defined in the test model layer to generate deviation data. The deviation data includes position deviation records, sequence deviation records, quality control point deviation records, manufacturing process parameter deviation records, performance evaluation result deviation records, and test indicator deviation records.

[0030] Furthermore, the process of handling change impact assessments includes:

[0031] The deviation data is correlated with the conflict detection results and design change information, and forward propagation and backward tracing are performed to identify the locations of affected model files, process documents, assembly process cards, quality control points, test cases, and verification data packages, and to generate a verification data package. The verification data package includes the locations of affected model files, affected process documents, affected assembly process cards, affected quality control points, affected test cases, corresponding deviation data, corresponding conflict detection results, and corresponding design change information.

[0032] Furthermore, an integrated collaborative system for electronic equipment design, manufacturing, and testing includes: an integrated model establishment module, a collaborative design data generation module, a manufacturing feasibility analysis and assembly evaluation module, a parametric correlation and multidisciplinary collaborative optimization module, an assembly sequence generation module, a digital assembly and manufacturing process automatic generation module, a change impact assessment module, and a digital archive management module; the system is used to implement the methods described in any of the above-mentioned embodiments.

[0033] The following are its main beneficial effects:

[0034] (1) It pioneered a multi-level model fusion-based integrated modeling and parameter connection technology for design, manufacturing and testing. This invention constructs an integrated fusion model that includes a design model layer, a manufacturing model layer and a testing model layer, and establishes a globally unique identifier and bidirectional connection rule for parameters between layers. This completely breaks down the data barriers of design, process and testing operating independently in the traditional model, and fundamentally overcomes the problem of data silos throughout the entire process of precision electronic equipment.

[0035] (2) Fully automated cross-domain propagation and impact analysis of design changes have been achieved. When design parameters change, the system can automatically locate and update the affected manufacturing process parameters and test criteria, and quantitatively evaluate their impact on assembly sequence, quality control and final performance, reducing change response time from days / weeks to minutes.

[0036] (3) A collaborative optimization mechanism driven by a two-way closed loop of “design-manufacturing-testing” has been formed. Not only can manufacturing deviations be fed back to optimize the design, but performance risks discovered in the testing process can also be automatically traced back to potential design or process root causes and trigger a new round of collaborative optimization, which significantly improves the first pass rate and long-term quality consistency of electronic equipment.

[0037] (4) In view of the problem that the manufacturing feasibility analysis and assembly evaluation analysis are delayed in the existing scheme, the present invention performs manufacturing feasibility analysis and assembly evaluation analysis on the collaborative design data and the change requirement data first, so that the parameterized association and multidisciplinary collaborative optimization receive the input objects that have been pre-screened, and the optimized structure data forms a continuous connection with the subsequent assembly sequence, assembly process card, quality control point and manufacturing process parameters.

[0038] (5) In view of the problem of scattered processing of real-time monitoring data and design change information in the existing scheme, the present invention processes the real-time monitoring data, the performance evaluation results, the quality control points, the manufacturing process parameters, the conflict detection results and the design change information in the same processing link, so that the deviation data no longer stays at the execution record layer, the verification data packet no longer stays at a separate record layer, and the model file, process file, assembly process card and quality control point can be associated in the same object link.

[0039] (6) In view of the lack of continuous association between deviation data, verification data package and digital archive in the existing scheme, the present invention performs structured storage, version management and full-link tracking processing on the deviation data and the verification data package, so that the digital archive maintains an object-level correspondence with parameter range suggestions, performance prediction and potential risk warning, and the preceding digital product model and integrated fusion model maintain continuous recording with the subsequent collaborative design data generation link. Attached Figure Description

[0040] Figure 1 A flowchart illustrating an integrated collaborative method for the design, manufacturing, and testing of electronic equipment, provided as an embodiment of this application;

[0041] Figure 2 This is a structural block diagram of an integrated collaborative system for the design, manufacturing, and testing of electronic equipment, provided as an embodiment of this application. Detailed Implementation

[0042] Example 1: Refer to Figure 1 This is a flowchart illustrating an integrated collaborative method for the design, manufacturing, and testing of electronic equipment provided in an embodiment of the present invention. The process may include at least steps S100-S400:

[0043] S100. Acquire multidisciplinary data of electronic equipment, perform integrated multi-level model fusion and parameter integration processing to obtain an integrated fusion model; the multidisciplinary data includes shape features, topology information, material type, geometric parameters, material properties, structural parameters, assembly model, model file, historical manufacturing data and test case data;

[0044] S200. Based on the integrated fusion model, perform design change analysis and data consistency check to obtain collaborative design data and change requirement data;

[0045] S300. Based on the collaborative design data and change requirement data, conduct manufacturing feasibility analysis and assembly evaluation analysis to obtain assembly sequence, assembly process card, quality control points and manufacturing process parameters.

[0046] S400: Based on the assembly sequence, assembly process card, quality control points and manufacturing process parameters, perform automatic generation of digital assembly and manufacturing process, and perform data comparison processing and change impact assessment processing to obtain digital archives, parameter range suggestions, performance predictions and potential risk warnings.

[0047] Step S100 includes at least steps S110-S130:

[0048] S110. Acquire multidisciplinary data of electronic equipment, perform parameterization and product structure tree establishment processing to obtain product structure tree and digital product model.

[0049] Specifically, the multidisciplinary data of the electronic equipment is accessed by clients oriented towards design, production, management, and testing, with the access point located in the data interface service of the collaborative design module.

[0050] The multidisciplinary data includes shape features, topology information, material types, geometric parameters, material properties, structural parameters, assembly models, model files, historical manufacturing data, and test case data. Specifically, the shape features represent the external shape, mounting boundaries, and interface outlines of electronic equipment parts; the topology information represents the connection positions, adjacency relationships, and assembly sequence relationships between parts; the material types are classifications of materials used for thermal conductivity, electrical conductivity, load-bearing capacity, and connection; the geometric parameters include parameters such as length, thickness, spacing, hole positions, and mounting surface positions; the material properties are related to strength, thermal conductivity, and processing capabilities corresponding to the material type; the structural parameters are related to module assembly, shell partitioning, board positions, and connector arrangement; and the test case data includes performance indicators, test sequences, test coverage, and fault criteria.

[0051] Parametric processing is performed by the collaborative design module. Specifically, the model file undergoes data format conversion first, and then shape features, topology information, material type, geometric parameters, material properties, and structural parameters are written into a unified field. Model files that cannot be directly matched are recorded as exceptions in the problem event module, and the design-oriented client is invoked to complete the data. For duplicate fields, the latest version is retained in the management record. For missing fields, parameter range suggestions from the knowledge base are used to fill in the missing fields, but the completed results are still recorded as fields awaiting confirmation.

[0052] The product structure tree creation process is performed after parameterization. Specifically, it involves establishing a parent-child hierarchy based on the functional modules, boards, housings, connectors, mounting components, and detection locations of the electronic equipment, and then writing the part relationships from the assembly model into the product structure tree.

[0053] The product structure tree includes at least a structure layer, an assembly layer, a process layer, and a test layer. The structure layer records the component combination relationship, the assembly layer records the assembly sequence candidate relationship, the process layer records the attachment position of subsequent manufacturing process documents and assembly process information, and the test layer is used to record test items, test sequences, performance indicators, test coverage, and fault criteria.

[0054] Understandably, the product structure tree is not a simple directory, but rather the input skeleton for subsequent assembly semantic establishment and assembly constraint relationship establishment processes; the digital product model is not a single three-dimensional solid model, but a digital product model composed of shape features, topological information, material type, geometric parameters, material properties, and structural parameters. After completing this section of processing, the system writes the "product structure tree" and "digital product model" as output field names into the central database, and makes the "product structure tree" and "digital product model" available for use in S120's "product structure tree, digital product model". Simultaneously, the digital product model also serves as the pre-input for S130's "digital product model" and the subsequent S210's "digital product model".

[0055] S120. Based on the product structure tree and the digital product model, perform assembly semantic establishment processing and assembly constraint relationship establishment processing to obtain assembly semantics and assembly constraint relationships.

[0056] Specifically, the assembly semantic establishment process is still executed by the collaborative design module. The triggering conditions include the project progress tracking entering the structural layout stage, the problem event module recording the interface adjustment, or the assembly modification suggestions from the production-oriented client being written back.

[0057] The assembly semantics define the roles of parts, boards, housings, fastening positions, connection positions, and detection positions in the assembly process, including at least fixing relationships, insertion relationships, fitting relationships, limiting relationships, detection reachability relationships, and disassembly / assembly sequence relationships. The system first reads the structural layer and assembly layer from the product structure tree, then extracts the interface outline, installation boundary, connection surface, and detection position from the digital product model, and performs assembly semantic matching on parts within the same parent-child level.

[0058] For objects that can be directly matched, the corresponding assembly semantics are written; for objects with multiple candidate assembly semantics, the spatial analysis processing results are compared, and the assembly semantics consistent with the current topology information are retained first; for objects that still cannot be determined, they are recorded as design change information candidates and do not directly enter the subsequent assembly constraint relationship establishment process. Furthermore, the assembly constraint relationship establishment process is executed after the assembly semantics establishment process. The assembly constraint relationship is a unified record of assembly position, assembly direction, assembly gap, assembly sequence, assembly interference information, and detection position constraints. In implementation, the system reads the geometric parameters, topology information, and material properties in the digital product model, and then, in conjunction with the assembly semantics, establishes positional constraint relationships, directional constraint relationships, and sequential constraint relationships for each group of adjacent parts. For the relationship between the board and the housing, the focus is on establishing assembly constraint relationships for the mounting surface and insertion direction; for the relationship between the connector and the fixing hole, the focus is on establishing assembly constraint relationships for the hole position, spacing, and limit; for the relationship between the detection position and the assembly path, the focus is on establishing detection reachability constraint relationships. If assembly interference information is found during spatial analysis, the assembly interference information is written into the assembly constraint relationship and simultaneously recorded in the preparatory field of the conflict detection result for subsequent use by S220.

[0059] If an inconsistency occurs between the structural, assembly, and process layers in an assembly relationship, it is processed through a data consistency check and written into an exception record. The current processing time and processing source are then generated in version management. Understandably, the assembly semantics expresses "what kind of relationship," and the assembly constraint relationship expresses "what boundaries to follow in executing the relationship." Together, they constitute the input conditions for establishing the integrated fusion model in S130. After completing this stage of processing, the system writes "assembly semantics" and "assembly constraint relationship" as output field names into the central database and makes the "digital product model, assembly semantics, and assembly constraint relationship" available for use in S130. Simultaneously, the assembly constraint relationship continues to be input in subsequent assembly unit planning, assembly sequence optimization, and assembly sequence merging in S330.

[0060] S130. Based on the digital product model, the assembly semantics, and the assembly constraint relationship, an integrated fusion model is established and parameters are processed to obtain the integrated fusion model.

[0061] The integrated fusion model includes at least a design model layer, a manufacturing model layer, and a testing model layer. The design model layer records model files, design change information, parametric processing records, and collaborative access control during the design phase. The manufacturing model layer records the relationships between manufacturing process documents, assembly process information, assembly process cards, quality control points, and manufacturing process parameters. The testing model layer records the relationships between performance indicators, test sequences, test coverage, fault criteria, test cases, and design and manufacturing parameters. Specifically, the integrated fusion model includes a digital design model, a digital production and manufacturing model, a digital management and control model, and a digital maintenance model. The digital design model records model files, design change information, parametric processing records, and collaborative access control during the design phase. The digital production and manufacturing model records the relationships between manufacturing process documents, assembly process information, assembly process cards, quality control points, and manufacturing process parameters. The digital management and control model records project progress tracking, task allocation, problem / event modules, and version management relationships. The digital maintenance model records the associated locations of subsequent real-time monitoring data, performance evaluation results, parameter change logs, verification data packages, and digital archives.

[0062] During the setup process, the collaborative design module first reads the shape features, topology information, material type, geometric parameters, and structural parameters from the digital product model. Then, it reads the assembly semantics and assembly constraints, and attaches process fields layer by layer according to the product structure tree: structural layer, assembly layer, process layer, and testing layer. For the design digital model, the system attaches the model files submitted by the design client, historical versions, and design change information to the corresponding structural nodes. For the manufacturing digital model, the system attaches manufacturing process files, assembly process information, subsequent assembly process card locations, and quality control point locations to the corresponding assembly nodes. For the management and control digital model, the system attaches task allocation, problem events, and collaborative permission control to the corresponding project nodes. For the maintenance digital model, the system reserves recording locations for real-time monitoring data, performance evaluation results, deviation data, parameter change logs, and verification data packages. For the testing model layer, the system attaches the correlation between performance indicators, test sequences, test coverage, fault criteria, and design and manufacturing parameters to the corresponding testing nodes.

[0063] Furthermore, the integrated model establishment process also includes input-output relationship verification. The system performs a pre- and post-processing check on each type of process field. The check includes whether the part object in the digital product model has a process attachment position, whether the assembly semantics have been established, whether the assembly constraint relationship has been written, and whether the problem event has been bound to the version management node. If there are unattached objects, an exception record is generated in the management and control digital model; if the same object is used repeatedly by multiple process fields, the latest version is retained and the replacement relationship is recorded.

[0064] Furthermore, parameter integration processing is performed: Globally unique identifiers are assigned to key geometric parameters, material properties, and structural parameters in the design model layer, and bidirectional links and transfer rules are established between these identifiers and process parameters in the manufacturing model layer and test thresholds in the testing model layer. When design parameters change, the system automatically triggers a linked update of manufacturing process parameters and test thresholds; conversely, manufacturing deviations or test feedback can also correct the tolerance range of the design parameters. Specifically, the parameter integration processing involves assigning globally unique identifiers to key geometric parameters, material properties, and structural parameters in the design model layer, and establishing bidirectional links and transfer rules between these identifiers and process parameters (such as tolerances and machining allowances) in the manufacturing model layer and test thresholds (such as performance upper and lower limits and fault criteria) in the testing model layer. When design parameters change, the system automatically triggers a linked update of manufacturing process parameters and test thresholds; conversely, manufacturing deviations or test feedback can also correct the tolerance range of the design parameters through the bidirectional links.

[0065] After this section of processing is completed, the integrated fusion model is written as an output field name into the central database, model library, and database, and the "digital product model, integrated fusion model" is made available for S210 to call. At the same time, the production and manufacturing digital model in the integrated fusion model provides the input location for manufacturing process documents and assembly process information for the manufacturing feasibility analysis processing of S310, and the maintenance digital model provides the recording location for real-time monitoring data, verification data packets, and digital archives of S410 to S430.

[0066] In summary, this step achieves the following technical benefits: It continuously establishes the product structure tree, digital product model, assembly semantics, assembly constraints, and integrated fusion model. It integrates design-phase objects with subsequent production, manufacturing, management control, and maintenance records into the same process chain, unlike methods that only generate model diagrams or process documents. By first establishing assembly semantics and assembly constraints, and then building the integrated fusion model, subsequent collaborative design data, manufacturing feasibility analysis, and change impact assessment all have clearly defined input and recording locations.

[0067] Step S200 includes at least steps S210-S230:

[0068] S210. Obtain the digital product model and the integrated fusion model, perform data format conversion processing and multi-professional mapping processing to obtain multi-professional related data.

[0069] Specifically, the input sources for this step are the digital product model and the integrated fusion model output by S130, the access point is located in the data interface service of the collaborative design module, and the execution point is located between the collaborative design module and the central database.

[0070] The digital product model includes shape features, topology information, material type, geometric parameters, material properties, and structural parameters. The integrated fusion model includes a design digital model, a production and manufacturing digital model, a management and control digital model, and a maintenance digital model. The data format conversion processing involves writing unified fields into model files, assembly process information, manufacturing process documents, problem events, and version management records. The processing object is not a single file, but rather the object fields in the digital product model and the process fields in the integrated fusion model.

[0071] During runtime, the collaborative design module first reads the digital product model corresponding to the current project progress tracking from the central database. Then, it reads the integrated fusion model corresponding to this digital product model from the model library and the database. Next, according to the structural layer, assembly layer, and process layer in the product structure tree, it aligns the model files, structural parameters, assembly semantics, assembly constraints, manufacturing process documents, and task allocation records in the management control digital model item by item. For objects with the same field names but different record formats, data format conversion is performed to convert them into unified fields. For objects with the same field names but different version management identifiers, the latest version management record is retained, and the old version is recorded as the source field of the parameter change log. For objects with missing fields, parameter range suggestions from the knowledge base are called to generate supplementary candidates, and the supplementary action is recorded in the issue event module.

[0072] Furthermore, the multi-disciplinary mapping process is an associated writing process performed after data format conversion. The core of this multi-disciplinary mapping process is to establish a one-to-one correspondence between the shape features, topology information, material types, geometric parameters, material properties, and structural parameters in the digital product model and the integrated fusion model's design digital model, manufacturing digital model, management control digital model, and maintenance digital model. Specifically, this involves first locating the functional modules of the electronic equipment according to the product structure tree, then reading the corresponding model files and manufacturing process files for each functional module, mapping structural parameters to the design digital model, mapping assembly semantics and assembly constraints to the manufacturing digital model, mapping task allocation and collaborative permission control to the management control digital model, and mapping parameter change logs, reserved locations for verification data packets, and reserved locations for digital archives to the maintenance digital model.

[0073] Understandably, the "multi-disciplinary" aspect in the multi-disciplinary mapping process does not refer to any arbitrary discipline, but rather to the correspondence between existing structural parameters, material properties, and assembly semantics in the digital product model and existing manufacturing process documents, management control records, and maintenance records in the integrated fusion model. During processing, if multiple manufacturing process documents are found to correspond to the same structural parameter, the system marks it as a multi-path record and records the source client; if the corresponding production and manufacturing digital model location cannot be found for the same model file, the system writes it to the problem event module and suspends the forward propagation of that object, but does not affect the continued execution of other objects.

[0074] In an operational engineering embodiment, after a product structure tree has been established for the housing, functional modules, connectors, and detection locations of an electronic equipment project, updated model files are submitted to the design client, new manufacturing process files and assembly process information are submitted to the production client, and task allocation and project progress tracking records are submitted to the management client. In the same round of processing, the collaborative design module first unifies the file fields, then maps the geometric parameters corresponding to the housing to the design digital model, maps the assembly constraints corresponding to the connectors to the production digital model, and maps the reserved locations of the verification data packets corresponding to the detection locations to the maintenance digital model, thereby obtaining a unified set of associations across models, processes, and records.

[0075] After processing, the system records the "multi-disciplinary related data" as the output field name and inputs the "multi-disciplinary related data" into the "multi-disciplinary related data" in S220. At the same time, the mapping relationship in the multi-disciplinary related data will continue to be called by the design change analysis and processing in S230, and will serve as the preliminary association basis for the formation of collaborative design data in S310.

[0076] S220. Based on the aforementioned multi-disciplinary related data, perform real-time synchronization processing and spatial analysis processing to obtain real-time updated professional data and conflict detection results.

[0077] Specifically, the input source for this step is the multi-disciplinary related data output by S210. The execution location is between the collaborative design module, the controller module, and the result visualization module. The triggering conditions include the project progress tracking entering the collaborative optimization decision period, the client submitting a new model file for design, the client submitting a new manufacturing process file for production, the problem event module recording a field conflict, or the version management record being updated.

[0078] The real-time synchronization process involves uniformly writing data from multiple disciplines according to the time order, version order, and client submission order. The real-time updated professional data refers to data records that, after unified writing, reflect the latest status of the current design digital model, production and manufacturing digital model, management and control digital model, and maintenance digital model. This includes at least the latest model file, latest manufacturing process file, latest assembly process information, latest task allocation record, and latest parameter change log source record. During runtime, the collaborative design module reads each mapping relationship from the multi-discipline related data, first comparing its version management record, then its source client timestamp, and then its most recent write time in the central database. Real-time synchronization is then completed in the order of "latest version first, latest write of the same version first, and abnormal records last." Records that still conflict after synchronization are not directly deleted but retained as pending judgment records and written to the problem event module. Furthermore, the spatial analysis process is executed after the real-time synchronization process.

[0079] The spatial analysis process targets fields related to assembly models, assembly semantics, assembly constraints, and detection locations in real-time updated professional data. The processing path involves first extracting shape features, topological information, geometric parameters, and structural parameters from the real-time updated professional data. Then, it reads assembly process information and reserved positions from the assembly process card in the digital manufacturing model, comparing the installation boundaries, connection positions, candidate assembly sequences, and detection reachability of adjacent objects item by item. If two objects overlap in position, assembly path, detection location is obscured, or assembly sequence is inconsistent with assembly constraints on the same assembly layer, a conflict detection result is generated. This conflict detection result includes at least the conflict object identifier, conflict location record, conflict source model, corresponding assembly semantics, corresponding assembly constraints, and current version management record.

[0080] Specifically, in an operational engineering scenario, when the position of the functional module housing of an electronic equipment is adjusted on the design-oriented client, while the manufacturing process file of the connector remains in the old version on the production-oriented client, real-time synchronization processing first updates the housing model file to the real-time updated professional data, then identifies the assembly path overlap between the housing and the connector through spatial analysis processing, and then writes the overlap relationship as a conflict detection result, while attaching the corresponding version management record, task allocation record and problem event record.

[0081] Understandably, the real-time synchronization processing addresses whether the record is in the current state, while the spatial analysis processing addresses whether there are conflicts between current states. Together, they form the direct input for S230. After processing, the system records "real-time updated professional data" and "conflict detection results" as output field names, and inputs the "real-time updated professional data and conflict detection results" into the "real-time updated professional data and conflict detection results" field of S230. Simultaneously, the conflict detection results are also called by the "conflict detection results" field of S420 as the input source for the change impact assessment processing.

[0082] S230. Based on the real-time updated professional data and the conflict detection results, perform design change analysis and data consistency checks to obtain collaborative design data, design change information, and change requirement data.

[0083] The design change analysis and processing not only identifies changes in the design model layer, but also further analyzes the propagation path of the impact of the change in the manufacturing model layer and the test model layer, generating design change information that includes the change object, change source, pre-change record, post-change record, corresponding conflict detection results, corresponding assembly semantics, corresponding assembly constraint relationships, and affected test items and test thresholds.

[0084] The data consistency check process examines the correspondence of the same object in the design model layer, manufacturing model layer, test model layer, and version management records to ensure that design parameters, manufacturing parameters, and test thresholds are kept updated synchronously under the same version.

[0085] Specifically, the input sources for this step are the real-time updated professional data output by S220 and the conflict detection results, and the execution location is between the collaborative design module, the problem event module, the central database, and the knowledge base. The design change analysis and processing involves classifying the causes, locating the impacts, and writing change records for objects in the real-time updated professional data that have undergone version changes, location changes, assembly semantic changes, assembly constraint relationship changes, and manufacturing process document changes.

[0086] The design change information is the direct output of design change analysis and processing. It includes at least the change object, change source, pre-change record, post-change record, corresponding conflict detection results, corresponding assembly semantics, and corresponding assembly constraint relationships. In specific implementation, the system first extracts model files, manufacturing process files, and assembly process information with the latest version identifier from the real-time updated professional data. Then, it compares these with the previous version management records item by item to identify changed fields. Subsequently, it reads the conflict detection results to determine if the changed fields are consistent with the conflict object. If they are consistent, the changed field is marked as a conflict-related change object; if they are inconsistent, the changed field is marked as an independent design change object. For independent design change objects, the system only records the pre- and post-change content. For conflict-related change objects, the system further reads the exception records and task allocation records from the problem event module, and writes the conflict location record, corresponding assembly semantics, and corresponding assembly constraint relationships into the design change information.

[0087] Furthermore, the data consistency check is performed after the design change analysis. The data consistency check examines the correspondence between real-time updated professional data, conflict detection results, and design change information.

[0088] The specific processing path involves checking for inconsistencies in fields, connections, or sequences of the same object across the digital product model, integrated fusion model, model file, manufacturing process file, assembly process information, and version management records. If consistent, the object is written into the collaborative design data; if inconsistent, parameter range suggestions and historical manufacturing data from the knowledge base are retrieved to generate revision candidates for the inconsistencies, and change request data is formed by combining these with conflict detection results. The collaborative design data is not simply aggregated data, but a dataset that, after data consistency checks, can be directly incorporated into manufacturing feasibility analysis and assembly evaluation analysis. It includes at least valid model fields, valid process fields, valid assembly fields, and corresponding version management fields from real-time updated professional data. The change request data is input data further refined from design change information and conflict detection results. It includes at least the structural parameters to be adjusted, the assembly constraints to be adjusted, the location of the manufacturing process file to be adjusted, and the location of the assembly process information to be supplemented.

[0089] In a complete engineering implementation, when the material type of a functional module of an electronic equipment is changed, resulting in the old record being retained in the connection order of the manufacturing process file, and at the same time the spatial analysis process identifies that the detection position is obstructed, the design change analysis process first writes the material type change into the design change information, and then writes the conflicting object corresponding to the obstructed detection position into the same record. After that, the data consistency check process checks the attachment position of the object in the digital product model, the digital manufacturing model, and the digital maintenance model. It finds that the detection position is inconsistent between the assembly layer and the process layer, so it generates change request data containing the assembly constraint relationship to be adjusted and the location of the assembly process information to be supplemented.

[0090] After processing, the system records "collaborative design data, design change information, and change requirement data" as output field names, inputs the "collaborative design data and change requirement data" into "collaborative design data and change requirement data" in S310, retains the "design change information" for subsequent input in S420, and writes the collaborative design data back to the central database for continued use in subsequent processing in S300 and S400.

[0091] In summary, this step integrates real-time updated professional data and conflict detection results into the same processing chain. Through design change analysis and data consistency checks, it yields collaborative design data, design change information, and change requirement data, unlike methods that only synchronize data or record conflicts. Consequently, subsequent manufacturing feasibility analysis and assembly evaluation analysis receive input data that has undergone design change analysis and data consistency checks, rather than the original design records. Similarly, subsequent change impact assessment receives design change information already bound to change source and process fields, rather than isolated conflict records.

[0092] Step S300 includes at least steps S310-S330:

[0093] S310. Obtain the collaborative design data and the change requirement data, perform manufacturing feasibility analysis and assembly evaluation analysis, and obtain manufacturability data and assembly modification suggestions.

[0094] After the manufacturing feasibility analysis and assembly evaluation analysis are completed, if the assembly sequence, assembly constraints, or quality control points change, the system automatically adds or modifies the corresponding test locations, test sequences, and test accessibility constraints in the test model layer. For example, when a test location is obstructed due to an adjustment in the assembly sequence, the system automatically replans the test path or adds new test points in the test model.

[0095] Specifically, the input sources for this step are the collaborative design data and the change request data output by S230. The collaborative design data includes real-time updated professional data, valid records corresponding to design change information, valid records corresponding to conflict detection results, and the current record in the version management record. The change request data includes structural parameters to be adjusted, assembly constraint relationships to be adjusted, the location of manufacturing process documents to be adjusted, and the location of assembly process information to be supplemented.

[0096] This step is executed jointly by the collaborative design module, which calls the central database, model library, knowledge base, and database. The triggering condition is that the collaborative design data and the change request data are written to the same version management record, and there are no abnormal records in the problem event module that would block the current processing link. Understandably, the manufacturing feasibility analysis is not a post-hoc check of the final result, but rather a preliminary screening of the input data before entering multidisciplinary collaborative optimization; the assembly evaluation analysis is not a separate assembly process simulation, but rather integrates assembly semantics, assembly constraints, assembly process information, and design change information into the same processing link for cross-judgment.

[0097] During actual operation, the collaborative design module first extracts the shape features, topology information, material type, geometric parameters, material properties and structural parameters corresponding to the digital product model from the collaborative design data, and then extracts the assembly constraint relationships to be adjusted, the location of the manufacturing process document and the location of the assembly process information from the change request data.

[0098] Subsequently, the system retrieves historical manufacturing data, parameter range suggestions, and potential risk warnings from the knowledge base to compare the connection points of the digital product model and the integrated fusion model within the digital manufacturing model. The manufacturability data mentioned here is a set of records processed by manufacturing feasibility analysis, including at least the corresponding records of structural parameters and manufacturing process documents, the corresponding records of material types and manufacturing process parameters, the corresponding records of assembly constraints and assembly process information, reserved locations for quality control points, and similar records from historical manufacturing data.

[0099] The manufacturing feasibility analysis process involves first checking if the structural parameters already have attachment positions in the current manufacturing process file; then checking for conflicts between the material type and existing manufacturing process parameters; and finally checking for inconsistencies in the order or position of assembly constraints in the assembly process information. For objects with existing attachment positions and consistent version management records, the system directly writes them into the manufacturability data. For objects with attachment positions but different version management records, the system calls parameter range suggestions for a secondary comparison and writes the comparison results into the adjustment record in the manufacturability data. For objects with missing attachment positions, the system writes the corresponding object into the problem event module and retains the object's record in the change requirement data as input for subsequent collaborative optimization, without discarding it in this step.

[0100] Furthermore, the assembly evaluation analysis is performed after the manufacturing feasibility analysis. The inputs to the assembly evaluation analysis include assembly semantics, assembly constraints, assembly process information, conflict detection results, and assembly-related records from the manufacturability data.

[0101] The processing path involves performing spatial analysis layer by layer at the part level, subassembly level, and product level, according to the structural layer, assembly layer, and process layer in the product structure tree. For the part level, it checks whether the installation boundaries, connection positions, and detection positions are consistent with the assembly semantics; for the subassembly level, it checks whether the assembly sequence, assembly interference information, and assembly constraint relationships are consistent; for the product level, it checks whether the overall assembly path in the assembly model is consistent with the current manufacturing process document and assembly process information.

[0102] If they match, the assembly record is written into the valid records of the assembly evaluation and analysis process; if they do not match, assembly modification suggestions are generated.

[0103] The assembly modification suggestions include at least the assembly sequence to be adjusted, the assembly constraints to be adjusted, the location of the assembly process information to be supplemented, and the location of the quality control points to be reattached. In an operational engineering embodiment, when the combination relationship between a circuit board and a housing of an electronic device is adjusted in the design change information, but the manufacturing process document of the connector still retains the previous version record, the manufacturing feasibility analysis process first extracts the structural parameters of the circuit board, the geometric parameters of the housing, and the manufacturing process parameters of the connector. By comparing with similar records in historical manufacturing data, it is found that the position of the connector is inconsistent with the current assembly constraints, so the object is written into the record to be adjusted in the manufacturability data. Subsequently, the assembly evaluation analysis process continues to check the assembly sequence and inspection position of the circuit board, housing, and connector in the assembly layer. It is found that the inspection position is postponed in the current assembly process information. Based on this, the system generates an assembly modification suggestion and writes the suggestion into the central database along with the aforementioned record to be adjusted.

[0104] After completing this step, the system records "manufacturability data" and "assembly modification suggestions" as output field names, and inputs the "manufacturability data and assembly modification suggestions" into "manufacturability data and assembly modification suggestions" in S320; at the same time, the reserved locations of quality control points and assembly-related records in the manufacturability data continue to serve as the prerequisite for subsequent S330 and S410.

[0105] S320. Based on the manufacturability data and the assembly modification suggestions, perform parametric correlation and multidisciplinary collaborative optimization to obtain optimized structural data.

[0106] Specifically, the input sources for this step are the manufacturability data and assembly modification suggestions output by S310. The execution location is between the collaborative design module, optimization model module, optimization algorithm module, and controller module. The triggering condition is that there is at least one set of valid records in the manufacturability data and the assembly modification suggestions have been written to the version management system.

[0107] The parametric association involves writing back the structural parameters, material properties, manufacturing process parameters, assembly constraints, and assembly process information from the manufacturability data to the digital product model and the integrated fusion model, using the same object identifier.

[0108] The multidisciplinary collaborative optimization refers to the collaborative solution process performed on the multidisciplinary data corresponding to structure, electrical, thermal, electromagnetic, and control aspects after the parametric association is completed. The optimized structural data mentioned here is not a single model result, but a unified set of records formed after parametric association and multidisciplinary collaborative optimization, including structural parameters, material properties, boundary conditions, assembly constraints, and manufacturing process parameters. It at least includes updated structural parameters, updated material properties, updated assembly constraints, updated manufacturing process parameters, corresponding performance indicators, and corresponding quality control point locations.

[0109] During actual operation, the system first extracts the structural parameters, material types, manufacturing process parameters, and assembly constraints to be adjusted from the manufacturability data. Then, it extracts the assembly sequence to be adjusted, the location of the assembly process information to be added, and the location of the quality control points to be reattached from the assembly modification suggestions. The parameterized association processing is first executed in the digital product model, rewriting the structural parameters, material properties, and topology information into the corresponding objects; then it is executed in the integrated fusion model, reattaching the manufacturing process parameters, assembly process information, and quality control point locations to the digital production model; finally, the sequence adjustment in the assembly modification suggestions is written into the task allocation record of the management and control digital model.

[0110] Furthermore, multidisciplinary collaborative optimization does not start from the original model again, but executes directly based on the parameterized and associated object records. The collaborative design module first distributes structural parameters, material properties, boundary conditions, and assembly constraints to the optimization model module, and then the optimization algorithm module selects the corresponding collaborative solution path according to the current project progress. For structure-related records, the focus is on checking whether there are new conflicts between structural parameters and assembly constraints; for material property-related records, the focus is on checking whether there are inconsistencies between material types and manufacturing process parameters; for boundary condition-related records, the focus is on checking whether there are obstructions or gaps between inspection locations, assembly paths, and quality control point locations. If all records are consistent under the same version management, the controller module outputs the updated structural parameters and manufacturing process parameters; if conflicts still exist, the conflict field is retained and written to the problem event module, while other fields that can continue to be executed are output, without blocking the entire processing chain.

[0111] After this step is completed, the system will record "optimized structure data" as the output field name and input the "optimized structure data" into the "optimized structure data" of S330; at the same time, the quality control point location and manufacturing process parameter update records in the optimized structure data will also be automatically generated and processed by the subsequent digital assembly and manufacturing process of S410.

[0112] S330. Based on the optimized structural data, perform assembly unit planning, assembly sequence optimization, and assembly sequence merging to obtain assembly sequence, assembly process card, quality control points, and manufacturing process parameters.

[0113] Specifically, the input source for this step is the optimized structure data output by S320, and the execution location is between the collaborative design module, the result output and post-processing module, and the central database.

[0114] The assembly unit planning process reorganizes the parts, boards, housings, connectors, inspection locations, and corresponding assembly constraints in the optimized structural data into executable assembly units. The assembly sequence optimization process rearranges the order of the assembly units. The assembly sequence merging process merges and writes continuously executable assembly sequences within the same structural layer or assembly layer. The assembly sequence is an assembly order record formed after assembly unit planning, assembly sequence optimization, and assembly sequence merging. The assembly process card is a process record corresponding one-to-one with the assembly sequence. The quality control point is a node record in the assembly sequence that requires the writing of inspection locations and version management records. The manufacturing process parameters are process field records corresponding to the assembly sequence.

[0115] During runtime, the collaborative design module first extracts updated structural parameters, updated assembly constraints, updated manufacturing process parameters, performance indicators, and quality control point locations from the optimized structural data. Then, it establishes assembly units according to the assembly layer in the product structure tree. These assembly units are based on assembly semantics and assembly constraints, and are not simply broken down into individual parts, but rather organized according to "continuously executable assembly relationships."

[0116] For example, the same board and its connectors, fastening positions, and detection positions can be organized into the same assembly unit if the assembly constraints are consistent; if there is assembly interference information between the housing and external connectors on the assembly path, they are divided into different assembly units.

[0117] After the assembly unit planning is completed, the result output and post-processing module performs assembly sequence optimization on each assembly unit. Assembly sequence optimization reads assembly process information, assembly modification suggestions, and current manufacturing process parameters, adjusting the order of each assembly unit item by item. If the detection position corresponding to a certain assembly unit is obscured in a preceding assembly unit, that assembly unit is moved forward; if the manufacturing process parameters corresponding to a certain assembly unit differ significantly from those of the preceding and following units, that assembly unit is removed and retained separately in the sequence. Subsequently, assembly sequence merging is performed, merging adjacent assembly units with consistent assembly constraints, continuous manufacturing process parameters, and non-conflicting quality control point positions into the same assembly sequence, and simultaneously generating corresponding assembly process cards. The assembly process card records the assembly object, assembly sequence, quality control point position, corresponding manufacturing process parameters, and version management records.

[0118] Furthermore, this step also re-attaches quality control points based on the performance indicators. If the performance indicators change after adjusting a certain structural parameter and material property, the quality control point of that object is moved to an earlier assembly sequence; if the performance indicators do not change, the original quality control point position is retained. In a complete engineering embodiment, when the housing position, board connection sequence, and detection position of an electronic device are optimized through multidisciplinary collaborative optimization to form new optimized structural data, the system first organizes the housing and connectors into a first assembly unit, and the boards and detection positions into a second assembly unit. Then, based on whether the detection positions are obstructed and whether the manufacturing process parameters are continuous, the order of the two is adjusted. Finally, the continuously executable connector installation and housing fixing are merged into the same assembly sequence, and a corresponding assembly process card is generated, and a quality control point is attached before the board detection position.

[0119] After completing this step, the system records "assembly sequence, assembly process card, quality control point and manufacturing process parameter" as output field names, and inputs the "assembly sequence, assembly process card, quality control point and manufacturing process parameter" into "assembly sequence, assembly process card, quality control point and manufacturing process parameter" in S410; at the same time, the assembly sequence and the assembly process card also serve as the direct execution basis for digital assembly, and the quality control point and the manufacturing process parameter serve as the reference basis for subsequent data comparison processing and change impact assessment processing.

[0120] Summary of the technical effects of this step: This step integrates manufacturing feasibility analysis, assembly evaluation analysis, multidisciplinary collaborative optimization, and assembly sequence generation into a single, continuous process. The result is not an isolated optimization outcome, but rather assembly sequences, assembly process cards, quality control points, and manufacturing process parameters that can be automatically generated and processed within the digital assembly and manufacturing workflow. Compared to methods that only perform multidisciplinary collaborative optimization or only perform assembly planning, this step connects preceding change request data and subsequent assembly execution data through optimized data structure. This ensures that assembly paths, quality control points, and manufacturing process parameters are uniformly organized under the same version management before entering the S400 system.

[0121] Step S400 includes at least steps S410-S430:

[0122] S410. Obtain the assembly sequence, the assembly process card, the quality control point, and the manufacturing process parameters, perform digital assembly and manufacturing process automatic generation processing, and obtain real-time monitoring data and performance evaluation results.

[0123] Specifically, during the digital assembly process, the system synchronously invokes test cases in the test model layer to perform virtual testing (such as model-based simulation) or semi-physical testing (such as physical-in-the-loop testing) on ​​key performance indicators, generating performance evaluation results. These results include not only structural status, detection location status, and assembly path status, but also performance indicator pass / fail judgment, test coverage, and failure mode analysis.

[0124] Specifically, the input sources for this step are the assembly sequence, assembly process card, quality control points, and manufacturing process parameters output by S330. The call location is between the collaborative design module, the result output and post-processing module, the production-oriented client, and the controller module. The digital assembly process involves sequentially assembling, verifying positions, and recording quality control points for parts, boards, housings, connectors, and inspection locations in the assembly model according to the assembly sequence and assembly process card. The automatic manufacturing process generation process generates manufacturing process files, machining process files, and the current execution record corresponding to the current assembly sequence, based on the manufacturing process parameters, assembly process information, and version management records.

[0125] During actual operation, the collaborative design module first reads the assembly unit sequence from the assembly sequence, then reads the assembly objects, assembly sequence, quality control point locations, and corresponding manufacturing process parameters from the assembly process card, and then sends this set of records to the production-oriented client. The production-oriented client executes the digital assembly item by item according to the assembly sequence.

[0126] During execution, upon completion of each assembly unit, an execution record is written at the corresponding quality control point, and the assembly position, assembly sequence, assembly process information, and manufacturing process parameters of the current assembly object are returned to the result output and post-processing module. If an assembly unit experiences inconsistencies in assembly semantics, assembly constraints, or assembly paths that do not match the assembly process card during execution, the system does not terminate all processing. Instead, it records the unit as an exception and links the exception record to the corresponding quality control point and the current version management record.

[0127] Furthermore, the automated manufacturing process generation is executed synchronously with digital assembly. The controller module, based on the manufacturing process parameters corresponding to the current assembly unit, retrieves the manufacturing process file location and assembly process information location from the digital production model, generating the manufacturing process file and execution record for the current batch. This generation is not a separate drawing output, but rather the integration of the assembly sequence, the objects in the assembly process card, and the inspection locations in the quality control points into the same execution chain. The real-time monitoring data is the current record generated during digital assembly and automated manufacturing process generation, including at least assembly location records, assembly sequence records, quality control point records, manufacturing process parameter execution records, and anomaly records. The performance evaluation result is an evaluation record formed by combining the quality control points and the current execution record, including at least the structural state record, inspection position state record, and assembly path state record corresponding to the assembly model.

[0128] After completing this step, the system will record "real-time monitoring data" and "performance evaluation results" as output field names, and will provide the "real-time monitoring data, performance evaluation results, quality control points, manufacturing process parameters, conflict detection results, and design change information" to S420 for use; at the same time, the abnormal records in the real-time monitoring data and the status records in the performance evaluation results will also be used for subsequent digital archive creation and processing in subsequent steps.

[0129] S420. Based on the real-time monitoring data, the performance evaluation results, the quality control points, the manufacturing process parameters, the conflict detection results, and the design change information, perform data comparison processing and change impact assessment processing to obtain deviation data and verification data packages.

[0130] The data comparison processing not only compares the real-time monitoring data with the assembly process card and quality control points, but also compares the performance evaluation results (virtual test or semi-physical test results) with the performance indicators and test thresholds defined in the test model layer, generating deviation data containing deviation records of performance evaluation results.

[0131] The change impact assessment process further identifies the locations of affected test cases and incorporates these locations into the verification data packet.

[0132] Specifically, the input sources for this step are the real-time monitoring data and performance evaluation results output by S410, as well as the conflict detection results output by the preceding S220 and the design change information output by the preceding S230. The execution location is between the collaborative design module, the central database, the issue / event module, and the maintenance digital model.

[0133] The data comparison processing involves checking the correspondence between the currently executed record and the previous input record for the same object, order, and position. The change impact assessment processing involves associating the difference records after data comparison processing with the conflict detection results and the design change information to identify the affected model files, process documents, assembly process cards, quality control points, and verification data package locations. In actual operation, the collaborative design module first extracts assembly position records, assembly sequence records, quality control point records, and manufacturing process parameter execution records from the real-time monitoring data. Then, it extracts structural status records, detection position status records, and assembly path status records from the performance evaluation results. Finally, it compares these records item by item with the assembly process cards, quality control points, and manufacturing process parameters output by S330.

[0134] If the current assembly position record matches the assembly object position in the assembly process card, and the current assembly sequence record matches the assembly sequence, then the object is written to a consistency record. If there are inconsistencies among the assembly position record, assembly sequence record, quality control point record, or manufacturing process parameter execution record, then the object is written to a difference record. The deviation data is a unified set of difference records, including at least position deviation records, sequence deviation records, quality control point deviation records, manufacturing process parameter deviation records, and performance evaluation result deviation records.

[0135] Furthermore, the system performs association processing on the deviation data with conflict detection results and design change information. If a deviation data point corresponds to the same assembly object as an existing conflict detection result, the deviation data point is marked as a conflict continuation record; if a deviation data point corresponds to the same structural parameter or the same assembly constraint relationship as design change information, the deviation data point is marked as a change association record; if a deviation data point corresponds to neither a conflict detection result nor design change information, the deviation data point is marked as a new difference record and written to the problem event module.

[0136] The verification data package is a set of records formed after the change impact assessment process, including at least the location of the affected model file, the location of the affected process file, the location of the affected assembly process card, the location of the affected quality control point, the corresponding deviation data, the corresponding conflict detection results, and the corresponding design change information.

[0137] After completing this step, the system records "deviation data" and "verification data package" as output field names, and makes the "deviation data" and "verification data package" available for S430 to call; at the same time, the conflict continuation record and change association record in the deviation data continue to serve as key inputs for subsequent version management and full-link tracing.

[0138] S430. Based on the deviation data and the verification data packet, perform structured storage, version management and full-link tracking processing to obtain digital archives, parameter range suggestions, performance predictions and potential risk warnings.

[0139] Specifically, the input sources for this step are the deviation data and the verification data package output by S420, and the execution location is between the central database, knowledge base, model library, database, management and control digital model, and maintenance digital model.

[0140] The structured storage is the processing content of splitting and attaching deviation data and verification data packets by object, location, order, version and source; the version management is the processing content of establishing the correspondence between old and new model files, process files, assembly process cards, quality control points and manufacturing process parameters of the same object in different processing rounds; the end-to-end tracking is the processing content of establishing the relationship between previous and subsequent records according to the order of product structure tree, digital product model, integrated fusion model, collaborative design data, assembly sequence, real-time monitoring data, deviation data and verification data packets.

[0141] During operation, the system first writes deviation data into the maintenance digital model according to location deviation records, sequence deviation records, quality control point deviation records, manufacturing process parameter deviation records, and performance evaluation result deviation records. Then, it writes the model file location, process file location, assembly process card location, and quality control point location from the verification data package into the corresponding object fields in the central database. Version management is then executed. If the current deviation data corresponds to the same object in the previous round of digital archives, a link between the old and new versions is established in version management, and the current record is treated as the latest version. If no correspondence exists, the record is written as a newly added object version.

[0142] Furthermore, the end-to-end tracking process establishes associations according to the source of each step. The system connects the product structure tree records, digital product model records, integrated fusion model records, collaborative design data records, assembly process card records, real-time monitoring data records, deviation data records, and verification data packet records related to the current object in each step from S110 to S430 into the same tracking chain.

[0143] The digital archive is an object-level record collection formed through structured storage, version management, and end-to-end tracing. It includes at least the object's origin, version order, process location, quality control point records, deviation data, and verification data packages. After generating the digital archive, the system continues to call upon the knowledge base to compare historical manufacturing data, historical deviation data, and historical verification data packages for similar objects, generating parameter range suggestions, performance predictions, and potential risk warnings. The parameter range suggestions record the acceptable ranges for subsequent structural parameters, assembly constraints, and manufacturing process parameters; the performance predictions record the trends in subsequent performance evaluation results; and the potential risk warnings record the locations where differences may occur in subsequent assembly paths, inspection locations, quality control points, and manufacturing process parameters.

[0144] After completing this step, the system records "digital archives, parameter range suggestions, performance predictions, and potential risk warnings" as output field names, and sends the "parameter range suggestions and potential risk warnings" back to the S110 multidisciplinary data access stage of the subsequent processing rounds, and sends the "digital archives and performance predictions" back to the knowledge base, model base, and database called by the S210 data format conversion processing and multi-professional mapping processing stage.

[0145] In summary, this step goes beyond simply providing structured storage and version management. It reorganizes deviation data and verification data packets into a retrievable digital archive, and then sends parameter range recommendations, performance predictions, and potential risk warnings back to the preceding processing links. Compared to methods that merely archive or track data, this step directly transforms the discrepancies recorded after digital assembly into input content that can be called upon for the next round of collaborative design and manufacturing feasibility analysis, creating a repeatable closed loop in the entire processing chain. Furthermore, by unifying the design, manufacturing, and testing domains into a single fusion model and achieving bidirectional parameter communication and automatic updates, this invention effectively solves the data silo problem throughout the entire process of precision electronic equipment. It forms a closed-loop collaborative optimization mechanism for design, manufacturing, and testing, significantly improving equipment R&D efficiency, manufacturing quality consistency, and test coverage.

[0146] In one specific embodiment, in S410, the input source for the automatic generation and processing of the digital assembly and manufacturing process is the assembly sequence, assembly process card, quality control point, and manufacturing process parameters output by S330. The call location is between the collaborative design module, the result output and post-processing module, the production-oriented client, and the controller module. The collaborative design module first reads the assembly unit sequence from the assembly sequence, then reads the assembly object, assembly sequence, quality control point location, and corresponding manufacturing process parameters from the assembly process card, and then sends this set of records to the production-oriented client. The production-oriented client executes the digital assembly item by item according to the assembly sequence. During execution, an execution record is written at the corresponding quality control point after each assembly unit is completed, and the assembly position, assembly sequence, assembly process information, and manufacturing process parameters of the current assembly object are returned to the result output and post-processing module. If an assembly unit experiences inconsistencies in assembly semantics, assembly constraints, or assembly paths that are inconsistent with the assembly process card during execution, the system does not terminate all processing but records the unit as an exception and links the exception record to the corresponding quality control point and the current version management record. The manufacturing process is automatically generated and executed synchronously with digital assembly. The controller module retrieves the manufacturing process file location and assembly process information location in the digital production model based on the manufacturing process parameters corresponding to the current assembly unit, and generates the manufacturing process file and execution record for the current batch. This generation process writes the sequence in the assembly sequence, the objects in the assembly process card, and the inspection location in the quality control point into the same execution link.

[0147] To quantify the degree of consistency in the digital assembly process, assembly path fit and assembly sequence consistency indices are introduced. Let the theoretical assembly path of the current assembly unit be an ordered set of points in three-dimensional space. The actual execution path is Each point is represented by spatial coordinates. Composition. The similarity between two paths is measured using a cross-correlation method. Formula ① is used to calculate the path similarity coefficient:

[0148] Formula①

[0149]

[0150] in:

[0151] Path fit coefficient, value range It is calculated using formula ①;

[0152] Summation operation, subscript The summation index variable takes values ​​from 1 to... ;

[0153] : Summation index, indicating the first index on the path There are 1 sampling points, which are positive integers;

[0154] The minimum value function represents the theoretical number of sampling points along the path. Compared with the actual number of sampling points along the path The smaller value in;

[0155] In the actual assembly path, the first... The location vector of each sampling point comes from the assembly location record field in the "real-time monitoring data";

[0156] The theoretical path defined in the assembly process card The position vector of each sampling point comes from the assembly object position field in the "assembly process card";

[0157] : The mean vector of all sampled points along the actual path, given by Calculated;

[0158] The mean vector of all sampling points along the theoretical path, derived from... Calculated;

[0159] : Euclidean norm (modulus) operation of vectors;

[0160] The number of sampling points for the theoretical path is derived from the path point set in the "Assembly Process Card";

[0161] The number of sampling points on the actual path is derived from the assembly position records in the "Real-time Monitoring Data".

[0162] Cross-correlation operations yield the path fit coefficient through dot product and norm normalization. value range , The closer the value is to 1, the closer the actual path matches the theoretical path. This is obtained by extracting the assembly unit sequence from the "Assembly Sequence" and the theoretical path point set from the "Assembly Process Card". It is extracted from the set of actual location points recorded during the digital assembly process. Together, they form the input for formula ①.

[0163] In an engineering embodiment, the theoretical path of the housing fixing unit of a certain electronic equipment consists of 10 points, and the actual execution is recorded at these 10 points, which is then calculated. This indicates a high degree of consistency in the assembly path. Assembly sequence consistency is obtained by comparing the actual assembly sequence with the sequence specified on the process card. Let the assembly sequence have a total of... Each assembly unit, theoretically in an ordered list. The actual execution order is as follows: Define the order deviation index The Kendall's τ distance between the actual order and the theoretical order is normalized. Formula ② is used to calculate the order consistency score:

[0164] Formula②

[0165]

[0166] in:

[0167] Sequential consistency score, range of values It is calculated using formula ②;

[0168] Total number of assembly units, a positive integer, derived from the "Assembly Sequence" field;

[0169] Double summation operation, subscript and For summation index variables, From 1 to , from arrive ;

[0170] : Summation index, indicating the first position in the assembly unit sequence. One location;

[0171] : Summation index, indicating the first position in the assembly unit sequence. One location;

[0172] : Indicator function, takes the value 1 when the condition inside the parentheses is true, otherwise takes the value 0;

[0173] In actual implementation, the first The identifier of each completed assembly unit comes from the assembly sequence record in the "real-time monitoring data";

[0174] In actual implementation, the first A completed assembly unit identifier;

[0175] The first step specified in the assembly process card Each assembly unit identifier is derived from the "assembly sequence" field;

[0176] The first step specified in the assembly process card Assembly unit identifier.

[0177] Formula ② calculates whether the relative order of all unordered pairs is consistent. Range of values The closer it is to 1, the more consistent the actual order is with the theoretical order.

[0178] Numerical example: three units: housing fixing, board insertion, and connector locking. The theoretical sequence is (shell fixing, board installation, connector locking), but the actual sequence is (shell fixing, connector locking, board installation). Therefore, there is one inconsistency: (board installation, connector locking) versus (connector locking, board installation). The above. and The data, along with quality control point records, manufacturing process parameter execution records, and anomaly records, are integrated into the real-time monitoring data. The performance evaluation results are formed by combining quality control points with the current execution records, including structural status records, inspection location status records, and assembly path status records.

[0179] This step outputs "real-time monitoring data" and "performance evaluation results" as input items for S420; at the same time, the anomaly records in the real-time monitoring data and the status records in the performance evaluation results are also used for subsequent digital archive creation and processing.

[0180] Furthermore, in S420, the input sources for data comparison processing and change impact assessment processing are the real-time monitoring data and performance evaluation results output from S410, as well as the conflict detection results output from the preceding S220 and the design change information output from the preceding S230. The execution location is between the collaborative design module, the central database, the problem event module, and the maintenance digital model. The collaborative design module first extracts assembly location records, assembly sequence records, quality control point records, and manufacturing process parameter execution records from the real-time monitoring data. Then, it extracts structural status records, detection location status records, and assembly path status records from the performance evaluation results. These are then compared item by item with the assembly process card, quality control points, and manufacturing process parameters output from S330. The data comparison processing checks the correspondence between the currently executed record and the preceding input records for the same object, same sequence, and same position. If the assembly location record matches the assembly object position in the assembly process card and the assembly sequence record matches the assembly sequence, a consistency record is written; otherwise, a difference record is written. Deviation data is a unified set of discrepancy records, including location deviation records, sequence deviation records, quality control point deviation records, manufacturing process parameter deviation records, and performance evaluation result deviation records. To quantitatively describe the degree of deviation, a deviation vector is defined. Each component is calculated using Euclidean distance or normalized difference. For example, positional deviation. Defined as the spatial distance between the actual location and the theoretical location:

[0181] Formula③

[0182]

[0183] in:

[0184] Positional deviation, calculated using formula ③;

[0185] : vector Norm (Euclidean norm) operations;

[0186] Actual assembly position coordinate vector This information originates from the assembly location record field in the "Real-time Monitoring Data";

[0187] : Actual assembly location Axis coordinates;

[0188] : Actual assembly location Axis coordinates;

[0189] : Actual assembly location Axis coordinates;

[0190] Theoretical assembly position coordinate vector This comes from the assembly object location field in the "Assembly Process Card";

[0191] Theoretical assembly position Axis coordinates;

[0192] Theoretical assembly position Axis coordinates;

[0193] Theoretical assembly position Axis coordinates.

[0194] Sequence deviation The order of calculation using formula ② is inconsistent, affecting the quantity or directly taking... Deviation at quality control points The absolute value of the difference between the measured quality parameter and the standard value, divided by the standard value (dimensionless); manufacturing process parameter deviation. Using similar relative bias; performance evaluation result bias It is obtained by weighting the differences between the structural state, the detection position state, the assembly path state, and the expected state.

[0195] After obtaining the deviation data, the system performs correlation processing with the conflict detection results and design change information, introducing bidirectional propagation influence weights. The design change information and conflict detection results are considered as a set of influence source nodes. Deviation data is considered as the set of affected nodes. Construct a directed graph using the product structure tree. ,in It contains all objects (parts, model files, process files, etc.). Define forward propagation weights for design dependencies (such as a design feature affecting its associated manufacturing processes). Backward tracing weights The reachability impact is calculated using the exponentiation operation of the adjacency matrix. Formula ④ calculates the propagation strength of the change impact:

[0196] Formula④

[0197]

[0198] in:

[0199] From the source node of the impact To the target node The total propagation intensity is calculated using formula ④.

[0200] Summation operation, subscript The summation index variable takes values ​​from 1 to... ;

[0201] : Summation index, indicating the propagation step size;

[0202] The maximum propagation step size is determined by the product structure tree depth.

[0203] Adjacency matrix, dimension 1 ,element Indicates from node To the node Are there direct design dependencies?

[0204] Adjacency matrix of The power of, its elements Indicates from node To the node Length is The number of paths;

[0205] :picture The total number of nodes, a positive integer;

[0206] :picture A collection of nodes containing all objects (parts, model files, process files, etc.).

[0207] : Affects the source node, belongs to The object identifier originates from the "conflict detection results" or "design change information";

[0208] Target node, belonging to This originates from the deviation object identifier in the "deviation data";

[0209] : Indicates the direction from the source node to the target node;

[0210] :matrix The Middle Line 1 The elements of the column.

[0211] Data source mapping: adjacency matrix It is constructed from the structural layer, assembly layer, and process layer connection relationships in the "product structure tree" and the dependency relationships in the "assembly constraint relationship"; Set according to the maximum depth of the "product structure tree"; and The specific object identifiers come from the conflict object identifiers in "Conflict Detection Results", the change object identifiers in "Design Change Information", and the deviation object identifiers in "Deviation Data".

[0212] Numerical Example: Suppose the depth of the structure tree for a certain electronic equipment product is 3, and the node corresponding to the change of shell structure parameters in the design change information is... This change directly affects the assembly process nodes of the connectors. (The direct edge exists), and then the influence propagates through two layers to the detection location node. ,but , (If a path of length 2 exists), (No path).

[0213] The system associates deviation data with conflict detection results and design change information. If a deviation data point corresponds to the same assembly object as an existing conflict detection result, it is marked as a conflict continuation record. If it corresponds to the same structural parameter or assembly constraint relationship as design change information, it is marked as a change association record. If it corresponds to neither a conflict detection result nor design change information, it is marked as a new difference record and written to the issue event module. The verification data package is a collection of records formed after the change impact assessment, and includes at least the location of the affected model file, the location of the affected process file, the location of the affected assembly process card, the location of the affected quality control point, the corresponding deviation data, the corresponding conflict detection result, and the corresponding design change information. In an engineering embodiment, after an electronic equipment board is installed, the real-time monitoring data records a detection position that deviates from the target position in the assembly process card. Performance evaluation results show that the assembly path state is inconsistent with the preset state. The system first records this difference as deviation data, then checks the preceding conflict detection results and finds that the detection position has already been marked as a conflict object in S220. Therefore, the deviation data is associated with this conflict detection result. Subsequently, the design change information is checked and it is found that the board already has an assembly constraint adjustment record in S230. Therefore, the deviation data is further marked as a change-related record, and the affected assembly process card position, quality control point position, and model file position are imported into the same verification data package. This step outputs "deviation data" and "verification data package" as inputs to S430; simultaneously, the conflict continuation record and change-related record in the deviation data continue to serve as key inputs for subsequent version management and end-to-end tracking.

[0214] Furthermore, in S430, the input sources for structured storage, version management, and end-to-end tracing processing are the deviation data and verification data packages output from S420. The execution location is between the central database, knowledge base, model library, database, management control digital model, and maintenance digital model. The system first writes the deviation data into the maintenance digital model according to location deviation records, sequence deviation records, quality control point deviation records, manufacturing process parameter deviation records, and performance evaluation result deviation records. Then, it writes the model file location, process file location, assembly process card location, and quality control point location from the verification data package into the corresponding object fields in the central database. Version management establishes a new and old correspondence for the same object in different processing rounds of model files, process files, assembly process cards, quality control points, and manufacturing process parameters. If the current deviation data has a correspondence with the same object in the previous round of digital archives, a link between the old and new versions is established in version management, and the current record is treated as the latest version; if no correspondence exists, the record is written as a new object version.

[0215] The end-to-end tracing process establishes connections based on the source of each step, linking the product structure tree records, digital product model records, integrated fusion model records, collaborative design data records, assembly process card records, real-time monitoring data records, deviation data records, and verification data package records related to the current object in steps S110 to S430 into a single tracing chain. The digital archive is a collection of object-level records formed after structured storage, version management, and end-to-end tracing, including at least the object source, version sequence, process location, quality control point records, deviation data, and verification data package. To quantify differences between versions and historical similarities, a version difference degree is defined. Match with history For records of the same object in two adjacent versions, let its key feature vector be... and (Including structural parameters, assembly constraints, manufacturing process parameters, etc.), the cosine similarity is used to measure the difference, and formula ⑤ defines the version difference degree:

[0216] Formula⑤

[0217]

[0218] in:

[0219] Version difference, value range It is calculated using formula ⑤;

[0220] The feature vector of the previous version object is derived from the feature fields of the corresponding version in the "Digital Archives".

[0221] The feature vectors of this version's objects are derived from relevant fields in the "deviation data" and "verification data package";

[0222] :vector Euclidean norm (modulus);

[0223] :vector Euclidean norm (modulus);

[0224] Cosine similarity, range of values ;

[0225] : A constant used to convert cosine similarity to dissimilarity.

[0226] Numerical Example: The feature vector of a connector in the previous version was (0.5, 0.8, 0.3), and the feature vector of the current version is (0.55, 0.78, 0.32). The cosine similarity is approximately 0.998. This indicates that the differences between versions are minimal.

[0227] After generating digital archives, the system calls upon a knowledge base to compare historical manufacturing data, historical deviation data, and historical verification data packages of similar objects, generating parameter range suggestions, performance predictions, and potential risk warnings. Weighted Euclidean distance or Mahalanobis distance is used to measure the similarity between the current object and historical records, and formula ⑥ calculates the historical matching degree. Select the most similar historical record:

[0228] Formula⑥

[0229]

[0230] in:

[0231] Historical matching score: The index of the best matching record selected from the historical record set, derived from... Calculation result;

[0232] : A function that maximizes the value of its argument and returns the function that maximizes the value of the argument. value;

[0233] The index variable for historical records comes from the historical record collection. ;

[0234] A collection of historical records of similar objects in a knowledge base;

[0235] Exponential function, expressed as a natural constant As the base;

[0236] The square of the Mahalanobis distance;

[0237] Mahalanobis distance is defined as follows: ;

[0238] The covariance matrix is ​​estimated from the historical eigenvectors and has the same dimension as the eigenvectors.

[0239] Gaussian kernel width controls the similarity decay rate; its value is determined based on the distribution of historical data.

[0240] The feature vector of the current object is derived from the feature fields in the "deviation data" and "verification data package";

[0241] : No. The feature vectors of each historical record are derived from historical manufacturing data, historical deviation data, and historical verification data packages in the "knowledge base";

[0242] : The square of the Gaussian kernel width.

[0243] After selecting the historical record most similar to the current object using formula ⑥, the system extracts the parameter range, performance change trend, and risk location from the historical record, which are used as parameter range suggestions, performance predictions, and potential risk warnings for the current object.

[0244] Numerical example: Current connector feature vector The historical database contains three records with Mahalanobis distances of 0.1, 0.8, and 2.0 respectively. Take... The matching degrees are 0.82, 0.28, and 0.00 respectively. The first historical record is selected as a reference. The recommended parameter range for this record is a connection torque of 1.2~1.5 N·m, a performance prediction that the contact resistance after assembly is stable below 0.5 mΩ, and a potential risk warning that is the risk of interference between the connector and the housing.

[0245] In an engineering embodiment, a connector of a certain electronic equipment continuously exhibits sequence deviation records and manufacturing process parameter deviation records during the current processing round. The system first writes these two types of deviation data and corresponding verification data packets into the maintenance digital model. Then, in version management, it establishes a new and old version link between the current connector record and the previous connector record. Subsequently, in the end-to-end tracking process, it connects all records of the connector from product structure tree establishment, assembly constraint relationship establishment, design change analysis and processing, assembly sequence optimization, digital assembly to deviation data generation, ultimately forming a digital archive of the connector. The knowledge base then compares this digital archive with historical manufacturing data and outputs suggestions on the parameter range that can be used for the connector in the future, corresponding performance predictions, and potential risk warnings.

[0246] This step outputs "digital archives", "parameter range suggestions", "performance predictions", and "potential risk warnings". The parameter range suggestions and potential risk warnings are sent back to the S110 multidisciplinary data access stage in subsequent processing rounds. The digitized archives and performance predictions are sent back to the knowledge base, model library, and database called by the S210 data format conversion processing and multi-professional mapping processing stage.

[0247] This section summarizes the technical effects: S430 organizes deviation data and verification data packets into retrievable digital archives through structured storage, version management, and end-to-end tracing. It also re-injects the knowledge base comparison results (parameter range suggestions, performance predictions, and potential risk warnings) into the preceding processing links, enabling the entire design and manufacturing collaborative method to form a repeatable closed loop. Formulas ⑤ and ⑥ provide quantitative basis from the two dimensions of version difference measurement and historical similarity matching, respectively, ensuring the traceability of digital archives and the accuracy of knowledge reuse.

[0248] Example 2: Figure 2 A structural block diagram of an integrated collaborative system for the design, manufacturing, and testing of electronic equipment according to an embodiment of the present invention is shown. Figure 2 As shown, the structure may include:

[0249] The integrated model building module 01 is used to acquire multidisciplinary data of electronic equipment, perform parametric processing, product structure tree building, assembly semantics building, assembly constraint relationship building, and integrated fusion model building to obtain a product structure tree, a digital product model, assembly semantics, assembly constraint relationships, and an integrated fusion model. Specifically, the integrated model building module receives multidisciplinary data from design-oriented clients, production-oriented clients, and management-oriented clients. This multidisciplinary data includes shape features, topology information, material type, geometric parameters, material properties, structural parameters, model files, manufacturing process files, and assembly process information. The integrated model building module first performs parametric processing on the model files, writing the shape features, topology information, material type, geometric parameters, material properties, and structural parameters of the same object into a unified field. Then, it builds a product structure tree according to functional modules, boards, housings, connectors, and detection locations. The integrated model building module then writes assembly semantics and assembly constraint relationships into the product structure tree and builds an integrated fusion model according to the design digital model, production manufacturing digital model, management control digital model, and maintenance digital model. During processing, missing field records are written to the problem event module, and version difference records are written to the version management record. The product structure tree, the digital product model, the assembly semantics, the assembly constraint relationship, and the integrated fusion model are written as the output objects of the current module into the central database, the model library, and the database. The integrated model building module provides the digital product model and the integrated fusion model to the collaborative design data generation module for subsequent data format conversion processing and multi-disciplinary mapping processing.

[0250] The collaborative design data generation module 02, connected to the integrated model establishment module, is used to acquire the digital product model and the integrated fusion model, and perform data format conversion, multi-disciplinary mapping, real-time synchronization, spatial analysis, design change analysis, and data consistency checks to obtain collaborative design data, design change information, and change requirement data. Specifically, the collaborative design data generation module receives the digital product model and the integrated fusion model from the integrated model establishment module and reads the corresponding version management records from the central database. The collaborative design data generation module first performs data format conversion on the model file, manufacturing process file, assembly process information, and management control records, and then performs multi-disciplinary mapping according to the structural layer, assembly layer, and process layer in the product structure tree, establishing corresponding relationships between structural parameters, assembly semantics, assembly constraints, manufacturing process file locations, and maintenance record locations. The collaborative design data generation module then performs real-time synchronization, aligning the currently written record with the most recent version management record, and then performs spatial analysis, comparing installation boundaries, connection locations, detection locations, and assembly paths to generate conflict detection results. The collaborative design data generation module then invokes design change analysis and data consistency checks to categorize and verify changed structural parameters, assembly constraints, manufacturing process document locations, and assembly process information locations, obtaining collaborative design data, design change information, and change request data. The collaborative design data, design change information, and change request data are written to a central database. The collaborative design data and change request data are provided to the manufacturing feasibility analysis and assembly evaluation module, while the design change information is retained for use by the change impact assessment module.

[0251] The manufacturing feasibility analysis and assembly evaluation module 03, connected to the collaborative design data generation module, is used to acquire the collaborative design data and the change request data, perform manufacturing feasibility analysis and assembly evaluation analysis, and obtain manufacturability data and assembly modification suggestions. Specifically, the manufacturing feasibility analysis and assembly evaluation module receives the collaborative design data and the change request data from the collaborative design data generation module, and calls historical manufacturing data, parameter range suggestions, and potential risk warning records from the knowledge base. The manufacturing feasibility analysis and assembly evaluation module first checks the connection relationship between structural parameters and manufacturing process documents, then checks the correspondence between material types and manufacturing process parameters, and then checks the sequential and positional relationships between assembly constraints and assembly process information to form manufacturability data. The manufacturing feasibility analysis and assembly evaluation module then performs assembly evaluation analysis at the part level, sub-assembly level, and product level, checking the assembly path, detection location, assembly sequence, and assembly interference information item by item to form assembly modification suggestions. Abnormal objects are written to the problem event module, and objects to be adjusted are retained in the current processing link. The manufacturability data and the assembly modification suggestions are written into the central database as the output objects of the current module. The manufacturing feasibility analysis and assembly evaluation module provides the manufacturability data and the assembly modification suggestions to the parameterized association and multidisciplinary collaborative optimization module for subsequent parameterized association and multidisciplinary collaborative optimization.

[0252] The parameterized association and multidisciplinary collaborative optimization module 04, connected to the manufacturing feasibility analysis and assembly evaluation module, is used to acquire the manufacturability data and assembly modification suggestions, perform parameterized association and multidisciplinary collaborative optimization, and obtain optimized structural data. Specifically, the parameterized association and multidisciplinary collaborative optimization module receives the manufacturability data and assembly modification suggestions, and calls the corresponding object records in the digital product model and the integrated fusion model. The parameterized association and multidisciplinary collaborative optimization module first writes the structural parameters, material properties, assembly constraint relationships, assembly process information locations, and manufacturing process parameters to be adjusted back to the corresponding objects, and then performs collaborative solution processing on the multidisciplinary data related to structure, electrical, thermal, electromagnetic, and control. The parameterized association and multidisciplinary collaborative optimization module updates the structural parameters, boundary conditions, material properties, and assembly constraint relationships in a linked manner under the current version management record, retains problem event records for conflicting fields, and forms a new round of object records for consistent fields. The output object is optimized structural data, which includes updated structural parameters, assembly constraint relationships, manufacturing process parameters, quality control point locations, and corresponding performance indicators. The parameterized association and multidisciplinary collaborative optimization module provides the optimized structure data to the assembly sequence generation module for assembly unit planning, assembly sequence optimization, and assembly sequence merging.

[0253] The assembly sequence generation module 05, connected to the parameterized association and multidisciplinary collaborative optimization module, is used to acquire the optimized structure data, perform assembly unit planning, assembly sequence optimization, and assembly sequence merging to obtain assembly sequences, assembly process cards, quality control points, and manufacturing process parameters. Specifically, the assembly sequence generation module receives the optimized structure data from the parameterized association and multidisciplinary collaborative optimization module and reads the assembly layer and process layer from the product structure tree. The assembly sequence generation module first performs assembly unit planning for parts, boards, housings, connectors, and inspection positions according to assembly semantics and assembly constraints. Then, it performs assembly sequence optimization according to assembly paths, assembly interference information, and quality control point positions. Finally, it merges assembly sequences for assembly units with consecutive order and continuous manufacturing process parameters. During the merging process, the assembly sequence generation module simultaneously generates assembly process cards and attaches quality control points and manufacturing process parameters to the corresponding assembly sequences. The assembly sequence, assembly process card, quality control point, and manufacturing process parameters are written into the central database and the digital production and manufacturing model as the current module output objects. The assembly sequence generation module provides the assembly sequence, assembly process card, quality control point, and manufacturing process parameters to the digital assembly and manufacturing process automatic generation module for subsequent automatic generation and processing of digital assembly and manufacturing processes.

[0254] The digital assembly and manufacturing process automatic generation module 06, connected to the assembly sequence generation module, is used to acquire the assembly sequence, the assembly process card, the quality control points, and the manufacturing process parameters, and perform automatic digital assembly and manufacturing process generation to obtain real-time monitoring data and performance evaluation results. Specifically, the digital assembly and manufacturing process automatic generation module receives the assembly sequence, the assembly process card, the quality control points, and the manufacturing process parameters, and sends the current processing object to the production-oriented client and the result output and post-processing module. The digital assembly and manufacturing process automatic generation module executes the assembly object processing in the assembly model item by item according to the assembly sequence, writes an assembly position record, an assembly sequence record, and a quality control point record for each assembly unit, and simultaneously generates a current execution record by calling the corresponding manufacturing process file position according to the manufacturing process parameters. During the processing, the digital assembly and manufacturing process automatic generation module continuously receives the current status from the production-oriented client and forms an inspection record at the quality control point position. The real-time monitoring data includes assembly position records, assembly sequence records, quality control point records, manufacturing process parameter execution records, and anomaly records, and the performance evaluation results include structural status records, detection position status records, and assembly path status records. The digital assembly and manufacturing process automatic generation module provides the real-time monitoring data and the performance evaluation results to the change impact assessment module for subsequent data comparison and change impact assessment processing.

[0255] The change impact assessment module 07, connected to the automatic digital assembly and manufacturing process generation module and the collaborative design data generation module, is used to acquire the real-time monitoring data, performance evaluation results, quality control points, manufacturing process parameters, conflict detection results, and design change information, perform data comparison processing and change impact assessment processing, and obtain deviation data and verification data packages. Specifically, the change impact assessment module receives the real-time monitoring data and performance evaluation results from the automatic digital assembly and manufacturing process generation module, retrieves the quality control points and manufacturing process parameters from the assembly sequence generation module, and retrieves the conflict detection results and design change information from the collaborative design data generation module. The change impact assessment module first performs data comparison processing on the assembly position record, assembly sequence record, quality control point record, manufacturing process parameter execution record, and performance evaluation results to form a difference record, and then performs association processing with the difference record and the conflict detection results and design change information. The change impact assessment module then performs change impact assessment processing according to object location, process location, assembly process card location, and quality control point location, identifying the affected model files, process files, assembly process cards, quality control points, and verification data package locations. The deviation data is output as a set of difference records, and the verification data package is output as a set of affected objects. The change impact assessment module provides the deviation data and the verification data package to the digital archive management module and writes the current correlation results into the maintenance digital model and problem event module.

[0256] The digital archive management module 08, connected to the change impact assessment module, is used to acquire the deviation data and the verification data package, perform structured storage, version management, and end-to-end tracking processing to obtain digital archives, parameter range suggestions, performance predictions, and potential risk warnings. Specifically, the digital archive management module receives the deviation data and the verification data package and calls corresponding records in the central database, knowledge base, model library, database, management control digital model, and maintenance digital model. The digital archive management module first performs structured storage on the deviation data and the verification data package according to object, location, order, version, and source. Then, it performs version management on the model files, process files, assembly process cards, quality control points, and manufacturing process parameters of the same object in different processing rounds. Subsequently, it performs end-to-end tracking processing according to the product structure tree, digital product model, integrated fusion model, collaborative design data, assembly sequence, real-time monitoring data, deviation data, and verification data package. After tracking processing, the digital archive management module generates digital archives and extracts historical manufacturing data, historical deviation data, and historical verification data packages of similar objects from the knowledge base to form parameter range suggestions, performance predictions, and potential risk warnings. The digital archive management module writes the digital archives into the central database and maintains the digital model. It sends the parameter range suggestions, performance predictions, and potential risk warnings back to the integrated model building module and the collaborative design data generation module as object records for subsequent multi-disciplinary data access, data format conversion processing, and multi-professional mapping processing calls, and completes the closed-loop update of the current processing link.

Claims

1. A collaborative method for the integrated design, manufacturing, and testing of electronic equipment, characterized in that, include: S100. Acquire multidisciplinary data of electronic equipment, perform integrated multi-level model fusion and parameter integration processing to obtain an integrated fusion model; The multidisciplinary data includes shape features, topological information, material type, geometric parameters, material properties, structural parameters, assembly model, model file, historical manufacturing data, and test case data; S200. Based on the integrated fusion model, perform design change analysis and data consistency check to obtain collaborative design data and change requirement data; S300. Based on the collaborative design data and change requirement data, conduct manufacturing feasibility analysis and assembly evaluation analysis to obtain assembly sequence, assembly process card, quality control points and manufacturing process parameters. S400: Based on the assembly sequence, assembly process card, quality control points and manufacturing process parameters, perform automatic generation of digital assembly and manufacturing process, and perform data comparison processing and change impact assessment processing to obtain digital archives, parameter range suggestions, performance predictions and potential risk warnings.

2. The method according to claim 1, characterized in that, The process of performing integrated multi-level model fusion processing includes: A product structure tree is established, generating a product structure tree containing a structural layer, an assembly layer, and a process layer, and a test layer is added; the test layer is used to define test items, test sequences, performance indicators, test coverage, and fault criteria; Assembly semantics are established to generate assembly semantics that include fixed relationships, plug-in relationships, fitting relationships, limit relationships, detection reachability relationships, and disassembly / assembly sequence relationships; Establish assembly constraint relationships, generating assembly constraint relationships that include assembly position, assembly direction, assembly gap, assembly sequence, assembly interference information, and detection position constraints.

3. The method according to claim 2, characterized in that, The parameter integration process includes: Assign globally unique identifiers to key geometric parameters, material properties, and structural parameters in the design model layer, and establish bidirectional links and transfer rules between them and process parameters in the manufacturing model layer and test thresholds in the test model layer; When design parameters change, the manufacturing process parameters and test thresholds are automatically updated. Conversely, manufacturing deviations or test feedback can also correct the tolerance range of the design parameters.

4. The method according to claim 1, characterized in that, The process of design change analysis and data consistency check includes: Spatial analysis is performed to extract shape features, topological information, geometric parameters, and structural parameters from real-time updated professional data. The installation boundaries, connection positions, assembly sequence candidate relationships, and detection reachability relationships of adjacent objects are compared item by item to generate conflict detection results that include conflict object identifiers, conflict location records, conflict source models, corresponding assembly semantics, corresponding assembly constraint relationships, and current version management records. Design change analysis is performed, and objects that have undergone version changes, location changes, assembly semantic changes, assembly constraint relationship changes, and manufacturing process document changes are associated with conflict detection results. The impact propagation path of the change in the test model layer is analyzed, and design change information is generated, including the changed object, change source, pre-change record, post-change record, corresponding conflict detection results, corresponding assembly semantics, corresponding assembly constraint relationship, and affected test items and test thresholds. Perform data consistency checks to examine the correspondence of the same object in digital product models, integrated fusion models, model files, manufacturing process files, assembly process information, and version management records, and generate collaborative design data and change request data.

5. The method according to claim 1, characterized in that, The manufacturing feasibility analysis process includes: By calling upon the process knowledge graph of associated design features, manufacturing processes, and historical defects, targeted analysis is performed on objects in the change request data that contain conflict detection result markers to generate manufacturability data.

6. The method according to claim 5, characterized in that, The manufacturability data includes: The manufacturability data includes records of the correspondence between structural parameters and manufacturing process documents, records of the correspondence between material types and manufacturing process parameters, records of the correspondence between assembly constraints and assembly process information, and reserved locations for quality control points.

7. The method according to claim 2, characterized in that, The assembly evaluation and analysis process includes: According to the structural, assembly, and process layers of the product structure tree, spatial analysis is performed layer by layer at the part level, sub-assembly level, and product level. The consistency between the installation boundary, connection position, detection position and assembly semantics is checked, and assembly modification suggestions are generated. The assembly modification suggestions include the assembly sequence to be adjusted, the assembly constraint relationship to be adjusted, the location of the assembly process information to be supplemented, and the location of the quality control point to be reattached.

8. The method according to claim 2, characterized in that, The data comparison and processing process includes: Based on the product structure tree, real-time monitoring data and performance evaluation results generated during the automatic generation process of digital assembly and manufacturing are compared with assembly process cards, quality control points, and manufacturing process parameters at the object level. Furthermore, the performance evaluation results are compared with the performance indicators and test thresholds defined in the test model layer to generate deviation data. The deviation data includes position deviation records, sequence deviation records, quality control point deviation records, manufacturing process parameter deviation records, performance evaluation result deviation records, and test indicator deviation records.

9. The method according to claim 8, characterized in that, The process of handling change impact assessment includes: The deviation data is correlated with the conflict detection results and design change information, and forward propagation and backward tracing are performed to identify the locations of affected model files, process documents, assembly process cards, quality control points, test cases, and verification data packages, and to generate a verification data package. The verification data package includes the locations of affected model files, affected process documents, affected assembly process cards, affected quality control points, affected test cases, corresponding deviation data, corresponding conflict detection results, and corresponding design change information.

10. An integrated collaborative system for the design, manufacturing, and testing of electronic equipment, characterized in that, include: The system comprises an integrated model building module, a collaborative design data generation module, a manufacturing feasibility analysis and assembly evaluation module, a parametric correlation and multidisciplinary collaborative optimization module, an assembly sequence generation module, a digital assembly and manufacturing process automatic generation module, a change impact assessment module, and a digital archive management module; the system is used to implement the method described in any one of claims 1-9.

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