Task allocation method and device, electronic equipment and medium

Abstract

The invention provides a task allocation method and device, electronic equipment and a medium. The method comprises the steps of obtaining task demand information, searching target technical data corresponding to the task demand information in a preset technical database, and determining a target task and a target part corresponding to the target task according to the task demand information and the target technical data, and determining target part affiliation information corresponding to the target part according to the task demand information and the target technical data, determining a task platform corresponding to the target task according to the target part affiliation information, and allocating the target task to the task platform. According to the invention, through intelligent matching of the task requirements and the technical database, the target task can be accurately and rapidly constructed, the attribution information of the parts in the target task can be accurately identified, and the target task can be automatically allocated to the corresponding task platform, so that manual intervention can be reduced, and the decision period can be shortened; and the adaptability between the target task and the task platform can be enhanced.

Description

Technical Field

[0001] The present invention relates to the field of task management, and in particular to a task allocation method, device, electronic equipment and medium. Background Art

[0002] Currently, the trend of new technology collaboration between enterprises and universities, research institutions, and third-party companies is significantly increasing, with a wide range of cooperation, multiple project types, and a wide range of professional fields. At the same time, the pace of technological iteration is accelerating, the industrialization cycle is shortening, and technological competition among different enterprises is intensifying, with increasingly stringent technical barriers and protection mechanisms.

[0003] The existing technical task management model is still mainly based on offline management and simple online entry. When faced with new technical tasks with different needs, it cannot achieve rapid matching of new technologies and tasks, and it cannot accurately identify the ownership information of parts in technical tasks, which makes it difficult for technical tasks to be efficiently adapted to different products or platforms. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a task allocation method, device, electronic device, and medium.

[0005] In a first aspect of the present invention, a task allocation method is provided, comprising:

[0006] Obtain task requirement information;

[0007] Searching for target technical data corresponding to the task requirement information in a preset technical database;

[0008] Determine a target task and a target component corresponding to the target task according to the task requirement information and the target technical data;

[0009] Determining target component ownership information corresponding to the target component according to the task requirement information and the target technical data;

[0010] Determine the task platform corresponding to the target task according to the target component ownership information;

[0011] Allocate the target task to the task platform.

[0012] Optionally, the task requirement information includes data requirement information, and searching a preset technical database for target technical data corresponding to the task requirement information includes:

[0013] Extracting technical keywords from the data requirement information;

[0014] Searching the preset technology database for a number of candidate technology data that matches the technology keyword;

[0015] respectively determining matching degree information between the technical keyword and a plurality of the candidate technical data;

[0016] The target technical data is selected from the plurality of candidate technical data according to the matching degree information.

[0017] Optionally, the task requirement information includes a task template, and determining the target task and the target component corresponding to the target task according to the task requirement information and the target technical data includes:

[0018] Fill the task template with the target technical data to obtain the target task;

[0019] Determining components corresponding to the target technical data according to the target technical data;

[0020] The component corresponding to the target technical data is used as the target component corresponding to the target task.

[0021] Optionally, determining the target component attribution information corresponding to the target component according to the task requirement information and the target technical data includes:

[0022] Determining maturity data corresponding to the target task based on the target technical data;

[0023] Determining the maintenance data corresponding to the target task according to the task requirement information and the target technical data;

[0024] Determining the conversion cycle data corresponding to the target task according to the task requirement information;

[0025] Determining the reusability data corresponding to the target task according to the target technical data;

[0026] Target component attribution information corresponding to the target component is determined according to at least one of the maintenance data, the conversion cycle data, the maturity data, and the reuse data.

[0027] Optionally, the target technology data includes technology usage status information, and determining the maturity data corresponding to the target task based on the target technology data includes:

[0028] Determining the stage indicators of the target task according to the technology usage status information;

[0029] Determine the maturity data corresponding to the target task according to the stage indicator.

[0030] Optionally, the target technical data includes target version data, the task requirement information includes requirement urgency information, and determining the maintenance data corresponding to the target task based on the target technical data and the task requirement information includes:

[0031] Searching the preset technical database for current technical data associated with the target technical data; the current technical data is data having the same function as the target technical data and being in the application stage; the current technical data includes current version data;

[0032] Comparing the current version data with the target version data to obtain version iteration information of the target technical data relative to the current technical data;

[0033] Determine the maintenance data corresponding to the target task according to the version iteration information and the demand urgency information.

[0034] Optionally, the task requirement information includes conversion cycle information, and determining the conversion cycle data corresponding to the target task according to the task requirement information includes:

[0035] The conversion cycle data corresponding to the target task is determined according to the conversion cycle information.

[0036] Optionally, determining the reusability data corresponding to the target task according to the target technical data includes:

[0037] Determining target component data and / or target software data corresponding to the target component according to the target technical data;

[0038] Determining at least one of target supplier data, target test process data, target test tool data, and target document call data corresponding to the target component according to the target component data;

[0039] The reusability data corresponding to the target task is determined according to at least one of the target component data, the target software data, the target supplier data, the target test process data, the target test tool data and the target document call data.

[0040] Optionally, determining the reusability data corresponding to the target task based on at least one of the target component data, the target software data, the target supplier data, the target test process data, the target test tool data, and the target document call data includes:

[0041] Obtaining a plurality of bill of materials data corresponding to different products from the preset technical database; the bill of materials data including component data, software data and supplier data;

[0042] Determining component reuse data based on the frequency of use of the target component data in a plurality of bill of materials data corresponding to different products;

[0043] determining software reuse data according to the frequency of use of the target software data in a plurality of bill of materials data corresponding to different products;

[0044] Determining supplier reuse data based on the frequency of use of the target supplier data in a plurality of bill of materials data corresponding to different products;

[0045] Acquire a plurality of component development data corresponding to different products from the preset technical database; the component development data includes test process data, test tool data, and literature call data during the component development process;

[0046] Determining test process reusability data based on the frequency of use of the target test process data in a plurality of component development data corresponding to different products;

[0047] Determining test tool reusability data based on the frequency of use of the target test tool data in the component development data corresponding to different products;

[0048] Determining document reuse data based on the frequency of use of the target document call data in a plurality of component development data corresponding to different products;

[0049] The reusability data corresponding to the target task is determined based on at least one of the component reusability data, the software reusability data, the supplier reusability data, the test process reusability data, the test tool reusability data, and the literature reusability data.

[0050] Optionally, determining the target component ownership information corresponding to the target component according to at least one of the maintenance data, the conversion cycle data, the maturity data, and the reuse data includes:

[0051] If the maturity data is greater than or equal to a preset first threshold, the maintenance data is greater than or equal to a preset second threshold, the conversion cycle data is greater than or equal to a preset third threshold, and the reuse data is greater than or equal to a preset fourth threshold, then the target component ownership information corresponding to the target component is determined based on the reuse data.

[0052] Optionally, allocating the target task to the task platform includes:

[0053] Determine the technical value data corresponding to the target task based on the target technical data and the current technical data;

[0054] Determining priority information of the target task based on the technical value data;

[0055] The target task is allocated to the task platform according to the priority information.

[0056] Optionally, the target technical data further includes at least one of target performance data, target cost data, and target experience data; the current technical data further includes at least one of current performance data, current cost data, and current experience data; and determining the technical value data corresponding to the target task based on the target technical data and the current technical data includes:

[0057] Comparing the target performance data with the current performance data to obtain performance change information of the target technical data relative to the current technical data;

[0058] Comparing the target cost data with the current cost data to obtain cost change information of the target technical data relative to the current technical data;

[0059] Comparing the target experience data with the current experience data to obtain experience change information of the target technical data relative to the current technical data;

[0060] Determine technical value data corresponding to the target task according to at least one of the performance change information, the cost change information, and the experience change information.

[0061] In a second aspect of the present invention, a task allocation device is provided, comprising:

[0062] Data acquisition module, used to obtain task requirement information;

[0063] A data search module is used to search for target technical data corresponding to the task requirement information in a preset technical database;

[0064] A task construction module, configured to determine a target task and a target component corresponding to the target task based on the task requirement information and the target technical data;

[0065] an ownership determination module, configured to determine target component ownership information corresponding to the target component according to the task requirement information and the target technical data;

[0066] A platform determination module is used to determine the task platform corresponding to the target task according to the target component ownership information;

[0067] The task allocation module is used to allocate the target task to the task platform.

[0068] In a third aspect of the implementation of the present invention, an electronic device is also provided, comprising a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method described above when executed by the processor.

[0069] In a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0070] The embodiments of the present invention have the following advantages:

[0071] In an embodiment of the present invention, by obtaining task requirement information and searching for target technical data corresponding to the task requirement information in a preset technical database, the target task and the target parts corresponding to the target task are determined based on the task requirement information and the target technical data. The present invention improves the matching accuracy of technology and tasks by intelligently matching task requirements with the technical database, and can accurately and quickly construct the target task and determine the target parts. According to the task requirement information and the target technical data, the target parts ownership information corresponding to the target parts is determined. The present invention can accurately identify the ownership information of the parts in the target task. The task platform corresponding to the target task is determined based on the target parts ownership information, and the target task is assigned to the task platform. The present invention can automatically assign the target task to the optimal platform based on the parts ownership information, which can not only reduce manual intervention and shorten the decision-making cycle, but also enhance the adaptability between the target task and the platform, thereby achieving efficient conversion of the target task. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for describing the embodiments or the prior art.

[0073] Figure 1 This is a flowchart of a task allocation method provided by one embodiment of the present invention;

[0074] Figure 2 This is a logic flow chart of task allocation provided by one embodiment of the present invention;

[0075] Figure 3 This is a flowchart of the steps of task evaluation provided by one embodiment of the present invention;

[0076] Figure 4 It is a structural diagram of a task allocation device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, each embodiment of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be understood by those skilled in the art that in each embodiment of the present invention, many technical details are provided to enable the reader to better understand the present invention. However, even without these technical details and various changes and updates based on the following embodiments, the technical solutions claimed in the present invention can be implemented. The division of the following embodiments is for convenience of description and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined with each other and referenced to each other under the premise that there is no contradiction.

[0078] The domestic new energy vehicle industry is currently experiencing rapid development, with accelerating technological innovation and iteration, increasingly fierce competition in the layout of forward-looking technologies, and increasingly diversified industry-university-research collaboration models. Because new energy vehicles involve multiple disciplines, the homogeneity of technological approaches, coupled with fluctuating decision-making cycles during the industrialization process, leads to numerous uncertainties in the allocation of technical tasks.

[0079] At the same time, there are significant differences among OEMs of different sizes (including traditional car companies, new forces with stable sales, and start-ups) in terms of financial strength, market performance, brand influence, and R&D system. This differentiated feature further increases the complexity of the allocation of technical tasks.

[0080] The existing technical task management model is still mainly based on offline management and simple online entry. When faced with new technical tasks with different needs, it cannot achieve rapid matching of new technologies and tasks, and it cannot accurately identify the ownership information of parts in technical tasks, which makes it difficult for technical tasks to be efficiently adapted to different products or platforms.

[0081] Therefore, the present invention provides a task assignment method, device, electronic device, and medium, which can obtain task requirement information, search for target technical data corresponding to the task requirement information in a preset technical database, determine the target task and the target component corresponding to the target task based on the task requirement information and the target technical data, determine the target component ownership information corresponding to the target component based on the task requirement information and the target technical data, determine the task platform corresponding to the target task based on the target component ownership information, and assign the target task to the task platform. By intelligently matching task requirements with a technical database, the present invention can accurately and quickly construct the target task, accurately identify the ownership information of the components in the target task, and automatically assign the target task to the corresponding task platform. This not only reduces manual intervention and shortens the decision-making cycle, but also enhances the adaptability between the target task and the task platform.

[0082] Reference Figure 1 , shows a step flow chart of a task allocation method provided by an embodiment of the present invention.

[0083] In an embodiment of the present invention, the task allocation method can be applied to a task allocation system, which can be a digital management platform based on an intelligent decision-making mechanism for efficiently identifying, evaluating, and allocating technology R&D or production tasks. In an embodiment of the present invention, the task allocation system can be used to construct and allocate target tasks.

[0084] The method may specifically include the following steps:

[0085] Step 101: Obtain task requirement information.

[0086] It should be noted that mission requirement information refers to the core input data that drives the operation of the mission allocation system. This information can include specific technical issues to be addressed, key parameter requirements, current R&D stage or cycle requirements, and required manpower, equipment, and funding. Mission requirement information can be obtained through internal submissions from departments such as R&D and product planning, external input such as partner requirements and policy / standard updates, and market analysis such as competitive technology trends and user feedback.

[0087] In an embodiment of the present invention, task requirement information may be acquired first, wherein the task requirement information may include information on technical requirement dimensions, resource and collaboration dimensions, and business and strategy dimensions required for the target task.

[0088] In specific implementation, the task can be any one of basic research topics, applied R&D projects, technology pre-research tasks, component development tasks, system integration projects, engineering implementation tasks, joint school-enterprise projects, supply chain collaboration tasks, and cross-departmental research projects.

[0089] Step 102: Searching for target technical data corresponding to the task requirement information in a preset technical database.

[0090] It should be noted that a technology database can be a systematic knowledge base for structured storage, management, and retrieval of technology-related data, used to support R&D decision-making, innovation management, and resource optimization. In an embodiment of the present invention, the technology database can include current technology data and prospective data. Among them, current data can be technology data that has been actually verified, is in use, or can be put into use immediately, which can reflect the current state of technology. Prospective technology data is technology data that is in the exploratory stage, not yet mature, but has potential value, and can represent future technology directions.

[0091] In an embodiment of the present invention, target technical data corresponding to the task requirement information may be searched in a preset technical database, wherein the target technical data may be forward-looking data.

[0092] In specific implementation, technical data in the technical database is mainly obtained through internal acquisition and external collaboration:

[0093] Internal acquisition of technical data can include crawling data from internal systems, such as crawling CAD (Computer-Aided Design) / CAE (Computer-Aided Engineering) simulation data and test reports from R&D management systems (PLM). Internal technical documents, patent libraries, and project summaries can be automatically captured from knowledge bases and documents. Process parameters and material data can also be extracted from production and supply chain systems such as MES (Manufacturing Execution System) and ERP (Enterprise Resource Planning).

[0094] Internal acquisition of technical data can also include contributions from specialized groups. For example, the platform R&D group can provide standardized technical modules (such as electric drive platforms and battery management system architectures), the technology reserve group can provide pre-research technical results (such as new material experimental data and undisclosed innovative solutions), and the test and verification group can submit reliability test data (such as durability reports and extreme environment performance).

[0095] Internal acquisition of technical data can also include obtaining technical data from specialized teams. These technical data can be specific R&D or technical breakthrough requirements proposed by specialized technical teams within the company (such as the Battery Research Institute or the Intelligent Driving Division). These requirements can be used to obtain pre-production technical data reserves that the company has prepared in advance to meet specific R&D or technical breakthrough requirements in preparation for future competition or technological iterations.

[0096] External collaboration on technical data can include resource exchange and data acquisition. Supplier data can be acquired, such as material parameters and component specifications provided by partners. Joint development results can be acquired, such as technical reports or prototype data produced jointly with universities and research institutes. Industry alliance data can also be acquired, such as standard data shared by industry alliances.

[0097] External collaboration on technical data can also include targeted data collection. Competitor technology updates (such as teardown reports and patent analysis) can be obtained through legal channels. Algorithmic models or experimental data from platforms like GitHub and IEEE can be integrated through open source technology. Data can also be obtained through third-party databases, such as commercial databases (such as material property libraries and regulatory certification libraries).

[0098] In specific implementations, technical data can be differentiated based on its source and stored in a structured manner. For example, technical data obtained from universities can be associated with information such as the subject, institution, and team, and saved as structured data. Technical data obtained from research institutions can be associated with information such as the subject, institution, and team, and saved as structured data. Technical data obtained from suppliers can be associated with information such as the subject, localization status, and supplier, and saved as structured data.

[0099] Step 103: Determine a target task and a target component corresponding to the target task according to the task requirement information and the target technical data.

[0100] In an embodiment of the present invention, a target task and a target component corresponding to the target task can be determined based on the task requirement information and the target technical data. The target task can be the task corresponding to the task requirement information, and the target task can be the task that requires the use of the target technical data. The target component can be a physical component or software component that needs to be designed or improved to achieve the target task.

[0101] In practice, the target task and target component can be directly linked through technical parameters and functional requirements. For example, if the target task is to improve motor efficiency, the target component could be the stator winding material.

[0102] Step 104 : determining target component ownership information corresponding to the target component according to the task requirement information and the target technical data.

[0103] It should be noted that the target component ownership information may be key attribute data that identifies the entity responsible for component development or the entity responsible for component use.

[0104] In the embodiment of the present invention, the target component attribution information corresponding to the target component can be determined according to the task requirement information and the target technical data.

[0105] Step 105: Determine the task platform corresponding to the target task according to the target component ownership information.

[0106] It should be noted that the task platform may refer to a technical implementation carrier or an organizational unit for executing, managing, and collaboratively completing a target task. In an embodiment of the present invention, the task platform may be used to execute a target task.

[0107] In the embodiment of the present invention, the task platform corresponding to the target task can be determined according to the target component ownership information.

[0108] In specific implementations, the task platform can also be a task domain. A domain is a logical boundary divided according to specific rules, which is used to classify and manage technologies, resources or tasks to ensure efficient collaboration and precise matching.

[0109] The target component ownership information may be information about the core assembly / component that reflects the ownership of the target component. Taking the new energy vehicle field as an example, the task platform corresponding to the target task may be determined based on the core assembly / component according to Table 1.

[0110] As shown in Table 1, the correspondence between mission platforms and their components in the new energy vehicle field is shown. Taking the new energy vehicle field as an example, the mission platform can include multiple platforms such as chassis platform, power platform, intelligent driving platform, intelligent cockpit platform, body platform, and electronic and electrical platform, and each platform has its corresponding core assembly / component. It should be noted that the core assembly / component corresponding to each platform in Table 1 is only an example. In actual application, each platform may include these core assemblies / components, but may also include other components corresponding to this platform.

[0111] Table 1 Mission platforms and components in the new energy vehicle field

[0112]

[0113] Step 106: Allocate the target task to the task platform.

[0114] In the embodiment of the present invention, the target task may be assigned to a task platform.

[0115] The present invention obtains task requirement information and searches for target technical data corresponding to the task requirement information in a preset technical database, and determines the target task and the target parts corresponding to the target task based on the task requirement information and the target technical data. The present invention improves the matching accuracy of technology and tasks by intelligently matching task requirements with the technical database, and can accurately and quickly construct the target task and determine the target parts. According to the task requirement information and the target technical data, the target parts ownership information corresponding to the target parts is determined. The present invention can accurately identify the ownership information of the parts in the target task. The task platform corresponding to the target task is determined based on the target parts ownership information, and the target task is assigned to the task platform. The present invention can automatically assign the target task to the optimal platform based on the ownership information of the target parts, which can not only reduce manual intervention and shorten the decision-making cycle, but also enhance the adaptability between the target task and the platform, thereby achieving efficient conversion of the target task.

[0116] In an optional embodiment of the present invention, the task requirement information includes data requirement information, and step 102 further includes the following sub-steps:

[0117] S111: extracting technical keywords from the data requirement information;

[0118] S112: searching the preset technology database for a plurality of candidate technology data that matches the technology keyword;

[0119] S113: Determine the matching degree information between the technical keyword and the candidate technical data respectively;

[0120] S114: Selecting the target technical data from the candidate technical data according to the matching degree information.

[0121] It should be noted that data requirement information can refer to the structured data description required to complete a specific task during technology research and development or product development. This information is used to clarify technical goals, resource requirements, and constraints, and is the core input for task allocation and database retrieval. In embodiments of the present invention, technical keywords can be extracted from data requirement information.

[0122] Technical keywords can be core terms or phrases extracted from technical requirement information to accurately characterize the technical direction, performance requirements, or resource types of the R&D task. In an embodiment of the present invention, technical data can be acquired based on technical keywords.

[0123] In an embodiment of the present invention, technical keywords can be extracted from data requirement information. A predetermined technical database is then searched for candidate technical data that matches the technical keywords. Matching information between the technical keywords and the candidate technical data is determined. Target technical data is then selected from the candidate technical data based on the matching information. The matching information can represent the degree of match between the candidate technical data and the technical keywords. The data requirement information can represent the data desired to be acquired by the task requirement information. The candidate technical data can be a number of technical data that match the technical keywords.

[0124] In a specific implementation, natural language processing (NLP) or a rule engine can be used to extract technical keywords from the data requirement information. Then, candidate technical data associated with the keywords is retrieved from the technical database based on the textual similarity between the technology name, function description, and the technical keywords. The degree of match between each candidate technical data and the technical keywords is determined separately. Candidate technical data with a match exceeding a preset value (e.g., >90%) can be selected as target technical data.

[0125] In an optional embodiment of the present invention, the task requirement information includes a task template, and step 103 further includes the following sub-steps:

[0126] S121: Filling the task template with the target technical data to obtain the target task;

[0127] S122: Determine components corresponding to the target technical data according to the target technical data;

[0128] S123: Using the component corresponding to the target technical data as the target component corresponding to the target task.

[0129] It should be noted that a task template may refer to a predefined standardized task framework, which may include reusable structures, fields, and rules and may be used to quickly generate specific task instances. In an embodiment of the present invention, a target task may be constructed using a task template.

[0130] The target task may refer to an executable task instance generated after filling a task template with technical data, and may include specific implementation requirements and resource allocation. In an embodiment of the present invention, the target task may be constructed to implement the allocation of a new task.

[0131] In an embodiment of the present invention, the target technical data can be used to fill in the task template to obtain the target task, and then the components corresponding to the target technical data are determined based on the target technical data, and then the components corresponding to the target technical data are used as the target components corresponding to the target task.

[0132] In the specific implementation, you can call a predefined task template, automatically fill in technical data into the template fields, and output a structured target task.

[0133] In specific implementations, the implementation carriers in the target technical data can be parsed. For example, if a technical solution needs to be implemented through specific components, it can be automatically mapped to the corresponding components in the product BOM (Bill of Materials).

[0134] The existing technical task management method lacks a method for accurately identifying the maintenance data of new technical tasks. In addition, the identification / decision-making cycle is long and the task matching accuracy is insufficient. It cannot systematically analyze key dimensions such as the maturity, conversion cycle, and component reusability of the target task, making it difficult to efficiently adapt the technology to different products / platforms.

[0135] In an optional embodiment of the present invention, determining the target component attribution information corresponding to the target component according to the task requirement information and the target technical data includes:

[0136] S131: Determine maturity data corresponding to the target task based on the target technical data;

[0137] S132: Determine the maintenance data corresponding to the target task according to the task requirement information and the target technical data;

[0138] S133: Determine the conversion cycle data corresponding to the target task according to the task requirement information;

[0139] S134: Determine the reusability data corresponding to the target task according to the target technical data;

[0140] S135: Determine target component ownership information corresponding to the target component according to at least one of the maintenance data, the conversion cycle data, the maturity data, and the reuse data.

[0141] It should be noted that maturity data can reflect the feasibility evaluation of the target technology at the current R&D stage.

[0142] Sustainability data can represent the ability of the technology / components required for the target mission to maintain availability during the life cycle.

[0143] Conversion cycle data can represent the estimated time cost from technical solutions to mass production applications.

[0144] Reusability data can reflect the potential for cross-platform or cross-model commonality of technologies / components.

[0145] In an embodiment of the present invention, maintenance data corresponding to the target task can be determined based on task requirement information and target technical data; conversion cycle data corresponding to the target task can be determined based on task requirement information; maturity data and reuse data corresponding to the target task can be determined based on target technical data; and target component ownership information corresponding to the target component can be determined based on at least one of the maintenance data, conversion cycle data, maturity data, and reuse data.

[0146] In a specific implementation, the maintenance data may be decay evaluation data.

[0147] In specific implementation, first, maintenance data can be generated based on mission requirement information and target technology data to evaluate the sustainability of technical solutions (such as technical stability and technology iteration risks). Secondly, conversion cycle data can be extracted from mission requirements to quantify the time cost of technology implementation (such as the standard cycle from laboratory verification to mass production). At the same time, maturity data (such as TRL level) and reusability data (such as cross-platform adaptability) can be obtained based on target technology data. Ultimately, these four types of data can be combined to determine component ownership information.

[0148] The present invention significantly improves the management efficiency of new target tasks by constructing a multi-dimensional intelligent evaluation system. Traditional methods are often limited to a single technology maturity assessment, while this solution innovatively introduces key dimensions such as maintenance, conversion cycle and reuse to comprehensively evaluate target tasks. Among them, maintenance data can reflect the life cycle status of the target task and can effectively predict iteration risks; conversion cycle data can quantify the time cost of landing the target task and optimize the resource scheduling rhythm; reuse evaluation opens up a cross-platform technology sharing channel. Through the collaborative analysis of four-dimensional data, the optimal component ownership strategy can be automatically recommended, which can not only ensure the strategic nature of the forward-looking technology layout, but also ensure the feasibility of mass production projects, realizing the paradigm upgrade from experience-driven to data-driven.

[0149] In an optional embodiment of the present invention, the target technology data includes technology usage status information, and step S131 further includes the following steps:

[0150] S141: Determine the stage indicator of the target task according to the technology usage status information;

[0151] S142: Determine maturity data corresponding to the target task according to the stage indicator.

[0152] It should be noted that the technology usage status information can represent the actual application status of the target technology data in the current task, reflecting the real-time position of the target technology data throughout the entire cycle from development to exit. In an embodiment of the present invention, the stage indicators of the target task can be determined based on the technology usage status information.

[0153] Phase indicators can quantify the degree of achievement of key nodes in the process of technology development or productization, and are used to objectively evaluate phase results. In an embodiment of the present invention, maturity data corresponding to the target task can be determined based on the phase indicators.

[0154] In the embodiment of the present invention, the stage indicator of the target task can be determined according to the technology usage status information, and the maturity data corresponding to the target task can be determined according to the stage indicator.

[0155] In practice, maturity data can be assessed using the TRL (Technology Readiness Level) model. In the new energy vehicle sector, the scoring and stage classification can be adjusted based on each OEM's actual forward-looking technology development scale, platform universality, and product strategy planning. The specific number of TRL levels and scoring coefficients can also be adjusted by each OEM. Maturity data can be calculated based on Table 2. Table 2 shows how maturity data corresponding to target tasks is calculated.

[0156] Table 2 Maturity data calculation method

[0157]

[0158]

[0159] In a specific implementation, the stage indicators of the target task can be determined based on the technology usage status information, and the maturity data corresponding to the target task can be determined based on the stage indicators.

[0160] If the technology usage status information indicates that the target technology data is at the initial level of technology readiness, and cooperation at this stage needs to consider cost, cycle and feasibility, then the stage indicator at this time is based on the basic principle discovery, the corresponding stage level is TRL1, and the maturity data A is 0.8.

[0161] If the technology usage status information indicates that the target technology data is in the target technology establishment stage and is in the initial stage of simple application, and the cooperation at this stage can take up the place of results, then the stage indicator at this time is that a technical solution has been formed, the corresponding stage level is TRL2, and the maturity data A is 1.2.

[0162] If the technology usage status information indicates that the target technology data is in the stage of starting the actual subsystem / product development of the target technology data, including analysis and experimental research, and starting theoretical verification work, then the stage indicator at this time is that the target technology function has been analyzed and experimented, the corresponding stage level is TRL3, and the maturity data A is 2.

[0163] If the technology usage status information indicates that the target technology data has entered the prototype device testing phase, and the simulated prototype is placed in the application environment for testing, the stage indicator at this point is the formation of a prototype and the completion of prototype verification, corresponding to the stage level of TRL4 and the maturity data A of 1.6.

[0164] If the technology usage status information indicates that the target technology data has been tested with the enterprise at the product application level prototype system, which is a key stage before mass production, then the stage indicator at this time is that it has been matched and verified with external cooperation, and the corresponding stage level is TRL5, and the maturity data A is 0.8.

[0165] If the technology usage status information indicates that the target technology data has formed mass production cooperation with the enterprise, and it is necessary to consider the protection of related sub-technologies while evaluating parallel sub-technological substitutions, then the stage indicator at this time is mass production application, the corresponding stage level is TRL6, and the maturity data A is 0.4.

[0166] In specific implementations, a multi-dimensional weighted evaluation method may also be used to determine maturity data.

[0167] Maturity data can be obtained by building an evaluation system that includes technology, business, and resources. First, three dimensions are established: technical feasibility (weight 40%), market adaptability (weight 30%), and resource security (weight 30%). Specific indicators are set up under these dimensions, such as patent coverage, supply chain maturity, and R&D team configuration. The comprehensive maturity value is calculated through expert scoring (0-10 points) combined with the analytic hierarchy process (AHP). For example, a battery technology has a patent coverage of 80% (8 points for technology), a market competitor match of 60% (6 points for business), and a production line transformation cycle of 12 months (7 points for resources). The final maturity is 7.2 points (out of 10 points). This method can be used for strategic-level project evaluations that need to balance technical risks and commercial value.

[0168] In a specific implementation, a dynamic learning correction model may also be used to determine maturity data.

[0169] Machine learning models can be trained based on historical project data, and maturity can be dynamically corrected by real-time monitoring of technological evolution. Input parameters may include: technology iteration speed (such as the number of experiments per week), defect convergence curve (such as the downward trend of failure rate), resource input intensity (such as average working hours per person), etc. The system automatically compares the historical development paths of similar technologies and outputs a maturity prediction value with a confidence interval. For example, when the monthly test failure rate of a certain electric drive technology decreases by 15%, the model will automatically increase the TRL level. This method can be used in cutting-edge technology fields with rapid iteration, and can significantly reduce the evaluation bias caused by the lag of manual experience.

[0170] In an optional embodiment of the present invention, the target technical data includes target version data, the task requirement information includes requirement urgency information, and step S132 further includes the following steps:

[0171] S151: searching the preset technology database for current technology data associated with the target technology data; the current technology data is data that has the same function as the target technology data and is in the application stage; the current technology data includes current version data;

[0172] S152: Compare the current version data with the target version data to obtain version iteration information of the target technical data relative to the current technical data;

[0173] S153: Determine the maintenance data corresponding to the target task according to the version iteration information and the demand urgency information.

[0174] It should be noted that the target version data can be one of the core attributes of the target technology data, used to identify the iteration status and evolution stage of the target technology, reflecting its maturity and applicability in different R&D or application cycles. In embodiments of the present invention, version iteration information can be determined using the target version data.

[0175] Requirement urgency information can be one of the key attributes of task requirement information, used to quantify the timeliness requirements of technology development or product implementation, and guide resource allocation priorities and decision path selection. In embodiments of the present invention, the urgency of the target task can be determined using the requirement urgency information.

[0176] In an embodiment of the present invention, current technical data associated with target technical data can be searched from a preset technical database. Current technical data is data that has the same function as the target technical data and is in the application phase. Current technical data includes current version data. Current version data may refer to version information of the current technical data.

[0177] The current version information and the target version information can be compared to obtain version iteration information of the target technical data relative to the current technical data, and the maintenance data corresponding to the target task can be determined based on the version iteration information and the demand urgency information.

[0178] In specific implementation, version iteration information can be reflected by the technical stability score. Technical stability represents the technical attenuation of target technical data within a certain industry cycle. Demand urgency information can be reflected by the implementation urgency score. Implementation urgency represents the urgency of the technology in the actual operation of the OEM.

[0179] The maintenance data can be calculated with reference to Table 3. Referring to Table 3, a calculation method of the maintenance data corresponding to the target task is shown.

[0180] Table 3 Maintenance data calculation method

[0181]

[0182] The maintenance data can be equal to the sum of the version iteration information and the demand urgency information, that is, the maintenance data can be equal to the sum of the technical stability score and the implementation urgency score.

[0183] Among them, the technical stability score is set to three levels: technical stability a1, technical stability a2, and technical stability a3; the implementation urgency score is set to three levels: implementation urgency b1, implementation urgency b2, and implementation urgency b3.

[0184] The scoring rules for technical stability and implementation urgency are as follows:

[0185] Parallel level:

[0186] Technology stability a1: Technology is in line with mainstream but lacks breakthrough innovation (assigned 0-0.3 points)

[0187] Urgency of implementation b1: Difficulty in promoting mass production. (Assigned 0-0.3 points)

[0188] Breakthrough level:

[0189] Technical stability a2: Technology is 0.5-1.5 generations ahead of the industry and possesses differentiated competitiveness (valued at 0.4-0.6 points)

[0190] Urgency of realization b2: Can be promoted to mass-produced products within the technology cycle. (Assigned 0.4-0.6 points)

[0191] Definition level:

[0192] Technical stability a3: Technology is more than 1.5 generations ahead and defines the future development direction; (assigned 0.7-1 points)

[0193] Urgency b3: Ability to promote to platform-level products within the technology cycle. (Assign 0.7-1 points)

[0194] In specific implementations, maintenance data can also be determined through a technology development trajectory model. A technology development trajectory model can be constructed to analyze the stage of the target task within the industry's evolution. First, indicators such as patent application trends, market penetration, and academic research interest in the technology field are collected to create a complete technology life cycle curve (including the introduction, growth, maturity, and decline phases). By comparing the position difference between the target task and the industry benchmark curve, its maintenance data can be automatically determined.

[0195] In practice, the maintenance data can also be determined by the maturity of the industrial chain. By constructing a supply chain stability index (0% to 100%), the system automatically lowers the maintenance data when the number of key material suppliers falls below a preset number or equipment relies on imports.

[0196] Here, the maintenance degree data is divided into three levels: maintenance degree data B1, maintenance degree data B2, and maintenance degree data B3.

[0197] The target task's maintenance data corresponds to the following maintenance levels:

[0198] When the maintenance data B1≤0.6, the maintenance data is at the parallel level. At this time, the technical competition and implementation difficulties of the target task are required, and the platform needs to re-evaluate;

[0199] When the maintenance data is 0.6<B2<1.3, the maintenance data is at the breakthrough level. At this time, the target task has certain competitiveness and certain implementation value, and the platform needs to evaluate again;

[0200] When the maintenance data B3 ≥ 1.3, the maintenance data is at the definition level. At this time, the target task is a competitive technology and has the potential to be promoted to platform products.

[0201] In an optional embodiment of the present invention, the task requirement information includes conversion cycle information, and step S133 further includes the following steps:

[0202] S161: Determine the conversion cycle data corresponding to the target task according to the conversion cycle information.

[0203] It should be noted that the conversion cycle information can refer to the time required for the target technology data to go from constructing the target task to completing the implementation of the target task, which can reflect the time cost of the technology industrialization process.

[0204] In an embodiment of the present invention, the conversion cycle data corresponding to the target task can be determined based on the conversion cycle information. If the current technical data contains technologies related to the target technical data, the conversion cycle can be adaptively shortened. If the current technical data does not contain technologies related to the target technical data, the conversion cycle can be adaptively lengthened.

[0205] In a specific implementation, the conversion cycle data can be calculated with reference to Table 4. Referring to Table 4, a calculation method for the conversion cycle data corresponding to the target task is shown.

[0206] Table 4 Calculation method of conversion cycle data

[0207]

[0208] Taking the new energy vehicle field as an example, if the conversion cycle information indicates that the target task can be installed on the vehicle within 3-12 months, and the production line compatibility is greater than 90%, and the cost fluctuation is less than 5%, then the scoring coefficient at this time is the mass production adaptation layer, and the conversion cycle data C is 0.8-1.

[0209] If the conversion cycle information indicates that the target task development cycle is 18 months ± 6 months, and > 50% requires joint development with suppliers, and the cost fluctuation is ± 20%, then the scoring coefficient at this time is the engineering conversion layer, and the conversion cycle data C is 0.4-0.7.

[0210] If the conversion cycle information indicates continuous investment of more than 2-5 years, the strength of professional barriers is greater than 50%, and the cost fluctuation is greater than 30% (including R&D expenses), then the scoring coefficient at this time is the basic research layer, and the conversion cycle data C is 0.1-0.3.

[0211] In specific implementation, the conversion cycle data can also be determined by using the data analogy method based on historical projects. A conversion cycle prediction model can be established by analyzing the implementation data of historical projects in the same field or with similar technical characteristics. In specific implementation, first build a historical project database containing dimensions such as technical field, R&D stage, team size, and resource investment. Then extract the key characteristic parameters of the target technology and match them with the database to screen out reference projects with similarity reaching the threshold. The system automatically calculates the weighted average of the actual conversion cycles of these reference projects. The weights are adjusted according to the technical similarity and time decay coefficient, and the predicted conversion cycle is obtained after weighting by similarity. The method of determining conversion cycle data based on the data analogy method of historical projects is suitable for fields with mature technology accumulation and can effectively reflect the uncertainty factors in the actual engineering environment.

[0212] In an optional embodiment of the present invention, step S134 further includes the following steps:

[0213] S171: Determine target component data and / or target software data corresponding to the target component according to the target technical data;

[0214] S172: Determine at least one of target supplier data, target test process data, target test tool data, and target document call data corresponding to the target component based on the target component data;

[0215] S173: Determine the reusability data corresponding to the target task based on at least one of the target component data, the target software data, the target supplier data, the target test process data, the target test tool data, and the target document call data.

[0216] It should be noted that the target component data may refer to physical parameters such as the target component's material code, name, geometric dimensions, material properties, interface standards, and other physical parameters, as well as engineering constraints such as reliability requirements (such as life cycle) and environmental adaptability (such as temperature range). In embodiments of the present invention, the target component data may include the target component's material code or name.

[0217] Software data refers to code modules, algorithmic logic, or digital functional requirements related to the target component, including architecture design (such as AUTOSAR compatibility), protocol standards (such as CAN communication protocol), performance parameters (such as response delay <50ms), etc. In embodiments of the present invention, target software data may include software data associated with the target component.

[0218] Supplier data is data on suppliers selected based on target component requirements, including technical compatibility (e.g., experience in mass production of silicon carbide devices), production capacity guarantees (e.g., monthly supply of 100,000 units), and quality management systems (e.g., IATF 16949 certification). In embodiments of the present invention, target supplier data may include supplier data associated with the target component.

[0219] Test process data is a standardized testing procedure designed to verify whether a target component or software meets technical requirements. It includes test items (such as high-low temperature cycling testing), acceptance criteria (such as charge and discharge efficiency degradation of less than 5%), and execution sequence (such as HIL testing followed by vehicle verification). In embodiments of the present invention, the target test process data may be the test process data for testing the target component.

[0220] Test tool data refers to the equipment, software, and environment configuration information required to complete the test process, such as charging and discharging equipment (such as the Keysight BT2200) used in battery testing, autonomous driving simulation tools (such as CARLA), and data acquisition cards (such as NIPXIe). In embodiments of the present invention, target test tool data may include test tool data associated with target components.

[0221] Literature retrieval data refers to reference materials such as patents, papers, or technical reports related to the target technology. The literature retrieval data may include the citation source, a technical relevance score (e.g., an 80% match with the target technology), and an applicability conclusion (e.g., a material has been verified to increase cycle life by 20%). In an embodiment of the present invention, the target literature retrieval data may include literature retrieval data associated with the target component.

[0222] In an embodiment of the present invention, the target component data and / or target software data corresponding to the target component can be determined based on the target technical data. Then, at least one of the target supplier data, target test process data, target test tool data, and target document call data corresponding to the target component can be determined based on the target component data. Finally, the reusability data corresponding to the target task can be determined based on at least one of the target component data, target software data, target supplier data, target test process data, target test tool data, and target document call data. In particular, if only the target software data corresponding to the target component can be determined based on the target technical data, the reusability data corresponding to the target task can be directly determined based on the target software data.

[0223] In an optional embodiment of the present invention, step S173 further includes the following steps:

[0224] S181: Obtaining a plurality of bill of materials data corresponding to different products from the preset technical database; the bill of materials data includes component data, software data, and supplier data;

[0225] S182: Determine component reuse data based on the frequency of use of the target component data in the plurality of bills of materials data corresponding to different products;

[0226] S183: Determine software reuse data based on the frequency of use of the target software data in the plurality of bill of materials data corresponding to different products;

[0227] S184: Determine supplier reuse data based on the frequency of use of the target supplier data in the plurality of bill of materials data corresponding to different products;

[0228] In an embodiment of the present invention, a plurality of bill of materials data corresponding to different products can be obtained from a preset technical database, the bill of materials data including component data, software data, and supplier data. The bill of materials corresponding to different products may include or exclude target components.

[0229] In an embodiment of the present invention, component reuse data can be determined based on the frequency of use of target component data in several bill of materials data corresponding to different products, wherein the component reuse data represents the reuse rate of the target component in the bill of materials corresponding to different products.

[0230] In an embodiment of the present invention, software reuse data can be determined based on the frequency of use of target software data in a number of bills of materials corresponding to different products. The software reuse data represents the reuse rate of the target software in the bills of materials corresponding to different products.

[0231] In an embodiment of the present invention, supplier reuse data can be determined based on the frequency of use of target supplier data in a number of bills of materials corresponding to different products. The supplier reuse data represents the reuse rate of the supplier in the bills of materials corresponding to different products.

[0232] S185: Acquire component development data corresponding to a plurality of different products from the preset technical database; the component development data includes test process data, test tool data, and literature call data during the component development process;

[0233] S186: Determine test process reusability data based on the frequency of use of the target test process data in the component development data corresponding to different products;

[0234] S187: Determine test tool reusability data based on the frequency of use of the target test tool data in the component development data corresponding to different products;

[0235] S188: Determine document reuse data based on the frequency of use of the target document call data in the component development data corresponding to different products;

[0236] In an embodiment of the present invention, component development data corresponding to a number of different products can be obtained from a preset technical database; the component development data includes test process data, test tool data, and literature call data during the component development process.

[0237] In an embodiment of the present invention, test process reuse data can be determined based on the frequency of use of target test process data in component development data corresponding to different products. The test process reuse data represents the reuse rate of the test process in component development data corresponding to different products.

[0238] In an embodiment of the present invention, test tool reuse data can be determined based on the frequency of use of target test tool data in component development data corresponding to different products. The test tool reuse data represents the reuse rate of the test tool in component development data corresponding to different products.

[0239] In an embodiment of the present invention, document reuse data can be determined based on the frequency of use of target document call data in component development data corresponding to different products. The document reuse data represents the reuse rate of document call data in component development data corresponding to different products.

[0240] S189: Determine the reusability data corresponding to the target task based on at least one of the component reusability data, the software reusability data, the supplier reusability data, the test process reusability data, the test tool reusability data, and the literature reusability data.

[0241] In an embodiment of the present invention, the reusability data corresponding to the target task can be determined based on at least one of component reusability data, software reusability data, supplier reusability data, test process reusability data, test tool reusability data and literature reusability data.

[0242] In a specific implementation, the multiplexing data may be calculated with reference to Table 5. Referring to Table 5, a calculation method of the multiplexing data corresponding to the target task is shown.

[0243] Table 5 Calculation method of reuse data

[0244]

[0245] In a specific implementation, the component reuse data can be the hardware reuse rate: the weight score is 25%, representing the proportion of shared components (such as motors / controllers / sensors);

[0246] Software reuse data can be software reuse rate: the weight score is 20%, representing the degree of sharing of basic code / algorithm modules;

[0247] The test process reuse data can be the development cycle overlap: the weight score is 15%, which represents the proportion of time reused in the verification test / calibration process;

[0248] Supplier reuse data can be supply chain reuse: the weight score is 25%, representing supplier overlap and material commonality;

[0249] The test tool reuse data can be test verification reuse: the weight score is 10%, representing the degree of sharing of test sites / simulation models / diagnostic tools;

[0250] Literature reuse data can be the knowledge sedimentation reuse: the weight score is 5%, representing the patent / technical document / experience database call rate;

[0251] In specific implementations, the evaluation dimensions and weight ratios here can be adjusted according to the specific architecture and R&D situation of different R&D / development systems. The scores corresponding to the above evaluation dimensions are all between 0 and 1. If the target component cannot obtain data in one of the above evaluation dimensions, the score of this evaluation dimension is 1. In other words, if it is impossible to obtain data for all evaluation dimensions in the component reuse data, software reuse data, supplier reuse data, test process reuse data, test tool reuse data, and literature reuse data corresponding to the target component, as long as there is data for any one of the evaluation dimensions, the calculation of the reuse data D can be realized.

[0252] In a specific implementation, the multiplexing data may also be determined with reference to Table 6. Referring to Table 6, a method for determining the multiplexing data corresponding to the target task is shown.

[0253] Table 6 Methods for determining reuse data

[0254]

[0255] Four levels of reuse data (D) and their corresponding technical reuse levels and cost-effectiveness are defined.

[0256] The first level (reusability data D is between 0.8-1) means that the target task can fully reuse the existing technology platform and can be used for a long time without major adjustments. It can also be included in the standardized module library for subsequent projects to call. It is expected to reduce costs by more than 30%, indicating that the target task can be used for the iterative upgrade of mature technologies.

[0257] The second level (reusability data D is between 0.6-0.8) indicates that the main body of the target task can be reused, but local adaptation and optimization (such as interface adjustment and parameter reconfiguration) are required to meet new requirements. The cost reduction is 15-25%, indicating that the target task can be used in scenarios with similar technical architecture but expanded functions.

[0258] The third level (reusability data D is between 0.4-0.6) reflects that the target task requires customized development, only core components (such as basic algorithms and key materials) can be reused, and the rest need to be redesigned. The cost reduction effect is limited (5-10%), indicating that the target task can be used in situations where the technical route is partially inherited but the application scenarios are quite different.

[0259] The fourth level (reuse data D is between 0-0.4) means that the target task needs to be developed almost independently, and only the underlying architecture (such as communication protocols and basic simulation models) can be reused. The cost is difficult to estimate and prone to overspending. It can be said that the target task is a technological gap or a disruptive innovation project.

[0260] In specific implementations, reuse data can also be used to analyze cross-components between different platforms. When analyzing cross-components between the body platform and the smart cockpit platform, the reuse data D can also be the average sum of the reuse data of the target component across different platforms. For example, luminous fabric belongs to both the body platform and the smart cockpit platform in terms of functional development. When comprehensively scoring the body platform and the smart cockpit platform, the reuse data can be the average sum of the body platform reuse data and the smart cockpit platform reuse data. Similarly, when the number of associated cross-platforms is n, the reuse data can be (D1+D2+D3+…+Dn) / n. Among them, D1, D2, D3…Dn are the reuse data of different platforms.

[0261] In an optional embodiment of the present invention, step S135 further includes the following steps:

[0262] S191: If the maturity data is greater than or equal to a preset first threshold, and the maintenance data is greater than or equal to a preset second threshold, and the conversion cycle data is greater than or equal to a preset third threshold, and the reuse data is greater than or equal to a preset fourth threshold, then determine the target component ownership information corresponding to the target component based on the reuse data.

[0263] In an embodiment of the present invention, if the maturity data is greater than or equal to a preset first threshold, the maintenance data is greater than or equal to a preset second threshold, the conversion cycle data is greater than or equal to a preset third threshold, and the reuse data is greater than or equal to a preset fourth threshold, the target component attribution information corresponding to the target component is determined based on the reuse data. The first, second, third, and fourth thresholds can all be set based on actual circumstances.

[0264] In an embodiment of the present invention, if the maturity data is greater than or equal to a preset first threshold, or the maintenance data is greater than or equal to a preset second threshold, or the conversion cycle data is greater than or equal to a preset third threshold, or the reuse data is greater than or equal to a preset fourth threshold, then after system review, the target component ownership information corresponding to the target component can be determined based on the reuse data.

[0265] In an optional embodiment of the present invention, step 106 further includes the following steps:

[0266] S201: Determine technical value data corresponding to the target task based on the target technical data and the current technical data;

[0267] S202: Determine priority information of the target task according to the technical value data;

[0268] S203: Allocate the target task to the task platform according to the priority information.

[0269] It should be noted that the technical value data can be a comprehensive quantitative assessment of the technological advancement, market potential, and feasibility of the target task, and can be derived based on a comparative analysis of the target technology data and current technology data. In embodiments of the present invention, the technical value data can be used to determine the execution priority of the target task.

[0270] The priority information may be a result of evaluating the target task based on the technical value data. In the embodiment of the present invention, the priority information may be used to guide the allocation of the target task.

[0271] In an embodiment of the present invention, technical value data corresponding to a target task can be determined based on target technical data and current technical data, priority information of the target task can be determined based on the technical value data, and the target task can be assigned to a task platform based on the priority information, wherein the priority information indicates the execution priority of the target task.

[0272] In an optional embodiment of the present invention, the target technical data includes at least one of target performance data, target cost data, and target experience data, and the current technical data includes at least one of current performance data, current cost data, and current experience data. Step S201 further includes the following steps:

[0273] S211: Compare the target performance data with the current performance data to obtain performance change information of the target technical data relative to the current technical data;

[0274] S212: Compare the target cost data with the current cost data to obtain cost change information of the target technical data relative to the current technical data;

[0275] S213: Compare the target experience data with the current experience data to obtain experience change information of the target technical data relative to the current technical data;

[0276] S214: Determine technical value data corresponding to the target task according to at least one of the performance change information, the cost change information, and the experience change information.

[0277] It should be noted that target performance data refers to a set of key performance parameters of the technical solution to be evaluated, which may include quantitative indicators (such as cruising range, charging speed, thermal efficiency, etc.) and qualitative requirements (such as NVH level, reliability standards, etc.). For example, for electric vehicle motors, target performance data may include peak power (200kW), efficiency MAP (>95% interval share), etc. In embodiments of the present invention, target performance data may reflect the performance of target technical data.

[0278] The current performance data may refer to the performance benchmark data of the currently mass-produced or mature application technology. In the embodiment of the present invention, the current performance data may reflect the performance of the current technology data.

[0279] Target cost data can refer to an estimate of the full lifecycle cost of a new technology solution, covering dimensions such as R&D investment (such as mold development costs), BOM costs (such as battery cell unit price), and manufacturing costs (such as labor hours consumed). In embodiments of the present invention, target cost data can reflect the cost of target technology data.

[0280] The current cost data may refer to actual cost statistics of existing technical solutions. In the embodiment of the present invention, the current cost data may reflect the cost of current technical data.

[0281] Target experience data can refer to the improvement in the perceived value of the technical solution to the end user, including subjective evaluation indicators (such as the cabin interaction fluency score) and objective experience parameters (such as the voice wake-up response time of 500ms). In this embodiment of the present invention, the target experience data can reflect the cost of the target experience data.

[0282] Current experience data may refer to actual user experience feedback from existing technologies, and may be derived from market research (e.g., a satisfaction survey score of 82 points) or measured data (e.g., a current HUD field of view angle of 7°). In embodiments of the present invention, current experience data may reflect the cost of current experience data.

[0283] In an embodiment of the present invention, the target performance data and the current performance data may be compared to obtain performance change information of the target technical data relative to the current technical data. The performance change information may refer to a differential analysis result obtained by comparing the target performance data with the current performance data.

[0284] In an embodiment of the present invention, the target cost data and the current cost data can be compared to obtain cost change information of the target technology data relative to the current technology data, wherein the cost change information may refer to the cost difference between the target technology and the current technology.

[0285] In an embodiment of the present invention, the target experience data and the current experience data may be compared to obtain experience change information of the target technical data relative to the current technical data. The experience change information may refer to user experience upgrade points identified by comparing the target and current experience data.

[0286] In an embodiment of the present invention, technical value data corresponding to the target task may be determined based on at least one of performance change information, cost change information, and experience change information.

[0287] In a specific implementation, the technical value data can be calculated with reference to Table 8. Referring to Table 8, a calculation method of the technical value data corresponding to the target task is shown.

[0288] Table 8 Calculation method of technical value data

[0289]

[0290] In specific implementations, performance change information may include lightweight / endurance indicators and safety / reliability indicators, cost change information may include manufacturing cost changes and full life cycle maintenance costs, and experience change information may include intelligence / experience indicators and comfort / convenience indicators.

[0291] Each secondary indicator can be scored in the following ways:

[0292] Excellence:

[0293] Performance change information: Battery life improved by >5% (e1 score 0.7-1 point); safety exceeds industry standards (e2 score 0.7-1 point);

[0294] Cost change information: Manufacturing cost reduction > 8% (e3 score 0.7-1 point); Maintenance cost reduction > 15% (e4 score 0.7-1 point);

[0295] Experience change information: Intelligent configuration leads the industry (e5 score 0.7-1 point); comfort leads the same product (e6 score 0.7-1 point).

[0296] Good level:

[0297] Performance change information: Battery life improved by 3-5% (e1 score 0.4-0.6 points); safety reached industry-leading level (e2 score 0.4-0.6 points);

[0298] Cost change information: Manufacturing costs decreased by 4-8% (e3 score 0.4-0.6 points); maintenance costs decreased by 8%-15% (e4 score 0.4-0.6 points);

[0299] User experience: The intelligent model is very competitive among its peers (e5 score 0.4-0.6 points); the comfort improvement is noticeably noticeable (e6 score 0.4-0.6 points).

[0300] Basic level:

[0301] Performance change information: Battery life improved by <3% (e1 score 0.4-0.6 points); safety meets industry standards (e2 score 0.4-0.6 points);

[0302] Cost change information: Manufacturing cost reduction <4% (e3 score 0.4-0.6 points); Maintenance cost reduction <8% (e4 score 0.4-0.6 points);

[0303] Experience change information: The intelligent interaction function has been slightly optimized on the existing finished product (e5 score 0.4-0.6 points); the comfort index has not changed significantly (e6 score 0.4-0.6 points).

[0304] In an embodiment of the present invention, by obtaining task requirement information and searching for target technical data corresponding to the task requirement information in a preset technical database, the target task and the target parts corresponding to the target task are determined based on the task requirement information and the target technical data. The present invention improves the matching accuracy of technology and tasks by intelligently matching task requirements with the technical database, and can accurately and quickly construct the target task and determine the target parts. According to the task requirement information and the target technical data, the target parts ownership information corresponding to the target parts is determined. The present invention can accurately identify the ownership information of the parts in the target task. The task platform corresponding to the target task is determined based on the target parts ownership information, and the target task is assigned to the task platform. The present invention can automatically assign the target task to the optimal platform based on the parts ownership information, which can not only reduce manual intervention and shorten the decision-making cycle, but also enhance the adaptability between the target task and the platform, thereby achieving efficient conversion of the target task.

[0305] In the specific implementation, refer to Figure 2 , shows a logical flow chart of task allocation provided by an embodiment of the present invention.

[0306] First, a large amount of technical data can be obtained through data crawling, professional group provision, professional group technical needs, resource exchanges, etc. The data obtained includes forward-looking technical data and current technical data.

[0307] The technical data is then classified and separated according to its source, and stored in a structured manner. For example, technical data obtained from universities is associated with information such as the project, school, and team, and saved as structured data. Technical data obtained from research institutions is associated with information such as the project, institution, and team, and saved as structured data. Technical data obtained from suppliers is associated with information such as the project, localization status, and supplier, and saved as structured data.

[0308] Store structured technical data in a technical database.

[0309] Then, the target task is determined based on the task requirement information and target technical data, and the maturity data, maintenance data, conversion cycle data, reuse data and technical value data of the target task are scored to obtain the scoring results of the target task.

[0310] Then, based on the scoring results of the target tasks, the target tasks will be assigned to the corresponding chassis platform, power platform, intelligent driving platform, intelligent cockpit platform, body platform, electronic and electrical platform and other platforms.

[0311] Then, according to the priority of the target tasks, the target tasks are divided into platform-level tasks, product mass production-level tasks, and technology reserve-level tasks.

[0312] Reference Figure 3 , shows a step flow chart of a task evaluation provided by an embodiment of the present invention.

[0313] First, task requirements can be entered. In an embodiment of the present invention, task requirement data can be obtained. The content of the task requirement data may include, but is not limited to: reporting platform (domain), reporting department / reporter, technical requirement data, potential resource unit, potential resource unit name, potential resource college / department, potential resource leader, task cooperation content, expected task benefits, task component jurisdiction department, task component development department, conversion cycle information, maturity data, maintenance data, conversion cycle data, reuse data, technical value data, and notes, etc. The content of the task requirement data can be pre-filled, such as technical requirement data and conversion cycle information, or it can be written after system evaluation, such as maturity data, maintenance data, conversion cycle data, reuse data, technical value data, etc.

[0314] A maturity assessment can be conducted on the target task. If the maturity data A of the target task is greater than or equal to 1.6, the target task maturity assessment is considered passed. If the maturity data A of the target task is less than 1.6, the target task maturity assessment is considered failed and a departmental review can be conducted. If the departmental review is passed, the next step is carried out. If the departmental review is not passed, the task is terminated.

[0315] The target task can be evaluated for both maintenance and conversion cycle. If the target task's maintenance data (B) is greater than or equal to 1.3 and the conversion cycle data (C) is greater than or equal to 0.8, the task is considered to have passed both evaluations. If the target task's maintenance data (B) is less than 1.3 or the conversion cycle data (C) is less than 0.8, the task is considered to have failed both evaluations. A platform review can be conducted. If the platform review passes, the task proceeds to the next step. If the platform review fails, the task is terminated.

[0316] The target task can be evaluated for reusability. If the reusability data D of the target task is greater than or equal to 0.6, the target task is considered to have passed the reusability evaluation. If the reusability data D of the target task is less than 0.6, the target task is considered to have failed the reusability evaluation and a R&D system review can be conducted. If the R&D system review passes, the next step is carried out. If the R&D system review fails, the task is terminated.

[0317] The target task can be evaluated for its technical value. If the technical value data E of the target task is greater than or equal to 0.75, the target task is considered to be a platform-level task, indicating that the target task is a disruptive technology that can define new industry standards or create new demands.

[0318] If the technical value data E of the target task is less than 0.75 and greater than 0.5, the target task is considered to be a product mass production-level task, indicating that the target task has differentiated competitiveness and can support product replacement premium.

[0319] If the technical value data E of the target task is less than or equal to 0.5, the target task is considered to be a technology reserve-level task, indicating that the target task has limited technical improvements and is suitable for low-cost iteration in mature markets.

[0320] According to the target task priorities of platform-level tasks, product mass production-level tasks, and technology reserve-level tasks, target tasks are assigned to different task platforms.

[0321] Reference Figure 4 , which shows a schematic structural diagram of a task allocation device provided by an embodiment of the present invention, the device comprising:

[0322] Data acquisition module 401, used to obtain task requirement information;

[0323] A data search module 402 is configured to search a preset technology database for target technology data corresponding to the task requirement information;

[0324] A task construction module 403 is configured to determine a target task and a target component corresponding to the target task based on the task requirement information and the target technical data;

[0325] An ownership determination module 404 is configured to determine target component ownership information corresponding to the target component based on the task requirement information and the target technical data;

[0326] The platform determination module 405 is used to determine the task platform corresponding to the target task according to the target component ownership information;

[0327] The task allocation module 406 is configured to allocate the target task to the task platform.

[0328] In an optional embodiment of the present invention, the data search module 402 includes:

[0329] A keyword extraction submodule, used to extract technical keywords from the data requirement information;

[0330] A keyword matching submodule, configured to search the preset technology database for a number of candidate technology data that matches the technology keyword;

[0331] a matching degree determination submodule, configured to respectively determine matching degree information between the technical keyword and a plurality of candidate technical data;

[0332] The target technology selection submodule is used to select the target technology data from the plurality of candidate technology data according to the matching degree information.

[0333] In an optional embodiment of the present invention, the task construction module 403 includes:

[0334] A data filling submodule, configured to fill the task template with the target technical data to obtain the target task;

[0335] A component determination submodule, configured to determine the component corresponding to the target technical data according to the target technical data;

[0336] The target component acquisition submodule is used to use the component corresponding to the target technical data as the target component corresponding to the target task.

[0337] In an optional embodiment of the present invention, the attribution determination module 404 includes:

[0338] A maturity determination submodule, configured to determine maturity data corresponding to the target task based on the target technical data;

[0339] A maintenance degree determination submodule, configured to determine the maintenance degree data corresponding to the target task according to the task requirement information and the target technical data;

[0340] A conversion cycle determination submodule, configured to determine the conversion cycle data corresponding to the target task according to the task requirement information;

[0341] A multiplexing determination submodule, configured to determine multiplexing data corresponding to the target task according to the target technical data;

[0342] The component ownership information determination submodule is used to determine the target component ownership information corresponding to the target component based on at least one of the maintenance data, the conversion cycle data, the maturity data and the reuse data.

[0343] In an optional embodiment of the present invention, the maturity determination submodule includes:

[0344] a stage indicator determination unit, configured to determine the stage indicator of the target task according to the technology usage status information;

[0345] A maturity determination unit is used to determine the maturity data corresponding to the target task according to the stage indicator.

[0346] In an optional embodiment of the present invention, the target technical data includes target version data, the task requirement information includes requirement urgency information, and the maintenance determination submodule includes:

[0347] a current technology acquisition unit, configured to search the preset technology database for current technology data associated with the target technology data; the current technology data is data having the same function as the target technology data and being in the application stage; the current technology data includes current version data;

[0348] a version iteration obtaining unit, configured to compare the current version data with the target version data to obtain version iteration information of the target technical data relative to the current technical data;

[0349] The maintenance degree determining unit is configured to determine the maintenance degree data corresponding to the target task according to the version iteration information and the demand urgency information.

[0350] In an optional embodiment of the present invention, the conversion period determination submodule includes:

[0351] The conversion cycle determining unit is used to determine the conversion cycle data corresponding to the target task according to the conversion cycle information.

[0352] In an optional embodiment of the present invention, the multiplexing determination submodule includes:

[0353] a hardware and software data acquisition unit, configured to determine target component data and / or target software data corresponding to the target component according to the target technical data;

[0354] a component-related data acquisition unit, configured to determine at least one of target supplier data, target test process data, target test tool data, and target document call data corresponding to the target component based on the target component data;

[0355] A reusability determination unit is used to determine the reusability data corresponding to the target task based on at least one of the target component data, the target software data, the target supplier data, the target test process data, the target test tool data and the target document call data.

[0356] In an optional embodiment of the present invention, the multiplexing determination unit includes:

[0357] A bill of materials acquisition subunit is used to acquire bill of materials data corresponding to a plurality of different products from the preset technical database; the bill of materials data includes component data, software data and supplier data;

[0358] A component reuse acquisition subunit, configured to determine component reuse data based on the frequency of use of the target component data in a plurality of bill of materials data corresponding to different products;

[0359] a software reuse acquisition subunit, configured to determine software reuse data based on the frequency of use of the target software data in the plurality of bill of materials data corresponding to different products;

[0360] a supplier reuse acquisition subunit, configured to determine supplier reuse data based on the frequency of use of the target supplier data in a plurality of bill of materials data corresponding to different products;

[0361] A development data acquisition subunit is used to acquire a number of component development data corresponding to different products from the preset technical database; the component development data includes test process data, test tool data, and literature call data during the component development process;

[0362] a test process reusability acquisition subunit, configured to determine test process reusability data according to a frequency of use of the target test process data in a plurality of component development data corresponding to different products;

[0363] a test tool reusability acquisition subunit, configured to determine test tool reusability data according to a frequency of use of the target test tool data in a plurality of component development data corresponding to different products;

[0364] a document reuse acquisition subunit, configured to determine document reuse data based on the frequency of use of the target document call data in a plurality of component development data corresponding to different products;

[0365] The reusability determination subunit is used to determine the reusability data corresponding to the target task based on at least one of the component reusability data, the software reusability data, the supplier reusability data, the test process reusability data, the test tool reusability data and the literature reusability data.

[0366] In an optional embodiment of the present invention, the component ownership information determination submodule includes:

[0367] A component ownership information determination unit is configured to determine, if the maturity data is greater than or equal to a preset first threshold, the maintenance data is greater than or equal to a preset second threshold, the conversion cycle data is greater than or equal to a preset third threshold, and the reuse data is greater than or equal to a preset fourth threshold, the target component ownership information corresponding to the target component is determined based on the reuse data.

[0368] In an optional embodiment of the present invention, the task allocation module 406 includes:

[0369] A technical value determination submodule, configured to determine technical value data corresponding to the target task based on the target technical data and the current technical data;

[0370] A priority determination submodule, configured to determine the priority information of the target task according to the technical value data;

[0371] The target task allocation submodule is used to allocate the target task to the task platform according to the priority information.

[0372] In an optional embodiment of the present invention, the target technology data further includes at least one of target performance data, target cost data, and target experience data; the current technology data further includes at least one of current performance data, current cost data, and current experience data; and the technology value determination submodule includes:

[0373] a performance change obtaining unit, configured to compare the target performance data with the current performance data to obtain performance change information of the target technical data relative to the current technical data;

[0374] a cost change obtaining unit, configured to compare the target cost data with the current cost data to obtain cost change information of the target technical data relative to the current technical data;

[0375] an experience change obtaining unit, configured to compare the target experience data with the current experience data to obtain experience change information of the target technical data relative to the current technical data;

[0376] A technical value determination unit is used to determine the technical value data corresponding to the target task based on at least one of the performance change information, the cost change information and the experience change information.

[0377] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0378] An embodiment of the present invention further provides an electronic device, which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the method described above is implemented.

[0379] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0380] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the present invention are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0381] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0382] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatus, or computer program products. Thus, embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0383] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0384] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0385] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0386] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and updates to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and updates that fall within the scope of the embodiments of the present invention.

[0387] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the above elements.

[0388] The above is a detailed introduction to the provided task allocation method, device, electronic device and medium. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for general technical personnel in this field, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A task allocation method, characterized in that: The method comprises: Obtain task requirement information; Searching for target technical data corresponding to the task requirement information in a preset technical database; Determine a target task and a target component corresponding to the target task according to the task requirement information and the target technical data; Determining target component ownership information corresponding to the target component according to the task requirement information and the target technical data; Determine the task platform corresponding to the target task according to the target component ownership information; Allocate the target task to the task platform.

2. The method according to claim 1, characterized in that The task requirement information includes data requirement information, and searching a preset technical database for target technical data corresponding to the task requirement information includes: Extracting technical keywords from the data requirement information; Searching the preset technology database for a number of candidate technology data that matches the technology keyword; respectively determining matching degree information between the technical keyword and a plurality of the candidate technical data; The target technical data is selected from a plurality of the candidate technical data according to the matching degree information.

3. The method according to claim 2, characterized in that The task requirement information includes a task template, and determining the target task and the target component corresponding to the target task according to the task requirement information and the target technical data includes: Fill the task template with the target technical data to obtain the target task; Determining components corresponding to the target technical data according to the target technical data; The component corresponding to the target technical data is used as the target component corresponding to the target task.

4. The method according to claim 1, wherein The determining target component attribution information corresponding to the target component according to the task requirement information and the target technical data includes: Determining maturity data corresponding to the target task based on the target technical data; Determining the maintenance data corresponding to the target task according to the task requirement information and the target technical data; Determining the conversion cycle data corresponding to the target task according to the task requirement information; Determining the reusability data corresponding to the target task according to the target technical data; Target component attribution information corresponding to the target component is determined according to at least one of the maintenance data, the conversion cycle data, the maturity data, and the reuse data.

5. The method according to claim 4, characterized in that The target technology data includes technology usage status information, and determining the maturity data corresponding to the target task based on the target technology data includes: Determining the stage indicators of the target task according to the technology usage status information; Determine the maturity data corresponding to the target task according to the stage indicator.

6. The method according to claim 4, characterized in that The target technical data includes target version data, the task requirement information includes requirement urgency information, and determining the maintenance data corresponding to the target task based on the target technical data and the task requirement information includes: Searching the preset technical database for current technical data associated with the target technical data; the current technical data is data having the same function as the target technical data and being in the application stage; the current technical data includes current version data; Comparing the current version data with the target version data to obtain version iteration information of the target technical data relative to the current technical data; Determine the maintenance data corresponding to the target task according to the version iteration information and the demand urgency information.

7. The method according to claim 4, characterized in that The task requirement information includes conversion cycle information, and determining the conversion cycle data corresponding to the target task according to the task requirement information includes: The conversion cycle data corresponding to the target task is determined according to the conversion cycle information.

8. The method according to claim 4, characterized in that The determining, based on the target technical data, the reusability data corresponding to the target task includes: Determining target component data and / or target software data corresponding to the target component according to the target technical data; Determining at least one of target supplier data, target test process data, target test tool data, and target document call data corresponding to the target component according to the target component data; The reusability data corresponding to the target task is determined according to at least one of the target component data, the target software data, the target supplier data, the target test process data, the target test tool data and the target document call data.

9. The method according to claim 8, characterized in that The determining the reusability data corresponding to the target task according to at least one of the target component data, the target software data, the target supplier data, the target test process data, the target test tool data, and the target document call data includes: Obtaining a plurality of bill of materials data corresponding to different products from the preset technical database; the bill of materials data including component data, software data and supplier data; Determining component reuse data based on the frequency of use of the target component data in a plurality of bill of materials data corresponding to different products; determining software reuse data according to the frequency of use of the target software data in a plurality of bill of materials data corresponding to different products; Determining supplier reuse data based on the frequency of use of the target supplier data in a plurality of bill of materials data corresponding to different products; Acquire a plurality of component development data corresponding to different products from the preset technical database; the component development data includes test process data, test tool data, and literature call data during the component development process; Determining test process reusability data based on the frequency of use of the target test process data in a plurality of component development data corresponding to different products; Determining test tool reusability data based on the frequency of use of the target test tool data in the component development data corresponding to different products; Determining document reuse data based on the frequency of use of the target document call data in a plurality of component development data corresponding to different products; The reusability data corresponding to the target task is determined based on at least one of the component reusability data, the software reusability data, the supplier reusability data, the test process reusability data, the test tool reusability data, and the literature reusability data.

10. The method according to claim 4, characterized in that The determining target component attribution information corresponding to the target component according to at least one of the maintenance data, the conversion cycle data, the maturity data, and the reuse data includes: If the maturity data is greater than or equal to a preset first threshold, the maintenance data is greater than or equal to a preset second threshold, the conversion cycle data is greater than or equal to a preset third threshold, and the reuse data is greater than or equal to a preset fourth threshold, then the target component ownership information corresponding to the target component is determined based on the reuse data.

11. The method according to claim 6, characterized in that The allocating the target task to the task platform includes: Determine the technical value data corresponding to the target task based on the target technical data and the current technical data; Determining priority information of the target task based on the technical value data; The target task is allocated to the task platform according to the priority information.

12. The method according to claim 11, characterized in that The target technical data further includes at least one of target performance data, target cost data, and target experience data; the current technical data further includes at least one of current performance data, current cost data, and current experience data; and determining the technical value data corresponding to the target task based on the target technical data and the current technical data includes: Comparing the target performance data with the current performance data to obtain performance change information of the target technical data relative to the current technical data; Comparing the target cost data with the current cost data to obtain cost change information of the target technical data relative to the current technical data; Comparing the target experience data with the current experience data to obtain experience change information of the target technical data relative to the current technical data; Determine technical value data corresponding to the target task according to at least one of the performance change information, the cost change information, and the experience change information.

13. A task allocation device, characterized in that: The device comprises: Data acquisition module, used to obtain task requirement information; A data search module is used to search for target technical data corresponding to the task requirement information in a preset technical database; A task construction module, configured to determine a target task and a target component corresponding to the target task based on the task requirement information and the target technical data; an ownership determination module, configured to determine target component ownership information corresponding to the target component according to the task requirement information and the target technical data; A platform determination module is used to determine the task platform corresponding to the target task according to the target component ownership information; The task allocation module is used to allocate the target task to the task platform.

14. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method according to any one of claims 1 to 12 when executed by the processor.

15. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 12 is implemented.

Images