A method for evaluating human resource investment in automobile process development

Abstract

The application relates to a method for evaluating human resource input in an automobile process development. The method comprises the following steps: constructing an automobile process development project model, and dividing the model into multiple projects; constructing an initial human resource input model through historical project data, inputting project information of a current project into the model, and outputting a human resource input work hour calibration value; obtaining actual human resource input work hours of the current project through a work hour system; comparing the actual human resource input work hours of the current project with the human resource input work hour calibration value, and correcting the initial human resource input model according to a comparison result to obtain an updated human resource input model. Through scientific project modeling, real-time work hour collection and model dynamic correction, the method not only improves the accuracy of human resource input evaluation, but also enhances the dynamic adaptability of the evaluation, can continuously optimize the model according to actual project conditions, and provides a reliable solution for human resource management in the field of automobile industrial process development.

Description

Technical Field

[0001] This invention belongs to the field of human resource assessment technology, and in particular relates to a method for assessing human resource input in automotive process development. Background Technology

[0002] In the field of automotive process development, scientifically assessing the human resource input at each stage and professional module of the process is a core requirement for achieving efficient resource allocation. Currently, with the increasing complexity of automotive manufacturing processes and the diversification of project types, traditional human resource assessment methods have many shortcomings. On the one hand, automotive process development encompasses various project types, including new platform development, styling modifications, and powertrain transfers, with significant differences in development scale, technical difficulty, and professional module requirements. Traditional human resource assessment methods typically rely on experience-based judgment or broad classification, making it difficult to accurately quantify human resource needs for different project levels. On the other hand, during process development, actual human resource input is significantly affected by factors such as project progress and technical changes. However, traditional models lack a linkage mechanism with real-time work hour data, making it impossible to compare actual human resource input with assessed values ​​to dynamically correct the model. This leads to inaccurate human resource input predictions, resource waste, or project delays, and makes it difficult to scientifically guide precise control in recruitment and job allocation. Summary of the Invention

[0003] Therefore, it is necessary to provide a method for evaluating human resource input in automotive process development to address the aforementioned technical issues. This method aims to achieve accurate quantification and evaluation of human resource input in automotive industrial processes through scientific model building and dynamic data correction mechanisms.

[0004] Firstly, this application provides a method for evaluating human resource input in automotive process development, including:

[0005] Based on the automotive manufacturing process, an automotive process development project model is constructed, which is divided into multiple projects, and project type, development mode, development stage and professional module are defined for each project.

[0006] Based on historical project data, an initial human resource input model is constructed. Project information of the current project is obtained and input into the initial human resource input model. The human resource input man-hour calibration value is output. The project information of the current project includes the project type, development mode, development stage and professional module of the current project.

[0007] The time management system allows for real-time acquisition of actual manpower input hours for the current project, based on project type, development model, development stage, and professional module.

[0008] The actual man-hours input for the current project are compared with the calibrated man-hours input. Based on the comparison results, the initial human resource input model is revised to obtain an updated human resource input model. The updated human resource input model is used to calculate the predicted man-hours input for the project to be carried out based on the project information.

[0009] In one embodiment, the automotive process development project model includes a hierarchy module, a development mode definition module, a development phase division module, and a professional division module.

[0010] The grading module is used to divide projects into different project grades, including Level 1, Level 2 and Level 3. Based on the project grade and the development content of the project, the project is classified to obtain the project type.

[0011] The development mode definition module is used to classify the development mode of a project based on a technical change ratio threshold, and obtain the corresponding development mode. The development modes include complete reuse, partial development and new development.

[0012] The development phase division module is used to divide the project process into phases based on the constraints of the manufacturing execution system nodes, thus obtaining the development phases;

[0013] The professional division module is used to divide the process development content of the project into professional fields, resulting in professional modules. These professional modules include stamping planning, welding planning, painting planning, final assembly planning, equipment planning, comprehensive matching, and non-professional units.

[0014] In one embodiment, the initial human resource input model is modified based on the comparison results, including:

[0015] When the comparison result shows that the actual man-hour input of the current project exceeds the calibrated value of man-hour input, the current project is classified and grouped by project type, development mode, development stage and professional module through the time system to obtain each group, and the weighted average of the time for each group is calculated.

[0016] The weighted average of working hours for each group is used to update the corresponding standard working hour reference value in the initial human resource input model, resulting in the updated human resource input model.

[0017] In one embodiment, the method further includes:

[0018] Calculate the relative difference between the weighted average working hours of each group and the corresponding standard working hour reference value in the initial human resource input model;

[0019] When the relative difference exceeds the preset difference threshold, an early warning instruction is generated, which is used to send warning information to the operator.

[0020] Upon receiving a feedback instruction, if the feedback instruction is a manual confirmation instruction, the corresponding standard working hour reference value in the initial human resource input model is updated using the manual confirmation value in the manual confirmation instruction, thus obtaining the updated human resource input model.

[0021] In one embodiment, the method further includes:

[0022] The standard working hour reference values ​​for each group in the updated human resource input model are stored as the new version calibration values ​​in the model version database, and the model version number of the updated human resource input model is recorded.

[0023] Store the corresponding standard working hour reference values ​​in the initial human resource input model to the model version database, and record the model version number and revision history information of the initial human resource input model. The revision history information includes the difference between the corresponding standard working hour reference values ​​in the initial human resource input model and the standard working hour reference values ​​of each group in the updated human resource input model.

[0024] When a rollback instruction is received, the currently used human resource input model is updated to the human resource input model with the corresponding model version number, based on the model version number in the rollback instruction.

[0025] In one embodiment, the method further includes:

[0026] Calculate the manpower shortage in the projects to be carried out by using the predicted manpower input hours;

[0027] Based on the manpower shortage figures, generate personnel recruitment needs and job allocation plans;

[0028] The predicted manpower input hours are compared with the preset manpower load threshold to generate a manpower load assessment report. Based on the manpower load assessment report, manpower costs are analyzed to generate cost reduction and efficiency improvement analysis results.

[0029] In one embodiment, the method further includes:

[0030] Based on historical project data, we aggregate historical manpower input hours data from multiple historical projects that share the same project type, development model, development stage, and professional module as the project to be carried out. Through time series clustering algorithms, we obtain the time series curve of manpower demand.

[0031] Peak features are extracted from the time-series curve of manpower demand to identify the periodic fluctuations in manpower demand and the characteristics of cross-project resource conflicts;

[0032] Based on the cyclical fluctuations in manpower demand and the characteristics of cross-project resource conflicts, a time-load correlation model is established to predict the peak periods of manpower shortages for projects to be carried out.

[0033] Based on the peak periods of manpower shortages and the resource idle status of projects running concurrently with the projects to be launched, a cross-project human resource secondment plan is dynamically generated.

[0034] Secondly, this application also provides a human resource input evaluation system for automotive process development, including:

[0035] The project multidimensional classification modeling module is used to build an automotive process development project model based on the automotive manufacturing process, divide it into multiple projects, and define the project type, development mode, development stage and professional module for each project.

[0036] The initial model building and evaluation module acquires and builds an initial human resource input model based on historical project data, obtains the project information of the current project, inputs the project information of the current project into the initial human resource input model, and outputs the human resource input man-hour calibration value. The project information of the current project includes the project type, development mode, development stage and professional module of the current project.

[0037] The multi-dimensional working hour data real-time acquisition module is used to obtain the actual manpower input working hours of the current project in real time through the working hour system, based on project type, development mode, development stage and professional module;

[0038] The model dynamic correction and iteration module is used to compare the actual man-hour input of the current project with the calibrated man-hour input, and to correct the initial man-hour input model based on the comparison results, so as to obtain an updated man-hour input model. The updated man-hour input model is used to calculate the predicted man-hour input of the project to be carried out based on the project information of the project to be carried out.

[0039] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the first aspect.

[0040] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when processed, implements the steps in the first aspect.

[0041] The aforementioned method for assessing human resource input in automotive process development, by constructing an automotive process development project model, can scientifically classify automotive process development projects, clearly defining the project type, development mode, development stage, and professional module of each project, providing a structured framework for accurate assessment of human resource input. An initial human resource input model is built based on historical project data, and current project information is input to output a calibrated value for human resource input hours, achieving a preliminary quantitative estimate of human resource input and providing a reference benchmark for human resource input assessment. Furthermore, the actual human resource input hours for each dimension of the current project are obtained in real time through a time system, ensuring the real-time nature and accuracy of the data, providing reliable data support for model correction. Comparing the actual human resource input hours with the calibrated values ​​and correcting the model allows for continuous optimization based on actual conditions, improving the accuracy of the assessment, and making the updated model more accurate in predicting the human resource input hours for projects to be undertaken.

[0042] Compared with traditional human resource assessment methods, this method, through scientific project modeling, utilization of historical data, real-time work hour collection, and dynamic model correction, not only improves the accuracy of human resource input assessment and can accurately quantify human resource needs for different project levels and development models, avoiding the problems of insufficient or excessive human resource input, but also enhances the dynamic adaptability of the assessment. It can continuously optimize the model according to the actual project situation, effectively reducing the risk of project delays and human resource waste, and providing an efficient and reliable solution for human resource management in the automotive industry process development field. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A flowchart of a method for evaluating human resource input in automotive process development, provided as an exemplary embodiment of the present invention;

[0045] Figure 2 A structural diagram of an automotive process development project model is provided as an exemplary embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of the structure of an automotive process development human resource input evaluation system, provided as an exemplary embodiment of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0048] In one embodiment, such as Figure 1 As shown, a method for evaluating human resource input in automotive process development is provided. This embodiment illustrates the application of this method to a terminal. It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0049] S101: Based on the automotive manufacturing process, construct an automotive process development project model, divide it into multiple projects, and define the project type, development mode, development stage, and professional modules for each project.

[0050] Specifically, in the automotive manufacturing field, process development is a complex and multi-stage process involving collaborative work across multiple professional fields. Therefore, a model of automotive process development projects can be constructed for further quantitative analysis. This model, based on the automotive manufacturing process flow, can subdivide the entire process development process into multiple projects. Each project has a clear definition, including its project type (e.g., new platform development project, minor modification project, powertrain swap project), development mode, development stage, and involved professional modules. For example, for a new platform development project, its project type can be a Level 1 project, its development mode can involve the development of multiple professional modules, and its development stage can start from product planning, go through multiple intermediate stages, and finally reach final acceptance and online maintenance. Through multi-dimensional classification and definition, this model can clearly present the characteristics and requirements of each project at different stages and professional modules, providing an accurate framework for subsequent human resource assessments.

[0051] S102: Obtain and construct an initial human resource input model based on historical project data, obtain the project information of the current project, input the project information of the current project into the initial human resource input model, and output the man-hour calibration value of human resource input. The project information of the current project includes the project type, development mode, development stage and professional module of the current project.

[0052] Specifically, historical project data includes the actual human resources invested in different stages and professional modules of past projects. In-depth analysis and statistics of this data can yield initial standard working hours for each project type, development model, development stage, and professional module. For example, historical data analysis reveals that for the stamping planning module in a new platform development project, 38.56 hours of manpower are typically required during the product planning phase. These multiple initial standard working hours form the basis of the initial human resource investment model. Once detailed project information for the current project is obtained, including its project type, development model, development stage, and professional modules, it can be input into the initial human resource investment model. This model can then match the project information and output calibrated working hours for the corresponding project type, development model, development stage, and professional module. This calibrated value provides a preliminary reference for the current project's human resource allocation.

[0053] S103: Through the time management system, the actual manpower input hours of the current project can be obtained in real time according to the project type, development mode, development stage and professional module.

[0054] Specifically, in actual project development, to ensure the accuracy and timeliness of human resource input assessment, it is necessary to obtain real-time data on the actual man-hours invested in the current project. This can be illustrated using a dedicated time management system. This system can record in detail the daily man-hours invested by employees within the project team, based on information such as project type, development model, development stage, and professional module. Employees need to enter their work content, stage, professional module, and total man-hours invested that day. Furthermore, this information can be collected and organized by the time management system to form a detailed breakdown of actual man-hours invested in each stage and professional module of the current project. For example, in a minor modification project, if an employee in the welding planning module invested 10 hours of work on a certain day during the process development stage, this information can be recorded in the time management system. Through this process, the time management system can continuously collect and update the actual man-hours invested in the current project, providing real-time data support for subsequent model adjustments.

[0055] S104: Compare the actual man-hour input of the current project with the calibrated man-hour input, and revise the initial man-hour input model based on the comparison results to obtain an updated man-hour input model. The updated man-hour input model is used to calculate the predicted man-hour input of the project to be carried out based on the project information of the project to be carried out.

[0056] Specifically, after obtaining the actual man-hour input data for the current project and the calibrated man-hour values ​​output by the initial human resource input model, the two can be compared. This comparison reveals the discrepancy between the actual man-hour input and the model's prediction. For example, if the actual man-hour input for a project at a certain stage is 2% higher than the model's calibrated value, it indicates a potential bias in the model's prediction for that stage. Based on this comparison, the initial human resource input model can be revised to more accurately reflect the actual situation. After revision, an updated human resource input model is obtained. This updated model is no longer a static model based on historical data but a dynamic model incorporating the actual data of the current project, enabling a more precise assessment of human resource input. When a new project is launched, its project information can be input into the updated human resource input model to calculate the predicted man-hour input for each stage and professional module. This predicted value is closer to the actual situation than the output of the initial model, providing a more scientific and reliable basis for human resource allocation in the project, thereby enabling accurate assessment and optimized management of human resource input during automotive process development.

[0057] The above method constructs an automotive process development project model, scientifically classifying projects and defining project types, development models, development stages, and professional modules, forming a standardized project classification framework that provides a structured analytical foundation for subsequent human resource input assessment. Secondly, an initial human resource input model is built based on historical project data, and current project information is input to output calibrated human resource input hours, achieving quantitative prediction of human resource input. This transforms historical experience data into a referable assessment benchmark, shifting human resource input assessment from experience-based to data-driven. Furthermore, the actual human resource input hours for each dimension of the current project are acquired in real time through a time management system, ensuring data timeliness and accuracy and providing feedback data for dynamic model correction. Finally, the model is corrected by comparing actual human resource input hours with calibrated values, forming a closed-loop model optimization mechanism. This allows the human resource input model to continuously improve itself based on actual project data, enhancing assessment accuracy. Consequently, the updated model's human resource input predictions for projects more closely align with actual needs, strengthening the model's adaptability and practicality.

[0058] In one embodiment, such as Figure 2 As shown, a structural diagram of an automotive process development project model 200 is presented. The model includes a hierarchy module 201, a development mode definition module 202, a development stage division module 203, and a professional division module 204.

[0059] Among them, the level classification module 201 is used to classify projects into different project levels, including level one, level two and level three, and classify projects based on project level and project development content to obtain project type;

[0060] The development mode definition module 202 is used to divide the development mode of the project by the technical change ratio threshold to obtain the corresponding development mode. The development modes include complete adoption, partial development and new development.

[0061] The development phase division module 203 is used to divide the project process into phases based on the manufacturing execution system node constraints, thus obtaining the development phases;

[0062] Specialized module 204 is used to divide the process development content of the project into specialized fields, resulting in specialized modules. These specialized modules include stamping planning, welding planning, painting planning, final assembly planning, equipment planning, comprehensive matching, and non-specialized units.

[0063] Specifically, the classification module 201 can categorize projects into different levels based on complexity, development scale, and resource requirements. For example, projects can be classified into Level 1, Level 2, and Level 3, each corresponding to different development difficulties and resource input requirements. Level 1 projects typically involve the development of entirely new platforms or large-scale technological changes, such as new platform vehicle development projects (including major platform overhauls) and new styling projects on mature platforms. Level 1 projects have high technical complexity, long development cycles, and require significant human and material resources. Level 2 projects can include minor modification projects, adaptive development projects, and initial matching projects of new powertrains. These Level 2 projects involve partial improvements or new functionalities based on existing platforms, with technical complexity and resource requirements falling between Level 1 and Level 3. Level 3 projects mainly involve simple adjustments or transplants based on existing technologies and platforms, such as mature powertrain transplant projects. These Level 3 projects have lower technical complexity, shorter development cycles, and relatively lower resource requirements. Furthermore, based on project level and specific development content, projects can be further subdivided into various types, such as 1-1 New platform vehicle development project, 1-2 Mature platform new styling vehicle project, 1-3 Major redesign project, 2-1 Minor redesign project, 2-2 Adaptive development project, 2-3 Replacement development project - first matching of new powertrain, 2-4 Right-hand drive development, 3-1 Replacement development project - mature powertrain transplant - V, and 3-2 Replacement development project - mature powertrain transplant - VI, etc. This allows project managers to quickly identify the characteristics and needs of the project type, providing clear guidance for subsequent human resource allocation.

[0064] Specifically, the development mode definition module 202 can classify the project's development mode based on the actual development needs of the project and a technology change ratio threshold. For example, when the technology change ratio of the project is below a certain set threshold, such as 10%, and it mainly relies on existing technologies and processes, it can be defined as a fully adopted mode. In this fully adopted mode, the focus of project development is on optimizing existing processes to ensure the stability and reliability of the technology. When the technology change ratio is between the set thresholds, such as 10%-50%, and it requires partial improvement or adjustment of existing technologies and processes, it can be defined as a partial development or fine-tuning mode to perform local optimization for specific needs while retaining the advantages of existing technologies. When the technology change ratio exceeds a certain high threshold, such as above 50%, and the project involves the application of a large number of new technologies and processes, it can be defined as a new development mode. The development phase division module 203 can divide the project process into multiple phases based on the project development process and nodes. This division can be based on the node constraints of the manufacturing execution system to ensure that each phase has a clear start and end point and task requirements. Indicatively, the project can be divided into 12 development phases: KO (Product Planning), P0 (Process Planning), P1 (Feasibility Analysis Phase 1), P2 (Feasibility Analysis Phase 2), P3 (Process Development Phase 1), P4 (Process Development Phase 2), P5 (In-Process Testing and Verification Phase 1), P6 (In-Process Testing and Verification Phase 2), P7 (Process Optimization and Maintenance Phase 1), P8 (Process Optimization and Maintenance Phase 2), P9 (Final Acceptance), and P10 (In-Production Maintenance). This allows project managers to clearly understand the key tasks and resource requirements at each phase, enabling refined management of project progress. The professional division module 204 further categorizes the project's process development content into professional areas, clearly defining the responsibilities and scope of each module. This module can include stamping planning, welding planning, painting planning, final assembly planning, equipment planning, integrated matching, and non-professional units, clearly defining different professional technical processes.

[0065] In one embodiment, the initial human resource input model is modified based on the comparison results, including:

[0066] When the comparison result shows that the actual man-hour input of the current project exceeds the calibrated value of man-hour input, the current project is classified and grouped by project type, development mode, development stage and professional module through the time system to obtain each group, and the weighted average of the time for each group is calculated.

[0067] The weighted average of working hours for each group is used to update the corresponding standard working hour reference value in the initial human resource input model, resulting in the updated human resource input model.

[0068] Specifically, when the actual man-hours invested in a project exceed the calibrated value, the initial model is not suitable for the actual production costs, and therefore needs to be updated. Illustratively, a time management system can record in real-time the daily man-hours invested by employees in specific projects based on project type, development mode, development stage, and professional module. The time management system then categorizes and groups the current project by project type, development mode, development stage, and professional module, obtaining each group and calculating the weighted average man-hours for each group. This more accurately reflects the average man-hour requirement for each group during the actual development process. By updating the corresponding standard man-hour reference value in the initial human resource input model with the weighted average man-hours of each group, the model can more accurately reflect the man-hour requirements during the actual development process, resulting in an updated human resource input model. For example, if the actual weighted average man-hours for a certain level of project in the stamping planning module is 40 hours, while the calibrated value in the initial model is 35 hours, the calibrated value can be updated to 40 hours.

[0069] In one embodiment, the method further includes:

[0070] Calculate the relative difference between the weighted average working hours of each group and the corresponding standard working hour reference value in the initial human resource input model;

[0071] When the relative difference exceeds the preset difference threshold, an early warning instruction is generated, which is used to send warning information to the operator.

[0072] Upon receiving a feedback instruction, if the feedback instruction is a manual confirmation instruction, the corresponding standard working hour reference value in the initial human resource input model is updated using the manual confirmation value in the manual confirmation instruction, thus obtaining the updated human resource input model.

[0073] Specifically, during the process of revising the initial human resource input model, the weighted average working hours of each group can be compared with the standard working hour reference value in the initial model. The relative difference between the two can be calculated to identify which groups have significant differences between their actual working hours and the model's estimated working hours, thus providing a basis for subsequent early warning and manual intervention. For example, if the weighted average working hours of a group is 40 hours, while the standard working hour reference value in the initial model is 35 hours, the relative difference is 14.29%. When the calculated relative difference is greater than a preset difference threshold, an early warning instruction can be generated to send a warning message to the operator, reminding them that there is a significant difference between the actual working hours of a certain group and the model's estimated working hours, i.e., further manual analysis and intervention are required. This preset difference threshold can be set to a reasonable value based on actual needs, such as ±5%. If the relative difference exceeds this threshold, it can be considered that the model's prediction deviates significantly from the actual situation. After receiving the early warning instruction, the operator can analyze and judge according to the actual situation and provide feedback instructions. If the feedback instruction is a manual confirmation instruction, it means that the operator, after analysis, believes that the model needs to be adjusted and has provided a manual confirmation value. This manually confirmed value is a more accurate reference value for working hours given by operators based on practical experience and analysis results. The manually confirmed value can then be used to update the corresponding standard working hour reference value in the initial human resource input model, resulting in an updated human resource input model.

[0074] In one embodiment, the method further includes:

[0075] The standard working hour reference values ​​for each group in the updated human resource input model are stored as the new version calibration values ​​in the model version database, and the model version number of the updated human resource input model is recorded.

[0076] Store the corresponding standard working hour reference values ​​in the initial human resource input model to the model version database, and record the model version number and revision history information of the initial human resource input model. The revision history information includes the difference between the corresponding standard working hour reference values ​​in the initial human resource input model and the standard working hour reference values ​​of each group in the updated human resource input model.

[0077] When a rollback instruction is received, the currently used human resource input model is updated to the human resource input model with the corresponding model version number, based on the model version number in the rollback instruction.

[0078] Specifically, the updated human resource input model can be stored in the model version database, recording the model's version number and related revision history information to achieve model version management. For example, the standard working hour reference values ​​for each group in the updated human resource input model can be stored as new version calibration values ​​in the model version database, recording their model version number. Furthermore, the corresponding standard working hour reference values ​​from the initial human resource input model can be stored in the model version database, recording the initial model's version number and revision history information. This revision history information can include the difference between the standard working hour reference values ​​in the initial model and the standard working hour reference values ​​for each group in the updated model. Note that the above storage process is not limited to storing the initial and updated human resource input models; it can also include storage after each iteration update to retain detailed information for each version, facilitating subsequent version rollback and issue tracking. For instance, when an operator discovers a problem with the current model or needs to revert to a historical version, they can input a rollback command through the interactive system interface, specifying the target version number. Then, based on the version number in the rollback instruction, the corresponding version of the human resource input model can be retrieved from the model version database and replaced with the currently used model. This ensures that if an error occurs during the model update process or historical data needs to be restored, the previous version can be quickly and accurately restored.

[0079] In one embodiment, the method further includes:

[0080] Calculate the manpower shortage in the projects to be carried out by using the predicted manpower input hours;

[0081] Based on the manpower shortage figures, generate personnel recruitment needs and job allocation plans;

[0082] The predicted manpower input hours are compared with the preset manpower load threshold to generate a manpower load assessment report. Based on the manpower load assessment report, manpower costs are analyzed to generate cost reduction and efficiency improvement analysis results.

[0083] Specifically, the updated human resource input model can calculate the projected man-hours for each stage and professional module of the project. Based on these calculations, the manpower gap can be further calculated to identify potential staffing shortages during project implementation. For example, the manpower gap can be calculated by comparing the projected man-hours with the available manpower hours. The required number of personnel and their skill requirements can then be determined. For instance, if the manpower gap is 20 hours and the work at this stage primarily involves stamping process design, personnel with stamping process design skills need to be recruited. A detailed recruitment plan, including recruitment channels, a recruitment schedule, and a budget, can be developed based on the manpower gap and project time requirements. Furthermore, the types and number of positions required can be determined based on the manpower gap and the project's professional module requirements. For example, if the manpower gap is 20 hours and the work at this stage involves stamping planning and welding planning, then stamping planning engineers and welding planning engineers are needed. Furthermore, based on job requirements and the skill levels of existing personnel, job allocation plans can be developed to ensure that human resource needs at each stage of the project are met.

[0084] Furthermore, a reasonable manpower load threshold can be set based on the company's actual operational capabilities and management experience to assess whether the manpower load during project implementation is too high or too low. By comparing the predicted manpower input hours with the preset manpower load threshold, a manpower load assessment report can be generated. This report can include the manpower load status of each stage and professional module, whether there are overload or underload situations, and corresponding recommended measures. Based on the manpower load assessment report, further analysis of labor costs can be conducted, generating cost reduction and efficiency improvement analysis results to provide optimization suggestions for the company. For example, based on the predicted manpower input hours and employee salary levels, the project's labor costs can be calculated, analyzing whether there is manpower waste or shortage, and proposing optimization suggestions. For example, if the manpower load at a certain stage is too high, it can be suggested to reduce manpower requirements by optimizing workflows or increasing equipment investment. Finally, based on the manpower load assessment report and cost analysis results, cost reduction and efficiency improvement analysis results can be generated. These results can include optimized labor costs, the expected efficiency improvement, and specific optimization measures.

[0085] In one embodiment, the method further includes:

[0086] Based on historical project data, we aggregate historical manpower input hours data from multiple historical projects that share the same project type, development model, development stage, and professional module as the project to be carried out. Through time series clustering algorithms, we obtain the time series curve of manpower demand.

[0087] Peak features are extracted from the time-series curve of manpower demand to identify the periodic fluctuations in manpower demand and the characteristics of cross-project resource conflicts;

[0088] Based on the cyclical fluctuations in manpower demand and the characteristics of cross-project resource conflicts, a time-load correlation model is established to predict the peak periods of manpower shortages for projects to be carried out.

[0089] Based on the peak periods of manpower shortages and the resource idle status of projects running concurrently with the projects to be launched, a cross-project human resource secondment plan is dynamically generated.

[0090] Specifically, based on historical project data, historical projects with the same project type, development model, development stage, and professional modules as the project to be undertaken can be selected. The manpower input and working hours data of these historical projects at each stage and professional module are then aggregated to form a comprehensive dataset. Time series clustering algorithms can then be used to analyze the aggregated data to obtain a manpower demand time-series curve. This curve reflects the changing trend of manpower demand over time. Further analysis of this curve can identify peak points in manpower demand. Illustratively, these peak points typically correspond to key stages or tasks in the project development process. By analyzing the frequency and time intervals of these peak points, the periodic fluctuations in manpower demand can be further identified. For example, a small peak in manpower demand for a particular professional module might be observed every two weeks. Furthermore, by comparing the development progress and manpower demand time-series curves of different projects, cross-project resource conflict characteristics can be identified. For example, it might be found that two projects simultaneously reach peak manpower demand for a particular professional module within the same time period, leading to resource conflicts.

[0091] By leveraging the cyclical fluctuations in manpower demand and the characteristics of cross-project resource conflicts, a work-hour-load correlation model can be established to predict peak periods of manpower shortages for projects to be undertaken. After identifying these peak periods, the development progress and manpower demand time-series curves of projects running concurrently with the projects can be analyzed to identify periods and modules with idle resources. Subsequently, based on the peak periods of manpower shortages and resource idleness, cross-project human resource secondment plans can be dynamically generated. These plans can include detailed information such as the number of seconded personnel, secondment duration, and secondment positions. The dynamic generation of cross-project human resource secondment plans can effectively resolve cross-project resource conflicts.

[0092] like Figure 3As shown, based on the same inventive concept, this application also provides an automotive process development human resource investment assessment system 300 for implementing the above-described method for assessing human resource investment in automotive process development. The solution provided by this system is similar to the implementation described in the above method; therefore, the specific limitations of one or more embodiments of the automotive process development human resource investment assessment system provided below can be found in the above-described limitations of the automotive process development human resource investment assessment method, and will not be repeated here. The system includes:

[0093] The multidimensional classification modeling module 301 is used to build an automotive process development project model based on the automotive manufacturing process flow, divide it into multiple projects, and define the project type, development mode, development stage and professional module for each project.

[0094] The initial model building and evaluation module 302 acquires and builds an initial human resource input model based on historical project data, obtains the project information of the current project, inputs the project information of the current project into the initial human resource input model, and outputs the human resource input man-hour calibration value. The project information of the current project includes the project type, development mode, development stage and professional module of the current project.

[0095] The multi-dimensional working hour data real-time acquisition module 303 is used to obtain the actual manpower input working hours of the current project in real time through the working hour system, based on project type, development mode, development stage and professional module;

[0096] The model dynamic correction and iteration module 304 is used to compare the actual man-hour input of the current project with the calibrated value of man-hour input, and to correct the initial man-hour input model based on the comparison result, so as to obtain an updated man-hour input model. The updated man-hour input model is used to calculate the predicted value of man-hour input for the project to be carried out based on the project information of the project to be carried out.

[0097] In the aforementioned system, the multi-dimensional project classification modeling module 301 constructs an automotive process development project model based on the automotive manufacturing process flow. This model divides the project into multiple projects and defines project types, development models, development stages, and professional modules, forming a standardized project evaluation framework. This clearly defines the characteristics of different projects and provides a unified analytical basis for subsequent human resource input evaluation. The initial model construction and evaluation module 302 acquires and constructs an initial human resource input model based on historical project data. After inputting current project information, it outputs a calibrated value for human resource input working hours, transforming historical experience data into a quantifiable evaluation benchmark. This shifts human resource input evaluation from relying on subjective experience to data-driven scientific prediction, improving the objectivity of the evaluation. The multi-dimensional working hour data real-time acquisition module 303 acquires the actual human resource input working hours of the current project in real time according to various dimensions of the project through the working hour system. This ensures the real-time, accurate, and comprehensive nature of data acquisition, providing reliable feedback data for dynamic model adjustments and enabling the system to promptly perceive the human resource input situation in the actual progress of the project. The model dynamic correction and iteration module 304 compares the actual manpower input hours with the calibration value and corrects the initial model, so that the human resource input model can continuously iterate and evolve based on actual project data, continuously improve the accuracy of the assessment, and make the updated model more in line with the actual needs of the manpower input prediction for the project to be carried out, thereby enhancing the system's adaptability and practicality to complex project scenarios.

[0098] In one exemplary embodiment, the present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the method for evaluating human resource input in automotive process development according to this application. A multi-core processor is preferred to improve the system's parallel processing capability. The memory provides sufficient temporary storage space to support program execution and data processing. The memory capacity should be large enough to accommodate a large amount of supply information and computational tasks.

[0099] In one exemplary embodiment, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for evaluating human resource input in automotive process development according to the present application.

[0100] The above-described embodiments are merely illustrative of several implementation methods of the embodiments of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the embodiments of this application, and these modifications and improvements all fall within the protection scope of the embodiments of this application.

Claims

1. A method for evaluating human resource input in automotive process development, characterized in that, The method includes: Based on the automotive manufacturing process, an automotive process development project model is constructed, which is divided into multiple projects, and project type, development mode, development stage and professional module are defined for each project. Based on historical project data, an initial human resource input model is constructed. Project information of the current project is obtained and input into the initial human resource input model. The human resource input man-hour calibration value is output. The project information of the current project includes the project type, development mode, development stage and professional module of the current project. The actual manpower input hours for the current project are obtained in real time through the work hour system, based on the project type, development mode, development stage, and professional module. The actual man-hour input of the current project is compared with the calibrated value of the man-hour input, and the initial human resource input model is corrected based on the comparison result to obtain an updated human resource input model. The updated human resource input model is used to calculate the predicted value of the man-hour input of the project to be carried out based on the project information of the project to be carried out. The standard working hour reference values ​​for each group in the updated human resource input model are stored as new version calibration values ​​in the model version database, and the model version number of the updated human resource input model is recorded. The corresponding standard working hour reference values ​​in the initial human resource input model are stored in the model version database, and the model version number and revision history information of the initial human resource input model are recorded. The revision history information includes the difference between the corresponding standard working hour reference values ​​in the initial human resource input model and the standard working hour reference values ​​of each group in the updated human resource input model. When a rollback instruction is received, the currently used human resource input model is updated to the human resource input model corresponding to the model version number in the rollback instruction. The updated human resource input model is obtained through the following steps: When the comparison result is that the actual manpower input hours of the current project exceed the manpower input hour calibration value, the current project is classified and grouped by the project type, development mode, development stage and professional module through the time system to obtain each group, and the time weighted average of each group is calculated. The corresponding standard working hour reference value in the initial human resource input model is updated by the time-weighted average of each group, thus obtaining the updated human resource input model. Calculate the relative difference between the weighted average working hours of each group and the corresponding standard working hour reference value in the initial human resource input model; when the relative difference is greater than a preset difference threshold, generate an early warning instruction, which is used to send warning information to the operator; receive a feedback instruction, and when the feedback instruction is a manual confirmation instruction, update the corresponding standard working hour reference value in the initial human resource input model using the manual confirmation value in the manual confirmation instruction to obtain the updated human resource input model.

2. The method according to claim 1, characterized in that, The automotive process development project model includes a hierarchy module, a development mode definition module, a development stage division module, and a professional division module. The level classification module is used to divide the project into different project levels, including level one, level two and level three, and classify the project based on the project level and the development content of the project to obtain the project type; The development mode definition module is used to divide the development mode of the project by a technology change ratio threshold to obtain the corresponding development mode. The development mode includes complete adoption, partial development and new development. The development phase division module is used to divide the project process into phases by manufacturing execution system node constraints, thereby obtaining the development phases. The professional division module is used to divide the process development content of the project into professional fields to obtain the professional modules. The professional modules include stamping planning, welding planning, painting planning, final assembly planning, equipment planning, comprehensive matching and non-professional units.

3. The method according to claim 1, characterized in that, The method further includes: The manpower shortage in the project to be carried out is calculated based on the predicted manpower input hours. Based on the stated manpower shortage, generate personnel recruitment needs and job allocation plans; The predicted manpower input hours are compared with the preset manpower load threshold to generate a manpower load assessment report. The manpower load assessment report is then used to analyze manpower costs and generate cost reduction and efficiency improvement analysis results.

4. The method according to claim 1, characterized in that, The method further includes: Based on the historical project data, the historical manpower input hours data of the same project type, development mode, development stage and professional module as the project to be carried out in multiple historical projects are aggregated, and the manpower demand time series curve is obtained through time series clustering algorithm; Peak features are extracted from the time-series curve of manpower demand to identify the periodic fluctuation pattern of manpower demand and the characteristics of cross-project resource conflicts; Based on the cyclical fluctuations in manpower demand and the characteristics of cross-project resource conflicts, a time-load correlation model is established to predict the peak periods of manpower shortages for the projects to be carried out. Based on the peak period of the manpower shortage and the resource idle status of projects running concurrently with the projects to be carried out, a cross-project human resource secondment plan is dynamically generated.

5. A human resource input evaluation system for automotive process development, characterized in that, The system includes: The project multidimensional classification modeling module is used to construct an automotive process development project model based on the automotive manufacturing process, divide it into multiple projects, and define project type, development mode, development stage and professional module for each project. The initial model building and evaluation module acquires and builds an initial human resource input model based on historical project data, obtains the project information of the current project, inputs the project information of the current project into the initial human resource input model, and outputs the human resource input man-hour calibration value. The project information of the current project includes the project type, development mode, development stage and professional module of the current project. The multi-dimensional working hour data real-time acquisition module is used to obtain the actual manpower input working hours of the current project in real time through the working hour system, based on the project type, development mode, development stage and professional module; The model dynamic correction and iteration module is used to compare the actual man-hour input of the current project with the calibrated value of the man-hour input, and to correct the initial man-hour input model based on the comparison result to obtain an updated man-hour input model. The updated man-hour input model is used to calculate the predicted value of the man-hour input of the project to be carried out based on the project information of the project to be carried out. The model version storage and rollback module is used to store the standard working hour reference values ​​of each group in the updated human resource input model as new version calibration values ​​in the model version database, and record the model version number of the updated human resource input model; store the corresponding standard working hour reference values ​​in the initial human resource input model in the model version database, and record the model version number and revision history information of the initial human resource input model, wherein the revision history information includes the difference between the corresponding standard working hour reference values ​​in the initial human resource input model and the standard working hour reference values ​​of each group in the updated human resource input model; when a rollback instruction is obtained, the currently used human resource input model is updated to the human resource input model corresponding to the model version number according to the model version number in the rollback instruction; The updated human resource input model is obtained through the following steps: When the comparison result is that the actual manpower input hours of the current project exceed the manpower input hour calibration value, the current project is classified and grouped by the project type, development mode, development stage and professional module through the time system to obtain each group, and the time weighted average of each group is calculated. The corresponding standard working hour reference value in the initial human resource input model is updated by the time-weighted average of each group, thus obtaining the updated human resource input model. Calculate the relative difference between the weighted average working hours of each group and the corresponding standard working hour reference value in the initial human resource input model; when the relative difference is greater than a preset difference threshold, generate an early warning instruction, which is used to send warning information to the operator; receive a feedback instruction, and when the feedback instruction is a manual confirmation instruction, update the corresponding standard working hour reference value in the initial human resource input model using the manual confirmation value in the manual confirmation instruction to obtain the updated human resource input model.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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