Product development process management method and system

Abstract

The invention relates to a product development process management method and system, and the method comprises the steps: obtaining demand information, carrying out the project creation stage review of the demand information, and determining whether to carry out project establishment or not according to a project creation review result, so as to generate a corresponding project establishment project; performing product design development review on the project approval project, and determining whether to perform a proofing application or not according to a design development review result so as to generate a corresponding sample; performing engineering verification test stage review on the sample, and determining whether to apply for mold opening according to a verification test review result so as to generate corresponding part data; performing design verification test stage review on the part data, and determining whether to perform trial production verification according to a design verification review result so as to generate corresponding trial production verification data; and carrying out production verification stage summarization on the trial production verification data, and determining whether to carry out mass production according to a summarization result of the production verification stage summarization so as to generate a corresponding product. The method has the effect of improving the product development efficiency.

Description

Technical Field

[0001] This application relates to the technical field of product development management, and particularly to a product development process management method and system. Background Art

[0002] Currently, the product development process usually includes multiple stages, such as requirement analysis, product design, prototyping, trial production, and mass production, etc. In traditional product development management, many links rely on manual experience and manual decision-making for review and judgment. Although this method can ensure the smooth progress of product development to a certain extent, there are also problems such as low efficiency, inconsistent review standards, and lack of timely adjustment of decisions. In addition, existing process management methods often cannot respond promptly to changes in market demand and technological uncertainties, resulting in a long product development cycle, high costs, and difficulty in quickly responding to market dynamics.

[0003] The above-mentioned existing technical solutions have the following defects: The traditional review process relies on manual decision-making, which is inefficient and prone to subjective biases, so there is room for improvement. Summary of the Invention

[0004] In order to improve the efficiency of product development, this application provides a product development process management method and system.

[0005] The first invention object of this application is achieved through the following technical solutions: A product development process management method, the product development process management method includes: Obtain requirement information, conduct a review in the project creation stage on the requirement information through a preset intelligent review algorithm, and determine whether to initiate a project based on the project creation review result of the project creation stage review, so as to generate a corresponding project for initiation; If the project initiation is successful, conduct a product design and development review on the initiated project, and determine whether to apply for prototyping based on the design and development review result of the product design and development review, so as to generate a corresponding sample; If a prototyping application is made, conduct a review in the engineering verification and testing stage on the sample, and determine whether to apply for mold opening based on the verification and testing review result of the engineering verification and testing stage review, so as to generate corresponding component data; If a mold opening application is made, conduct a review in the design verification and testing stage on the component data, and determine whether to conduct a trial production verification based on the design verification review result of the design verification and testing stage review, so as to generate corresponding trial production verification data; If a trial production verification is conducted, summarize the production verification stage on the trial production verification data, and determine whether to conduct mass production based on the summary result of the production verification stage summary, so as to generate a corresponding product; Automatically optimize the criteria and processes for each review stage based on real-time data feedback and historical data analysis, and automatically adjust the decision results of the review stage.

[0006] By adopting the above technical solution, by obtaining requirement information and applying a preset intelligent review algorithm to review the requirement information in the project creation stage, it is possible to automatically evaluate the project feasibility in a data-driven manner at the initial stage of the project, help automatically determine whether the project meets the project establishment criteria, thereby improving the efficiency and accuracy of the review process; when the project is successfully established, reviewing the product design and development can ensure that the design scheme meets the requirement standards and market requirements. Through the automated review mechanism, combining requirement information and market feedback can reduce resource waste and project delays caused by non-conforming design schemes; after the proofing application, through the review in the engineering verification and testing stage, it can ensure that the samples meet the standards in the actual production process. Through the review of this stage, defects or inappropriateness in the design scheme can be discovered and adjusted in a timely manner, which can improve the accuracy and response speed of the testing, reduce manual intervention, and improve the accuracy of the verification and testing stage; through the review of the design verification and testing stage for component data, it can ensure that the component design meets the production and functional requirements. Through the automated verification process, design defects can be discovered in a timely manner, reducing the later production costs and time delays caused by component problems; in the trial production verification stage, by summarizing and analyzing the trial production data, it is possible to effectively evaluate the quality and production capacity of the trial production products; by combining real-time data feedback and historical data analysis, the criteria and processes for each review stage can be automatically optimized, making the decisions in each stage more accurate and efficient.

[0007] In a preferred example, this application can be further configured as: the obtaining of requirement information, reviewing the requirement information in the project creation stage through a preset intelligent review algorithm, and determining whether to establish a project based on the project creation review result of the project creation stage to generate the corresponding established project includes: Conduct a structured analysis of the requirement information to generate a preliminary specification; Based on the preliminary specification, conduct a general design to generate a preliminary design scheme; Identify the feasibility and market demand of the preliminary design scheme to form the project creation review result; Based on the project creation review result, determine whether the preliminary design scheme meets the project establishment criteria. If the preliminary design scheme does not meet the project establishment criteria, return the preliminary design scheme to the general design for re-design; If the preliminary design scheme meets the project establishment criteria, establish the project to generate the corresponding established project.

[0008] By adopting the above technical solution, through the structured analysis of the requirement information, the original requirement information can be transformed into a more operable preliminary specification. By clearly defining the requirements and specifications, it ensures that all parties have the same expectations for the product and avoids ambiguity in the later development. Based on the preliminary specification, a general design is carried out and a preliminary design scheme is generated, which helps to clarify the overall architecture, main functions and technical paths of the product, determine the feasibility of technical implementation, identify the key modules and implementation methods of the product functions, and avoid resource waste caused by prematurely entering the detailed design stage. By conducting a feasibility analysis of the preliminary design scheme and evaluating it in combination with market demands, it can be judged whether the scheme meets the actual production capacity and market acceptance, improving the accuracy and market fit of the product design scheme and reducing the risk of resource waste. According to the project creation review result, it is judged whether the preliminary design scheme meets the project approval criteria, ensuring that the project enters the project approval stage only when the design scheme meets the company's strategy and market demands. If the preliminary design scheme does not meet the project approval criteria, it is promptly returned to the general design stage for re-design, which can avoid wasting a lot of time and resources when problems are found after the project enters the project approval stage. When the preliminary design scheme meets the project approval criteria, entering the project approval stage in a timely manner can ensure that the development team has a clear and feasible design scheme before starting the specific implementation.

[0009] In a preferred example of the present application, it can be further configured that: before judging whether the preliminary design scheme meets the project approval criteria based on the project creation review result, the method for managing a product development process further includes: Conduct a risk analysis on the preliminary design scheme to generate a risk assessment result; Adjust the project approval criteria according to the risk assessment result.

[0010] By adopting the above technical solution, through the risk analysis of the preliminary design scheme, the possible risk factors in the design can be systematically identified. Through risk assessment, the possible bottlenecks or problems in the project can be discovered in advance, providing data-based risk prediction for decision-makers, significantly improving the accuracy of decision-making, reducing the risk of project failure, and enhancing the controllability of project development. By dynamically adjusting the project approval criteria, the project can maximize the avoidance of possible risks while ensuring feasibility and market demands, ensuring that the project is more stable during the implementation process and helping to increase the probability of project success.

[0011] In a preferred example of the present application, it can be further configured that: for the approved project, a product design and development review is conducted, and based on the design and development review result of the product design and development review, it is determined whether to apply for a prototype to generate the corresponding sample, including: Conduct a review based on the matching degree between the approved project and the requirement information to generate the design and development review result; Based on the design and development review result, determine whether the approved project meets the design standards. If the approved project does not meet the design standards, generate design improvement suggestions and enter the design improvement stage for the approved project according to the design improvement suggestions; If the approved project meets the design standards, enter the sample making application to generate the corresponding samples.

[0012] By adopting the above technical solution, through the evaluation of the matching degree, the accuracy of design and development can be effectively improved, avoiding design deviation from market demands or technical goals, thereby improving the success rate and benefits of project development; by judging whether the approved project meets the design standards according to the design and development review result, deficiencies and non-conforming items in the design can be timely discovered to ensure that the product meets the technical requirements and quality standards in the design stage; if the approved project meets the design standards, immediately enter the sample making application, which means that the project enters the actual manufacturing and verification stage, providing a basis for subsequent sample production.

[0013] This application can be further configured in a preferred example as follows: If a sample making application is carried out, conduct a review in the engineering verification test stage for the sample. According to the verification test review result of the engineering verification test stage, determine whether to apply for mold opening to generate the corresponding component data, including: During the verification test process, collect the sample test data in real time through Internet of Things devices, identify the anomalies in the test, and mark the priority of the abnormal data that appears to generate a dynamic test report; Analyze the dynamic test report to generate the verification test review result; Based on the verification test review result, determine whether the sample meets the mold opening standards. If the sample does not meet the mold opening standards, generate sample improvement suggestions and return to the design improvement stage for improvement according to the sample improvement suggestions; if the sample meets the mold opening standards, enter the mold opening application to generate the corresponding component data; When judging whether the sample meets the mold opening standards, identify the abnormal type of the abnormal data that appears and adjust the mold opening standards according to the abnormal type.

[0014] By adopting the above technical solution, real-time collection of the test data of the sample through the Internet of Things device can continuously monitor and record various performance indicators of the sample during the test, ensure the timeliness and comprehensiveness of the test data, identify abnormalities in the test and mark the priority of the abnormal data, and can automatically distinguish key issues from minor issues, so as to focus on handling the most urgent or important abnormal situations during the test; through the automated data analysis and review process, the review efficiency can be improved and human analysis errors can be reduced; by judging whether the sample meets the mold opening standard based on the verification test review result, it can be ensured that only the samples that have passed strict verification will enter the mold opening stage, reducing the risk of unqualified products entering the production link; finally, the mold opening standard can be flexibly adjusted to optimize the standard in a timely manner according to the abnormal data, improving the adaptability of product design and the level of quality control.

[0015] In a preferred example of the present application, it can be further configured as: performing a review on the component data in the design verification test stage, and determining whether to conduct a trial production verification based on the design verification review result of the design verification test stage to generate corresponding trial production verification data, including: Determining the components based on the component data. If the component data does not meet the component standard, enter the mold improvement stage for improvement; If the component data meets the component standard, generate a mold prototype according to the component data; Conduct a proofing test on the mold prototype and monitor the proofing data of the mold prototype in real time; Conduct quality control analysis on the proofing data to generate a quality analysis result, and based on the quality analysis result, judge whether the mold prototype meets the proofing production standard. If the mold prototype does not meet the proofing production standard, return the component data to the mold improvement stage for secondary improvement; If the mold prototype meets the proofing production standard, enter the trial production verification to generate the corresponding trial production verification data.

[0016] By adopting the above technical solutions, through the confirmation and detection of component data, it is ensured that only component data meeting the standards enters the subsequent mold design stage. By timely discovering and processing unqualified data in the early stage, the modification cost can be reduced, the quality and accuracy of the final mold can be ensured, thereby improving production efficiency; through the generation of mold prototypes, proofing tests, and real-time data monitoring, problems can be timely discovered and corrected during the trial production stage to ensure that the final mold meets the production standards; in the quality control analysis of mold prototypes, the automated quality assessment improves the accuracy and reduces human errors; if the mold prototype does not meet the standards, it can enter the mold improvement stage for correction through the feedback mechanism, ensuring high-quality standards for each link; finally, the mold prototype meeting the standards will enter the trial production verification stage, providing reliable data support for the production link.

[0017] In a preferred example of the present application, it can be further configured as follows: if trial production verification is carried out, summarize the trial production verification data in the production verification stage, and determine whether to carry out mass production according to the summary result of the production verification stage summary, so as to generate the corresponding product, including: Based on the trial production verification data, use the k-means algorithm to summarize the product verification results and generate a summary result; Generate a mass production feasibility report according to the summary result and mark the production bottlenecks; Summarize and review the mass production feasibility report. If the review of the mass production feasibility report fails, improve it according to the mass production feasibility report; If the review of the mass production feasibility report passes, carry out mass production to generate the corresponding product.

[0018] By adopting the above technical solutions, through the use of the k-means algorithm to perform clustering analysis on the trial production verification data, the patterns and trends in the product verification process can be effectively identified, thereby discovering potential laws and problems, and avoiding the errors that may be brought by traditional empirical decision-making; by generating a mass production feasibility report and marking the production bottlenecks in the report, it can help the development team evaluate the feasibility of mass production from a global perspective, and help the team foresee and solve the problems that may affect production efficiency and quality before officially entering mass production; the review mechanism ensures that the problems in the report are timely discovered and solved, thereby avoiding the risks in mass production; finally, after the review of the mass production feasibility report passes, it smoothly enters the mass production stage to ensure the stability of product quality and production efficiency.

[0019] The second above-mentioned invention object of the present application is achieved through the following technical solutions: A product development process management system, the product development process management system includes: Create a review module for obtaining requirement information, reviewing the requirement information in the project creation phase through a preset intelligent review algorithm, and determining whether to initiate a project based on the project creation review results of the project creation phase review, so as to generate a corresponding initiated project; Develop a review module for, if the project initiation is successful, reviewing the initiated project in the product design and development review, and determining whether to apply for sample production based on the design and development review results of the product design and development review, so as to generate a corresponding sample; Verify a review module for, if a sample production application is made, reviewing the sample in the engineering verification test phase, and determining whether to apply for mold opening based on the verification test review results of the engineering verification test phase, so as to generate corresponding component data; Design a review module for, if a mold opening application is made, reviewing the component data in the design verification test phase, and determining whether to conduct trial production verification based on the design verification review results of the design verification test phase, so as to generate corresponding trial production verification data; Summarize a module for, if trial production verification is conducted, summarizing the trial production verification data in the production verification phase, and determining whether to mass produce based on the summary results of the production verification phase, so as to generate a corresponding product; An optimization module for automatically optimizing the standards and processes of each review phase and automatically adjusting the decision results of the review phase based on real-time data feedback and historical data analysis.

[0020] By adopting the above technical solutions, by obtaining requirement information and applying a preset intelligent review algorithm to review the requirement information in the project creation stage, it is possible to automatically evaluate the project feasibility in a data-driven manner at the initial stage of the project, helping to automatically determine whether the project meets the project approval criteria, thereby improving the efficiency and accuracy of the review process; after the project approval is successful, reviewing the product design and development can ensure that the design scheme meets the requirement standards and market requirements. Through the automated review mechanism, by combining requirement information and market feedback, it is possible to reduce resource waste and project delays caused by inconsistent design schemes; after the proofing application, through the review in the engineering verification and testing stage, it can be ensured that the samples meet the standards in the actual production process. Through the review of this stage, defects or inappropriateness in the design scheme can be discovered and adjusted in a timely manner, which can improve the accuracy and response speed of the testing, reduce manual intervention, and improve the accuracy of the verification and testing stage; by reviewing the component data in the design verification and testing stage, it can be ensured that the component design meets the production and functional requirements. Through the automated verification process, design defects can be discovered in a timely manner, reducing the later production costs and time delays caused by component problems; in the trial production verification stage, by summarizing and analyzing the trial production data, it is possible to effectively evaluate the quality and production capacity of the trial production products; by combining real-time data feedback and historical data analysis, it is possible to automatically optimize the standards and processes of each review stage, making the decisions in each stage more accurate and efficient.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: 1. By obtaining requirement information and applying a preset intelligent review algorithm to review the requirement information in the project creation stage, it is possible to automatically evaluate the project feasibility in a data-driven manner at the initial stage of the project, helping to automatically determine whether the project meets the project approval criteria, thereby improving the efficiency and accuracy of the review process; after the project approval is successful, reviewing the product design and development can ensure that the design scheme meets the requirement standards and market requirements. Through the automated review mechanism, by combining requirement information and market feedback, it is possible to reduce resource waste and project delays caused by inconsistent design schemes; 2. Through the review in the engineering verification test stage, it can be ensured that the samples meet the standards during the actual production process. By passing the review of this stage, defects or inappropriateness in the design scheme can be discovered and adjusted in a timely manner, which can improve the accuracy and response speed of the test, reduce manual intervention, and improve the accuracy of the verification test stage. By reviewing the component data in the design verification test stage, it can be ensured that the component design meets the production and functional requirements. Through the automated verification process, design defects can be discovered in a timely manner, reducing the late production costs and time delays caused by component problems. In the trial production verification stage, by summarizing and analyzing the trial production data, the quality and production capacity of the trial production products can be effectively evaluated. By combining real-time data feedback and historical data analysis, the standards and processes of each review stage can be automatically optimized, making the decisions in each stage more accurate and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a flowchart of a product development process management method according to an embodiment of the present application; Figure 2 is an implementation flowchart of step S10 in a product development process management method according to an embodiment of the present application; Figure 3 is an implementation flowchart of step S14 in a product development process management method according to an embodiment of the present application; Figure 4 is an implementation flowchart of step S20 in a product development process management method according to an embodiment of the present application; Figure 5 is an implementation flowchart of step S30 in a product development process management method according to an embodiment of the present application; Figure 6 is an implementation flowchart of step S40 in a product development process management method according to an embodiment of the present application; Figure 7 is an implementation flowchart of step S50 in a product development process management method according to an embodiment of the present application; Figure 8 is a schematic block diagram of a product development process management system according to an embodiment of the present application; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The present application will be further described in detail below with reference to the accompanying drawings.

[0024] In one embodiment, as Figure 1 shown, the present application discloses a product development process management method, which specifically includes the following steps: S10: Obtain requirement information, conduct a review during the project creation phase on the requirement information through a preset intelligent review algorithm, and determine whether to initiate a project based on the project creation review results of the project creation phase review, so as to generate the corresponding initiated project.

[0025] Specifically, during the project creation phase, the requirement information enters the review system through user input or file upload. The requester uploads relevant documents, such as new product development forms, feasibility analysis reports, requirement evaluations, preliminary specifications, preliminary design plans, A-BOM costs, etc. to the platform. The platform uses the preset intelligent review algorithm to perform structured processing on this requirement information, automatically identify and extract key information, and score each piece of data through an algorithm model. The scoring criteria are based on historical data and industry rules. The intelligent review algorithm will automatically calculate the review results by combining multiple dimensions such as market demand, technical feasibility, and project costs. If the review passes, the system will automatically generate an initiated project document and enter the next phase; if the review fails, the system will feedback modification opinions and require the requester to make adjustments. The review results of this phase will generate project creation documents, including development forms, pre-research task books, initial versions of technical specifications, A-BOM cost tables, etc. The scoring algorithm can be, for example, S = ω 1 ×M + ω 2 ×T + ω 3 ×C, where M is the market capacity, T is the technical feasibility, and C is the production cost. Based on this comprehensive scoring result, the review result is to initiate a project or not.

[0026] S20: If the project initiation is successful, conduct a product design and development review on the initiated project, and determine whether to apply for a prototype based on the design and development review results of the product design and development review, so as to generate the corresponding samples.

[0027] Specifically, after the project initiation is successful, the project will enter the product design and development phase. Detailed designs will be carried out according to the project initiation documents, and documents such as design drawings, DFMEA analysis tables, manufacturability and certification evaluation reports will be uploaded to the review platform. In this phase, the intelligent review algorithm will automatically analyze and compare these design documents, focusing on evaluating factors such as design feasibility, production costs, certification requirements, and market demand. The system will automatically generate a review score and determine whether to pass by comparing the design data of historical projects. If the review passes, the project will enter the prototype application phase, and relevant documents such as design and development project initiation letters, project schedules, etc. will be generated; if the review fails, the system will automatically return the project for modification until the review passes.

[0028] S30: If a prototype application is made, conduct a review during the engineering verification and testing phase on the samples, and determine whether to apply for tooling based on the verification and testing review results of the engineering verification and testing phase, so as to generate the corresponding component data.

[0029] Specifically, during the review of the engineering verification test phase, the samples will be rigorously tested in a controlled environment. The test contents include but are not limited to material strength, performance stability, and actual service life. By comparing historical data and industry standards, the quality of the samples will be comprehensively verified. The reviewers will give conclusions based on the test results. Whether the test results meet the production requirements will be obtained through an evaluation algorithm. The algorithm formula is, is the actual test data, X 2 is the design expected data, σ is the standard deviation of the test data. According to the comparison calculation results, T is the preset threshold to determine whether to enter the mold opening application stage. If the review results indicate that the samples meet the requirements and there is market potential, then enter the mold opening stage. If they do not meet the requirements, adjust the design according to the review conclusions or conduct engineering verification again. At the end of this stage, the following documents will be output: structural data package, product data package, heat dissipation, optical simulation report, electrical data package, DFMEA, packaging design drawings, B-BOM quotation, test-related reports in the engineering verification test phase, and review form in the engineering verification test phase.

[0030] S40: If a mold opening application is made, conduct a review of the component data in the design verification test phase. According to the design verification review results in the design verification test phase, determine whether to conduct a trial production verification to generate corresponding trial production verification data.

[0031] Specifically, the design verification test phase mainly conducts rigorous functional and durability tests on the components before production. The test process includes tests in different working environments to simulate the usage in actual production, ensuring that no major failures will occur during the long-term use of the components. At the same time, collect the component design documents, mold drawings, etc. uploaded by the design team. The system analyzes the documents through the intelligent review module to identify the manufacturability of the components, the design accuracy of the molds, and the potential risks in the production process. The system will automatically evaluate these data, compare them with the historical design verification data, and use machine learning algorithms to determine whether they meet the design standards. If the review results are qualified, the system will automatically generate a trial production verification application document and notify the relevant departments to enter the trial production verification stage; if the review fails, the system will automatically feedback modification opinions and require the team to readjust the design.

[0032] S50: If a trial production verification is conducted, summarize the trial production verification data in the production verification phase. According to the summary results in the production verification phase, determine whether to conduct mass production to generate corresponding products.

[0033] Specifically, during the summary process of the trial production verification phase, a comprehensive inspection is carried out on the first batch of trial production products, including dimensional accuracy, appearance quality, and functional testing, etc. The data collector records various production data and compares them with the standard parameters to evaluate the production process, quality control, and whether the product meets the mass production standards. Based on the data in the production verification phase, the system will automatically conduct quality assessment and generate a summary report to produce a trial production summary document. If the review is passed, the system will automatically generate a mass production application document and enter the mass production phase; if the review fails, the system will provide feedback, requiring adjustments to the production process and re-conducting the trial production verification.

[0034] S60: Based on real-time data feedback and historical data analysis, automatically optimize the standards and processes of each review phase, and automatically adjust the decision results of the review phase.

[0035] Specifically, through real-time data feedback and historical data analysis, continuously adjust the standards and processes of each review phase. During the real-time data analysis process, the review results of each phase will be collected and analyzed, and model training will be carried out through machine learning algorithms. According to the historical review data, the key decision points of each phase will be predicted, so as to adjust and optimize the review standards to improve the accuracy and efficiency of the review. For example, if historical data shows that at a certain stage, the failure rate of the project due to design problems is relatively high, the system will automatically adjust the design review standards at this stage to increase the attention to design defects. The optimized standards will be automatically applied to all subsequent projects to ensure that the review decisions are more accurate. The system will dynamically adjust the decision thresholds of the review according to these optimization results. For example, the reinforcement learning method is used to optimize the decision-making process of the review phase, and the algorithm formula is: R = E[r t + γV(s t+1 )], where rt is the feedback reward of the current phase, γ is the discount factor, and V(s t+1 ) is the expected reward of the future state. Optimize the standards of the review phase according to historical data, automatically adjust the review process and decision results to ensure that the review of each phase achieves the best effect.

[0036] Furthermore, the development of the entire project has several major stages. Each stage consists of several processes, which are interrelated to ensure that the work in each stage is not missing and the project information can flow efficiently, thereby effectively improving the development efficiency and quality. In the project creation stage, requirement information is obtained and automatically processed, scored, and reviewed through a preset intelligent review algorithm to decide whether to initiate a project. If there are problems in the input link of the requirement information, subsequent steps such as project initiation and design will not be able to proceed smoothly; after the project is successfully initiated, the project enters the product design and development stage. At this time, the detailed design of the product begins. According to the project initiation document and requirement information, the design team will submit design drawings, DFMEA analysis tables, manufacturability reports, certification evaluations and other documents. The quality of design and development directly affects subsequent processes such as prototyping and verification testing. If the design documents do not pass the review of the intelligent review system, the project cannot enter the prototyping application stage; the review result of the prototyping application decides whether to enter the engineering verification testing stage. If the test fails at this stage, the design scheme needs to be optimized again before entering the subsequent production link; before entering the mold opening stage, the design verification of the parts needs to be strictly reviewed. At this time, the design verification test includes tests simulating the production environment to ensure the function and durability of the parts in various environments. If the design verification fails, it will affect the mold making and the production of parts. This stage also involves the uploading and intelligent analysis of part design documents and mold drawings, and the review result directly affects the subsequent processes; the trial production stage is the final inspection before mass production. By comprehensively inspecting the first batch of products produced, it is ensured that the production process, appearance quality, function, etc. all meet the standards. The summary report of the trial production verification will decide whether to officially enter mass production. If problems are found during the trial production process, the production process needs to be adjusted or trial production needs to be carried out again. There is a close correlation between each stage of the entire project development process and the processes within it. The smooth connection and efficient flow of these processes ensure that the project can cover every link from requirement review, design and development, verification testing to mass production without omission, and based on the review results of each stage, the relevant processes and standards are adjusted and optimized in a timely manner. In this way, the development efficiency of the project is improved, and at the same time, the development quality is guaranteed.

[0037] By adopting the above technical solutions, by obtaining requirement information and applying a preset intelligent review algorithm to review the requirement information in the project creation stage, it is possible to automatically evaluate the project feasibility in the initial stage of the project in a data-driven manner, help automatically determine whether the project meets the project establishment criteria, thereby improving the efficiency and accuracy of the review process; after the project is successfully established, reviewing the product design and development can ensure that the design scheme meets the requirement standards and market requirements. Through the automated review mechanism, combined with requirement information and market feedback, it is possible to reduce resource waste and project delays caused by non-compliant design schemes; after the proofing application, through the review in the engineering verification and testing stage, it can be ensured that the samples meet the standards in the actual production process. Through the review in this stage, defects or inappropriateness in the design scheme can be found and adjusted in a timely manner, which can improve the accuracy and response speed of the testing, reduce manual intervention, and improve the accuracy of the verification and testing stage; through the review of the component data in the design verification and testing stage, it can be ensured that the component design meets the production and functional requirements. Through the automated verification process, design defects can be found in a timely manner, reducing the later production costs and time delays caused by component problems; in the trial production verification stage, by summarizing and analyzing the trial production data, it is possible to effectively evaluate the quality and production capacity of the trial production products; by combining real-time data feedback and historical data analysis, the standards and processes of each review stage can be automatically optimized, making the decision-making in each stage more accurate and efficient.

[0038] In one embodiment, as Figure 2 shown, in step S10, that is, obtaining requirement information, reviewing the requirement information in the project creation stage through a preset intelligent review algorithm, and determining whether to establish a project according to the project creation review result of the project creation stage to generate a corresponding established project, specifically including: S11: Perform a structured analysis on the requirement information to generate a preliminary specification.

[0039] Specifically, through the structured analysis of the requirement information, natural language processing (NLP) technology can be used to parse the requirement document text, extract key information such as relevant functional requirements, performance requirements, and design constraints, and convert this information into a structured format, such as JSON or XML structure. During the analysis process, first perform word segmentation on the requirement text, compare the core requirement points in the text with existing templates through rule matching and semantic analysis, and mark inconsistent or ambiguous requirements as items to be confirmed. Subsequently, classify the parsed information by module, sub-module, and function point, and assign necessary priorities and weights to each function point for subsequent development. Finally, this structured information will be integrated into a preliminary specification, which includes detailed descriptions of each functional module, input and output requirements, performance indicators, and other contents.

[0040] S12: Conduct a preliminary design based on the preliminary specification to generate a preliminary design plan.

[0041] Specifically, based on the functional requirements and performance standards in the preliminary specification, carry out the preliminary design. First, in the preliminary design stage, the general architecture of the system will be divided according to the function points in the requirements document, such as the hardware architecture, software architecture, communication interfaces between modules, etc. When designing, factors such as modularity, scalability, and stability will be considered. At this stage, the focus is on defining the responsibilities of each module, input and output interfaces, and their interaction methods with other modules. The object-oriented design method is adopted in the design process, and tools such as UML class diagrams, sequence diagrams, and data flow diagrams are used to describe the main processes and data exchange methods of the system. At the same time, a preliminary evaluation of the key technical paths of the system will be carried out to identify possible technical difficulties and make corresponding technical reserves and plan adjustments. Finally, a preliminary design plan is generated, which includes design sketches of the main functional modules, preliminary layouts of the system architecture, module interface definitions, and flowcharts, etc.

[0042] S13: Identify the feasibility of the preliminary design plan and market demand to form the project creation review result.

[0043] Specifically, to identify the feasibility of the preliminary design plan and market demand, it is first necessary to analyze the market demand intensity and potential user groups for this design plan through market research data, compare the performance, price and other indicators of existing similar products, and judge whether this plan meets the market demand. To ensure the feasibility of the design plan, it is also necessary to evaluate its technical feasibility, use engineering analysis methods to calculate and simulate the plan, and evaluate its operability in actual applications. For example, through means such as performance test simulation, resource consumption evaluation, and technology maturity analysis, judge whether there are technical bottlenecks or infeasible risks in this design plan. If both the market demand and technical feasibility meet expectations, a project creation review result will be formed, and suggestions on whether to continue to promote will be given according to the review result. The review result may include market potential analysis reports, technical risk assessments, cost-benefit analyses, etc.

[0044] S14: Based on the project creation review result, judge whether the preliminary design plan meets the project establishment criteria. If the preliminary design plan does not meet the project establishment criteria, return the preliminary design plan to the preliminary design for re-design.

[0045] Specifically, based on the review results of the project creation, the judgment of the project establishment criteria is carried out. First, it is necessary to compare the review results with the preset project establishment criteria to determine whether the preliminary design scheme meets the conditions for project initiation. The review criteria may include multiple dimensions such as market demand intensity, technical feasibility, cost-benefit ratio, and innovation. If the review results of the preliminary design scheme fail to meet these criteria, feedback will be given on the review results, and a redesign will be required. This process is executed by establishing a decision tree. Each node of the decision tree represents a judgment on a certain review criterion, and the output of the node determines the next operation. For example, if the market demand is insufficient, it will return to the general design stage for redesign; if the technology is not feasible, it will return to the design stage to re-evaluate the technical path. After the redesign, the team will re-examine all review criteria to ensure that all conditions are met.

[0046] S15: If the preliminary design scheme meets the project establishment criteria, project establishment will be carried out to generate the corresponding established project.

[0047] Specifically, once the preliminary design scheme meets the project establishment criteria, the review results will be used to initiate the project. First, an establishment meeting will be organized. At the meeting, the overall framework and goals of the project will be discussed based on the confirmed design scheme and review results. After the meeting is passed, the project will officially enter the implementation stage. The project leader will form a project team according to the project establishment plan, arrange development tasks, and formulate a project plan. At this time, the project establishment plan will clarify the content such as the project goals, milestones, budget, and risk management plan. The project after establishment will enter the detailed design and development stage. In this process, the team will start to make a detailed plan, resource allocation, and time arrangement for the scheme. The success or failure of the project will be used as a reference for subsequent evaluation based on the review criteria in the project establishment stage.

[0048] In an embodiment, as Figure 3 shown, before step S14, that is, before judging whether the preliminary design scheme meets the project establishment criteria based on the review results of the project creation, this product development process management method further includes: S141: Conduct a risk analysis on the preliminary design scheme to generate a risk assessment result.

[0049] Specifically, by comprehensively evaluating the various contents of the preliminary design plan and identifying potential risk factors, risk analysis can include multiple aspects such as technical risks, market risks, and resource risks. First, technical risk analysis conducts simulations and simulations on the key technologies in the design plan to analyze whether there are technical bottlenecks or implementation difficulties. For example, if the design plan uses immature technologies or there are risks of unqualified performance, historical data can be used for technical feasibility analysis, calculating the probability of possible failures, and evaluating alternative technical paths; market risk analysis evaluates the acceptance and competitiveness of the plan in the market through investigations of market demand, competitors, and user feedback. Based on existing market research data, methods such as regression analysis and volatility analysis are used to estimate the market changes and demand fluctuations that the product may face; resource risk analysis assesses the possible resource shortages or supply chain problems during the project implementation process, and uses sensitivity analysis to evaluate the impact of insufficient resources on the project schedule and quality in different situations. All these analysis results will be combined with the possibility and severity of each risk, and a risk assessment result will be comprehensively obtained through the weighted scoring method.

[0050] S142: According to the risk assessment result, adjust the project approval criteria.

[0051] Specifically, based on the risk assessment result, for the impact and possibility of each risk, adjust the original project approval criteria to ensure that the project approval criteria can reasonably cover potential risks. For example, in the case of high technical risks, it may be necessary to increase the requirements for technical feasibility verification in the project approval criteria, such as requiring a small-scale prototype test or technical pre-research before project approval to ensure the smooth progress of the project technically; if the market risk is high, it may be necessary to strengthen the market research link in the project approval criteria, such as requiring a larger-scale market survey before project approval to understand a wider range of user needs and market dynamics, so as to reduce the risks brought by market uncertainties. In addition, the adjustment of the project approval criteria will consider the priority of each risk in the risk assessment and pay special attention to high-risk areas to ensure the successful initiation and smooth progress of the project.

[0052] In one embodiment, as Figure 4 shown, in step S20, that is, conduct a product design and development review on the approved project, and determine whether to apply for proofing to generate corresponding samples according to the design and development review results of the product design and development review, which specifically includes: S21: Conduct a review based on the matching degree between the approved project and the requirement information to generate a design and development review result.

[0053] Specifically, through a comprehensive matching analysis of the project under consideration and the requirement information, first identify the design objectives, functional requirements, technical specifications, etc. of the project under consideration, and compare them with factors such as market demand, user requirements, and technical feasibility in the requirement information. By setting weights for each element in the project under consideration and the requirement information, calculate the matching score between the two. For example, if the requirement information emphasizes the low-power consumption feature of the product, but the design of the project under consideration does not fully consider this requirement, the score will be relatively low; if the two match highly, the score will be high. Finally, through the calculation of the weighted total score, obtain the comprehensive review result of the project's matching with the requirements. The review result may be a numerical score or a risk assessment report, reflecting whether the project under consideration meets the key requirements of the requirement information. Based on the review result, a conclusion for the design and development review can be generated, such as whether to enter the proof-of-concept application stage and whether design modifications are required.

[0054] S22: Based on the design and development review result, determine whether the project under consideration meets the design standards. If the project under consideration does not meet the design standards, generate design improvement suggestions, and enter the design improvement stage for the project under consideration according to the design improvement suggestions.

[0055] Specifically, according to the product design and development review result, evaluate whether the project meets the predetermined design standards, which may include aspects such as functionality, reliability, cost control, and material selection. Use the difference analysis method to compare the review result with the design standards. If certain design objectives are not met, generate corresponding design improvement suggestions. For example, if the review result shows that the cost of the project under consideration is higher than the budget, the adjusted cost range can be calculated through a cost analysis algorithm, providing possible directions for design improvement, such as optimizing materials and simplifying functions, to achieve a design that meets the budget; if the design does not meet the requirement standards in certain functions, it can be recommended to add specific functional modules or adjust the existing design. Once the improvement suggestions are determined, the project will enter the design improvement stage. In this stage, the product design will be modified and improved according to the improvement suggestions until the design standards are met.

[0056] S23: If the project under consideration meets the design standards, enter the proof-of-concept application to generate the corresponding samples.

[0057] Specifically, if the review result shows that the project under consideration meets the design standards and all key design requirements are effectively met, the project will enter the proof-of-concept application stage. At this time, the goal of the proof-of-concept stage is to generate samples for testing and verification, which are used to further verify the feasibility of the design. In this process, first, specific requirements for sample production will be generated according to the design documents, such as parameters of materials, processes, dimensions, etc., and then the samples will be manufactured and processed to generate preliminary samples.

[0058] In one embodiment, as Figure 5As shown, in step S30, that is, if a proofing application is made, a review of the engineering verification test phase for the sample is carried out. According to the verification test review results of the engineering verification test phase, it is determined whether to apply for mold opening to generate corresponding component data, specifically including: S31: During the verification test, the sample test data is collected in real time through Internet of Things devices, the anomalies in the test are identified, and the priority of the abnormal data that appears is marked to generate a dynamic test report.

[0059] Specifically, in the verification test phase, the sample is monitored in real time through Internet of Things devices, and data including various parameters such as temperature, pressure, vibration, and current is collected. These Internet of Things devices upload the data to the data processing platform in real time through wireless communication protocols for rapid analysis and processing. By setting threshold rules or using machine learning algorithms, the collected data is compared in real time to determine whether the data exceeds the predetermined normal range. For example, when the sensor measures that the temperature exceeds the set value, the system will identify this as an anomaly, mark and classify it as a "high temperature anomaly", and record the specific time, duration, and related parameters when the anomaly occurs. Each item of abnormal data will be assigned a priority, usually evaluated according to its impact on product quality and safety. For example, "high priority" may be an anomaly that affects the structural strength, while "low priority" may be a minor problem that has no impact on the appearance. Through real-time analysis and processing, the system generates a dynamic test report, which includes the data and anomaly marks of each stage in the test process, providing a detailed test status and problem list.

[0060] S32: Analyze the dynamic test report to generate the verification test review results.

[0061] Specifically, the generated dynamic test report is further analyzed. First, all the collected test data is compared with the preset standard data to find all items that do not conform to the standard and classify them in detail. For each abnormal item, the system calculates its occurrence frequency, influence range, and possible causes. If the abnormal data appears multiple times and is related to multiple test parameters, the system will mark this abnormal item as high risk and needs to be processed first. Further, the system uses data mining and trend analysis methods to identify potential patterns in the data to help the reviewers judge whether the anomaly is repetitive, whether it is a design defect or a temporary problem. Based on this analysis, the verification test review results will show the overall feasibility of the sample, such as whether there are major design defects or non-conformance to the expected performance standards.

[0062] S33: Based on the verification test review results, judge whether the sample meets the mold opening standard. If the sample does not meet the mold opening standard, generate improvement suggestions for the sample and return to the design improvement stage for improvement according to the sample improvement suggestions.

[0063] Specifically, based on the results of the verification test review, the system uses a series of verification criteria to determine whether the sample meets the mold opening criteria. If the abnormal data in the test review results indicates that the sample fails to meet the standards in certain aspects, such as insufficient strength or poor temperature tolerance, the system will automatically generate improvement suggestions for the sample. The improvement suggestions may include adjusting design parameters, using different materials, improving the process, etc. After generating the suggestions, the project will be assigned back to the design improvement stage, in which the design team will modify the design according to the improvement suggestions and optimize the sample until the problems in the test are solved and the mold opening criteria are met. If the sample still fails to pass the verification test after multiple rounds of improvement, the review results may suggest reexamining the design goals or technical routes.

[0064] S34: If the sample meets the mold opening criteria, enter the mold opening application to generate the corresponding component data.

[0065] Specifically, if the sample passes all verification tests and meets the mold opening criteria, the system will trigger the mold opening application process. The system generates the corresponding component data, such as 3D CAD models, dimensional parameters, material data, etc., based on the sample data after passing the verification test, and transfers it to the mold manufacturing department. In this way, after the sample meets the mold opening criteria, it can smoothly progress to the mass production of components and the subsequent mass production verification stage.

[0066] S35: When determining whether the sample meets the mold opening criteria, identify the abnormal type of the abnormal data that appears, and adjust the mold opening criteria according to the abnormal type.

[0067] Specifically, when determining whether the sample meets the mold opening criteria, the type of abnormal data will have an important impact on the adjustment of the mold opening criteria. For example, if a temperature abnormality is found during the test, the system will determine whether it is a problem with the sample material. If so, it may be necessary to adjust the material requirements in the mold opening criteria and select a material with higher temperature resistance; if the dimensional accuracy does not meet the standard during the test, the accuracy requirements for the mold may be adjusted, and a higher-precision processing technology may be used to produce the mold. According to different types of abnormalities, the mold opening criteria will be adjusted flexibly to address different test problems and ensure that the final components can meet the production requirements and the final design goals.

[0068] In one embodiment, as Figure 6 shown, in step S40, that is, during the review of the design verification test stage for the component data, determine whether to conduct a trial production verification based on the design verification review results of the design verification test stage to generate the corresponding trial production verification data, specifically including: S41: Conduct component determination on the component data. If the component data does not meet the component standards, enter the mold improvement stage for improvement.

[0069] Specifically, when determining the component data, first compare the design parameters of the components with the preset component standards, which include requirements in aspects such as but not limited to dimensional accuracy, material properties, mechanical properties, durability, etc. Automatically calculate and analyze the various data of the components through algorithms. For example, whether the dimensions are within the tolerance range, whether the material meets the strength and heat resistance requirements, etc. If there are situations where the component data does not meet the standards, such as excessive dimensional deviation, inappropriate material selection, etc., the system will automatically generate improvement suggestions and feedback these data to the mold improvement stage, notifying the designers to adjust the design or replace the material until the components meet the standards.

[0070] S42: If the component data meets the component standards, generate a mold prototype based on the component data.

[0071] Specifically, if the component data meets the component standards, the next step is to generate a mold prototype based on this data. In this process, according to the specifications and dimensional requirements of the components, use CAD software to generate the corresponding mold design drawings and perform 3D modeling. These data include design elements such as the specific shape, material, cooling channels, gating system, etc. of the mold. According to the physical and chemical characteristics of the components, the material and process parameters of the mold will also be precisely designed. For example, if the component is a high-temperature material, the mold may need to use high-temperature-resistant steel; if the component requires high-precision machining, the machining accuracy of the mold also needs to be specially set. After the design of the mold prototype is completed, it will be handed over to the mold manufacturing department for the production of the prototype.

[0072] S43: Conduct proofing tests on the mold prototype and monitor the proofing data of the mold prototype in real time.

[0073] Specifically, after the mold prototype is manufactured, it will enter the proofing stage for actual production testing. In this process, use the mold prototype to produce multiple samples, and monitor key parameters such as temperature, pressure, injection time, etc. in real time during each proofing process. By installing Internet of Things devices such as sensors, various data during the proofing process of the mold can be collected in real time, and these data will be transmitted to the test platform in real time for storage and processing. For example, the temperature sensor can monitor the heating temperature of the mold in real time, and the pressure sensor can monitor the pressure fluctuations during the injection process to ensure the stability of the parameters during the production process and avoid product defects caused by equipment failures or abnormal parameters. All these data will be dynamically recorded during the proofing test and provide basic data for subsequent quality analysis.

[0074] S44: Conduct quality control analysis on the proofing data, generate the quality analysis results, and based on the quality analysis results, determine whether the mold prototype meets the proofing production standards. If the mold prototype does not meet the proofing production standards, return the component data to the mold improvement stage for secondary improvement.

[0075] Specifically, after the proofing test is completed, all the collected proofing data will enter the quality control analysis stage. In this stage, the proofing data is comprehensively analyzed through data analysis software, including comparing the differences between the actual production data and the standard requirement data, calculating the deviation values, and identifying potential problems. For example, if there are obvious dimensional errors in certain areas of the proofing results of the mold prototype, the system will automatically mark these areas and analyze the reasons. It may be that some parameters in the mold design do not meet the actual production conditions, such as uneven cooling speed resulting in uneven material shrinkage. If serious quality problems are found in the samples, the quality analysis results will determine that the mold prototype does not meet the proofing production standards, and the system will automatically return the unqualified component data to the mold improvement stage, requiring further optimization of the mold design and modification of the problematic parameters in order to proof again and meet the production standards.

[0076] S45: If the mold prototype meets the proofing production standards, enter the trial production verification to generate the corresponding trial production verification data.

[0077] Specifically, if the mold prototype passes the quality control analysis and meets the proofing production standards, the next step will be to enter the trial production verification stage. In the trial production stage, the mold prototype will be used for small-batch production, and the data generated during the trial production process will be recorded in detail. These data include aspects such as production cycle, production stability, and product quality, especially the changes related to the key parameters in the production process. By further analyzing these trial production data, it is possible to verify whether the performance of the mold in actual production meets the long-term production requirements and timely discover potential optimization space.

[0078] In one embodiment, as Figure 7 shown, in step S50, that is, if trial production verification is carried out, summarize the production verification stage for the trial production verification data, and based on the summary results of the production verification stage summary, determine whether to carry out mass production to generate the corresponding products, specifically including: S51: Based on the trial production verification data, use the k-means algorithm to summarize the product verification results and generate the summary results.

[0079] Specifically, the trial production verification data contains a large amount of information about various parameters in the production process, such as production efficiency, production time, product quality, equipment operation status, etc. After collecting this data, the k-means algorithm is used for data clustering analysis. In actual operation, the k-means algorithm first selects the initial k clustering centers and divides the data points into the corresponding clusters according to the distance from these centers, and then continuously updates the clustering centers until the clustering results converge. The center point of each cluster represents the average performance of the data in that class. In this way, the system can identify the performance patterns in different production stages and classify these patterns into several main "groups". For example, some production batches may perform poorly in quality control, while others may perform better in production speed. Finally, the k-means algorithm will output the center points of each cluster and the corresponding data distribution information, and these data will be used as the summary results of product verification.

[0080] S52: Generate a mass production feasibility report based on the summary results and mark the production bottlenecks.

[0081] Specifically, based on the summary results generated by the k-means algorithm, in-depth analysis is carried out on the production data of different clusters. For example, the bottlenecks in some production stages may occur in areas with too high equipment downtime frequency, or there are quality fluctuations in some links of the production process, resulting in the instability of the production process. During the analysis process, potential production bottlenecks will be marked by comparing the key performance indicators such as time, cost, and quality of each production link. For example, the cycle time of a certain production step is relatively long, which may become a bottleneck in the overall production process and affect the product delivery time.

[0082] S53: Summarize and review the mass production feasibility report. If the review of the mass production feasibility report fails, improvements will be made according to the report.

[0083] Specifically, after the mass production feasibility report is completed, the system will automatically enter the review stage. During the review process, the system will check item by item according to the data analysis, bottleneck identification, solution, etc. in the report. The focus of the review is to confirm whether the problems in the report are comprehensively and accurately identified, and whether the proposed improvement measures are practical. If the system review result believes that some of the analysis or improvement measures in the report are not perfect, for example, a certain bottleneck is not fully explored, or the solution is too rough, the system will automatically give improvement opinions and require the report to be revised. The revised report will be resubmitted for review until it meets the feasible standard.

[0084] S54: If the review of the mass production feasibility report passes, mass production will be carried out to generate the corresponding product.

[0085] Specifically, once the mass production feasibility report is reviewed and approved, it can enter the mass production stage. In this stage, based on the analysis results and improvement suggestions in the mass production feasibility report, the production line will be adjusted and optimized. For example, if the bottleneck problem in a certain link is pointed out in the report and has been solved, the production line will be adjusted accordingly according to the optimization plan, such as adding equipment, optimizing the process flow, adjusting the production rhythm, etc., to ensure that all links in the production process can proceed smoothly. At the same time, during mass production, production data will be continuously monitored to ensure that product quality and production efficiency meet the expected goals. In the mass production stage, the final products will be produced according to the previous verification data and quality standards, and finally large-scale products that meet the design and quality standards will be generated. These products will be subject to final inspection and delivered according to customer requirements.

[0086] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0087] In one embodiment, a product development process management system is provided. This product development process management system corresponds one-to-one with the product development process management method in the above embodiment. As Figure 8 shown, this product development process management system includes a creation review module, a development review module, a verification review module, a design review module, a summary module, and an optimization module. The detailed descriptions of each functional module are as follows: The creation review module is used to obtain requirement information, conduct a review of the project creation stage on the requirement information through a preset intelligent review algorithm, and determine whether to initiate a project based on the project creation review result of the project creation stage, so as to generate a corresponding project for initiation; The development review module is used to, if the project initiation is successful, conduct a product design and development review on the initiated project, and determine whether to apply for a prototype based on the design and development review result of the product design and development review, so as to generate a corresponding sample; The verification review module is used to, if a prototype application is made, conduct a review of the engineering verification test stage on the sample, and determine whether to apply for mold opening based on the verification test review result of the engineering verification test stage, so as to generate corresponding component data; The design review module is used to, if a mold opening application is made, conduct a review of the design verification test stage on the component data, and determine whether to conduct a trial production verification based on the design verification review result of the design verification test stage, so as to generate corresponding trial production verification data; The summary module is used to, if a trial production verification is conducted, conduct a summary of the production verification stage on the trial production verification data, and determine whether to conduct mass production based on the summary result of the production verification stage, so as to generate corresponding products; Optimization module, which is used to automatically optimize the criteria and processes of each review stage based on real-time data feedback and historical data analysis, and automatically adjust the decision results of the review stage.

[0088] Optionally, the review creation module includes: Structural analysis sub-module, which is used to perform structural analysis on the requirement information and generate a preliminary specification; General design sub-module, which is used to perform general design based on the preliminary specification and generate a preliminary design plan; Identification sub-module, which is used to identify the feasibility of the preliminary design plan and market demand, and form a project creation review result; Redesign sub-module, which is used to judge whether the preliminary design plan meets the project approval criteria based on the project creation review result. If the preliminary design plan does not meet the project approval criteria, the preliminary design plan will be returned to the general design for redesign; Project approval sub-module, which is used to approve the project if the preliminary design plan meets the project approval criteria, so as to generate the corresponding approved project.

[0089] Optionally, the identification sub-module includes: Risk assessment unit, which is used to perform risk analysis on the preliminary design plan and generate a risk assessment result; Adjustment unit, which is used to adjust the project approval criteria according to the risk assessment result.

[0090] Optionally, the development review module includes: Matching sub-module, which is used to conduct a review based on the matching degree between the approved project and the requirement information and generate a design and development review result; Design improvement sub-module, which is used to judge whether the approved project meets the design criteria based on the design and development review result. If the approved project does not meet the design criteria, design improvement suggestions will be generated, and the approved project will enter the design improvement stage according to the design improvement suggestions; Prototype-making sub-module, which is used to enter the prototype-making application if the approved project meets the design criteria, so as to generate the corresponding sample.

[0091] Optionally, the verification review module includes: Abnormal marking sub-module, which is used to collect sample test data in real time through Internet of Things devices during the verification test, identify abnormalities in the test, and mark the priority of the abnormal data that appears, and generate a dynamic test report; Report analysis sub-module, which is used to analyze the dynamic test report and generate a verification test review result; Sample improvement sub-module, which is used to judge whether the sample meets the mold opening criteria based on the verification test review result. If the sample does not meet the mold opening criteria, sample improvement suggestions will be generated, and the sample will be returned to the design improvement stage for improvement according to the sample improvement suggestions; The mold opening sub-module is used to enter a mold opening application to generate corresponding component data if the sample meets the mold opening standard; The anomaly adjustment sub-module is used to identify the anomaly type of the anomaly data that appears when judging whether the sample meets the mold opening standard, and adjust the mold opening standard according to the anomaly type.

[0092] Optionally, the design review module includes: The component confirmation sub-module is used to confirm the components for the component data. If the component data does not meet the component standard, it enters the mold improvement stage for improvement; The prototype generation sub-module is used to generate a mold prototype according to the component data if the component data meets the component standard; the proofing test sub-module is used to conduct a proofing test on the mold prototype and monitor the proofing data of the mold prototype in real time; The quality analysis sub-module is used to conduct quality control analysis on the proofing data, generate a quality analysis result, and judge whether the mold prototype meets the proofing production standard based on the quality analysis result. If the mold prototype does not meet the proofing production standard, the component data is returned to the mold improvement stage for secondary improvement; The trial production sub-module is used to enter trial production verification to generate corresponding trial production verification data if the mold prototype meets the proofing production standard.

[0093] Optionally, the summary module includes: The algorithm summary sub-module is used to summarize the product verification result using the k-means algorithm based on the trial production verification data and generate a summary result; The marking sub-module is used to generate a mass production feasibility report according to the summary result and mark the production bottleneck; The feasibility improvement sub-module is used to conduct a summary review on the mass production feasibility report. If the mass production feasibility report fails the review, improvement is made according to the mass production feasibility report; The mass production sub-module is used to conduct mass production to generate corresponding products if the mass production feasibility report passes the review.

[0094] For the specific limitations of a product development process management system, reference can be made to the limitations of a product development process management method in the above text, which will not be elaborated here. Each module in the above product development process management system can be implemented in whole or in part through software, hardware, and their combination. The above modules can be embedded in the processor of a computer device in hardware form or be independent of it, or be stored in the memory of a computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to the above modules.

[0095] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be allocated to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0096] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A product development process management method, characterized in that: The product development process management method comprises: Obtaining demand information, conducting a project creation phase review on the demand information through a preset intelligent review algorithm, and determining whether to initiate a project based on a project creation review result of the project creation phase review, so as to generate a corresponding project establishment project; If the project is successfully established, a product design and development review will be conducted on the project, and according to the design and development review results of the product design and development review, it will be determined whether to apply for proofing to generate corresponding samples; If a proofing application is made, the sample is reviewed at the engineering verification test stage, and based on the verification test review results of the engineering verification test stage review, it is determined whether to apply for mold opening to generate corresponding component data; If a mold opening application is made, the component data is reviewed at the design verification test stage, and whether to conduct a trial production verification is determined based on the design verification review results of the design verification test stage review to generate corresponding trial production verification data; If trial production verification is carried out, a production verification phase summary is carried out on the trial production verification data, and according to the summary result of the production verification phase summary, it is determined whether to carry out mass production to generate the corresponding product; Based on real-time data feedback and historical data analysis, the standards and processes of each review stage are automatically optimized, and the decision results of the review stage are automatically adjusted.

2. A product development process management method according to claim 1, characterized in that: The step of obtaining demand information, conducting a project creation phase review on the demand information through a preset intelligent review algorithm, and determining whether to initiate a project based on a project creation review result of the project creation phase review to generate a corresponding project establishment project includes: Conduct structured analysis on the demand information and generate preliminary specifications; Conduct a rough design based on the preliminary specifications and generate a preliminary design plan; Identify the feasibility and market demand of the preliminary design scheme and form the project creation review results; Based on the project creation review result, determine whether the preliminary design plan meets the project establishment criteria. If the preliminary design plan does not meet the project establishment criteria, return the preliminary design plan to the outline design for redesign; If the preliminary design plan meets the project establishment standards, the project will be established to generate the corresponding project establishment item.

3. A product development process management method according to claim 2, characterized in that: Before judging whether the preliminary design scheme meets the project establishment criteria based on the project creation review result, the product development process management method further includes: Conduct risk analysis on the preliminary design scheme and generate risk assessment results; Adjust the project establishment standards based on the risk assessment results.

4. A product development process management method according to claim 1, characterized in that: The product design and development review of the project is conducted, and according to the design and development review result of the product design and development review, whether to apply for proofing to generate corresponding samples includes: Conducting an evaluation based on the matching degree between the project and the demand information, and generating the design and development evaluation result; Based on the design development review results, determine whether the project meets the design standards. If the project does not meet the design standards, generate design improvement suggestions, and enter the design improvement stage according to the design improvement suggestions. If the project meets the design standards, a proofing application will be submitted to generate the corresponding sample.

5. A product development process management method according to claim 4, characterized in that: If a proofing application is made, the sample is reviewed in the engineering verification test phase, and according to the verification test review results of the engineering verification test phase review, it is determined whether to apply for mold opening to generate corresponding component data including: During the verification test, the sample test data is collected in real time through the IoT device, anomalies in the test are identified, and the abnormal data that appears is marked with priority to generate a dynamic test report; Analyzing the dynamic test report to generate the verification test review result; Based on the verification test review results, determine whether the sample meets the mold opening standard. If the sample does not meet the mold opening standard, generate sample improvement suggestions, and return to the design improvement stage for improvement according to the sample improvement suggestions; If the sample meets the mold opening standard, the mold opening application is entered to generate the corresponding component data; When judging whether the sample meets the mold opening standard, the abnormal type of the abnormal data is identified, and the mold opening standard is adjusted according to the abnormal type.

6. A product development process management method according to claim 1, characterized in that: The step of conducting a design verification test phase review on the component data, and determining whether to conduct a trial production verification based on the design verification review result of the design verification test phase review to generate corresponding trial production verification data includes: The component data is determined as a component. If the component data does not meet the component standard, the mold improvement stage is entered for improvement; If the component data meets the component standard, a mold prototype is generated according to the component data; Performing a proofing test on the mold prototype and monitoring the proofing data of the mold prototype in real time; Performing quality control analysis on the proofing data to generate quality analysis results, and judging whether the mold prototype meets the proofing production standard based on the quality analysis results. If the mold prototype does not meet the proofing production standard, returning the component data to the mold improvement stage for secondary improvement; If the mold prototype meets the proofing production standard, it enters the trial production verification to generate the corresponding trial production verification data.

7. A product development process management method according to claim 1, characterized in that: If trial production verification is performed, the trial production verification data is summarized in the production verification stage, and according to the summary result of the production verification stage summary, it is determined whether to perform mass production to generate the corresponding product, including: Based on the trial production verification data, the product verification results are summarized using a k-means algorithm to generate a summary result; Generate a mass production feasibility report based on the summary results and mark the production bottlenecks; Summarize and review the mass production feasibility report. If the mass production feasibility report fails the review, make improvements based on the mass production feasibility report; If the mass production feasibility report is reviewed and approved, mass production will be carried out to generate the corresponding product.

8. A product development process management system, characterized in that: The product development process management system comprises: A creation review module is used to obtain demand information, conduct a project creation phase review on the demand information through a preset intelligent review algorithm, and determine whether to initiate a project based on the project creation review result of the project creation phase review to generate a corresponding project establishment project; The development review module is used to conduct a product design and development review on the project if the project is successfully established, and determine whether to apply for proofing based on the design and development review results of the product design and development review to generate corresponding samples; The verification and review module is used to conduct an engineering verification test phase review on the sample if a proofing application is made, and determine whether to apply for mold opening according to the verification test review result of the engineering verification test phase review, so as to generate corresponding component data; A design review module is used to review the component data at the design verification test stage if a mold opening application is made, and determine whether to conduct a trial production verification based on the design verification review result of the design verification test stage review to generate corresponding trial production verification data; A summary module is used to summarize the trial production verification data in the production verification stage if trial production verification is performed, and determine whether to perform mass production according to the summary result of the production verification stage summary to generate the corresponding product; The optimization module is used to automatically optimize the standards and processes of each review stage based on real-time data feedback and historical data analysis, and automatically adjust the decision results of the review stage.

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