Project management method and system based on industrial digitization
Through a project management method based on industrial digitalization, utilizing production data collection, prediction models and blockchain collaborative management, the problems of inefficiency and decision-making bias in traditional project management methods have been solved, achieving the effects of shortening production time, improving efficiency and reducing costs.
Patent Information
- Application Number
- CN202510794036.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-13
- Publication Date
- 2025-09-16
AI Technical Summary
Traditional project management methods rely on managers' personal experience and lack data support, resulting in decision-making bias, inefficiency, high labor costs, low collaboration efficiency, chaotic version control, and serious information asymmetry, which affects project execution efficiency and quality.
Adopting a project management method based on industrial digitalization, through the collection of production data of the target industry, building a project database, adding priority coefficients and pre-coefficients, building an industrial chain production forecast model, simulation forecasting, optimizing project management methods, and promoting projects through blockchain collaborative management.
Under the premise of ensuring quality and quantity, shorten production time, improve production efficiency, timely adjust project management methods, reduce production costs, avoid information silos, reduce industrial production risks, and rationally utilize resources.
Smart Images
Figure CN120655034A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of industrial digitalization technology, and more specifically, to a project management method and system based on industrial digitalization. Background Art
[0002] Industrial digitalization refers to the deep integration of advanced digital technologies into every link and all key elements of the industry. This process involves not only technological innovation, but also a comprehensive transformation of business processes, management models, and corporate culture. It requires companies to carry out systematic planning and execution to ensure that digital transformation can proceed smoothly and achieve the expected results.
[0003] In contrast, traditional project management approaches often rely on managers' personal experience and intuition to make decisions. This approach is highly subjective and lacks necessary data support, which can easily lead to biased decisions. Traditional methods rely heavily on manual processes for data collection, report creation, and project progress tracking, which is not only inefficient, but also costly and prone to errors. Furthermore, due to a lack of effective collaboration tools, collaboration between team members is often inefficient, version control is chaotic, and information asymmetry is severe, all of which significantly impact the overall efficiency and quality of project execution. Summary of the Invention
[0004] In response to the problems existing in the prior art, the purpose of the present invention is to provide a project management method and system based on industrial digitalization, aiming to solve the above-mentioned background technical problems.
[0005] To achieve the above objectives, the present invention adopts the following technical solutions: The project management method based on industrial digitalization includes the following management steps: S1. Collect production data of the target industry, where the production data refers to the production data of each node in the target industry chain; S2. Build a target industry project database to store the collected production data and the production data of existing target industries; S3. Add priority coefficients and pre-coefficients to the production data of each node in the industrial chain, build an industrial chain production prediction model based on the industrial knowledge graph, and use the industrial chain production prediction model to simulate and predict the collected production data; S4. Optimize the production management methods of each node project in the target industry based on the simulation results, priority coefficients, and pre-coefficients of the industrial chain production forecast model, and compare the optimization results; S5. Generate project management plans for each node of the target industry based on the optimization results and implement them according to the management plans.
[0006] As a further description of the above technical solution: The collected production data is preprocessed before being stored in the industrial project database, and the preprocessing includes data encryption and data desensitization.
[0007] As a further description of the above technical solution: The target industry project database is a time series database. The collected production data imported into the industrial chain production forecast model adjusts the production time series of each node in the industrial chain production forecast model according to the added priority coefficient and pre-coefficient, and adjusts the project overlap and the order of the projects.
[0008] As a further description of the above technical solution: The basis for adjusting the production sequence of each node in the industrial chain production forecast model is to shorten the production time of the target industry chain and reduce the production cost input.
[0009] As a further description of the above technical solution: The simulation prediction process of S3 is as follows: The production data of the existing target industry is used as raw data, and the raw data is input into the industrial chain production forecast model; The industrial chain production forecast model is trained based on the original data to obtain an optimized industrial chain production forecast model; The collected production data is input into the optimized industrial chain production forecasting model for forecasting analysis to obtain the forecast results.
[0010] As a further description of the above technical solution: The management plan in S5 is implemented by dividing the target industry chain into multiple blockchains, and according to the node project management plan, multiple blockchains are collaboratively managed to promote the project.
[0011] As a further description of the above technical solution: The blockchain collaborative management is carried out through conference communication and joint review.
[0012] As a further description of the above technical solution: The target industry project database stores the raw material reserve data of each node of the target industry chain in real time. The optimization method of step S4 also includes predicting production capacity using a spatiotemporal fusion prediction model based on the raw material reserve data, and adjusting the production time axis of each node of the target industry chain based on the predicted production capacity; the architecture of the spatiotemporal fusion prediction model is: Input layer, time series data, spatial topology data of industrial chain nodes, and spatiotemporal embedding layer; Fusion encoder, spatial and temporal cross attention; Prediction decoder, spatiotemporal decoder, dynamic weighted fusion; Probability output.
[0013] The present invention also adopts: Project management system based on industrial digitalization, including: The industrial chain node production data collection module is used to collect production data of each node in the target industry chain; Target industry project database, used to store collected production data and production data of existing target industries; The production forecast model construction module is used to build the industrial chain production forecast model and input the original data to train and optimize the industrial chain production forecast model; The node project production management optimization module is used to optimize the production management mode of each node project in the target industry based on the simulation results, priority coefficients and pre-coefficients of the industrial chain production forecast model, and compare the optimization results; The node project management module is used to generate project management plans for each node of the target industry based on the optimization results and implement them according to the management plans; The spatiotemporal fusion prediction model is used to predict production capacity based on raw material reserve data using the spatiotemporal fusion prediction model, and to adjust the production timeline of each node in the target industry chain according to the predicted production capacity.
[0014] Compared with the prior art, the advantages of the present invention are: (1) This plan, under the premise of ensuring production quality and quantity, allows the production of the industrial chain to overlap and synchronize, thereby greatly reducing the production time of the target industry and improving production efficiency.
[0015] (2) This solution constructs an industrial chain production forecasting model to predict subsequent production costs, duration, etc., which facilitates direct access to the management results of the current project management method, and is conducive to adjustment and optimization. Compared with the traditional adjustment method after implementation, this solution can adjust the project management method in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 Schematic diagram of the project management process of the present invention; Figure 2 Schematic diagram of the prediction process of the industrial chain production prediction model of the present invention; Figure 3 Schematic diagram of the project management principle of the present invention. DETAILED DESCRIPTION
[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention; See also Figure 1-3 , the present invention provides embodiment 1: The project management method based on industrial digitalization includes the following management steps: S1. Collect production data of the target industry. Production data refers to the production data of each node in the target industry's industrial chain. Collecting data from the target industry's industrial chain can build the Internet of Things and facilitate industrial digitalization based on the Internet of Things. The collected production data is preprocessed before being stored in the industrial project database. The preprocessing includes data encryption and data desensitization.
[0018] S2. Build a target industry project database to store the collected production data and the production data of existing target industries.
[0019] S3. Add priority coefficients and pre-coefficients to the production data of each node in the industrial chain, build an industrial chain production prediction model based on the industrial knowledge graph, and use the industrial chain production prediction model to simulate and predict the collected production data; The target industry project database is a time series database. The collected production data imported into the industrial chain production forecast model is used to adjust the production time series of each node in the industrial chain production forecast model according to the added priority coefficient and pre-coefficient, and adjust the project overlap and order. The basis for adjusting the production sequence of each node in the industrial chain production forecast model is to shorten the production time of the target industry chain and reduce the production cost input; The order and priority of production at each node in the industrial chain are determined based on the added priority coefficient and pre-coefficient. Under the premise of ensuring quality and quantity, the production of the industrial chain can be overlapped and synchronized, thereby greatly reducing the production time of the target industry and improving production efficiency.
[0020] The simulation prediction process of S3 is as follows: The production data of the existing target industry is used as raw data, and the raw data is input into the industrial chain production forecast model; The industrial chain production forecast model is trained based on the original data to obtain an optimized industrial chain production forecast model; The collected production data is input into the optimized industrial chain production forecasting model for forecasting analysis to obtain the forecast results.
[0021] An industrial chain production forecasting model is constructed to predict subsequent production costs, duration, etc., which facilitates direct access to the management results of the current project management method, and is conducive to adjustment and optimization. Compared with the traditional adjustment method after implementation, the project management method can be adjusted in a timely manner.
[0022] S4. Optimize the production management mode of each node project of the target industry according to the simulation results, priority coefficient and pre-coefficient of the industrial chain production forecast model, and compare the optimization results.
[0023] S5. Generate project management plans for each node of the target industry based on the optimization results and implement them according to the management plans.
[0024] Among them, the management plan is implemented by dividing the target industry chain into multiple blockchains, and according to the node project management plan, multiple blockchains are collaboratively managed to promote the project; blockchain collaborative management is carried out through meeting communication and joint review.
[0025] Blockchain collaborative management facilitates cross-organizational collaboration, avoids the problem of information islands, greatly reduces industrial production risks, facilitates resource allocation, and rationally utilizes resources.
[0026] The target industry project database stores the raw material reserve data of each node of the target industry chain in real time. The optimization method of step S4 also includes predicting production capacity using a spatiotemporal fusion prediction model based on the raw material reserve data, and adjusting the production time axis of each node of the target industry chain based on the predicted production capacity; the architecture of the spatiotemporal fusion prediction model is: Input layer, time series data, spatial topology data of industrial chain nodes, and spatiotemporal embedding layer; Fusion encoder, spatial and temporal cross attention; Prediction decoder, spatiotemporal decoder, dynamic weighted fusion; Probability output.
[0027] The spatiotemporal fusion prediction model predicts the resource requirements of each node based on the production data and raw material reserve data stored in the target industry project database, and adds priority coefficients and pre-coefficients to each node. Based on the predicted data, the production rate and process of each node are regulated to ensure smooth transitions between nodes of the target project and improve the efficiency of project management.
[0028] See also Figure 1-3 , the present invention further provides Example 2 based on Example 1: Project management system based on industrial digitalization, including: The industrial chain node production data collection module is used to collect production data of each node in the target industry chain; Target industry project database, used to store collected production data and production data of existing target industries; The production forecast model construction module is used to build the industrial chain production forecast model and input the original data to train and optimize the industrial chain production forecast model; The node project production management optimization module is used to optimize the production management mode of each node project in the target industry based on the simulation results, priority coefficients and pre-coefficients of the industrial chain production forecast model, and compare the optimization results; The node project management module is used to generate project management plans for each node of the target industry based on the optimization results and implement them according to the management plans.
[0029] The above description is merely a preferred embodiment of the present invention; however, the scope of protection of the present invention is not limited thereto. Any person skilled in the art who, within the technical scope disclosed by the present invention, makes equivalent substitutions or modifications based on the technical solutions and improved concepts of the present invention shall be covered by the scope of protection of the present invention.
Claims
1. The project management method based on industrial digitalization is characterized by: The management steps include: S1. Collect production data of the target industry, where the production data refers to the production data of each node in the target industry chain; S2. Build a target industry project database to store the collected production data and the production data of existing target industries; S3. Add priority coefficients and pre-coefficients to the production data of each node in the industrial chain, build an industrial chain production prediction model based on the industrial knowledge graph, and use the industrial chain production prediction model to simulate and predict the collected production data; S4. Optimize the production management methods of each node project in the target industry based on the simulation results, priority coefficients, and pre-coefficients of the industrial chain production forecast model, and compare the optimization results; S5. Generate project management plans for each node of the target industry based on the optimization results and implement them according to the management plans.
2. The project management method based on industrial digitalization according to claim 1 is characterized by: The collected production data is preprocessed before being stored in the industrial project database, and the preprocessing includes data encryption and data desensitization.
3. The project management method based on industrial digitalization according to claim 1 is characterized by: The target industry project database is a time series database. The collected production data imported into the industrial chain production forecast model adjusts the production time series of each node in the industrial chain production forecast model according to the added priority coefficient and pre-coefficient, and adjusts the project overlap and the order of the projects.
4. The project management method based on industrial digitalization according to claim 1 is characterized by: The basis for adjusting the production sequence of each node in the industrial chain production forecast model is to shorten the production time of the target industry chain and reduce the production cost input.
5. The project management method based on industrial digitalization according to claim 1 is characterized by: The simulation prediction process of S3 is as follows: The production data of the existing target industry is used as raw data, and the raw data is input into the industrial chain production forecast model; The industrial chain production forecast model is trained based on the original data to obtain an optimized industrial chain production forecast model; The collected production data is input into the optimized industrial chain production forecasting model for forecasting analysis to obtain the forecast results.
6. The project management method based on industrial digitalization according to claim 1 is characterized by: The management plan in S5 is implemented by dividing the target industry chain into multiple blockchains, and according to the node project management plan, multiple blockchains are collaboratively managed to promote the project.
7. The project management method based on industrial digitalization according to claim 6 is characterized by: The blockchain collaborative management is carried out through conference communication and joint review.
8. The project management method based on industrial digitalization according to claim 1 is characterized by: The target industry project database stores the raw material reserve data of each node of the target industry chain in real time. The optimization method of step S4 also includes predicting production capacity using a spatiotemporal fusion prediction model based on the raw material reserve data, and adjusting the production time axis of each node of the target industry chain based on the predicted production capacity; the architecture of the spatiotemporal fusion prediction model is: Input layer, time series data, spatial topology data of industrial chain nodes, and spatiotemporal embedding layer; Fusion encoder, spatial and temporal cross attention; Prediction decoder, spatiotemporal decoder, dynamic weighted fusion; Probability output.
9. The project management system based on industrial digitalization is characterized by: include: The industrial chain node production data collection module is used to collect production data of each node in the target industry chain; Target industry project database, used to store collected production data and production data of existing target industries; The production forecast model construction module is used to build the industrial chain production forecast model and input the original data to train and optimize the industrial chain production forecast model; The node project production management optimization module is used to optimize the production management mode of each node project in the target industry based on the simulation results, priority coefficients and pre-coefficients of the industrial chain production forecast model, and compare the optimization results; The node project management module is used to generate project management plans for each node of the target industry based on the optimization results and implement them according to the management plans; The spatiotemporal fusion prediction model is used to predict production capacity based on raw material reserve data using the spatiotemporal fusion prediction model, and to adjust the production timeline of each node in the target industry chain according to the predicted production capacity.