Method, system and device for technology path planning based on marginal investment maturity

Abstract

This application relates to the field of production planning technology, and provides a technology path planning method, system, and equipment based on marginal investment maturity. This application obtains information on intelligent manufacturing technologies in steel enterprises and their interdependencies, decomposes the total cost of intelligent manufacturing technologies in steel enterprises into independent intelligent manufacturing technology costs and infrastructure transformation costs, constructs a path planning model with the optimization objective of maximizing the overall increase in marginal investment maturity, and using technology dependencies and the total cost of intelligent manufacturing technologies as constraints, with the choice of technology itself as an independent variable. Sensitivity analysis is conducted in conjunction with changes in infrastructure transformation costs in steel enterprises to simulate the changes in technology planning paths for different steel enterprises under different infrastructure transformation cost conditions. This allows production enterprises to refer to and select different paths during the technology planning process according to their own characteristics to meet their current urgent needs and improve the implementation effect of the path planning scheme.

Description

Technical Field

[0001] This application relates to the field of production planning technology, specifically to a technology path planning method, system, and equipment based on marginal investment maturity. Background Technology

[0002] Currently, steel companies are gradually adopting mathematical models to replace traditional expert experience when planning intelligent manufacturing technologies. This aims to solve problems such as subjectivity, bias, and inefficiency caused by over-reliance on human judgment. By using mathematical models for technology path planning, steel companies can improve the comprehensiveness and scientific nature of their technology planning and development processes.

[0003] However, due to differences in the construction period, the age of equipment, and the current state of infrastructure, there are significant differences in the actual infrastructure transformation costs of various enterprises when implementing the same intelligent manufacturing technology for steel enterprises—especially in terms of on-site transformation and system integration. If only a fixed planning strategy is adopted, with the total infrastructure transformation cost as the only constraint variable, and the differences in infrastructure transformation costs between different enterprises are not taken into account as key variables, the planning results cannot dynamically reflect the real situation of the enterprises. As a result, the generated technology path planning scheme lacks applicability and cannot meet the urgent needs of enterprises, leading to poor implementation effect of the path planning scheme. Summary of the Invention

[0004] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0005] In view of the shortcomings of the prior art described above, this application provides a technology path planning method, system and equipment based on marginal investment maturity to improve the implementation effect of technology planning path.

[0006] This application provides a technology path planning method, system, and electronic device based on marginal investment maturity, comprising: acquiring a technology knowledge base, wherein the technology knowledge base includes multiple intelligent manufacturing technologies of steel enterprises and the technology dependencies between the intelligent manufacturing technologies of each steel enterprise; constructing a path planning model using the technology dependencies and total technology cost as constraints, and taking the maximization of the overall increase in marginal investment maturity as the optimization objective, wherein the total technology cost includes the independent technology cost corresponding to the intelligent manufacturing technology of each steel enterprise, and the infrastructure transformation cost for infrastructure transformation of the intelligent manufacturing technology of each steel enterprise, and the maturity increase is obtained by evaluating and calculating the technology planning path composed of intelligent manufacturing technologies of steel enterprises; performing sensitivity analysis on the infrastructure transformation cost according to preset different infrastructure transformation investment coefficients, and adjusting the infrastructure transformation cost according to the sensitivity analysis results; solving the path planning model according to the adjusted infrastructure transformation cost to obtain the technology planning path corresponding to each infrastructure transformation investment coefficient, and generating a path planning scheme according to each technology planning path.

[0007] In one embodiment of this application, the intelligent manufacturing technology for steel enterprises includes original basic technologies and original process technologies. The total technology cost corresponding to the original basic technologies is determined as follows: from the original basic technologies, the target basic technologies selected by the technology planning path are determined, and the independent technology cost is calculated based on the preset input cost corresponding to the target basic technologies; from the original process technologies associated with the target basic technologies, the target process technologies selected by the technology planning path are determined, and the infrastructure transformation cost is calculated based on the number of target process technologies; the total technology cost corresponding to the original basic technologies is calculated based on the independent technology costs and the infrastructure transformation costs.

[0008] In one embodiment of this application, the maturity increase corresponding to any technology planning path is obtained in the following manner: multiple capability dimensions are obtained, and capability assessment model calculation formulas are set for each capability dimension; the technology planning path based on intelligent manufacturing of steel enterprises is evaluated and calculated according to each capability assessment model calculation formula to obtain the evaluation calculation results of the technology planning path for each capability dimension; based on each evaluation result, the maturity score corresponding to the technology planning path is calculated, and the maturity change between different technology combinations is calculated, which is the maturity increase of different solutions.

[0009] In one embodiment of this application, the capability dimension includes at least one of the following: a planning and scheduling dimension, used to characterize the optimization capability of production scheduling; a production operation dimension, used to characterize task execution efficiency and / or production quality; an equipment management dimension, used to characterize equipment operating efficiency and / or equipment health status; a warehousing and distribution dimension, used to characterize logistics costs and / or logistics efficiency; and an energy management dimension, used to characterize the energy cost of the intelligent manufacturing technology of the steel enterprise.

[0010] In one embodiment of this application, the method further includes: setting dimension scoring thresholds corresponding to each of the capability dimensions; determining the target technology selected for the technology planning path from the intelligent manufacturing technology of the steel enterprise, and calculating the dimension score of the technology planning path corresponding to each of the capability dimensions based on the evaluation results of the target technology in each of the capability dimensions; and adding the target technology that meets the constraint conditions to the path planning model, with each dimension score being greater than or equal to the corresponding dimension scoring threshold as a constraint condition.

[0011] In one embodiment of this application, a path planning model is constructed using the aforementioned technological dependencies and total technology cost as constraints, and maximizing the overall increase in marginal investment maturity as the optimization objective. The model includes: constructing model independent variables, wherein the independent variables include technology selection states, which characterize whether the technology planning path includes the intelligent manufacturing technology of the steel enterprise; calculating the overall increase in marginal investment maturity per unit of marginal investment for each of the intelligent manufacturing technologies of the steel enterprise based on the ratio between the maturity score corresponding to the technology planning path and the total cost; and using the overall increase in maturity per unit of marginal investment corresponding to the technology planning path as the objective function, wherein the objective function is used to maximize the marginal investment maturity of the technology planning path. The overall increase in marginal investment maturity is calculated based on the overall increase in marginal investment maturity per unit of marginal investment. Constraints are constructed, including cost constraints, technology dependency constraints, and technology dimension category constraints. The cost constraint includes a total technology cost corresponding to the technology planning path being less than a preset technology cost threshold. The technology dependency constraint includes the intelligent manufacturing technology of steel enterprises in the technology planning path satisfying technology dependency relationships. The technology dimension category constraint includes each dimension score being greater than or equal to its corresponding dimension score threshold. A mathematical model is constructed based on the model independent variables, the objective function, and the constraints to obtain the path planning model.

[0012] In one embodiment of this application, the path planning model is solved in the following way: Based on the actual situation and needs of steel enterprises, the calculation parameters for basic transformation costs differ among different steel enterprises, requiring sensitivity analysis to find the basic cost calculation parameters that best match the actual situation. During the sensitivity analysis, the infrastructure transformation investment coefficient is continuously changed, and the technology path planning model is called to analyze the impact of different values ​​of the infrastructure transformation investment coefficient on the technology planning path. The optimization objective is to maximize the overall increase in marginal investment maturity, thus obtaining the path planning scheme that best meets the business needs of steel enterprises. The path planning scheme and sensitivity analysis results are statistically analyzed and presented to users in a visual form.

[0013] In one embodiment of this application, the path planning model is solved in the following way: using a preset programming library, the path planning model is converted into a standardized model of mixed integer linear programming; a preset computing engine is called to solve the standardized model to obtain the technical planning path.

[0014] This application also provides a technology path planning system based on marginal investment maturity, comprising: an acquisition module for acquiring a technology knowledge base, wherein the technology knowledge base includes multiple intelligent manufacturing technologies of steel enterprises and the technology dependencies between the intelligent manufacturing technologies of each steel enterprise; a construction module for constructing a path planning model using the technology dependencies and total technology cost as constraints and maximizing the overall increase in marginal investment maturity as the optimization objective, wherein the total technology cost includes the independent technology cost corresponding to the intelligent manufacturing technology of the steel enterprise and the infrastructure transformation cost for infrastructure transformation of the intelligent manufacturing technology of the steel enterprise, and the overall increase in marginal investment maturity is obtained by evaluating and calculating the technology planning path composed of intelligent manufacturing technologies of steel enterprises; an adjustment module for performing sensitivity analysis on the infrastructure transformation cost according to preset different infrastructure transformation investment coefficients, and adjusting the infrastructure transformation cost according to the sensitivity analysis results; and a generation module for solving the path planning model according to the adjusted infrastructure transformation cost to obtain the technology planning path corresponding to each infrastructure transformation investment coefficient, and generating a path planning scheme according to each technology planning path.

[0015] This application also provides an electronic device, including: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the method described above.

[0016] The beneficial effects of this application are:

[0017] By acquiring information on intelligent manufacturing technologies and their interdependencies within steel enterprises, the total technology cost is decomposed into independent intelligent manufacturing technology costs and infrastructure upgrade costs associated with these dependencies. A path planning model is constructed, with the overall increase in marginal investment maturity as the optimization objective and technological dependencies and total technology cost as constraints. A variable infrastructure upgrade investment coefficient is introduced to dynamically adjust the infrastructure upgrade cost. Solving the model separately generates a set of technology planning paths corresponding to different infrastructure upgrade investment coefficients, forming path planning schemes. In this way, the infrastructure upgrade cost corresponding to technological dependencies is treated as an independent adjustable variable in the model, and adjusted using the infrastructure upgrade investment coefficient. This simulates application scenarios for production enterprises under different cost structures or investment preferences, allowing them to refer to and select different technology planning paths to meet their current urgent needs and improve the implementation effectiveness of the path planning schemes. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0019] In the attached diagram: Figure 1 This is a flowchart illustrating a technology path planning method based on marginal investment maturity in an embodiment of this application. Figure 2 This is a schematic diagram of a technology dependency relationship in an embodiment of this application; Figure 3 This is a schematic diagram of a technical planning path in an embodiment of this application; Figure 4 This is a schematic diagram of the total maturity level corresponding to one technology planning path in this application embodiment; Figure 5 This is a flowchart illustrating another technology path planning method based on marginal investment maturity in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of a technology path planning system based on marginal investment maturity in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of an electronic device in an embodiment of this application. Detailed Implementation

[0020] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0021] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0022] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the present application. However, it will be apparent to those skilled in the art that embodiments of the present application may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the present application.

[0023] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0024] Unless otherwise stated, the term "multiple" means two or more.

[0025] In this application, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0026] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0027] Combination Figure 1 As shown, this application provides a technology path planning method based on marginal investment maturity, including: Step S101: Obtain the technical knowledge base; The technical knowledge base includes intelligent manufacturing technologies of multiple steel enterprises and the technical dependencies between these intelligent manufacturing technologies. Step S102: Using the aforementioned technology dependency relationship and total technology cost as constraints, and taking the maximization of the overall increase in marginal investment maturity as the optimization objective, a path planning model is constructed. The total technology cost includes the independent technology cost corresponding to the intelligent manufacturing technology of the steel enterprise, as well as the infrastructure transformation cost of the intelligent manufacturing technology of the steel enterprise. The maturity increase was calculated by evaluating the technology planning path based on the intelligent manufacturing technology of steel enterprises. Step S103: Perform a sensitivity analysis on the infrastructure renovation cost based on preset different infrastructure renovation investment coefficients, and adjust the infrastructure renovation cost according to the sensitivity analysis results; Step S104: Solve the path planning model according to the adjusted infrastructure renovation cost to obtain the technical planning path corresponding to each infrastructure renovation investment coefficient, so as to generate a path planning scheme based on each technical planning path.

[0028] This application employs a technology path planning method based on marginal investment maturity. By acquiring the intelligent manufacturing technologies of steel enterprises and their interdependencies, the total technology cost is decomposed into independent intelligent manufacturing technology costs and infrastructure transformation costs associated with these dependencies. A path planning model is constructed with the overall increase in marginal investment maturity as the optimization objective and technology dependencies and total technology cost as constraints. A variable infrastructure transformation investment coefficient is introduced to dynamically adjust the infrastructure transformation cost. The model is solved separately to generate a set of technology planning paths corresponding to different infrastructure transformation investment coefficients, forming a path planning scheme. In this way, the infrastructure transformation cost corresponding to the technology dependency is used as an independent adjustable variable in the model, and the infrastructure transformation cost is adjusted using the infrastructure transformation investment coefficient. This simulates application scenarios for production enterprises under different cost structures or investment preferences, enabling production enterprises to refer to and select different technology planning paths to meet their current urgent needs and improve the implementation effect of the path planning scheme.

[0029] Optionally, intelligent manufacturing technologies for steel enterprises include original basic technologies and original process technologies.

[0030] In some embodiments, intelligent manufacturing technologies for steel enterprises are divided into three categories: the first category is digital infrastructure, which mainly includes original basic technologies such as plant-wide networks and industrial internet platforms; the second category is process equipment, which includes the application of key intelligent equipment to optimize labor allocation, improve quality and safety, and increase operational efficiency; and the third category is process production, which includes the application of software functions that combine process models and data analysis to improve production efficiency and reduce production costs.

[0031] In some embodiments, a portion of the original underlying technology is shown in Table 1.

[0032] Table 1

[0033] In some embodiments, a portion of the process equipment class is shown in Table 2.

[0034] Table 2

[0035] In some embodiments, a portion of the process production class is shown in Table 3.

[0036] Table 3

[0037] Combination Figure 2 As shown, this application provides a schematic diagram of technological dependencies, in which digital infrastructure is classified as A, process equipment as B, and process production as C.

[0038] Optionally, using the aforementioned technological dependencies and total technology cost as constraints, and maximizing the overall increase in marginal investment maturity as the optimization objective, a path planning model is constructed, including: constructing model independent variables, wherein the model independent variables include the technology selection state, which characterizes whether the technology planning path includes the intelligent manufacturing technology of the steel enterprise; calculating the overall increase in marginal investment maturity per unit marginal investment for each of the intelligent manufacturing technologies of the steel enterprise based on the ratio between the maturity score corresponding to the technology planning path and the total cost; and using the overall increase in maturity per unit marginal investment corresponding to the technology planning path as the objective function, wherein the objective function is used to maximize the impact of each step in the technology planning path on the steel enterprise's intelligent manufacturing technology. The overall increase in maturity under total marginal investment is calculated based on the increase in maturity under unit marginal investment. Constraints are constructed, including cost constraints, technology dependency constraints, and technology dimension category constraints. The cost constraint includes that the total technology cost corresponding to the technology planning path is less than a preset technology cost threshold. The technology dependency constraint includes that the intelligent manufacturing technology of steel enterprises in the technology planning path meets the technology dependency relationship. The technology dimension category constraint includes that the score of each dimension is greater than or equal to the corresponding dimension score threshold. A mathematical model is constructed based on the model independent variables, the objective function, and the constraints to obtain the path planning model.

[0039] In some embodiments, a path planning model is constructed using the technological dependency relationship and technological cost as constraints and maturity score as the optimization objective. This includes: constructing model independent variables, wherein the model independent variables include a technology selection state, a technology association state, and a technology cost function. The technology selection state characterizes whether the technology planning path includes the intelligent manufacturing technology of the steel enterprise; the technology association state characterizes the technological dependency relationship; and the technology cost function characterizes the technological cost of the intelligent manufacturing technology of the steel enterprise. Based on the ratio between the maturity score and the technological cost, the maturity increase corresponding to each production technology is calculated, and an objective function is generated based on the maturity increase corresponding to the technology planning path. The objective function maximizes the maturity increase corresponding to the technology planning path. Constraints are constructed, including cost constraints, dependency constraints, and technological constraints. The cost constraints include that the technological cost corresponding to the technology planning path is less than a preset technological cost threshold; the dependency constraints include that the production technologies in the technology planning path satisfy technological dependency relationships; and the technological constraints include that the scores of each dimension are greater than or equal to the corresponding dimension score thresholds. A mathematical model is constructed based on the model independent variables, the objective function, and the constraints to obtain the path planning model.

[0040] In some embodiments, an objective function is constructed with the goal of maximizing the overall increase in maturity under the total marginal investment corresponding to the technology planning path.

[0041] In some embodiments, the technology selection state is represented as In the formula, For the first The status of intelligent manufacturing technology choices for individual steel enterprises. The technology planning path includes the first Intelligent manufacturing technologies for individual steel enterprises This indicates that the technology planning path does not include the first... Intelligent manufacturing technologies for individual steel enterprises It is a collection of intelligent manufacturing technologies for steel enterprises.

[0042] In some embodiments, if all intelligent manufacturing technologies in steel enterprises are associated with the original underlying technologies of digital technology infrastructure, the technology association status is represented as follows: In the formula, This is a collection of intelligent manufacturing technologies for steel enterprises in the category of digital technology facilities.

[0043] Optionally, the intelligent manufacturing technology for steel enterprises includes original basic technologies and original process technologies. The total technology cost corresponding to the original basic technologies is determined as follows: from the original basic technologies, the target basic technologies selected in the technology planning path are determined, and the independent technology cost is calculated based on the preset input cost corresponding to the target basic technologies; from the original process technologies associated with the target basic technologies, the target process technologies selected in the technology planning path are determined, and the infrastructure transformation cost is calculated based on the number of target process technologies to obtain the infrastructure transformation cost; the total technology cost corresponding to the original basic technologies is calculated based on the independent technology costs and the infrastructure transformation costs.

[0044] In some embodiments, the maturity score corresponding to any production technology is obtained by: acquiring multiple capability dimensions and setting capability assessment models corresponding to each capability dimension; evaluating the production technology according to each capability assessment model to obtain the evaluation results of the production technology for each capability dimension; and calculating the maturity score corresponding to the production technology based on each evaluation result.

[0045] In some embodiments, the difference in maturity scores between different technology combinations is calculated, and this difference is used as the maturity increment.

[0046] In some embodiments, since the original foundational technologies provide computing power, data storage, and data transmission support for the original process technologies, the more original process technologies included in the technology planning path, the higher the demand for the original foundational technologies in terms of underlying networks, computing power, and data resources, resulting in infrastructure transformation costs.

[0047] In some embodiments, the total technology cost corresponding to the original foundational technology is expressed as:

[0048] In the formula,

[0049] Optionally, the overall increase in marginal investment maturity corresponding to any technology planning path can be obtained by: acquiring multiple capability dimensions and setting calculation formulas for capability assessment models corresponding to each capability dimension; evaluating and calculating the technology planning path based on intelligent manufacturing of steel enterprises according to the calculation formulas for each capability assessment model, and obtaining the evaluation calculation results of the technology planning path corresponding to each capability dimension; calculating the maturity score corresponding to the technology planning path according to the evaluation results, and calculating the overall increase in marginal investment maturity corresponding to the technology planning path according to the maturity score.

[0050] In some embodiments, the maturity score is used to represent the quantitative score of the overall level that an enterprise can achieve in each capability dimension under the technology planning path. In this embodiment, multiple capability dimensions are predefined, and the scores of each capability dimension are weighted and summed according to the dimension score of the selected technology planning path to obtain the maturity score.

[0051] In some embodiments, maturity increment is used to characterize the change in maturity score resulting from switching from one technology solution to another; that is, the capability improvement benefit brought about by the change of technology solution is measured based on the difference between the two technology solutions.

[0052] In some embodiments, the overall increase in marginal investment maturity is used to characterize the increase in maturity brought about by a unit investment, that is, the cost-effectiveness between the increase in maturity and the investment cost. When making decisions, the model not only needs to take the maximum increase in maturity as the optimization objective, but also needs to consider the overall investment efficiency of the technology planning path, so as to ensure that each decision step is the wisest and most cost-effective choice within a limited budget.

[0053] Optionally, the overall increase in marginal investment maturity corresponding to any technology planning path can be obtained by: acquiring multiple capability dimensions and setting calculation formulas for capability assessment models corresponding to each capability dimension; evaluating the intelligent manufacturing technology of steel enterprises according to the calculation formulas of each capability assessment model to obtain the evaluation results of the intelligent manufacturing technology of steel enterprises in each capability dimension; and calculating the overall increase in marginal investment maturity corresponding to the technology planning path based on the evaluation results.

[0054] In some embodiments, each capability dimension includes multiple requirements, and the score for intelligent manufacturing technology in steel enterprises in any capability dimension is represented as follows:

[0055] In the formula,

[0056] In some embodiments, the maturity level corresponding to a technology planning path is represented as:

[0057] In the formula,

[0058] In some embodiments, the maturity increment corresponding to the technology planning path is represented as:

[0059] In the formula, represents the maturity increment between the i-th scheme and the j-th technology planning path.

[0060] Optionally, the capability dimensions include at least one of the following: a planning and scheduling dimension, used to characterize the optimization capability of production scheduling; a production operation dimension, used to characterize task execution efficiency and / or production quality; an equipment management dimension, used to characterize equipment operating efficiency and / or equipment health status; a warehousing and distribution dimension, used to characterize logistics costs and / or logistics efficiency; and an energy management dimension, used to characterize the energy cost of the intelligent manufacturing technology of the steel enterprise.

[0061] In some embodiments, the evaluation criteria for scheme maturity are shown in Table 4.

[0062] Table 4

[0063] In some embodiments, the overall increase in the marginal investment maturity corresponding to intelligent manufacturing technologies in steel enterprises is expressed as:

[0064] In the formula,

[0065] In some embodiments, the objective function is expressed as:

[0066] in,

[0067] In the formula,

[0068] In some embodiments, the planning of intelligent manufacturing technology at each step may not simply involve adding a single technology, but rather adding multiple technologies. Meanwhile, the objective function formula (5) represents maximizing the sum of the overall increase in the total unit marginal investment and maturity of all planning steps, thus ensuring that each step achieves maximum benefit within limited resources. In some embodiments, manufacturing enterprises first face capital budgeting issues, needing to consider total investment constraints, set technology dependency constraints, and plan within a limited budget to maximize technological benefits. The technology dependency constraints are expressed as follows:

[0069] In the formula:

[0070] In some embodiments, the technological dependencies between the intelligent manufacturing technologies of various steel enterprises, for example, the dynamic optimization technology C4 for ironmaking production, depends on the limited deployment and stable operation of the sintered ore automatic tracking technology B6 and the blast furnace simulation and automatic pulverized coal injection technology B7. To reflect the hierarchy and collaboration among the intelligent manufacturing technologies of steel enterprises, technological dependency constraints are added to the path planning model, whereby the technological dependency constraints are expressed as follows:

[0071] In the formula:

[0072] Optionally, the method further includes: setting dimension scoring thresholds corresponding to each of the capability dimensions; determining the target technology selected for the technology planning path from the intelligent manufacturing technologies of the steel enterprise, and calculating the dimension scores of the technology planning path corresponding to each of the capability dimensions based on the evaluation results of the target technology in each of the capability dimensions; and adding the target technology that meets the constraint conditions to the path planning model, with each dimension score being greater than or equal to the corresponding dimension scoring threshold as a constraint condition.

[0073] Optionally, the method further includes: setting dimension score thresholds corresponding to each capability dimension; determining the target technology selected for the technology planning path from the intelligent manufacturing technology of steel enterprises, and calculating the dimension score of the technology planning path corresponding to each capability dimension based on the evaluation results of the target technology in each capability dimension; and adding the constraint condition that each dimension score is greater than or equal to the corresponding dimension score threshold to the path planning model.

[0074] In some embodiments, since the overall increase in the maturity of intelligent manufacturing technology for steel enterprises is achieved through marginal investment across different capability dimensions, in order to ensure that the intelligent manufacturing technology for steel enterprises selected in the technology planning path can produce positive effects in each capability dimension, it is necessary to ensure that each capability dimension meets the technology coverage requirements through technology dimension category constraints. These technology dimension category constraints are expressed as follows:

[0075] In the formula:

[0076] Optionally, the path planning model can be solved by: using a pre-defined programming library to convert the path planning model into a standardized model of mixed-integer linear programming; and calling a pre-defined computing engine to solve the standardized model to obtain the technical planning path.

[0077] Optionally, the path planning model can be solved in the following way: by continuously changing the infrastructure renovation investment coefficient and calling the technology path planning model, the impact of the infrastructure renovation investment coefficient on the technology planning path under different values ​​is analyzed. The optimization objective is to maximize the overall increase in marginal investment maturity. The path planning scheme that best meets the business needs of steel enterprises is obtained. In this process, sensitivity analysis is performed based on different infrastructure renovation investment coefficients according to the business needs of steel enterprises to find the basic cost calculation parameters that best match the actual situation. The path planning scheme and sensitivity analysis results are statistically analyzed and presented to users in a visual form.

[0078] In some embodiments, the technology planning path that maximizes the overall increase in marginal investment maturity is selected as the path planning scheme that best meets the business needs of steel companies.

[0079] In some embodiments, this application is not limited to using the Python programming language as the implementation platform for modeling and solving. It utilizes programming libraries such as the docplex library to convert the path planning model in MILP (Mixed-Integer Linear Programming) model format into a standard form recognizable by the CPLEX optimizer, and calls the CPLEX computing engine for optimization calculation. CPLEX, as an efficient mixed-integer programming solver, can provide a global optimal solution for MILP model problems, has strong stability and solution efficiency, and is particularly suitable for handling intelligent manufacturing decision problems containing multiple 0-1 variables, a large number of linear constraints and dependent logic.

[0080] Optionally, a path planning scheme is generated based on each technical planning path, including: obtaining current user needs; matching the investment coefficients of each infrastructure transformation according to the current user needs to obtain target coefficients; and visualizing the technical planning paths corresponding to the target coefficients according to the execution order to obtain a path planning scheme in icon format.

[0081] In some embodiments, if the production enterprise has complete equipment and has reserved network pipelines and computer room space, it can add new smart manufacturing technologies for steel enterprises simply by connecting the equipment and configuring the software. In this case, the production enterprise can choose a lower infrastructure transformation investment coefficient. If the production equipment is outdated, it may be necessary to carry out transformation tasks such as rewiring, upgrading the power distribution system, and setting up new servers. In this case, the production enterprise needs to choose a higher infrastructure transformation investment coefficient.

[0082] In some embodiments, the infrastructure upgrade cost corresponding to each technology dependency is set to 1, and the investment coefficient for low infrastructure upgrade is set to 0.1, for medium infrastructure upgrade to 4, and for high infrastructure upgrade to 9. The adjusted infrastructure upgrade cost is then the product of the existing infrastructure upgrade cost and the infrastructure upgrade investment coefficient. Based on different infrastructure upgrade investment coefficients, the technology planning paths are shown in Table 5 and... Figure 3 As shown, the total maturity level corresponding to the technology planning path is as follows: Figure 4 As shown; combined with Figure 3 and Figure 4 It can be seen that the infrastructure renovation investment coefficient is a direct mapping of the current situation of the enterprise in the mathematical model. The difference in the infrastructure renovation investment coefficient has a significant impact on the technology planning path. By changing the infrastructure renovation investment coefficient, the underlying cost-benefit calculation logic of the mathematical model is affected, so that the path planning model can re-evaluate the technology trade-offs under different cost constraints and generate different technology planning paths.

[0083] Table 5

[0084] In some embodiments, a path planning model is constructed using technical information on intelligent manufacturing technology in steel enterprises. An evaluation system for the overall increase in marginal investment maturity is introduced. Then, the actual situation of the enterprise is characterized by the infrastructure renovation investment coefficient. Sensitivity analysis is conducted on the path planning model based on different infrastructure renovation investment coefficients to determine the impact of the infrastructure renovation investment coefficient on the technology planning path. Finally, based on the technology planning path derived from the sensitivity analysis, the following table (Table 5) is generated. Figure 3 , Figure 4 The visualization charts are used to record the complete technical planning path and its derivation process, forming a path planning scheme.

[0085] Combination Figure 5 As shown, this application provides a technology path planning method based on marginal investment maturity, including: Step S501: Obtain the technical knowledge base; The technology knowledge base includes intelligent manufacturing technologies of multiple steel companies and the technological dependencies between these technologies. Step S502: Evaluate the intelligent manufacturing technology of steel enterprises based on different capability dimensions to obtain the total maturity level corresponding to the technology planning path; Step S503: Calculate the total technology cost corresponding to the intelligent manufacturing technology of steel enterprises based on the independent technology cost and the infrastructure transformation cost corresponding to the technology dependence relationship. Step S504: Obtain the marginal investment maturity increase by dividing the total maturity increase by the total investment, and take maximizing the total marginal investment maturity increase of the planned path as the objective function; The objective function is used to maximize the overall increase in marginal investment maturity corresponding to the technology planning path; The constraints include cost constraints, technology dependency constraints, and technology dimension category constraints. Among them, the cost constraint condition includes that the total technology cost corresponding to the technology planning path is less than the preset technology cost threshold; Among them, the technology dependency constraint includes the requirement that the intelligent manufacturing technology of steel enterprises in the technology planning path meets the technology dependency. Among them, the technical dimension category constraints include that the score of each dimension is greater than or equal to the corresponding dimension score threshold; Step S505: Construct a mathematical model based on the objective function and constraints to obtain the path planning model; Step S506: Adjust the infrastructure renovation cost according to different infrastructure renovation investment coefficients, and solve the path planning model according to the adjusted infrastructure renovation cost to obtain the technical planning path corresponding to each infrastructure renovation investment coefficient. Step S507: Generate a path planning scheme based on each technical planning path.

[0086] This application employs a technology path planning method based on marginal investment maturity. By acquiring the intelligent manufacturing technologies of steel enterprises and their interdependencies, the total technology cost is decomposed into independent total costs of intelligent manufacturing technologies for steel enterprises and infrastructure transformation costs associated with these technology dependencies. A path planning model is constructed with the overall increase in marginal investment maturity as the optimization objective and technology dependencies and total technology cost as constraints. By introducing a variable infrastructure transformation investment coefficient, the infrastructure transformation cost is dynamically adjusted. The model is solved separately to generate a set of technology planning paths corresponding to different infrastructure transformation investment coefficients, forming a path planning scheme. In this way, the infrastructure transformation cost corresponding to the technology dependencies is used as an independent adjustable variable in the model, and the infrastructure transformation cost is adjusted using the infrastructure transformation investment coefficient. This simulates application scenarios for production enterprises under different cost structures or investment preferences, enabling production enterprises to refer to and select different technology planning paths to meet their current urgent needs and improve the implementation effect of the path planning scheme.

[0087] Combination Figure 6 As shown, this application provides a technology path planning system based on marginal investment maturity, including an acquisition module 601, a construction module 602, and a calculation module 603.

[0088] The acquisition module 601 is used to acquire a technology knowledge base, wherein the technology knowledge base includes intelligent manufacturing technologies of multiple steel enterprises and the technology dependencies between the intelligent manufacturing technologies of each steel enterprise.

[0089] The construction module 602 is used to construct a path planning model with the aforementioned technology dependency relationship and total technology cost as constraints and the goal of maximizing the overall increase in marginal investment maturity as the optimization objective. The total technology cost includes the independent technology cost corresponding to the intelligent manufacturing technology of the steel enterprise and the infrastructure transformation cost of the intelligent manufacturing technology of the steel enterprise. The overall increase in marginal investment maturity is obtained by evaluating and calculating the technology planning path based on the intelligent manufacturing technology of the steel enterprise.

[0090] The adjustment module 603 is used to perform sensitivity analysis on the infrastructure renovation cost based on different preset infrastructure renovation investment coefficients, so as to adjust the infrastructure renovation cost according to the sensitivity analysis results.

[0091] The generation module 604 is used to solve the path planning model according to the adjusted infrastructure transformation cost to obtain the technical planning path corresponding to each infrastructure transformation investment coefficient, so as to generate a path planning scheme based on each technical planning path.

[0092] This application employs a technology path planning system based on marginal investment maturity. By acquiring the intelligent manufacturing technologies of steel enterprises and their interdependencies, the total technology cost is decomposed into independent total costs of intelligent manufacturing technologies for steel enterprises and infrastructure transformation costs associated with these technology dependencies. A path planning model is constructed with the overall increase in marginal investment maturity as the optimization objective and technology dependencies and total technology cost as constraints. By introducing a variable infrastructure transformation investment coefficient, the infrastructure transformation cost is dynamically adjusted. The model is solved separately to generate a set of technology planning paths corresponding to different infrastructure transformation investment coefficients, forming a path planning scheme. In this way, the infrastructure transformation cost corresponding to the technology dependencies is used as an independent adjustable variable in the model, and the infrastructure transformation cost is adjusted using the infrastructure transformation investment coefficient. This simulates application scenarios for production enterprises under different cost structures or investment preferences, enabling production enterprises to refer to and select different technology planning paths to meet their current urgent needs and improve the implementation effect of the path planning scheme.

[0093] This application also provides an electronic device, including: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device performs the above-described method.

[0094] Figure 7 A schematic diagram of a computer system suitable for implementing the embodiments of this application is shown. It should be noted that... Figure 7 The computer system 700 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0095] like Figure 7As shown, the computer system 700 includes a Central Processing Unit (CPU) 701, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on programs stored in Read-Only Memory (ROM) 702 or programs loaded from storage portion 708 into Random Access Memory (RAM) 703. The RAM 703 also stores various programs and data required for system operation. The CPU 701, ROM 702, and RAM 703 are interconnected via a bus 704. An Input / Output (I / O) interface 705 is also connected to the bus 704.

[0096] The following components are connected to I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 710 as needed so that computer programs read from it can be installed into storage section 708 as needed.

[0097] The electronic device disclosed in this embodiment includes a processor, a memory, a transceiver, and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and enable communication between them. The memory is used to store computer programs, the communication interface is used for communication, and the processor and transceiver are used to run the computer programs, causing the electronic device to perform the various steps of the above method. The above description and drawings fully illustrate the embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Unless explicitly required, individual components and functions are optional, and the order of operation may vary. Parts and subsamples of some embodiments may be included in or replace parts and subsamples of other embodiments. Moreover, the terminology used in this application is only for describing embodiments and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated subsamples, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other subsamples, wholes, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes the element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0098] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0099] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some sub-samples may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to implement this embodiment according to actual needs. Furthermore, the functional units in this application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0100] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of the systems, methods, and computer program products according to this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than those disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A technology path planning method, system, and electronic device based on marginal investment maturity, characterized in that, include: Acquire a technology knowledge base, wherein the technology knowledge base includes intelligent manufacturing technologies of multiple steel enterprises and the technology dependencies between the intelligent manufacturing technologies of each steel enterprise; Using the aforementioned technological dependencies and total technological costs as constraints, and taking the maximization of the overall increase in marginal investment maturity as the optimization objective, a path planning model is constructed. The total technological costs include the independent technological costs corresponding to the intelligent manufacturing technologies of the steel enterprises, as well as the infrastructure transformation costs for the infrastructure transformation of the intelligent manufacturing technologies of the steel enterprises. The maturity increase is obtained by evaluating and calculating the technological planning path based on the intelligent manufacturing technologies of the steel enterprises. Sensitivity analysis is performed on the infrastructure renovation cost based on different preset infrastructure renovation investment coefficients, and the infrastructure renovation cost is adjusted according to the results of the sensitivity analysis. Based on the adjusted infrastructure renovation costs, the path planning model is used to solve the problem and obtain the technical planning paths corresponding to each infrastructure renovation investment coefficient. A path planning scheme is then generated based on each technical planning path.

2. The method according to claim 1, characterized in that, The intelligent manufacturing technology for steel enterprises includes original basic technologies and original process technologies. The total technology cost corresponding to the original basic technologies is determined in the following way: From the original basic technologies, the target basic technologies selected for the technology planning path are determined, and the independent technology costs are calculated based on the preset investment costs corresponding to the target basic technologies. From the original process technologies associated with the target basic technology, the target process technologies selected in the technology planning path are determined, and the infrastructure transformation cost is calculated based on the number of target process technologies. The total cost of the original basic technology is calculated based on the cost of the independent technology and the cost of infrastructure transformation.

3. The method according to claim 1, characterized in that, The maturity increase corresponding to any technology planning path can be obtained through the following methods: Obtain multiple capability dimensions and set the capability assessment model calculation formula corresponding to each capability dimension; The technology planning path based on the intelligent manufacturing of steel enterprises is evaluated and calculated according to the calculation formula of each capability assessment model, and the evaluation results of the technology planning path in each capability dimension are obtained respectively. Based on the evaluation results, calculate the maturity score corresponding to the technology planning path, and calculate the maturity change between different technology combinations as the maturity increase.

4. The method according to claim 3, characterized in that, The capability dimension includes at least one of the following: The planning and scheduling dimension is used to characterize the optimization capability of production scheduling; Production operation dimension is used to characterize task execution efficiency and / or production quality; Equipment management dimension, used to characterize equipment operating efficiency and / or equipment health status; The warehousing and distribution dimension is used to characterize logistics costs and / or logistics efficiency. The energy management dimension is used to characterize the energy cost of the intelligent manufacturing technologies of the steel enterprises.

5. The method according to claim 3, characterized in that, The method further includes: Set the dimension scoring thresholds for each of the aforementioned capability dimensions; From the intelligent manufacturing technologies of the steel enterprises, the target technologies selected for the technology planning path are determined, and the dimension scores of the technology planning path in each of the capability dimensions are calculated based on the evaluation results of the target technologies in each of the capability dimensions. Using the constraint that all the scores of each dimension are greater than or equal to the corresponding dimension score threshold, the target technology that meets the constraint is added to the path planning model.

6. The method according to claim 1, characterized in that, Using the aforementioned technological dependencies and total technology cost as constraints, and taking the maximization of the overall increase in marginal investment maturity as the optimization objective, a path planning model is constructed, including: Construct model independent variables, wherein the model independent variables include technology selection status, which is used to characterize whether the technology planning path includes the intelligent manufacturing technology of the steel enterprise; Based on the ratio between the maturity score corresponding to the technology planning path and the total cost, the overall increase in marginal investment maturity under unit marginal investment for each of the steel enterprises' intelligent manufacturing technologies is calculated. The overall increase in maturity under total marginal investment corresponding to the technology planning path is used as the objective function, wherein the objective function is used to maximize the overall increase in marginal investment maturity of the technology planning path, and the overall increase in maturity under total marginal investment is calculated based on the overall increase in marginal investment maturity under unit marginal investment. The constraints are constructed, including cost constraints, technology dependency constraints, and technology dimension category constraints. The cost constraints include that the total technology cost corresponding to the technology planning path is less than a preset technology cost threshold. The technology dependency constraints include that the intelligent manufacturing technology of steel enterprises in the technology planning path meets the technology dependency relationship. The technology dimension category constraints include that the scores of each dimension are greater than or equal to the corresponding dimension score thresholds. A mathematical model is constructed based on the independent variables, the objective function, and the constraints to obtain the path planning model.

7. The method according to claim 1, characterized in that, The path planning model is solved using the following method: Based on the actual situation and needs of steel enterprises, the calculation parameters for basic renovation costs vary among different steel enterprises. Sensitivity analysis is required to find the basic cost calculation parameters that best match the actual situation. During the sensitivity analysis, the infrastructure renovation investment coefficient was continuously changed and the technology path planning model was called to solve the problem. The impact of different values ​​of the infrastructure renovation investment coefficient on the technology planning path was analyzed. The optimization objective was to maximize the overall increase in marginal investment maturity. The solution was then obtained to find the path planning scheme that best meets the business needs of steel companies. The path planning scheme and sensitivity analysis results are statistically analyzed and presented to users in a visual format.

8. The method according to claim 1, characterized in that, The path planning model is solved using the following method: Using a pre-defined programming library, the path planning model is converted into a standardized model of mixed-integer linear programming; The preset computing engine is invoked to solve the standardized model and obtain the technology planning path.

9. A technology path planning system based on marginal investment maturity, characterized in that, include: The acquisition module is used to acquire a technology knowledge base, wherein the technology knowledge base includes intelligent manufacturing technologies of multiple steel enterprises and the technology dependencies between the intelligent manufacturing technologies of each steel enterprise; A construction module is used to construct a path planning model with the aforementioned technology dependencies and total technology costs as constraints and the goal of maximizing the overall increase in marginal investment maturity as the optimization objective. The total technology costs include the independent technology costs corresponding to the intelligent manufacturing technology of the steel enterprise and the infrastructure transformation costs for the infrastructure transformation of the intelligent manufacturing technology of the steel enterprise. The maturity increase is obtained by evaluating and calculating the technology planning path based on the intelligent manufacturing technology of the steel enterprise. The adjustment module is used to perform sensitivity analysis on the infrastructure renovation cost based on different preset infrastructure renovation investment coefficients, so as to adjust the infrastructure renovation cost according to the sensitivity analysis results; The generation module is used to solve the path planning model according to the adjusted infrastructure transformation cost to obtain the technical planning path corresponding to each infrastructure transformation investment coefficient, so as to generate a path planning scheme based on each technical planning path.

10. An electronic device, characterized in that, include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-8.

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