Assembly line rapid reconstruction method based on forward transformation network

Abstract

The invention discloses an assembly line rapid reconstruction method based on a forward variant network, and the method comprises the steps: summarizing a multi-domain conduction principle of product similarity-system configuration similarity-system execution similarity of a man-machine cooperation assembly line; the physical and logic reconstruction connotation of the man-machine cooperation assembly line is described through five dimensions of function-structure-behavior-execution-performance, all levels of the assembly line are comprehensively considered, and the comprehensiveness and coordination of the overall design are improved. In the flexible production line design process with the production line rapid variant design as the core, the parameterized node network model and the set pair theory are adopted, the optimal production line change scheme can be selected more scientifically and objectively, and the time period from information induction to scheme implementation is shortened. According to the method, a mathematical model taking change of propagation risks, change of propagation time and change of propagation cost as a comprehensive target is constructed depending on the actual production condition of an enterprise, fine management and cost optimization are realized, and the cost is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of assembly line reconstruction, and in particular to a method for rapid assembly line reconstruction based on a forward variant network. Background Art

[0002] In a market environment with rapidly changing demands, companies are faced with frequent product design updates, which places higher demands on flexible production of production lines. Traditional assembly line upgrades or reorganizations often focus on single-aspect adjustments, such as focusing only on structural changes while ignoring the combined impact of functions, behaviors, execution, and performance. The understanding of production line reconstruction needs is not systematic and comprehensive enough, resulting in low system efficiency. At the same time, traditional assembly line upgrade or reorganization technologies often rely on manual evaluation, calculation, and design with subjective influences. Reconstructing production lines is time-consuming, costly, and error-prone. There is a lack of refined management in risk assessment, time, and cost forecasting of change propagation, making it difficult to adapt to complex and changing market demands. In addition, in traditional assembly line management, each device works independently, and information sharing cannot be achieved, which reduces decision-making efficiency. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method for rapid reconstruction of an assembly line based on a forward variant network.

[0004] To achieve the above purpose, the technical solution provided by the present invention is:

[0005] A fast assembly line reconfiguration method based on a forward variant network, comprising:

[0006] S1. Confirm product change requirements, including changes to product features and expected effects;

[0007] S2. Analyze the impact of the change on the existing assembly line;

[0008] S3. Gradually decompose the functions involved in the change and summarize them into different modules;

[0009] S4, characterize the physical and logical reconstruction relationship of the human-machine collaborative assembly line through multi-dimensional information;

[0010] S5. Based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line, a network model reflecting the assembly line structure is preliminarily established;

[0011] S6. Optimizing the established network model reflecting the assembly line structure to obtain a network association relationship model between nodes based on the network topology structure;

[0012] S7, optimizing the network association relationship model between nodes based on the network topology structure to obtain a multi-dimensional change model;

[0013] S8. Optimize the multi-dimensional change model to obtain a mathematical model for quantifying the change propagation path;

[0014] S9. Rapid reconfiguration of assembly lines through a mathematical model that quantifies the change propagation path.

[0015] Furthermore, based on the multi-domain conduction principle of “product similarity-system configuration similarity-system execution similarity”, the impact of the change on the existing assembly line is analyzed.

[0016] Furthermore, the five dimensions of "function-structure-behavior-execution-performance" are used to characterize the physical and logical reconstruction relationship of the human-machine collaborative assembly line, ensuring that the basic functional characteristics of the modules, the physical structure layout, the interactive behavior patterns between modules, the execution efficiency and the final output performance are taken into account during the change process, so as to achieve compatibility and consistency at the physical and logical levels.

[0017] Furthermore, based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line, a network model reflecting the assembly line structure is preliminarily established, including:

[0018] Analyze the relationship between modules based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line;

[0019] Identify the key components in each module, parameterize the key components, and convert the key attributes of the key components into operational parameters;

[0020] Use parameterized key components as nodes and establish connections between nodes;

[0021] Determine the degree of correlation between nodes and preliminarily establish a network model that reflects the assembly line structure.

[0022] Furthermore, the correlation between modules, the correlation between nodes and the correlation degree between nodes are analyzed based on performance correlation, function correlation, behavior correlation and structural correlation.

[0023] Furthermore, the established network model reflecting the assembly line structure is optimized, including:

[0024] By simplifying complex multiple dependencies into single or bidirectional dependencies, coupling and restrictions are set between various components and their changing characteristics on the assembly line.

[0025] Furthermore, the network association relationship model between nodes based on the network topology structure is optimized, including:

[0026] Set pair theory is used to characterize different aspects of the assembly line to ensure the comprehensiveness and accuracy of the model. At the same time, relational equations and mapping matrices are used to define the coupling and constraint relationships between key components to ensure that the model can reflect the complexity of reality.

[0027] Furthermore, the multi-dimensional change model is optimized, including:

[0028] Taking change propagation risk, change propagation time and change propagation cost as key indicators, the change propagation path planning objectives are defined. According to the actual situation of the enterprise and the market, the priority and optimization strategy of the objectives are set to obtain a mathematical model for quantifying the change propagation path.

[0029] Compared with the prior art, the principles and advantages of this technical solution are as follows:

[0030] 1. Summarize the multi-domain conduction principle of "product similarity-system configuration similarity-system execution similarity" of the human-machine collaborative assembly line, and use the five dimensions of "function-structure-behavior-execution-performance" to characterize the physical and logical reconstruction connotation of the human-machine collaborative assembly line, comprehensively consider all aspects of the assembly line, and improve the comprehensiveness and coordination of the overall design.

[0031] 2. In the flexible production line design process with rapid production line variation design as the core, the use of parameterized node network model and set pair theory can more scientifically and objectively select the optimal production line change plan and shorten the time period from information induction to plan implementation.

[0032] 3. Relying on the actual production situation of the enterprise, a mathematical model with comprehensive objectives of change propagation risk, change propagation time and change propagation cost is constructed to achieve refined management and cost optimization and reduce costs. At the same time, the use of the forward variant network model makes the production line more flexible.

[0033] 4. Use high-order semantic models to perform multi-dimensional change modeling, effectively integrate and share information, break down information silos, strengthen collaboration among modules, and improve decision-making efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 The figure is a principle flow chart of a method for rapid reconstruction of an assembly line based on a forward variant network of the present invention;

[0036] Figure 2 Analyze the schematic diagram for the assembly line module;

[0037] Figure 3 Modeling diagram for assembly line change feature association relationship;

[0038] Figure 4 Simplified diagrams for module and feature dependencies;

[0039] Figure 5 This is the forward variation network model diagram of “function-structure-behavior-execution-performance”. DETAILED DESCRIPTION

[0040] The present invention will be further described below in conjunction with specific embodiments:

[0041] like Figure 1 As shown, the method for rapid reconstruction of an assembly line based on a forward variant network described in this embodiment includes the following steps:

[0042] S1. Confirm product change requirements, including changes to product features and expected effects;

[0043] S2. Based on the multi-domain conduction principle of "product similarity-system configuration similarity-system execution similarity", analyze the impact of the change on the existing assembly line;

[0044] S3. Gradually decompose the functions involved in the change and summarize them into different modules;

[0045] like Figure 2 As shown in the figure, if we conduct a module analysis of a mobile phone assembly line, we first decompose the total function of the production line into basic function 1, basic function 2, auxiliary function 1, auxiliary function 2, etc., and further refine them into basic module 1, basic module 2, auxiliary module 1, auxiliary module 2, etc. Based on the above modules, we construct a specific assembly process of the mobile phone assembly line, including a manipulator, lifting equipment on both sides, fixture rotation equipment, double-sided tape pasting equipment, auxiliary material pasting equipment, shell screw mechanism, feeder equipment, pressing equipment, equipment positioning mechanism, circulation flipping mechanism, etc.

[0046] S4. After the original assembly line is carefully modularized, a crucial step is to conduct an in-depth analysis of the internal relationships between these independent modules. This process requires not only a macroscopic understanding of the role and function of each module in the production line, but also a detailed exploration of the intricate interaction mechanisms between modules.

[0047] This step uses the five dimensions of "function-structure-behavior-execution-performance" to characterize the physical and logical reconstruction relationship of the human-machine collaborative assembly line, ensuring that the basic functional characteristics of the module, the physical structure layout, the interactive behavior patterns between modules, the execution efficiency and the final output performance are taken into account during the change process, so as to achieve compatibility and consistency at the physical and logical levels.

[0048] S5. Based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line, a network model reflecting the assembly line structure is preliminarily established;

[0049] This step includes:

[0050] Analyze the relationship between modules based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line;

[0051] Identify the key components in each module, parameterize the key components, and convert the key attributes of the key components into operational parameters;

[0052] Use parameterized key components as nodes and establish connections between nodes;

[0053] Determine the degree of correlation between nodes and preliminarily establish a network model that reflects the assembly line structure.

[0054] like Figure 3 As shown above, the correlation between modules, the correlation between nodes and the correlation degree between nodes are analyzed based on performance correlation (W1), function correlation (W2), behavior correlation (W3) and structure correlation (W4).

[0055] Through systematic and comprehensive analysis, we can not only deeply understand the internal connections between modules, but also quickly and accurately adjust the configuration of the assembly line when faced with product change requirements, ensuring that the production line can respond efficiently and flexibly to rapid changes in the market.

[0056] S6. Optimizing the established network model reflecting the assembly line structure to obtain a network association relationship model between nodes based on the network topology structure;

[0057] In order to more intuitively and comprehensively understand the interaction between modules, a principle of simplicity is followed: when expressing associations, one-way associations are preferred because of their clarity and directness; secondly, if the complexity is slightly increased, simple two-way associations can effectively balance the difficulty of understanding and information integrity, and are more desirable than more complex compound two-way associations. Therefore, this implementation prefers to simplify complex multiple dependencies into single or two-way dependencies, and use these relationships to describe the coupling and constraint relationships between various parts and change features of the assembly line. According to the characteristics of the network topology, a suitable complex network association model between parameter nodes is built, which can make the various parts of the assembly line easier to track and manage, and the enterprise can efficiently identify and analyze the chain reactions caused by the changes in various parts, providing a solid foundation for the flexible reconstruction of the production line.

[0058] S7, optimizing the network association relationship model between nodes based on the network topology structure to obtain a multi-dimensional change model;

[0059] In this step, optimization includes:

[0060] Set pair theory is used to characterize different aspects of the assembly line to ensure the comprehensiveness and accuracy of the model. At the same time, relational equations and mapping matrices are used to define the coupling and constraint relationships between key components to ensure that the model can reflect the complexity of reality.

[0061] S8. Optimize the multi-dimensional change model to obtain a mathematical model for quantifying the change propagation path;

[0062] In order to ensure the effective application and implementation effect of the model, this embodiment relies on the actual production situation of the enterprise, studies the comprehensive goals of designing the change propagation path with change propagation risk, change propagation time and change propagation cost, clarifies the optimization rules of each goal, clarifies and sets the calculation rules of different change goals in the change propagation path planning, establishes the change propagation path planning mathematical model of the problem, and finally establishes the "function-structure-behavior-execution-performance" forward variation network driven by product change requirements, such as Figure 5 As shown in the figure, M1 to M7 represent different functional modules. This network model reflects the relationship between function, structure, behavior, execution and performance, and systematically solves the problem of how to plan the optimal change propagation path while considering the above multi-objective constraints. This model enables the production line to respond quickly and accurately to product change requirements, adjust the production line, and keep up with the rapid pace of market changes, providing powerful tool support for complex production line change management.

[0063] S9, quickly reconfigure the assembly line by quantifying the mathematical model of the change propagation path. The above-mentioned implementation examples are only preferred embodiments of the present invention, and are not intended to limit the scope of implementation of the present invention. Therefore, all changes made according to the shape and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for rapid reconstruction of an assembly line based on a forward variant network, characterized in that: include: S1. Confirm product change requirements, including changes to product features and expected effects; S2. Analyze the impact of the change on the existing assembly line; S3. Gradually decompose the functions involved in the change and summarize them into different modules; S4, characterize the physical and logical reconstruction relationship of the human-machine collaborative assembly line through multi-dimensional information; S5. Based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line, a network model reflecting the assembly line structure is preliminarily established; S6. Optimizing the established network model reflecting the assembly line structure to obtain a network association relationship model between nodes based on the network topology structure; S7, optimizing the network association relationship model between nodes based on the network topology structure to obtain a multi-dimensional change model; S8. Optimize the multi-dimensional change model to obtain a mathematical model for quantifying the change propagation path; S9. Rapid reconfiguration of assembly lines through a mathematical model that quantifies the change propagation path.

2. According to claim 1, a method for rapid reconstruction of an assembly line based on a forward variant network is characterized in that: Based on the multi-domain conduction principle of "product similarity-system configuration similarity-system execution similarity", the impact of changes on existing assembly lines is analyzed.

3. The method for rapid assembly line reconstruction based on a forward variant network according to claim 1 is characterized in that: The five dimensions of "function-structure-behavior-execution-performance" are used to characterize the physical and logical reconstruction relationship of the human-machine collaborative assembly line, ensuring that the basic functional characteristics of the module, the physical structure layout, the interactive behavior patterns between modules, the execution efficiency and the final output performance are taken into account during the change process, so as to achieve compatibility and consistency at the physical and logical levels.

4. The method for rapid assembly line reconstruction based on a forward variant network according to claim 1 is characterized in that: Based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line, a network model reflecting the assembly line structure is initially established, including: Analyze the relationship between modules based on the physical and logical reconstruction relationship of the human-machine collaborative assembly line; Identify the key components in each module, parameterize the key components, and convert the key attributes of the key components into operational parameters; Use parameterized key components as nodes and establish connections between nodes; Determine the degree of correlation between nodes and preliminarily establish a network model that reflects the assembly line structure.

5. The method for rapid assembly line reconstruction based on a forward variant network according to claim 1, characterized in that: The correlation between modules, the correlation between nodes and the degree of correlation between nodes are analyzed based on performance correlation, functional correlation, behavioral correlation and structural correlation.

6. The method for rapid assembly line reconstruction based on a forward variant network according to claim 1, characterized in that: Optimize the established network model that reflects the assembly line structure, including: By simplifying complex multiple dependencies into single or bidirectional dependencies, coupling and restrictions are set between various components and their changing characteristics on the assembly line.

7. The method for rapid assembly line reconstruction based on a forward variant network according to claim 1 is characterized in that: Optimize the network association relationship model between nodes based on the network topology structure, including: Set pair theory is used to characterize different aspects of the assembly line to ensure the comprehensiveness and accuracy of the model. At the same time, relational equations and mapping matrices are used to define the coupling and constraint relationships between key components to ensure that the model can reflect the complexity of reality.

8. The method for rapid assembly line reconstruction based on a forward variant network according to claim 1, characterized in that: Optimize the multi-dimensional change model, including: Taking change propagation risk, change propagation time and change propagation cost as key indicators, the change propagation path planning objectives are defined. According to the actual situation of the enterprise and the market, the priority and optimization strategy of the objectives are set to obtain a mathematical model for quantifying the change propagation path.

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