Method for performing intelligent industrial management method on basis of mes

Abstract

A method for performing intelligent industrial management on the basis of an MES. The method comprises: acquiring historical production data of an enterprise, analyzing the historical production data, and determining a production process, a production scale, and product characteristics; analyzing the product characteristics, and determining key control points in the production process; acquiring enterprise management requirements, and determining actual production requirements and personnel management requirements on the basis of the enterprise management requirements, the key control points, and the production scale; and on the basis of the actual production requirements and the personnel management requirements, developing a management module, and integrating an MES system. In this way, production links are accurately determined, and the utilization rate of an MES system is improved, thereby avoiding the waste of human resources. A dedicated MES system is customized for an enterprise, which reduces trial and error costs, thus more efficiently optimizing production processes, improving the production efficiency, enhancing the quality of products, optimizing personnel management, and improving the overall operation efficiency of the enterprise, such that the market competitiveness of the enterprise is strengthened.

Description

A MES-based Industrial Intelligent Management Method Technical Field

[0001] This application relates to the field of industrial management technology, and in particular to an industrial intelligent management method based on MES. Background Technology

[0002] MES (Manufacturing Execution System) is a crucial information management system in modern manufacturing. It enables the transmission of information, allows for responses and reporting of real-time events, and provides guidance and processing based on accurate current data, thereby improving production efficiency and quality, reducing costs, and enhancing market competitiveness.

[0003] However, MES systems are large and have numerous modules with complex logical relationships, making it difficult for enterprises to fully understand their functions and roles during implementation. Some enterprises lack system knowledge when selecting a system, making it difficult to choose an MES system that truly suits their needs. Summary of the Invention

[0004] This application provides an industrial intelligent management method based on MES to solve the above problems and customize a suitable MES system for enterprises.

[0005] Firstly, this application provides an industrial intelligent management method based on MES, including:

[0006] Obtain the company's historical production data, analyze the historical production data, and determine the production process, production scale, and product characteristics;

[0007] Analyze the product characteristics to identify the key control points in the production process;

[0008] Obtain enterprise management requirements, and determine actual production requirements and personnel management requirements based on the enterprise management requirements, the key control nodes, and the production scale;

[0009] Based on the actual production needs and personnel management needs, a management module was developed and integrated with the MES system.

[0010] Optionally, the analysis of the historical production data to determine the production process, production scale, and product characteristics includes:

[0011] Analyze the historical production data to determine the data characteristics of each historical production data point, classify the historical production data based on the data characteristics, and obtain the production process based on the classification results;

[0012] The production process is obtained by screening the aforementioned production stages;

[0013] Based on the classification results, production data is determined, and based on the production data, the production volume per unit time is determined.

[0014] The production scale is determined based on the production volume per unit time and the preset enterprise planning volume;

[0015] Based on the classification results, determine the testing data; based on the testing data, determine the product qualification rate;

[0016] The product composition is determined based on the production process and the production data.

[0017] The product characteristics are determined based on the product composition and the product qualification rate.

[0018] Optionally, the analysis of the product characteristics to determine the key control nodes in the production process includes:

[0019] Analyze the classified historical production data to determine the unit production time and defect quantity for each production process;

[0020] Based on the defect quantity and the product characteristics, determine the production defect rate per unit time.

[0021] Obtain the production task volume for each production process, and determine the production difficulty of each production process based on the production task volume, the unit production time, and the production defect rate per unit time.

[0022] The production difficulty of each production process is ranked, and key control nodes are determined based on the ranking results.

[0023] Optionally, the production difficulty of each production process is determined based on the production task volume, the unit production time, and the production defect rate per unit time, referring to the following formula:

[0024] Among them, D i Indicates production difficulty; T i t represents the production task quantity of the i-th production process; i R represents the unit production time for the i-th production process; i This represents the production defect rate per unit time for the i-th production process.

[0025] Optionally, obtaining enterprise management needs includes:

[0026] Obtain enterprise architecture information;

[0027] Analyze the enterprise structure information to determine employee types;

[0028] Based on the employee type, determine the job responsibilities for each employee type;

[0029] Based on the job responsibilities, send a request acquisition signal to the manager corresponding to each employee type, and receive management requests sent by the corresponding manager;

[0030] Based on the job responsibilities and the management requirements sent by the corresponding managers, the enterprise management requirements are obtained.

[0031] Optionally, determining the actual production needs and personnel management needs based on the enterprise management requirements, the key control nodes, and the production scale includes:

[0032] Determine the unit production volume based on the aforementioned production scale;

[0033] Based on the unit production volume and the production process, determine the material consumption and equipment consumption per unit time.

[0034] The actual production demand is determined based on the material consumption and the equipment consumption.

[0035] Based on the key control nodes, determine the personnel requirements for each production position;

[0036] Based on the production scale, determine the skill requirements for each production position;

[0037] Based on the personnel needs and skill requirements, the personnel management requirements are determined.

[0038] Optionally, based on the actual production needs and personnel management needs, a management module is developed and integrated with the MES system, including:

[0039] Based on the aforementioned actual production needs, an MES simulation system was established;

[0040] Based on the personnel management requirements, run the MES simulation system and determine the smoothness of operation based on the results.

[0041] Based on the described smoothness of operation, determine whether there are any problems with the current operation;

[0042] If problems exist, the stuttering nodes will be identified and analyzed based on the reported results to determine the operational issues.

[0043] Based on the actual production needs, personnel management needs, and operational issues, a management module was developed and integrated into the MES system.

[0044] Optionally, determining the smoothness of operation based on the results includes:

[0045] Based on the results, determine the throughput and average response time during the operation.

[0046] Acquire and analyze the setup data of the MES simulation system, and determine the material data and component data of the MES simulation system based on the data analysis results;

[0047] Based on the component data, determine the contact area of ​​the moving parts of the MES simulation system and the relative speed of the moving parts of the MES simulation system;

[0048] Based on the material data, determine the friction coefficient between the building materials and the mass of the MES simulation system;

[0049] By comprehensively analyzing the component data and the material data, the stiffness coefficient of the MES simulation system is determined.

[0050] The smoothness of operation is determined based on the contact area, relative velocity, coefficient of friction, stiffness coefficient, and mass, with reference to the following formula:

[0051] Wherein, C represents operational smoothness; T represents throughput; A represents average response time; k represents the stiffness coefficient; m represents the mass; H represents the contact area; μ represents the coefficient of friction; v represents the relative velocity of the moving parts of the MES simulation system; ρ represents the medium density of the working environment of the MES simulation system; c represents the medium damping coefficient of the working environment; α represents the influence coefficients of k and m on damping; β represents the influence coefficients of μ, H, and v on damping; and γ represents the influence coefficients of ρ, c, and H on damping.

[0052] Optionally, determining the material consumption and equipment consumption per unit time based on the unit production volume and the production process includes:

[0053] Based on the aforementioned production process, determine the data for raw materials and equipment used in production;

[0054] Based on the aforementioned raw materials, determine the material consumption per unit time, referring to the following formula:

[0055] Among them, M t This represents the material consumption per unit time; n represents the quantity of the raw materials used in production; P represents the unit production volume; M i This represents the unit consumption of the i-th type of raw material;

[0056] Based on the device data, determine the device usage parameters;

[0057] Based on the equipment usage parameters, determine the equipment consumption per unit time, referring to the following formula:

[0058] Among them, T eThis represents the equipment consumption per unit time; m represents the number of devices; W j T represents the power of the j-th device; j This represents the unit running time of the j-th device.

[0059] Secondly, this application provides an industrial intelligent management system based on MES, including:

[0060] The data analysis module is used to acquire the company's historical production data, analyze the historical production data, and determine the production process, production scale, and product characteristics.

[0061] The node determination module is used to analyze the product characteristics and determine the key control nodes in the production process.

[0062] The requirements analysis module is used to obtain enterprise management requirements and determine actual production requirements and personnel management requirements based on the enterprise management requirements, the key control nodes, and the production scale.

[0063] The system development module is used to develop a management module and integrate the MES system based on the actual production needs and personnel management needs.

[0064] Optionally, the data analysis module is specifically used for:

[0065] Analyze the historical production data to determine the data characteristics of each historical production data point, classify the historical production data based on the data characteristics, and obtain the production process based on the classification results;

[0066] The production process is obtained by screening the aforementioned production stages;

[0067] Based on the classification results, production data is determined, and based on the production data, the production volume per unit time is determined.

[0068] The production scale is determined based on the production volume per unit time and the preset enterprise planning volume;

[0069] Based on the classification results, determine the testing data; based on the testing data, determine the product qualification rate;

[0070] The product composition is determined based on the production process and the production data.

[0071] The product characteristics are determined based on the product composition and the product qualification rate.

[0072] Optionally, the node determination module is specifically used for:

[0073] Analyze the classified historical production data to determine the unit production time and defect quantity for each production process;

[0074] Based on the defect quantity and the product characteristics, determine the production defect rate per unit time.

[0075] Obtain the production task volume for each production process, and determine the production difficulty of each production process based on the production task volume, the unit production time, and the production defect rate per unit time.

[0076] The production difficulty of each production process is ranked, and key control nodes are determined based on the ranking results.

[0077] Optionally, when determining the production difficulty of each production process based on the production task volume, the unit production time, and the production defect rate per unit time, the node determination module is specifically used for:

[0078] Among them, D i Indicates production difficulty; T i t represents the production task quantity of the i-th production process; i R represents the unit production time for the i-th production process; i This represents the production defect rate per unit time for the i-th production process.

[0079] Optionally, the requirements analysis module is specifically used for:

[0080] Obtain enterprise architecture information;

[0081] Analyze the enterprise structure information to determine employee types;

[0082] Based on the employee type, determine the job responsibilities for each employee type;

[0083] Based on the job responsibilities, send a request acquisition signal to the manager corresponding to each employee type, and receive management requests sent by the corresponding manager;

[0084] Based on the job responsibilities and the management requirements sent by the corresponding managers, the enterprise management requirements are obtained.

[0085] Optionally, the requirements analysis module is specifically used for:

[0086] Determine the unit production volume based on the aforementioned production scale;

[0087] Based on the unit production volume and the production process, determine the material consumption and equipment consumption per unit time.

[0088] The actual production demand is determined based on the material consumption and the equipment consumption.

[0089] Based on the key control nodes, determine the personnel requirements for each production position;

[0090] Based on the production scale, determine the skill requirements for each production position;

[0091] Based on the personnel needs and skill requirements, the personnel management requirements are determined.

[0092] Optionally, the system development module is specifically used for:

[0093] Based on the aforementioned actual production needs, an MES simulation system was established;

[0094] Based on the personnel management requirements, run the MES simulation system and determine the smoothness of operation based on the results.

[0095] Based on the described smoothness of operation, determine whether there are any problems with the current operation;

[0096] If problems exist, the stuttering nodes will be identified and analyzed based on the reported results to determine the operational issues.

[0097] Based on the actual production needs, personnel management needs, and operational issues, a management module was developed and integrated into the MES system.

[0098] Optionally, the system development module is specifically used for:

[0099] Based on the results, determine the throughput and average response time during the operation.

[0100] Acquire and analyze the setup data of the MES simulation system, and determine the material data and component data of the MES simulation system based on the data analysis results;

[0101] Based on the component data, determine the contact area of ​​the moving parts of the MES simulation system and the relative speed of the moving parts of the MES simulation system;

[0102] Based on the material data, determine the friction coefficient between the building materials and the mass of the MES simulation system;

[0103] By comprehensively analyzing the component data and the material data, the stiffness coefficient of the MES simulation system is determined.

[0104] The smoothness of operation is determined based on the contact area, relative velocity, coefficient of friction, stiffness coefficient, and mass, referring to the following formula:

[0105] Wherein, C represents operational smoothness; T represents throughput; A represents average response time; k represents the stiffness coefficient; m represents the mass; H represents the contact area; μ represents the coefficient of friction; v represents the relative velocity of the moving parts of the MES simulation system; ρ represents the medium density of the working environment of the MES simulation system; c represents the medium damping coefficient of the working environment; α represents the influence coefficients of k and m on damping; β represents the influence coefficients of μ, H, and v on damping; and γ represents the influence coefficients of ρ, c, and H on damping.

[0106] Optionally, the requirements analysis module is specifically used for:

[0107] Based on the aforementioned production process, determine the data for raw materials and equipment used in production;

[0108] Based on the aforementioned raw materials, determine the material consumption per unit time, referring to the following formula:

[0109] Among them, M t This represents the material consumption per unit time; n represents the quantity of the raw materials used in production; P represents the unit production volume; M i This represents the unit consumption of the i-th type of raw material;

[0110] Based on the device data, determine the device usage parameters;

[0111] Based on the equipment usage parameters, determine the equipment consumption per unit time, referring to the following formula:

[0112] Among them, T e This represents the equipment consumption per unit time; m represents the number of devices; W j T represents the power of the j-th device; j This represents the unit running time of the j-th device. Attached Figure Description

[0113] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0114] Figure 1 is a schematic diagram of an application scenario provided by an embodiment of this application;

[0115] Figure 2 is a flowchart of an industrial intelligent management method based on MES provided in an embodiment of this application;

[0116] Figure 3 is a schematic diagram of the structure of an industrial intelligent management system based on MES provided in an embodiment of this application. Detailed Implementation

[0117] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0118] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0119] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0120] MES systems are large and have numerous modules with complex logical relationships, making it difficult for enterprises to fully understand their functions and roles during implementation. Some enterprises lack systemic understanding during the selection process, making it difficult to choose an MES system that truly suits their needs. Therefore, determining the appropriate MES system based on the enterprise's own characteristics is crucial for achieving more efficient intelligent industrial management.

[0121] Based on this, this application provides an industrial intelligent management method based on MES (Manufacturing Execution System). By deeply analyzing a company's historical production data, it can more accurately understand existing production processes, production scale, and product characteristics, thus providing data support for determining the company's production needs. Identifying key control nodes helps implement more effective monitoring and management during the production process, ensuring product quality and production efficiency. Based on the company's management needs, key control nodes, and production scale, determining actual production needs and personnel management needs allows for more precise identification of production stages, improving the utilization rate of the MES system, ensuring sufficient human resources on the production line, and avoiding waste of human resources. Developing management modules based on actual production and personnel management needs, and integrating them with the MES system, allows for the customization of a dedicated MES system for the company, reducing trial-and-error costs, more efficiently optimizing production processes, improving production efficiency, enhancing product quality, and optimizing personnel management, thereby improving the company's overall operational efficiency and enhancing its market competitiveness.

[0122] Figure 1 is a schematic diagram of an application scenario provided by this application. When an enterprise needs to build an MES system, it can apply the method provided by this application to build a suitable MES system according to its own characteristics, thereby improving management efficiency and reducing trial and error costs.

[0123] Specifically, the method provided in this application can be applied to any server, where the server interacts with the enterprise's production management system. By acquiring and analyzing historical production data and enterprise management needs from the enterprise's production management system, the actual production and personnel management needs of the enterprise can be accurately determined. This allows for the development of management modules, enabling the creation of a customized MES system for the enterprise. This, in turn, optimizes production processes, improves production efficiency, enhances product quality, optimizes personnel management, and improves the overall operational efficiency of the enterprise, thereby strengthening its market competitiveness.

[0124] For specific implementation details, please refer to the following examples.

[0125] Figure 2 is a flowchart of an industrial intelligent management method based on MES according to an embodiment of this application. The method of this embodiment can be applied to the server in the above scenario. As shown in Figure 2, the method includes:

[0126] S201. Obtain the company's historical production data, analyze the historical production data, and determine the production process, production scale, and product characteristics.

[0127] Historical production data can be understood as all the data generated by a company's factories during a historical period; it can be obtained from the company's existing production management system.

[0128] Specifically, a process analysis model is established, historical production data is input into the process analysis model, the production links of the factory are determined, and the dependencies of each link are obtained, thereby obtaining the corresponding production process.

[0129] By using data mining techniques to analyze historical production data, production patterns in each production process can be identified. These patterns may include the unit production volume, production cycle, and downtime for each process. Based on these patterns, the company's production scale can be assessed.

[0130] Analyze historical production data to determine the quantity and cause of non-conforming products generated in each production process and each production cycle. Based on the quantity and cause of non-conforming products, determine the product characteristics.

[0131] S202. Analyze product characteristics and identify key control points in the production process.

[0132] Key control points can be understood as points that require special attention. These points may have a significant impact on whether the product is qualified or not, or they may have a significant impact on the operation of the equipment itself.

[0133] Specifically, after obtaining the product characteristics, based on the reasons for the non-conforming products obtained above, the locations where these non-conforming products are generated are determined. The locations where non-conforming products are generated are statistically analyzed to determine the number of non-conforming products at each location. Based on the quantity, a weighted calculation is performed on each location to determine the critical control points.

[0134] S203. Obtain enterprise management needs. Based on enterprise management needs, key control nodes, and production scale, determine actual production needs and personnel management needs.

[0135] Actual production demand can be understood as the actual management needs of a company's factory during the production process. This actual production demand is obtained through a comprehensive analysis of the company's management needs, key control points, and production scale, and may differ from the production demand described by relevant personnel of the company.

[0136] Personnel management needs can be understood as the requirements put forward by the aforementioned enterprise for personnel management. These requirements may be derived from the analysis of the aforementioned historical production data and may differ from the personnel management needs described by the relevant personnel of the enterprise.

[0137] Specifically, when a company needs to build an MES system, it can proactively initiate a build request, which includes the company's management requirements. Based on the production process, production scale, and product characteristics obtained from the analysis of historical production data, the company's production capacity is assessed. Then, combined with the company's production capacity, current market demand, and key control nodes, the company's management requirements are verified. Based on the verification results, discrepancies are identified, and the company's actual production needs are determined accordingly.

[0138] Based on the above production process, identify the positions and corresponding responsibilities within the enterprise. Based on the characteristics of key control nodes, determine the specific responsibilities required for these positions. Based on the above, determine the personnel management requirements.

[0139] S204. Based on actual production and personnel management needs, develop a management module and integrate it with the MES system.

[0140] Specifically, integration goals are determined based on actual production and personnel management needs. Based on the aforementioned setup request, the company's setup cost is determined. Combining the setup cost and integration goals, an integration plan is designed, and suitable technical tools and platforms are selected. Based on this integration plan, management modules are developed to create an MES system that perfectly matches the company's actual situation.

[0141] The solution provided in this application allows for in-depth analysis of a company's historical production data, leading to a more accurate understanding of existing production processes, scale, and product characteristics. This data support provides a basis for determining the company's production needs. Identifying key control points facilitates more effective monitoring and management during production, ensuring product quality and production efficiency. Based on the company's management needs, key control points, and production scale, actual production and personnel management requirements are determined, enabling more precise identification of production stages and improving the utilization rate of the MES system. Developing management modules based on actual production and personnel management needs and integrating them with the MES system allows for customized MES systems tailored to the company's specific requirements. This reduces trial-and-error costs, more efficiently optimizes production processes, improves production efficiency, enhances product quality, and optimizes personnel management, thereby improving the company's overall operational efficiency and enhancing its market competitiveness.

[0142] In some embodiments, historical production data is analyzed to determine the data characteristics of each historical production data point. Based on these characteristics, the historical production data is classified, and production stages are obtained based on the classification results. These production stages are then screened to obtain the production process. Based on the classification results, production data is determined, and based on the production data, the production volume per unit time is determined. Based on the production volume per unit time and the preset enterprise planning volume, the production scale is determined. Based on the classification results, testing data is determined. Based on the testing data, the product qualification rate is determined. Based on the production process and production data, the product composition is determined. Based on the product composition and product qualification rate, the product characteristics are determined.

[0143] The production process can be understood as the entire process involved in industrial production. In addition to all the production processes that produce the product, it can also include the procurement of raw materials and the subsequent transportation process.

[0144] The preset enterprise planning volume can be understood as the production volume per unit time determined by the enterprise before production, based on the characteristics of the product and an assessment of its own production equipment and equipment performance. This is the production volume under an ideal state.

[0145] Inspection data can be understood as the data corresponding to the product inspection stage in the production process. Product pass rate can be understood as the product pass rate determined by analyzing the inspection data per unit time, or the pass rate after all products have been inspected in this production run.

[0146] Product ingredients can be understood as the raw materials required to produce the aforementioned products.

[0147] Product characteristics can be understood as the inherent features of a product.

[0148] Specifically, natural language processing technology is used to analyze historical production data and identify data characteristics such as time, quantifiers, and materials. These characteristics determine the data type; for example, time can be the usage time of corresponding materials or products, production time, or equipment start-up or shutdown time. To determine the specific type, the contextual information of the data can be combined for more precise identification, thereby enabling a more detailed classification of data types.

[0149] After determining the data type, identify all production stages of the product, and then screen all production stages to determine the process when actually producing the product. For example, determine the production process as injection molding, while the purchase of raw materials for injection molding is not part of the production process.

[0150] Based on the classification results obtained above, we determine which data corresponds to the production process, and thus determine the production volume of the aforementioned product per unit time. Simultaneously, based on the classification results, we determine which data belongs to the testing process, thereby obtaining the testing data. Using the testing data, we determine the product qualification rate in the historical production of the aforementioned product.

[0151] Because there is a discrepancy between the company's self-positioning and its actual production volume, the company's actual production scale is determined by combining the actual production volume per unit time with the company's own pre-planned production volume.

[0152] Based on production data and processes, the raw materials used in each process are determined, thereby determining the product composition. Combining the analysis results of product composition and product qualification rate, the key characteristics of the product (such as physical properties, chemical properties, service life, etc.) are determined.

[0153] The solution provided in this embodiment analyzes and categorizes historical production data, enabling a clearer identification of production stages and processes. Production scale is determined based on production volume per unit time and pre-planned enterprise volume, avoiding situations where a lack of clear self-awareness leads to an incompatible MES system and unnecessary cost waste. Analyzing product characteristics in conjunction with product composition and product qualification rate also helps to gain a deeper understanding of product uniqueness, facilitating the subsequent functional construction of the MES system for the manufactured products and improving the utilization rate of the MES system.

[0154] In some embodiments, the classified historical production data is analyzed to determine the unit production time and defect quantity for each production process; the production defect rate per unit time is determined based on the defect quantity and product characteristics; the production task quantity for each production process is obtained; the production difficulty of each production process is determined based on the production task quantity, unit production time, and production defect rate per unit time; the production difficulty of each production process is sorted, and key control nodes are determined based on the sorting results.

[0155] Unit production time can be understood as the time required to produce one product.

[0156] Defective quantity can be understood as the number of products that are found to be defective out of all products produced.

[0157] Production defect rate can be understood as the ratio of defective products to all products produced per unit of time.

[0158] Specifically, the categorized historical production data is analyzed to determine if there is data on non-conforming products and production volume. If so, the number of products detected as non-conforming during the corresponding time period is calculated based on the non-conforming data, thus obtaining the defect quantity for that period. Using the production volume data, the average production value for the corresponding time period is calculated to obtain the unit production time required for each production process to produce one product.

[0159] Calculate the production defect rate per unit time (e.g., per hour, per day) based on the defect quantity and the corresponding production quantity. The calculation formula is: Defect Rate = Defect Quantity / Production Quantity × 100%.

[0160] Obtain the production task quantity for each production process from the production plan, i.e., the total planned production volume. This production plan can be obtained from order demand. Combine unit production time, production defect rate per unit time, and production task quantity to comprehensively assess the production difficulty of each production process. Sort all production processes according to their production difficulty, either from high to low or low to high. Based on the ranking results, identify the production processes with the highest production difficulty as critical control nodes.

[0161] The solution provided in this embodiment analyzes categorized historical production data, ensuring the objectivity and accuracy of the analysis. By comprehensively considering multiple factors such as production workload, unit production time, and production defect rate per unit time, the difficulty of the production process is quantified, making comparisons between different production processes easier and enabling clearer and more accurate identification of production bottlenecks. This allows the subsequent construction of the MES system to better align with actual production processes and key control nodes, reducing cost waste and improving system utilization and management efficiency.

[0162] In some embodiments, the production difficulty of each production process is determined based on the production task volume, unit production time, and production defect rate per unit time, with reference to the following formula (1):

[0163] Among them, D i Indicates production difficulty; T i t represents the production task quantity of the i-th production process; i R represents the unit production time for the i-th production process; i This represents the production defect rate per unit time for the i-th production process.

[0164] The solution provided in this embodiment comprehensively considers multiple factors such as production workload, unit production time, and production defect rate per unit time, and designs a formula to calculate the production difficulty of each production process. This more comprehensively reflects the actual situation of the production process, enabling an objective comparison of the difficulty between different production processes, avoiding bias caused by subjective judgment, and ensuring that the assessment of production difficulty is more scientific and accurate.

[0165] In some embodiments, enterprise architecture information is obtained; the enterprise architecture information is analyzed to determine employee types; based on the employee types, the job responsibilities of each employee type are determined; based on the job responsibilities, a requirement acquisition signal is sent to the manager corresponding to each employee type, and the management requirements sent by the corresponding manager are received; based on the job responsibilities and the management requirements sent by the corresponding manager, the enterprise management requirements are obtained.

[0166] Enterprise architecture information can be understood as data related to the enterprise's structure, such as department setup, job division, and employee hierarchy.

[0167] Demand acquisition signals can be understood as signals sent to each manager, requiring them to summarize the requirements of the MES system.

[0168] Specifically, corporate structure information is obtained through channels such as the company's official website, internal documents, organizational charts, and employee handbooks. This information is then analyzed to determine the job divisions and employee types.

[0169] Based on employee types and the departmental setup and employee hierarchy in the organizational structure, the job responsibilities of each employee in their respective positions are determined. Based on these job responsibilities, the corresponding department managers are identified, and a request signal is sent to them. Upon receiving this signal, the department managers receive the management requests compiled by their respective managers, integrate the job responsibilities with the management requests sent by their managers, and obtain the enterprise management requirements.

[0170] The solution provided in this embodiment starts by acquiring enterprise architecture information, and through a series of orderly analyses, ultimately yields enterprise management requirements, ensuring the systematic and comprehensive nature of the information and avoiding omissions or biases. First, the enterprise architecture information is analyzed to determine employee types. Job responsibilities and the management requirements sent by corresponding managers are comprehensively considered to ensure the comprehensiveness and practicality of the management requirements.

[0171] In some embodiments, the unit production volume is determined based on the production scale; the material consumption and equipment consumption per unit time are determined based on the unit production volume and production process; the actual production demand is determined based on the material consumption and equipment consumption; the personnel requirements for each production position are determined based on key control nodes; the skill requirements for each production position are determined based on the production scale; and the personnel management requirements are determined based on the personnel and skill requirements.

[0172] Actual production demand can be understood as the actual demand throughout the entire production process.

[0173] Personnel requirements can be understood as the personality traits, characteristics, or character that personnel are required to possess at corresponding key control points.

[0174] Skill requirements can be understood as the skills that production personnel need to master in the production of the aforementioned products.

[0175] Specifically, based on the production scale of the enterprises, their production capacity is assessed to determine the unit production volume for each production cycle or time period. Based on the unit production volume, the average material consumption required to produce these products is calculated, given the known production volume. In a practical implementation, this can be calculated by combining the total production volume per unit time with the extent of material waste.

[0176] The system acquires equipment operating data, obtains the energy consumption during product production from the equipment operating data, and then calculates the equipment energy consumption per unit time based on the total energy consumption.

[0177] Based on the material and equipment consumption data obtained above, mathematical analysis is used to calculate what aspects of production management the company should implement after actual production commences. These include, for example, equipment maintenance cycle management and material replenishment or procurement management.

[0178] By using historical production data, the complexity and workload of each critical control node are assessed, thereby determining the required number of personnel for each critical control node and obtaining personnel requirements. Furthermore, by utilizing the complexity of each critical control node, the professional skills that personnel at that node should possess are determined, thus obtaining the skill requirements for each critical control node. Correspondingly, the skill requirements for other production processes can also be obtained by assessing the complexity of the corresponding processes.

[0179] Based on personnel and skill requirements, clarify the goals of personnel management, such as improving production efficiency and reducing costs, and determine personnel management needs. For example, refer to Table (1) for personnel management planning:

[0180] Table (1)

[0181] The solution provided in this embodiment determines the unit production volume based on production scale, ensuring that production capacity matches market demand. Determining material and equipment consumption per unit time based on unit production volume and production process helps enterprises optimize resource allocation, reduce waste, and improve resource utilization efficiency through the built MES system. Determining personnel requirements for each production position based on key control nodes ensures sufficient human resources support for key positions, improving the stability and efficiency of the production process. Determining personnel management requirements based on personnel and skill requirements helps improve enterprise management, reduce system construction costs, and increase the efficiency of automated management.

[0182] In some embodiments, an MES simulation system is established based on actual production needs; the MES simulation system is run according to personnel management needs, and the smoothness of operation is determined based on the running results; the smoothness of operation is used to determine whether there are problems in the current operation; if there are problems, the bottleneck nodes are identified and analyzed based on the running results to determine the operation problems; and a management module is developed and integrated into the MES system based on actual production needs, personnel management needs, and operation problems.

[0183] Specifically, by analyzing actual production needs, we obtain several aspects such as production scale, product characteristics, production process, key control nodes, and skill requirements disclosed in the above embodiments. We then select appropriate simulation tools and use the above data to establish an MES simulation system to simulate the operation of the MES system.

[0184] The MES system is simulated in a simulation environment to simulate various activities and decision-making processes throughout the entire product production cycle. Key indicators of the simulation process, such as production efficiency, material consumption, and equipment consumption, are determined, and the smoothness of the MES system's operation is evaluated based on these key indicators.

[0185] By assessing the smoothness of operation, we can determine if there are any bottlenecks in certain processes. If so, we can identify the bottleneck points through simulation playback or log analysis. Then, we conduct in-depth analysis of these bottleneck points to determine their causes, such as insufficient data processing capacity or uneven resource allocation. In practical implementation, we can consider the uncertainties and dynamic changes in the actual production environment, such as equipment failure, material shortages, and personnel changes. These factors can be added to the simulation environment to evaluate the MES system's ability to handle a range of problems in a real production environment, thus conducting a comprehensive assessment and determining the smoothness of operation. Finally, based on actual production needs, personnel management requirements, and operational issues discovered during simulation, we develop a management module and integrate it with the MES system.

[0186] The solution provided in this embodiment utilizes actual production needs to establish an MES simulation system, thereby determining whether there are any defects in the initially built system that affect its operation. If so, these defects are addressed promptly. At the same time, the MES simulation system, which has been built based on actual production and personnel management needs, is optimized, enabling the system to assist enterprises in management more quickly and efficiently, thereby improving overall production efficiency.

[0187] In some embodiments, based on the operating results, the throughput and average response time during the operation are determined; the setup data of the MES simulation system are acquired and analyzed, and based on the data analysis results, the material data and component data of the MES simulation system are determined; based on the component data, the contact area of ​​the moving parts of the MES simulation system and the relative speed of the moving parts of the MES simulation system are determined; based on the material data, the friction coefficient between the building materials and the mass of the MES simulation system are determined; and the stiffness coefficient of the MES simulation system is determined by comprehensively analyzing the component data and material data.

[0188] The smoothness of operation is determined based on the contact area, relative velocity, coefficient of friction, stiffness coefficient, and mass, referring to the following formula (2):

[0189] Where C represents operational smoothness; T represents throughput; A represents average response time; k represents stiffness coefficient; m represents mass; H represents contact area; μ represents friction coefficient; v represents relative velocity of moving parts in the MES simulation system; ρ represents medium density of the working environment of the MES simulation system; c represents medium damping coefficient of the working environment; α represents the influence coefficients of k and m on damping; β represents the influence coefficients of μ, H, and v on damping; and γ represents the influence coefficients of ρ, c, and H on damping.

[0190] Throughput can be understood as the amount of data successfully transmitted per unit of time by a network, device, port, virtual circuit or other facility, and can reflect the data processing capability of the MES system.

[0191] Average response time can be understood as the average time taken from the start of queuing to the end of execution after a request is performed through the MES system. It can reflect the speed and efficiency of the MES system in processing requests.

[0192] Data setup can be understood as all the data needed to build an MES system, which may include hardware-related data and software-related data.

[0193] Material data can be understood as the data related to the materials used in the hardware required to build the MES system. This can include properties such as material type, density, and hardness.

[0194] Component data can be understood as the data of the parts in the hardware-related data required to build an MES system. This can include the size, shape, and movement trajectory of each component.

[0195] Moving parts can be understood as components that physically operate during the operation of an MES system.

[0196] Specifically, after obtaining the execution results, the total number of tasks processed by the MES during this execution process is calculated from the results and used as the throughput. Then, the processing time of each task is calculated, and the sum of all processing times is divided by the total number of tasks to obtain the average response time.

[0197] Data from the establishment process of the MES simulation system is captured and analyzed to determine the materials and components used in the process, thus obtaining corresponding data. Using geometric calculations, the contact area between each moving component and the others is calculated. Then, the relative velocity of the moving components is obtained through their relative motion relationships. Based on the obtained material data, the friction coefficients between these materials are located or calculated. These friction coefficients can be obtained experimentally or using existing knowledge in materials science.

[0198] After obtaining the material and component data, the corresponding material or component property information is obtained, thus determining the corresponding mass. This mass is then summed to obtain the mass of the MES simulation system. By comprehensively analyzing the component and material data and using engineering mechanics formulas or simulation software, the stiffness coefficient of the MES simulation system is calculated.

[0199] After obtaining the contact area, relative velocity, friction coefficient, stiffness coefficient and mass through the above method, these parameters are quantified and the formula (2) is designed to calculate the smoothness of operation.

[0200] The solution provided in this embodiment comprehensively considers multiple factors, and the designed formula more accurately reflects the smoothness of the MES simulation system in actual operation, avoiding the one-sidedness of evaluation by a single indicator. By quantifying contact area, relative velocity, friction coefficient, stiffness coefficient, and mass, the evaluation results of operational smoothness are more accurate and objective, providing an accurate data foundation for judging whether there are problems in the MES system simulation.

[0201] In some embodiments, production raw material and equipment data are determined according to the production process; material consumption per unit time is determined according to the production raw materials, referring to the following formula (3):

[0202] Among them, M t This represents the material consumption per unit time; n represents the quantity of raw materials used in production; P represents the unit production output; M i This represents the unit consumption of the i-th type of raw material;

[0203] Based on the equipment data, determine the equipment usage parameters; based on the equipment usage parameters, determine the equipment consumption per unit time, referring to the following formula (4):

[0204] Among them, T e This represents the equipment consumption per unit time; m represents the number of devices; W j T represents the power of the j-th device; j This represents the unit running time of the j-th device.

[0205] The solution provided in this embodiment considers the unit consumption and unit production volume of all production raw materials, and designs a formula to accurately calculate the material consumption per unit time. This makes the calculation results more reliable and practical, and helps to achieve refined management and optimize the production process. By considering the power and unit operating time of all equipment, the designed formula accurately calculates the equipment consumption per unit time, which helps to assess the overall energy consumption and operating costs of the equipment.

[0206] Figure 3 is a schematic diagram of the structure of an industrial intelligent management system based on MES provided in an embodiment of this application. As shown in Figure 3, the industrial intelligent management system 300 based on MES in this embodiment includes: a data analysis module 301, a node determination module 302, a demand analysis module 303, and a system development module 304.

[0207] Data analysis module 301 is used to acquire the company's historical production data, analyze the historical production data, and determine the production process, production scale, and product characteristics;

[0208] The node determination module 302 is used to analyze the characteristics of the product and determine the key control nodes in the production process.

[0209] The demand analysis module 303 is used to obtain enterprise management requirements and determine actual production requirements and personnel management requirements based on the enterprise management requirements, the key control nodes and the production scale.

[0210] System development module 304 is used to develop a management module and integrate the MES system based on the actual production needs and personnel management needs.

[0211] Optionally, the data analysis module 301 is specifically used for:

[0212] Analyze the historical production data to determine the data characteristics of each historical production data point, classify the historical production data based on the data characteristics, and obtain the production process based on the classification results;

[0213] The production process is obtained by screening the aforementioned production stages;

[0214] Based on the classification results, production data is determined, and based on the production data, the production volume per unit time is determined.

[0215] The production scale is determined based on the production volume per unit time and the preset enterprise planning volume;

[0216] Based on the classification results, determine the testing data; based on the testing data, determine the product qualification rate;

[0217] The product composition is determined based on the production process and the production data.

[0218] The product characteristics are determined based on the product composition and the product qualification rate.

[0219] Optionally, the node determination module 302 is specifically used for:

[0220] Analyze the classified historical production data to determine the unit production time and defect quantity for each production process;

[0221] Based on the defect quantity and the product characteristics, determine the production defect rate per unit time.

[0222] Obtain the production task volume for each production process, and determine the production difficulty of each production process based on the production task volume, the unit production time, and the production defect rate per unit time.

[0223] The production difficulty of each production process is ranked, and key control nodes are determined based on the ranking results.

[0224] Optionally, when determining the production difficulty of each production process based on the production task volume, the unit production time, and the production defect rate per unit time, the node determination module 302 is specifically used for:

[0225] Among them, D i Indicates production difficulty; T i t represents the production task quantity of the i-th production process; i R represents the unit production time for the i-th production process; i This represents the production defect rate per unit time for the i-th production process.

[0226] Optionally, the requirements analysis module 303 is specifically used for:

[0227] Obtain enterprise architecture information;

[0228] Analyze the enterprise structure information to determine employee types;

[0229] Based on the employee type, determine the job responsibilities for each employee type;

[0230] Based on the job responsibilities, send a request acquisition signal to the manager corresponding to each employee type, and receive management requests sent by the corresponding manager;

[0231] Based on the job responsibilities and the management requirements sent by the corresponding managers, the enterprise management requirements are obtained.

[0232] Optionally, the requirements analysis module 303 is specifically used for:

[0233] Determine the unit production volume based on the aforementioned production scale;

[0234] Based on the unit production volume and the production process, determine the material consumption and equipment consumption per unit time.

[0235] The actual production demand is determined based on the material consumption and the equipment consumption.

[0236] Based on the key control nodes, determine the personnel requirements for each production position;

[0237] Based on the production scale, determine the skill requirements for each production position;

[0238] Based on the personnel needs and skill requirements, the personnel management requirements are determined.

[0239] Optionally, the system development module 304 is specifically used for:

[0240] Based on the aforementioned actual production needs, an MES simulation system was established;

[0241] Based on the personnel management requirements, run the MES simulation system and determine the smoothness of operation based on the results.

[0242] Based on the described smoothness of operation, determine whether there are any problems with the current operation;

[0243] If problems exist, the stuttering nodes will be identified and analyzed based on the reported results to determine the operational issues.

[0244] Based on the actual production needs, personnel management needs, and operational issues, a management module was developed and integrated into the MES system.

[0245] Optionally, the system development module 304 is specifically used for:

[0246] Based on the results, determine the throughput and average response time during the operation.

[0247] Acquire and analyze the setup data of the MES simulation system, and determine the material data and component data of the MES simulation system based on the data analysis results;

[0248] Based on the component data, determine the contact area of ​​the moving parts of the MES simulation system and the relative speed of the moving parts of the MES simulation system;

[0249] Based on the material data, determine the friction coefficient between the building materials and the mass of the MES simulation system;

[0250] By comprehensively analyzing the component data and the material data, the stiffness coefficient of the MES simulation system is determined.

[0251] The smoothness of operation is determined based on the contact area, relative velocity, coefficient of friction, stiffness coefficient, and mass, with reference to the following formula:

[0252] Wherein, C represents operational smoothness; T represents throughput; A represents average response time; k represents the stiffness coefficient; m represents the mass; H represents the contact area; μ represents the coefficient of friction; v represents the relative velocity of the moving parts of the MES simulation system; ρ represents the medium density of the working environment of the MES simulation system; c represents the medium damping coefficient of the working environment; α represents the influence coefficients of k and m on damping; β represents the influence coefficients of μ, H, and v on damping; and γ represents the influence coefficients of ρ, c, and H on damping.

[0253] Optionally, the requirements analysis module 303 is specifically used for:

[0254] Based on the aforementioned production process, determine the data for raw materials and equipment used in production;

[0255] Based on the aforementioned raw materials, determine the material consumption per unit time, referring to the following formula:

[0256] Among them, M t This represents the material consumption per unit time; n represents the quantity of the raw materials used in production; P represents the unit production volume; M i This represents the unit consumption of the i-th type of raw material;

[0257] Based on the device data, determine the device usage parameters;

[0258] Based on the equipment usage parameters, determine the equipment consumption per unit time, referring to the following formula:

[0259] Among them, T e This represents the equipment consumption per unit time; m represents the number of devices; W j T represents the power of the j-th device; j This represents the unit running time of the j-th device.

[0260] The system in this embodiment can be used to execute the methods of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

Claims

1. A MES-based industrial intelligent management method, characterized in that, The application relates to a method for developing a management module and integrating an MES system, comprising the following steps: obtaining historical production data of an enterprise, analyzing the historical production data, determining a production process, a production scale and product characteristics; analyzing the product characteristics, determining a key control node in the production process; obtaining enterprise management requirements, determining actual production requirements and personnel management requirements according to the enterprise management requirements, the key control node and the production scale; developing a management module based on the actual production requirements and the personnel management requirements, and integrating an MES system.

2. The method of claim 1, wherein, The step of analyzing the historical production data, determining a production process, a production scale and product characteristics comprises the following steps: analyzing the historical production data, determining data characteristics of each historical production data, classifying the historical production data based on the data characteristics, and obtaining a production link according to a classification result; screening the production link to obtain a production process; determining production data according to the classification result, and determining a unit-time production capacity according to the production data; determining the production scale according to the unit-time production capacity and a preset enterprise planning amount; determining detection data according to the classification result, and determining a product qualification rate according to the detection data; determining product components according to the production process and the production data; determining the product characteristics according to the product components and the product qualification rate.

3. The method of claim 2, wherein, The step of analyzing the product characteristics, determining a key control node in the production process comprises the following steps: analyzing the classified historical production data, determining a unit production time and a defective amount of each production process; determining a production defective rate in unit time according to the defective amount and the product characteristics; obtaining a production task amount of each production process, determining a production difficulty of each production process according to the production task amount, the unit production time and the production defective rate in unit time; sorting the production difficulty of each production process, and determining a key control node according to a sorting result.

4. The method of claim 3, wherein, The production difficulty of each production process is determined according to the production task amount, the unit production time and the production defective rate per unit time, and the following formula is referred to: wherein, D i represents the production difficulty; T i represents the production task amount of the i-th production process; t i represents the unit production time of the i-th production process; R i represents the production defective rate per unit time of the i-th production process.

5. The method of claim 1, wherein, The step of obtaining enterprise management requirements comprises the following steps: obtaining enterprise architecture information; analyzing the enterprise architecture information, and determining an employee type; determining a work responsibility of each employee type according to the employee type; sending a requirement obtaining signal to a management personnel corresponding to each employee type according to the work responsibility, and receiving a management requirement sent by the corresponding management personnel; obtaining an enterprise management requirement according to the work responsibility and the management requirement sent by the corresponding management personnel.

6. The method of claim 4, wherein, The step of determining actual production requirements and personnel management requirements according to the enterprise management requirements, the key control node and the production scale comprises the following steps: determining a unit production amount according to the production scale; determining a material consumption and a device consumption in unit time according to the unit production amount and the production process; determining the actual production requirements according to the material consumption and the device consumption; determining a personnel requirement of each production post according to the key control node; determining a skill requirement of each production post according to the production scale; determining the personnel management requirements according to the personnel requirement and the skill requirement.

7. The method of claim 1, wherein, The step of developing a management module based on the actual production requirements and the personnel management requirements, and integrating an MES system comprises the following steps: Based on the actual production demand, an MES simulation system is established; According to the personnel management demand, the MES simulation system is run, and the running fluency is determined according to the running result; According to the running fluency, it is determined whether there is a problem in the current running; If there is a problem, the running problem is determined and analyzed according to the running result; According to the actual production demand, the personnel management demand and the running problem, a management module is developed, and an MES system is integrated.

8. The method of claim 7, wherein, The running fluency is determined according to the running result, including: According to the running result, the throughput and the average response time in the running process are determined; The establishment data of the MES simulation system is obtained and analyzed, and the material data and the component data of the MES simulation system are determined based on the data analysis result; According to the component data, the contact area of the moving component of the MES simulation system and the relative speed of the moving component of the MES simulation system are determined; According to the material data, the friction coefficient between the building materials and the mass of the MES simulation system are determined; The component data and the material data are comprehensively analyzed to determine the stiffness coefficient of the MES simulation system; The running smoothness is determined according to the contact area, the relative speed, the friction coefficient, the stiffness coefficient, and the mass, with reference to the following formula: Wherein, C represents the running fluency; T represents the throughput; A represents the average response time; k represents the stiffness coefficient; m represents the mass; H represents the contact area; μ represents the friction coefficient; v represents the relative speed of the moving component of the MES simulation system; ρ represents the medium density of the working environment of the MES simulation system; c represents the medium damping coefficient of the working environment; α represents the influence coefficient of k and m on damping; β represents the influence coefficient of μ, H and v on damping; γ represents the influence coefficient of ρ, c and H on damping.

9. The method of claim 6, wherein, The material consumption and equipment consumption per unit time are determined according to the unit production quantity and the production process, including: According to the production process, the production raw material and equipment data are determined; According to the production raw materials, the material consumption per unit time is determined, referring to the following formula: wherein M t represents the material consumption per unit of time; n represents the number of production materials; P represents the unit production; M i represents the unit consumption of the i-th production material; According to the equipment data, the equipment use parameters are determined; According to the device usage parameter, the device consumption per unit time is determined, referring to the following formula: Wherein, T e represents the equipment consumption per unit time; m represents the number of equipment; W j represents the power of the jth equipment; T j represents the unit operation time of the jth equipment.

10. An MES-based industrial intelligent management system, characterized in that, Including: The data analysis module is used to obtain the historical production data of the enterprise, analyze the historical production data, and determine the production process, production scale and product characteristics; The node determination module is used to analyze the product characteristics and determine the key control nodes in the production process; The demand analysis module is used to obtain the enterprise management demand, and determine the actual production demand and personnel management demand according to the enterprise management demand, the key control nodes and the production scale; The system development module is used to develop a management module based on the actual production demand and the personnel management demand, and integrate an MES system.

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