High-speed rail gear box production intelligent management control system

Abstract

The invention relates to the technical field of intelligent control, in particular to a high-speed rail gearbox production intelligent management control system which comprises a production task planning module, a real-time monitoring execution module, a quality detection and feedback module and a production optimization instruction module. According to the invention, the task process is designed through accurate production demand and resource availability analysis, high matching and fine management of production line configuration are realized, the production efficiency is improved, and real-time monitoring is combined to realize real-time acquisition and analysis of data in the production process, so that the production efficiency is improved. The instant response capability of production line efficiency and quality control is obviously enhanced, the system can instantly identify production deviation and quality problems, rapidly feed back adjustment measures, reduce identification and response time, guarantee optimal configuration of resources and high efficiency of production scheduling through continuous optimization of production parameters, and improve production efficiency. The cost is obviously reduced, the overall quality of the product is improved, and the market competitiveness is enhanced.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and in particular to an intelligent management and control system for the production of high-speed rail gearboxes. Background Technology

[0002] The field of intelligent control technology encompasses the use of advanced algorithms, sensors, and automation systems to achieve intelligent management and control of equipment, systems, or processes. Key objectives include improving efficiency, reducing costs, and enhancing the autonomy and adaptability of systems. Intelligent control technology has applications in various fields, including manufacturing, transportation, energy management, and healthcare, encompassing a wide range of technologies such as machine learning, artificial intelligence, automation control, and sensor technology, bringing revolutionary changes and improvements to various industries.

[0003] The intelligent management and control system for high-speed rail gearbox production aims to optimize the production process of high-speed rail gearboxes using intelligent control technology. The system combines sensor technology, data analysis, and automated control to achieve real-time monitoring and intelligent management of the production process. By collecting, analyzing, and feeding back production data, the system can optimize and adjust the production process, improve production efficiency and product quality, reduce production costs, thereby meeting market demands and enhancing competitiveness.

[0004] Existing technologies still have significant shortcomings in real-time monitoring and data-driven decision-making in the production process. Particularly in the production of high-precision products such as high-speed rail gearboxes, traditional control systems often fail to make immediate adjustments due to slow response times and insufficient data processing capabilities, resulting in limited production efficiency and increased material waste and costs. For example, traditional systems require considerable time to diagnose and adjust for sudden quality issues on the production line. This delay not only affects the production rhythm but may also lead to inconsistent quality in batches of products. Furthermore, existing technologies typically lack flexibility in resource optimization and automation of scheduling strategies, limiting the adaptability of production systems to highly volatile market demands and reducing the company's ability to respond quickly to market changes. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and propose an intelligent management and control system for high-speed rail gearbox production.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A smart management and control system for high-speed rail gearbox production includes: The production task planning module designs the task process based on production demand and resource availability, adjusts the production line configuration to match the precision requirements of high-speed rail gearbox components, arranges the work sequence according to the configuration adjustment results, determines the production process and resource allocation, and outputs a detailed list of work instructions. The real-time monitoring and execution module uses the detailed work instruction list to coordinate the operation time between different processes through the production line synchronization strategy, monitors key production points through sensors, collects processing data in real time, analyzes production line efficiency and execution deviation, and generates real-time execution analysis records. Based on the real-time execution analysis record, the quality inspection and feedback module uses quality inspection sensors to perform dimensional and surface quality inspections on the high-speed rail gearbox components. Based on the inspection results, it compares them with production quality standards, identifies deviations and unqualified products, and generates a gearbox quality certificate. Based on the gearbox quality certificate, the production optimization instruction module analyzes production data, identifies areas for improvement in the process, adjusts production parameters, reconfigures production line resources based on the parameter adjustment results, optimizes the production scheduling plan, and generates a high-speed rail gearbox optimized production process guide.

[0007] As a further aspect of the present invention, the adjustment steps for the production line configuration are as follows: Collect current production demands for high-speed rail gearbox components, including specifications, quantities, and delivery times; analyze the machine status and operator skill levels of existing production lines; and use the following formula: ; in, Represents the number of available machines. This represents average operating efficiency. Represents order demand. To adjust the coefficients and match variations in technology levels, the resource efficiency index is calculated. Generate resource and demand matching records; Based on the resource and demand matching records, a production task flow is designed, referencing the principle of minimizing machine idle time and operator waiting time, using the following formula: ; in, For the first The processing time per piece for one machine. Due to operation delay, For process optimization coefficients, This is the delay adjustment factor. Given the total number of machines, calculate the overall process efficiency. Generate an optimized task flow design scheme; Based on the aforementioned task flow design scheme, the actual configuration of the production line is adjusted, and the machine settings are adjusted to match the precision requirements of the high-speed rail gearbox, using the formula: ; in, For target accuracy, For current accuracy, To adjust configuration costs, To adjust the complexity coefficient, Calculate the adjusted configuration cost for a safety margin. This generates the production line configuration adjustment results.

[0008] As a further aspect of the present invention, the step of obtaining the detailed work instruction list is as follows: Based on the production line configuration adjustment results, optimize the work sequence, analyze the time dependencies between processes, and use the following formula: ; in, This indicates the operation sequence of the i-th process. Let i be the priority weight of the i-th process. Adjust the coefficients in order. Calculate the job sequence optimization index for the total number of processes. Generate a job sequence arrangement plan; Based on the work sequence arrangement plan, the tasks and resource allocation for each process are planned, and resources are dynamically allocated using the formula: ; in, For total resources, For the first Resource consumption of the process To adjust the factors, calculate the remaining resources for each process. Generate process and resource allocation plans; Based on the aforementioned process and resource allocation plan, create a list of work instructions, organize the operation steps, responsible persons, estimated completion time and required resources, and generate a detailed list of work instructions.

[0009] As a further aspect of the present invention, the step of obtaining the real-time execution analysis record is as follows: Based on the detailed work instruction list, adjust the process times to ensure a continuous flow without delays, using the following formula: ; in, Represents the average synchronization time window. This refers to the start time of the process. This is the end time of the process. Generate a synchronous time window record for the total number of processes; Based on the recorded synchronization time window, sensors are deployed within the synchronization time window to monitor and collect data from key production points in real time, using the formula: ; in, For the first Actual data collected from each monitoring point Weights for each data point, Given the total number of monitoring points, calculate and generate the average real-time data collection record. ; Using the real-time data acquisition records, production efficiency and execution deviations are analyzed using the following formula: ; in, For production efficiency and execution deviation percentage, and Efficiency and deviation analysis results were obtained by using both expected and actual data. Based on the efficiency and deviation analysis results, the data and analysis results are integrated, and the following formula is used: ; in, This indicates the merging operation of data and analysis results, forming a real-time execution analysis log. .

[0010] As a further aspect of the present invention, the steps for inspecting the dimensions and surface quality of the high-speed rail gearbox assembly are as follows: Based on the real-time execution analysis records, select and configure the quality inspection sensor using the following formula: ; in, Indicates sensor Sensitivity level, Indicates sensor The importance and weight in quality inspection It is the sensor's environmental adaptability coefficient. These are calibration parameters to ensure that all critical measurement points are covered. Generate sensor configuration results for the number of sensors. ; The sensor configuration results are used to perform size and surface quality inspection, using the following formula: ; in, For the first The measured values ​​at each detection point For the first Standardization coefficient of each detection point To measure the depth coefficient, Calculate the weighted average measurement value based on the total number of inspection points to generate the quality inspection result. ; Based on the quality inspection results, all inspection data are summarized and recorded to ensure data integrity and accuracy, generating a high-speed rail gearbox quality inspection data record. .

[0011] As a further aspect of the present invention, the step of obtaining the gearbox quality certificate is as follows: Using the aforementioned high-speed rail gearbox quality inspection data records, and comparing them with production quality standards, the following formula is used: ; in, For the first Quality standards for each testing point Standard deviation weights are used to adjust the importance of quality standards at each point, calculate the total deviation, and generate deviation analysis results. ; Based on the deviation analysis results To identify all non-conforming products that exceed quality standards, the following formula is used: ; in, Generate a list of non-conforming products based on the non-conforming threshold. ; Based on the aforementioned list of non-conforming products, the following formula is used: like ,but Pass; like ,but Fail; Generate a certificate of conformity for the gearbox quality.

[0012] As a further aspect of the present invention, the adjustment steps for the production parameters are as follows: Based on the gearbox quality certificate, a deep analysis of the high-speed rail gearbox production data was conducted, using the following formula: ; in, Representing the The original values ​​of each data point This indicates the corresponding importance weight. It is an adjustment factor for environmental factors. The total number of data points. This represents a weighted average value that combines data importance and environmental factors, used to assess overall production quality and generate production data analysis results. Using the production data analysis results, key improvement areas are identified, using the following formula: ; in, It is a preset quality standard. It is the contribution weight of each point, which generates improved recognition results. ; Based on the improved identification results, the production parameters are adjusted using the following formula: ; in, For the adjusted parameter settings, Count Calculate the number of data points marked as improved. The original parameters are used as the basis for adjusting the original parameters using the square root function. By matching the changes in the dataset, the adjusted production parameters are obtained.

[0013] As a further aspect of the present invention, the steps for obtaining the high-speed rail gearbox optimized production process guide are as follows: Based on the production parameter adjustment results, the production line resources are reconfigured using the following formula: ; in, It is a new efficiency value for resource allocation. These are the adjusted parameters. It is an efficiency factor, and the effect of the efficiency factor is enhanced by squaring to obtain the resource allocation result; Using the resource allocation results, the production scheduling scheme is optimized using the following formula: ; in, For the total scheduling cost, For the first The time cost of each task is adjusted by quadratically to enhance the scheduling's impact. This represents the total number of tasks, from which the optimized scheduling scheme is obtained. Based on the optimized scheduling scheme, the production process was optimized, and a guideline for optimizing the production process of high-speed rail gearboxes was compiled.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, task processes are designed through precise analysis of production needs and resource availability, achieving a high degree of matching in production line configuration. This refined management not only improves production efficiency but also, combined with real-time monitoring, enables instant data collection and analysis during the production process. This significantly enhances the system's ability to respond instantly to production line efficiency and quality control. The system can instantly identify production deviations and quality issues, quickly provide feedback on adjustment measures, and reduce identification and response time. Through continuous optimization of production parameters, the system ensures optimal resource allocation and efficient production scheduling, significantly reducing costs and improving overall product quality, thereby enhancing market competitiveness. Attached Figure Description

[0015] Figure 1 This is a system flowchart of the present invention; Figure 2 A flowchart illustrating the adjustment process for the production line configuration of this invention; Figure 3 This is a flowchart illustrating the process of obtaining the detailed work instruction list for this invention. Figure 4 This is a flowchart illustrating the real-time execution analysis record acquisition process of this invention. Figure 5 This is a flowchart illustrating the dimensional and surface quality testing process for high-speed rail gearbox components according to the present invention. Figure 6 This is a flowchart illustrating the process of obtaining the quality certificate for the gearbox of this invention. Figure 7 This is a flowchart illustrating the adjustment of production parameters for this invention. Figure 8 This is a flowchart illustrating the process for obtaining the optimized production process guide for high-speed rail gearboxes according to the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0018] Example 1: Please refer to Figure 1 A smart management and control system for high-speed rail gearbox production includes: The production task planning module designs the task process based on production demand and resource availability, adjusts the production line configuration to match the precision requirements of high-speed rail gearbox components, arranges the work sequence according to the configuration adjustment results, determines the production process and resource allocation, and outputs a detailed list of work instructions. The real-time monitoring and execution module uses a detailed list of work instructions, coordinates the operation time between different processes through production line synchronization strategies, monitors key production points through sensors, collects processing data in real time, analyzes production line efficiency and execution deviations, and generates real-time execution analysis records. The quality inspection and feedback module is based on real-time execution analysis records. It uses quality inspection sensors to inspect the dimensions and surface quality of high-speed rail gearbox components. Based on the inspection results, it compares them with production quality standards, identifies deviations and unqualified products, and generates a gearbox quality certificate. The production optimization instruction module analyzes production data based on the gearbox quality certificate, identifies areas for improvement in the process, adjusts production parameters, reconfigures production line resources based on the parameter adjustment results, optimizes the production scheduling plan, and generates a guide to optimize the production process of high-speed rail gearboxes.

[0019] The detailed work instruction list includes task number, detailed process content, and resource allocation table. The real-time execution analysis record includes efficiency data, operational deviations, and production line status analysis results. The gearbox quality certificate includes dimensional compliance standards, surface inspection results, and quality grade. The high-speed rail gearbox optimized production process guide includes production efficiency improvement measures, resource reallocation schemes, and scheduling optimization measures.

[0020] Please see Figure 2 The steps for adjusting the production line configuration are as follows: Collect current production demands for high-speed rail gearbox components, including specifications, quantities, and delivery times; analyze the machine status and operator skill levels of existing production lines; and use the following formula: ; in, Represents the number of available machines. This represents average operating efficiency. Represents order demand. To adjust the coefficients and match variations in technology levels, the resource efficiency index is calculated. Generate resource and demand matching records; Based on resource and demand matching records, design the production task flow, referencing the principle of minimizing machine idle time and operator waiting time, using the following formula: ; in, For the first The processing time per piece for one machine. Due to operation delay, For process optimization coefficients, This is the delay adjustment factor. Given the total number of machines, calculate the overall process efficiency. Generate an optimized task flow design scheme; Based on the task flow design plan, the actual configuration of the production line was adjusted, and the machine settings were adjusted to match the precision requirements of the high-speed rail gearbox, using the formula: ; in, For target accuracy, For current accuracy, To adjust configuration costs, To adjust the complexity coefficient, Calculate the adjusted configuration cost for a safety margin. This generates the production line configuration adjustment results.

[0021] Assuming the current production line has 10 machines available, what is the operating efficiency of each machine? 80% of order demand For 20 gearboxes, variations in technology lead to a 10% reduction in efficiency, i.e. =0.1, substituting into the formula, we get: ; The result of 0.364 indicates that, considering variations in technological levels, the current matching efficiency between production resources and demand is 36.4%. This means that resource utilization efficiency is low, and it is necessary to increase the number of machines or improve operational efficiency.

[0022] Assuming the production line has 3 machines, the processing time of each machine is... The operation will take 2 hours. The process optimization coefficient is 0.5 hours. The delay adjustment factor is 1.5. Substituting 1.1 into the formula, we get: The result value of 1.765 represents the overall efficiency of the process design, with the higher value reflecting the improved production efficiency achieved by reducing delays and processing time through parameter optimization.

[0023] Assuming target accuracy The current precision is 0.01. The configuration adjustment cost is 0.015. for Adjust the complexity coefficient The safety factor is 1.2. Substituting 1.05 into the formula, we get: ; The result value of 667.507 represents the total cost after the configuration adjustment. The lower current accuracy led to the increased cost, but the adjustment ensured that the accuracy requirements were met.

[0024] Please see Figure 3 The steps to obtain a detailed list of work instructions are as follows: Based on the production line configuration adjustment results, optimize the work sequence, analyze the time dependencies between processes, and use the following formula: ; in, This indicates the operation sequence of the i-th process. Let i be the priority weight of the i-th process. Adjust the coefficients in order. Calculate the job sequence optimization index for the total number of processes. Generate a job sequence arrangement plan; Based on the work sequence, a plan is devised, outlining the tasks and resource allocation for each process. Resources are then dynamically allocated using the following formula: ; in, For total resources, For the first Resource consumption of the process To adjust the factors, calculate the remaining resources for each process. Generate process and resource allocation plans; Based on the work process and resource allocation plan, create a list of work instructions, organize the operation steps, responsible persons, estimated completion time and required resources, and generate a detailed list of work instructions.

[0025] Assume there are 3 processes, and their operation sequence is as follows: Assume the weight of process 1 is 1.2, that of process 2 is 1.0, and that of process 3 is 0.8. The value is 0.95. Based on the production line configuration adjustment results, the priority and process balance of each process are considered, and the work sequence is arranged. Substituting these values ​​into the formula, we get: ; The result value of 5.32 indicates that the operation sequence optimization index is obtained by comprehensively considering the process priority and operation sequence in a weighted manner. A higher value indicates that the optimization of the production sequence is more effective and can better meet the needs of production efficiency and process balance.

[0026] Assume a total resource of 1800 units, allocated to 3 processes. Process 1 consumes 300 units, Process 2 consumes 400 units, and Process 3 consumes 500 units. Adjustments are made to each process based on its resource consumption. The value is set to 0.8 to allow for flexibility in resource allocation. Taking process 1 as an example, substituting the values ​​into the formula, we get: ; For process 1, the remaining resources are 160 units. Similar calculations show that the resource allocations for processes 2 and 3 are 80 and 0 units, respectively. This represents the actual amount of resources available for each process after considering resource consumption and adjustment factors. Lower remaining resource values ​​indicate a need to reconsider resource allocation or optimize process scheduling.

[0027] Based on the process and resource allocation plan, create a detailed list of work instructions, including a detailed description of the operation steps for each process, a designated person in charge, the estimated completion time, and the remaining resources.

[0028] The person in charge of process 1 is A, the estimated completion time is 2 days, and the remaining resources are 160 units.

[0029] B is in charge of process 2, the estimated completion time is 3 days, and there are 80 units of resources remaining.

[0030] The person in charge of process 3 is C, the estimated completion time is 4 days, and the remaining resources are 0 units.

[0031] Ensuring clear tasks, well-defined responsibilities, and appropriate resource allocation for each process improves overall production efficiency and execution quality. A detailed instruction list for each process reflects the specific needs and resource utilization of the actual operation, facilitating smooth workflow.

[0032] Please see Figure 4 The steps for obtaining real-time analysis records are as follows: Based on a detailed list of work instructions, adjust the process times to ensure a continuous workflow without delays, using the following formula: ; in, Represents the average synchronization time window. This refers to the start time of the process. This is the end time of the process. Generate a synchronous time window record for the total number of processes; Based on the synchronization time window records, sensors are deployed within the synchronization time window to monitor and collect data from key production points in real time, using the formula: ; in, For the first Actual data collected from each monitoring point Weights for each data point, Given the total number of monitoring points, calculate and generate the average real-time data collection record. ; By utilizing real-time data acquisition and recording, production efficiency and execution deviations are analyzed using the following formula: ; in, For production efficiency and execution deviation percentage, and Efficiency and deviation analysis results were obtained by using both expected and actual data. Based on the efficiency and deviation analysis results, the data and analysis results are integrated, and the following formula is used: ; in, This indicates the merging operation of data and analysis results, forming a real-time execution analysis log. .

[0033] Suppose there are three processes, with the following start and end times: Process 1: Starts at 08:00 (8.0 hours) and ends at 12:00 (12.0 hours).

[0034] Process 2: Starts at 09:00 (9.0 hours) and ends at 13:00 (13.0 hours).

[0035] Process 3: Starts at 09:30 (9.5 hours) and ends at 14:00 (14.0 hours).

[0036] Calculate the duration of each process: Process 1: Hour; Process 2: Hour; Process 3: Hour; Calculate the synchronization time window: ; This indicates that the average operation time for each process is 4.17 hours, providing a standardized time window to coordinate the synchronous operation of each process.

[0037] Assuming there are three monitoring points, the actual data and weights of each point are as follows: Monitoring point 1: Data = 100, weight = 1.0.

[0038] Monitoring point 2: Data = 150, weight = 1.5.

[0039] Monitoring point 3: Data = 200, weight = 1.2.

[0040] Calculate the weighted sum of the data: ; This indicates that the average weighted data value per monitoring point is 188.33, which is used to analyze real-time production status.

[0041] Assume the expected data is as follows: Monitoring point 1: Expected value = 120.

[0042] Monitoring point 2: Expected value = 140.

[0043] Monitoring point 3: Expected value = 180.

[0044] The actual data are consistent with the above, namely 100, 150 and 200; Calculate the sum of squares of the deviations and the expected sum of squares: Sum of squared deviations: ; Expected sum of squares: ; Calculation efficiency and percentage of deviation: ; The results show that the production line efficiency is [percentage]% of the execution deviation. This demonstrates high production efficiency and low deviation.

[0045] Based on the combined efficiency analysis results and real-time data, we can conclude that: ; By combining comprehensive information from efficiency analysis and real-time data collection, a complete perspective is provided for the production management of high-speed rail gearboxes.

[0046] Please see Figure 5 The steps for inspecting the dimensions and surface quality of high-speed rail gearbox components are as follows: Based on real-time execution analysis records, select and configure the quality inspection sensor using the following formula: ; in, Indicates sensor Sensitivity level, Indicates sensor The importance and weight in quality inspection It is the sensor's environmental adaptability coefficient. These are calibration parameters to ensure that all critical measurement points are covered. Generate sensor configuration results for the number of sensors. ; Dimensioning and surface quality are inspected using the sensor configuration results, employing the following formula: ; in, For the first The measured values ​​at each detection point For the first Standardization coefficient of each detection point To measure the depth coefficient, Calculate the weighted average measurement value based on the total number of inspection points to generate the quality inspection result. ; Based on the quality inspection results, all inspection data are summarized and recorded to ensure data integrity and accuracy, generating a high-speed rail gearbox quality inspection data record. .

[0047] Assuming there are 3 sensors, with the parameters set as follows: Sensor 1: ; Sensor 2: ; Sensor 3: ; Substitute the values ​​into the formula to calculate the total score for the sensor configuration: ; ; The overall configuration score is 2.73, reflecting the overall quality and adaptability of the sensor setup.

[0048] Assume quality testing is conducted at 3 testing points: Measurement point 1: ; measuring point ; measuring point ; Calculate the weighted average measurement: ; ; The value 207.67 represents the average quality index detected, used to assess the overall quality level of the gearbox assembly.

[0049] Finally, by summarizing and recording all the test data, we can obtain the high-speed rail gearbox quality test data record, which provides detailed data for further analysis and recording.

[0050] Please see Figure 6 The steps to obtain a quality certificate for a gearbox are as follows: Using high-speed rail gearbox quality inspection data records, compared with production quality standards, the following formula is used: ; in, For the first Quality standards for each testing point Standard deviation weights are used to adjust the importance of quality standards at each point, calculate the total deviation, and generate deviation analysis results. ; Based on the deviation analysis results To identify all non-conforming products that exceed quality standards, the following formula is used: ; in, Generate a list of non-conforming products based on the non-conforming threshold. ; Based on the list of non-conforming products, the following formula is used: like ,but Pass; like ,but Fail; Generate a certificate of conformity for the gearbox quality.

[0051] Assume there are standard values ​​and measurement results for 3 detection points as follows: Measurement point 1: Standard value , measured value Weight .

[0052] Measurement point 2: Standard value , measured value Weight .

[0053] Measurement point 3: Standard value , measured value Weight .

[0054] Calculate the total deviation: ; ; Deviation analysis results It indicates the overall deviation from production standards and is used to assess the overall conformity of high-speed rail gearboxes.

[0055] Set a non-compliance threshold A deviation of 9 was set as the maximum acceptable deviation value, and a deviation value of 11.87 was used with the threshold. Compare: ; Based on the aforementioned calculations, only the deviation at measuring point 1 is considered. The threshold was exceeded, therefore a list of non-conforming products was generated. The presence of test point 1 indicates that the product failed the quality standard inspection.

[0056] because Including measurement point 1, therefore ,but “Fail”.

[0057] This indicates that the generated quality certificate is "unqualified" because the measurement result at at least one test point did not meet the standard.

[0058] Please see Figure 7 The steps for adjusting production parameters are as follows: Based on the gearbox quality certificate, an in-depth analysis of the high-speed rail gearbox production data was conducted, using the following formula: ; in, Representing the The original values ​​of each data point This indicates the corresponding importance weight. It is an adjustment factor for environmental factors. The total number of data points. This represents a weighted average value that combines data importance and environmental factors, used to assess overall production quality and generate production data analysis results. Using production data analysis results, identify key areas for improvement, using the following formula: ; in, It is a preset quality standard. It is the contribution weight of each point, which generates improved recognition results. ; Based on the improved identification results, production parameters were adjusted using the following formula: ; in, For the adjusted parameter settings, Count Calculate the number of data points marked as improved. The original parameters are used as the basis for adjusting the original parameters using the square root function. By matching the changes in the dataset, the adjusted production parameters are obtained.

[0059] Assuming there are 3 data points, the parameters are set as follows: Data point 1: ; Data points ; Data point 3: ; Calculate the weighted average analysis results: ; ; The result 232.67 represents a weighted average value after considering data importance and environmental factors, providing a quantitative assessment of production data quality.

[0060] Assuming a threshold : Data point 1: (Needs improvement).

[0061] Data point 2: (satisfy).

[0062] Data point 3: (satisfy).

[0063] Calculate the results of the improvement process identification: ; A result of 0.67 indicates the intensity of the identified improvement need based on the set threshold and the importance of the data points.

[0064] Assuming the original parameters Furthermore, based on the aforementioned calculations, we know that one data point (data point 1) needs improvement. Substituting this into the formula, we get: ; The result 133.33 represents the adjusted parameter value, used to adapt to the identified improvement needs, with the aim of optimizing production efficiency.

[0065] Please see Figure 8 The steps to obtain the "Guidelines for Optimizing the Production Process of High-Speed ​​Railway Gearboxes" are as follows: Based on the adjustments to production parameters, production line resources are reconfigured using the following formula: ; in, It is a new efficiency value for resource allocation. These are the adjusted parameters. It is an efficiency factor, and the effect of the efficiency factor is enhanced by squaring to obtain the resource allocation result; Utilizing resource allocation results, optimize the production scheduling scheme using the following formula: ; in, For the total scheduling cost, For the first The time cost of each task is adjusted by quadratically to enhance the scheduling's impact. This represents the total number of tasks, from which the optimized scheduling scheme is obtained. Based on the optimized scheduling scheme, the production process was optimized, and a guideline for optimizing the production process of high-speed rail gearboxes was compiled.

[0066] Based on the aforementioned calculations, let's assume the adjusted parameters... and efficiency factor Substituting into the formula, we get: ; The result of 161.33 represents the new efficiency value of resource allocation, reflecting the impact of adjusting parameters on the resource allocation of the production line, that is, the efficiency of resource utilization is further enhanced on the basis of improving parameters.

[0067] Assume there are 3 production tasks, and the time cost of each task is set as follows: Task 1: ; Task 2: ; Task 3: ; And from the aforementioned calculations, we know ,but: ; ; result Representing total scheduling cost, it reflects how optimized resource allocation improves overall production efficiency by increasing task time costs.

[0068] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A high iron gear box production intelligent management control system, characterized in that, The system comprises: The production task planning module designs task flow based on production demand and resource availability, adjusts production line configuration to match the precision requirements of high-speed rail gear box assembly, arranges job sequence according to configuration adjustment result, determines production process and resource allocation, and outputs detailed job instruction list; The real-time monitoring execution module uses the detailed job instruction list to coordinate operation time between different processes through production line synchronization strategy, monitors key production points through sensors, collects processing data in real time, analyzes production line efficiency and execution deviation, and generates real-time execution analysis record; The quality detection and feedback module detects the size and surface quality of high-speed rail gear box assembly based on the real-time execution analysis record, compares the detection result with production quality standard, identifies deviation and unqualified products, and generates gear box quality qualification certificate; The production optimization instruction module analyzes production data according to the gear box quality qualification certificate, identifies improvement links in the process, adjusts production parameters, reconfigures production line resources according to parameter adjustment result, optimizes production scheduling scheme, and generates high-speed rail gear box optimized production process guide.

2. The intelligent management control system for high-speed rail gear box production according to claim 1, characterized in that: The adjustment steps of the production line configuration are: Collect the production demand of current high-speed rail gear box assembly, including specification quantity and delivery time, analyze the machine state of existing production line and the technical level of operating personnel, and use the formula: ； wherein, represents the number of available machines, represents the average operating efficiency, represents the order demand, is an adjustment factor matching the technology level variation, the computing resource efficiency index , generating a resource and demand matching record; According to the resource and demand matching record, design the production task flow, refer to the minimum machine idle and operator waiting time, and use the formula: ； wherein, is the first is the single piece processing time of the machine, is the operation delay, is the flow optimization coefficient, is the delay adjustment coefficient, is the total number of machines, and calculating the overall flow efficiency generates an optimized task flow design scheme; According to the task flow design scheme, adjust the actual configuration of the production line, adjust the machine settings to match the precision requirements of high-speed rail gear box, and use the formula: ； wherein, is a target accuracy, is a current accuracy, is a configuration adjustment cost, is an adjustment complexity coefficient, is a safety coefficient, the adjusted configuration cost is calculated a production line configuration adjustment result is generated.

3. The intelligent management control system for high-speed rail gear box production according to claim 2, characterized in that: The acquisition steps of the detailed job instruction list are: According to the production line configuration adjustment result, optimize the job sequence, analyze the time dependency between processes, and use the formula: ； wherein, represents the operation sequence of the i-th process, is the priority weight of the i-th process, is the sequence adjustment coefficient, is the total number of processes, and the operation sequence optimization index is calculated to generate the operation sequence arrangement scheme; According to the job sequence arrangement scheme, plan the task and resource configuration of each process, and dynamically allocate resources, and use the formula: ； wherein, is the total amount of resources, is the first resource consumption of the process, is the adjustment factor, the remaining resources of each process are calculated , a process and resource allocation plan is generated; According to the process and resource allocation plan, create the job instruction list, sort the operation steps, responsible person, estimated completion time and required resources, and generate the detailed job instruction list.

4. The intelligent management control system for high-speed rail gear box production according to claim 1, characterized in that: The acquisition steps of the real-time execution analysis record are: Based on the detailed job instruction list, adjust the process time to ensure continuous process without delay, and use the formula: ； wherein, represents the average synchronization time window, is the process start time, is the process end time, is the total number of processes, a synchronization time window record is generated; According to the synchronization time window record, deploy sensors within the synchronization time window, monitor and collect key production point data in real time, and use the formula: ； wherein, is the number of monitoring points, is the actual data collected for the is the weight for each data point, is the total number of monitoring points, the average real-time data acquisition record is calculated and generated ; Use the real-time data collection record to analyze production efficiency and execution deviation, and use the formula: ； wherein, for production efficiency and execution bias percentage, and are the expected data and actual data, respectively, resulting in efficiency and bias analysis results; According to the efficiency and deviation analysis result, integrate data and analysis result, and use the formula: ； wherein, representing a merge operation of data and analysis results, forming a real-time execution analysis record .

5. The intelligent management control system for high-speed rail gear box production according to claim 1, characterized in that: The detection steps of the size and surface quality of high-speed rail gear box assembly are: According to the real-time execution analysis record, select and configure quality detection sensors, and use the formula: ； wherein, represents the sensitivity level of the sensor , represents the importance weight of the sensor in the quality detection, is the sensor environment adaptation coefficient, is the calibration parameter, ensuring that all key measurement points are covered, is the number of sensors, generating the sensor configuration result ; Use the sensor configuration result to detect the size and surface quality, and use the formula: ； wherein, is the measurement value of the nth detection point, is the standardized coefficient of the nth detection point, is the measurement depth coefficient, is the total number of detection points, the weighted average measurement value is calculated, and the quality detection result is generated ;​​ According to the quality detection result, all detection data are summarized and recorded to ensure data integrity and accuracy, and high-speed rail gear box quality detection data record is generated .

6. The intelligent management control system for high-speed rail gear box production according to claim 5, characterized in that: The acquisition steps of the gear box quality qualification certificate are: Use the high-speed rail gear box quality detection data record to compare with production quality standard, and use the formula: ； Wherein, is the quality standard of the first detection point, is the quality standard of the nth detection point, is the standard deviation weight, used to adjust the importance of each point quality standard, calculate the total deviation, and generate the deviation analysis result ; Based on the deviation analysis results , all substandard products that exceed the quality standards are identified using the formula: ； wherein, is a non-conformance threshold, a non-conformance product list is generated ; According to the unqualified product list, use the formula: If then Pass; If then Fail; A gearbox quality qualification certificate is generated.

7. The intelligent management control system for high-speed rail gear box production according to claim 1, characterized in that: The adjusting step of the production parameter is: According to the gearbox quality qualification certificate, the production data of the high-speed railway gearbox are analyzed in depth, and a formula is used: ； wherein, represent the original numerical values of the first data points, represent the corresponding importance weights, are the adjustment coefficients of the environmental factors, is the total number of data points, represent the weighted average values after combining the data importance and the environmental factors, which are used to evaluate the overall production quality and generate the production data analysis results; Using the production data analysis result, the key improvement link is identified, and a formula is used: ； wherein, is a pre-set quality benchmark, is a contribution weight of each point, generating an improved recognition result ; Based on the improvement identification result, the production parameter is adjusted, and a formula is used: ； wherein, Count is the number of data points labeled as improved, calculating the number of data points labeled as improved, the original parameters, adjusting the original parameters by a root function, matching the data set changes, and obtaining the production parameter adjustment result.

8. The intelligent management control system for high-speed rail gear box production according to claim 7, characterized in that: The obtaining step of the high-speed railway gearbox optimized production process guide is: According to the production parameter adjustment result, the production line resource is reconfigured, and a formula is used: ； wherein, is a new efficiency value of resource configuration, is an adjusted parameter, is an efficiency factor, the influence of which is enhanced by squaring to obtain a resource configuration result; Using the resource configuration result, the production scheduling scheme is optimized, and a formula is used: ； wherein, is the total scheduling cost, is the time cost of the i-th task, the configuration result is adjusted by squaring to enhance the influence of scheduling, is the time cost of the i-th task, the configuration result is adjusted by squaring to enhance the influence of scheduling, represents the total number of tasks, and an optimized scheduling scheme is obtained. Based on the optimized scheduling scheme, the production process is optimized, and the high-speed railway gearbox optimized production process guide is compiled.

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