A numerical control machine tool parameter optimization method and system based on data analysis
By analyzing and processing the historical operating data of CNC machine tools, and combining it with real-time order optimization solutions, the problem of CNC machine tools working under overload conditions was solved, extending their service life and reducing energy consumption.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 广州台茂精密机械有限公司
- Filing Date
- 2026-03-27
- Publication Date
- 2026-06-12
AI Technical Summary
In pursuit of producing orders in the shortest possible time, existing CNC machine tools are often overloaded for extended periods, which reduces their lifespan and increases energy consumption and costs.
By acquiring historical operating data of CNC machine tools, performing data preprocessing and feature analysis, identifying anomalies, and combining this with real-time orders to design optimization solutions, we can avoid overload operation, extend service life, and reduce energy consumption.
This has enabled the optimization of CNC machine tools, avoiding overload operation, extending service life, reducing energy consumption, and increasing profits.
Smart Images
Figure CN122194854A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of electrical data processing technology, specifically to a method and system for optimizing CNC machine tool parameters based on data analysis. Background Technology
[0002] A Computer Numerical Control (CNC) lathe is a lathe controlled by a computer, a highly efficient automated machine that automatically processes workpieces according to a pre-programmed numerical control program. CNC lathes are mainly used for cutting internal and external cylindrical surfaces, internal and external conical surfaces with arbitrary cone angles, complex rotating internal and external curved surfaces, and cylindrical and conical threads on shaft or disc-shaped parts. They can also perform grooving, drilling, reaming, boring, and other machining operations. The working principle of a CNC lathe is to compile the machining process route, process parameters, tool movement trajectory, displacement, cutting parameters, and auxiliary functions into a machining program sheet according to the instruction codes and program format specified by the CNC lathe. The contents of this program sheet are then recorded on a control medium and input into the CNC lathe's numerical control unit, thereby directing the lathe to process the parts.
[0003] In order to produce the products required by orders in the shortest possible time, existing CNC machine tools are often overloaded for long periods of time, which reduces their service life. Furthermore, prolonged overload operation leads to excessively high temperatures and abnormally increased energy consumption, which reduces profits and increases costs. Summary of the Invention
[0004] To address the aforementioned technical problems, this paper provides a method and system for optimizing CNC machine tool parameters based on data analysis. This technical solution solves the problem mentioned in the background that existing CNC machine tools, in pursuit of producing the required products for orders in the shortest possible time, are subjected to prolonged overload operation, which reduces their service life. Furthermore, prolonged overload operation leads to excessively high temperatures and abnormally increased energy consumption, thereby reducing profits and increasing costs.
[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for optimizing CNC machine tool parameters based on data analysis, comprising: Acquire historical operating data of CNC machine tools, perform data preprocessing on the historical operating data of CNC machine tools, and obtain complete historical operating data of CNC machine tools; Perform feature analysis on the complete historical operating data of CNC machine tools to determine whether there are any abnormal points in the equipment operating data; If there are no abnormal points in the equipment operation data, obtain the real-time orders of the CNC machine tools, analyze and process the real-time orders of the CNC machine tools, and determine the optimization plan for the CNC machine tools.
[0006] Preferably, the step of acquiring historical operating data of the CNC machine tool, performing data preprocessing on the historical operating data of the CNC machine tool, and acquiring complete historical operating data of the CNC machine tool specifically includes the following steps: The database system is used to read and process data to obtain a diagram of the equipment distribution inside the production plant. Data processing is performed on the equipment distribution diagram inside the production plant to determine the installation location of CNC machine tools; The database system is used to read and process data based on the installation location of the CNC machine tool to obtain the historical operating data of the CNC machine tool; Data analysis and processing are performed on the historical operating data of CNC machine tools to obtain complete historical operating data of CNC machine tools.
[0007] Preferably, the step of performing data analysis and processing on the historical operating data of the CNC machine tool to obtain complete historical operating data of the CNC machine tool specifically includes the following steps: The historical operating data of CNC machine tools are classified and processed based on data type to obtain historical data of CNC machine tools of different data types; By using heatmaps, historical data of CNC machine tools of different data types are traversed to determine the location and type of missing data values. The mean of the historical data of the remaining CNC machine tools of different data types is calculated according to the missing value type to obtain the missing position filling data; wherein, the missing value type is the same as the data type of the historical data of the CNC machine tools of different data types; Data is filled in based on missing locations to obtain complete historical operating data of CNC machine tools.
[0008] Preferably, the step of performing feature analysis on the complete historical operating data of the CNC machine tool to determine whether there are any abnormal points in the equipment operating data specifically includes the following steps: The complete historical operating data of CNC machine tools are read and processed based on equipment capacity and equipment energy consumption, respectively, to obtain the capacity data and energy consumption data of CNC machine tools; Data analysis and processing are performed on the production capacity data and energy consumption data of CNC machine tools to obtain curve approximation values; Comparative analysis of the curve approximation values is performed to determine whether there are any abnormal points in the equipment operation data.
[0009] Preferably, the step of performing data analysis and processing on the production capacity data and energy consumption data of the CNC machine tool to obtain the curve approximation value specifically includes the following steps: The production capacity data and energy consumption data of CNC machine tools are normalized separately to obtain normalized equipment production capacity data and normalized equipment energy consumption data. Construct a Cartesian coordinate system, and plot the normalized data of equipment capacity and normalized data of equipment energy consumption in the same Cartesian coordinate system to obtain the capacity curve and energy consumption curve of CNC machine tool. Distance calculations are performed on the production capacity curve and energy consumption curve of CNC machine tools to obtain the curve convergence value.
[0010] Preferably, the step of comparing and analyzing the curve convergence values to determine whether there are any abnormal points in the equipment operation data specifically includes the following steps: The system performs judgment and processing on the curve approach value and the set curve approach value threshold. If the curve approach value is greater than or equal to the set first curve approach value threshold, or the curve approach value is less than or equal to the set second curve approach value threshold, there is an abnormal point in the equipment operation data, an abnormality occurs inside the CNC machine tool, and CNC machine tool maintenance information is sent to the maintenance personnel's electronic equipment. If the curve approach value is less than the set first curve approach value threshold and the curve approach value is greater than the set second curve approach value threshold, there are no abnormal points in the equipment operation data, and the CNC machine tool is operating normally.
[0011] Preferably, the steps of obtaining real-time orders for CNC machine tools, analyzing and processing these orders, and determining the optimal solution for the CNC machine tools specifically include the following steps: The order platform is used to read and process data to obtain all order data to be processed. All order data to be processed is filtered based on time information to obtain real-time orders for CNC machine tools; The system reads and processes real-time orders from CNC machine tools to obtain the quantity of products to be processed. The quantity of products to be processed, equipment capacity, and equipment energy consumption are calculated and processed to obtain a set of order profit data. The profit data set of orders is adjusted based on the complete historical operating data of CNC machine tools to obtain the optimal profit for each order.
[0012] Preferably, the step of performing profit correction processing on the order profit data set based on the complete historical operating data of the CNC machine tool to obtain the optimal order profit specifically includes the following steps: Based on the maximum value function, the order profit data set is filtered to obtain the maximum profit of each order; The system reads and processes data on the maximum profit of an order to obtain the corresponding equipment capacity and energy consumption. The complete historical operating data of CNC machine tools is read and processed based on the equipment capacity and energy consumption corresponding to the maximum profit of the order, and the equipment temperature data corresponding to the maximum profit of the order is determined. By comparing and analyzing the equipment temperature data corresponding to the maximum profit of an order, the optimal profit for that order can be determined.
[0013] Preferably, the step of comparing and analyzing the equipment temperature data corresponding to the maximum profit of an order to determine the optimal profit specifically includes the following steps: The system performs judgment and processing on the equipment temperature data corresponding to the maximum profit of the order and the set equipment temperature data threshold. If the equipment temperature data corresponding to the maximum profit of an order is greater than or equal to the set equipment temperature data threshold, the CNC machine tool will be overloaded. Based on the maximum value function, the remaining data in the order profit data set will be reselected to determine the maximum profit of the order. Then, the maximum profit of the order will be analyzed and processed to determine the optimal profit of the order. If the equipment temperature data corresponding to the maximum profit of an order is less than the set equipment temperature data threshold, the CNC machine tool will operate normally, and the maximum profit of the order will be set as the optimal profit of the order.
[0014] Furthermore, a data analysis-based CNC machine tool parameter optimization system is proposed to implement the aforementioned data analysis-based CNC machine tool parameter optimization method, including: The intelligent analysis terminal is used to control various modules to perform data preprocessing, data normalization, curve plotting, curve analysis, and data comparison analysis on the historical operating data of the CNC machine tool, and to determine the optimization scheme of the CNC machine tool. The intelligent analysis terminal is also used to control the data transmission and information interaction between various modules. A database system for storing historical data of production equipment; The data preprocessing module is used to process the historical operating data of the CNC machine tool to obtain the complete historical operating data of the CNC machine tool; The data normalization processing module is used to normalize the production capacity data and energy consumption data of CNC machine tools to obtain normalized equipment production capacity data and normalized equipment energy consumption data. The curve plotting module plots curves in the same rectangular coordinate system based on the normalized data of equipment capacity and the normalized data of equipment energy consumption, thereby obtaining the capacity curve and energy consumption curve of the CNC machine tool. The curve analysis module is used to calculate and process the production capacity curve and energy consumption curve of the CNC machine tool to obtain the curve approximation value. The data analysis module is used to analyze the curve approximation values to determine whether there are any abnormal points in the operating data of the CNC machine tool. The optimization scheme design module is used to comprehensively analyze and process the real-time orders and complete historical operating data of CNC machine tools to determine the optimization scheme for CNC machine tools.
[0015] Compared with the prior art, the present invention provides a CNC machine tool optimization method and system based on multivariate data analysis, which has the following beneficial effects: This invention analyzes historical operating data of CNC machine tools to determine their production capacity and energy consumption data. By combining and analyzing these data, an optimization scheme for the CNC machine tool is designed to determine the optimal profit for orders. This approach avoids overloading the CNC machine tool and extends its service life. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating steps S100-S300 in a data analysis-based CNC machine tool parameter optimization method proposed in this invention. Figure 2 This is a structural block diagram of a CNC machine tool parameter optimization system based on data analysis proposed in this invention. Detailed Implementation
[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.
[0018] Reference Figure 1 As shown, a method for optimizing CNC machine tool parameters based on data analysis includes: S100: Obtain historical operating data of CNC machine tool, perform data preprocessing on historical operating data of CNC machine tool, and obtain complete historical operating data of CNC machine tool; S200: Perform feature analysis on the complete historical operating data of CNC machine tools to determine whether there are any abnormal points in the equipment operating data; S300. If there are no abnormal points in the equipment operation data, obtain the real-time orders of the CNC machine tool, analyze and process the real-time orders of the CNC machine tool, and determine the optimization plan for the CNC machine tool. Those skilled in the art will understand that the production capacity data and energy consumption data of CNC machine tools are a pair of related features. Therefore, by extracting and processing historical operating data of CNC machine tools to obtain their production capacity and energy consumption data, and analyzing the convergence values (i.e., curve convergence values) between them, it can be determined whether there are any abnormalities in the CNC machine tool. If no abnormalities are found, data analysis can be performed based on the relationship between the production capacity and energy consumption data to determine the optimal profit for the order. If abnormalities are found, the CNC machine tool can be repaired. This method not only determines the optimal profit for the order but also extends the service life of the CNC machine tool. Example
[0019] Step S100: Obtain historical operating data of the CNC machine tool. Preprocessing the historical operating data of the CNC machine tool to obtain complete historical operating data specifically includes the following steps: S101. Perform data reading and processing on the database system to obtain the equipment distribution diagram inside the production plant; S102. Read and process the equipment distribution diagram inside the production plant to determine the installation location of CNC machine tools; S103. Using the installation location of the CNC machine tool as a feature, perform data reading and processing on the database system to obtain the historical operating data of the CNC machine tool; S104. Perform data analysis and processing on the historical operating data of the CNC machine tool to obtain complete historical operating data of the CNC machine tool; It is understandable that a production plant will have many machines installed inside, and the data of these machines is stored in a database system according to their installation location. Therefore, when it is necessary to read the historical operating data of CNC machine tools, the installation location of the CNC machine tools must first be determined. Specifically, step S104, which involves analyzing and processing the historical operating data of the CNC machine tool to obtain complete historical operating data, includes the following steps: S1041. Classify and process the historical operating data of CNC machine tools based on data type to obtain historical data of CNC machine tools of different data types; S1042. By using heatmaps, perform data traversal processing on historical data of CNC machine tools of different data types to determine the location and type of missing data values; A heatmap uses special colors or markers to represent missing values, contrasting them with the colors of normal data. By observing the color distribution of the heatmap, patterns or areas of missing data can be identified. If some areas are more uniformly colored while other areas are more sparsely colored, it may mean that the latter have more missing data. S1043. Calculate the mean of the remaining historical data of CNC machine tools of different data types according to the missing value type, and obtain the missing position filling data; wherein, the missing value type is the same as the data type of the historical data of CNC machine tools of different data types; S1044. Fill in the missing data according to the missing position to obtain the complete historical operation data of the CNC machine tool. Example
[0020] Step S200: Perform feature analysis on the complete historical operating data of the CNC machine tool to determine whether there are any abnormal points in the equipment operating data. This specifically includes the following steps: S201. Read and process the complete historical operating data of the CNC machine tool based on the characteristics of equipment capacity and equipment energy consumption respectively, and obtain the capacity data and energy consumption data of the CNC machine tool. S202. Perform data analysis and processing on the production capacity data and energy consumption data of CNC machine tools to obtain curve approximation values; S203. Compare and analyze the curve approximation values to determine whether there are any abnormal points in the equipment operation data.
[0021] Specifically, step S202, which involves analyzing and processing the production capacity data and energy consumption data of the CNC machine tool to obtain the curve approximation value, includes the following steps: S2021. Perform data normalization processing on the production capacity data and energy consumption data of CNC machine tools respectively to obtain normalized equipment production capacity data and normalized equipment energy consumption data. S2022. Construct a rectangular coordinate system, and plot the normalized data of equipment capacity and normalized data of equipment energy consumption in the same rectangular coordinate system to obtain the capacity curve and energy consumption curve of the CNC machine tool. S2023. Perform distance calculation processing on the production capacity curve and energy consumption curve of CNC machine tool to obtain the curve approximation value; Step S203, which involves comparing and analyzing the curve convergence values to determine whether there are any abnormal points in the equipment operation data, specifically includes the following steps: S2031. Perform judgment and processing on the curve approach value and the set curve approach value threshold; S2032. If the curve approach value is greater than or equal to the set first curve approach value threshold, or the curve approach value is less than or equal to the set second curve approach value threshold, there is an abnormal point in the equipment operation data, and an abnormality occurs inside the CNC machine tool. The CNC machine tool maintenance information is sent to the electronic equipment of the maintenance personnel. S2033. If the curve approach value is less than the set first curve approach value threshold and the curve approach value is greater than the set second curve approach value threshold, there are no abnormal points in the equipment operation data, and the CNC machine tool is operating normally. It is understandable that the values between the production capacity data and the energy consumption data of CNC machine tools may differ too much, making it impossible to observe their correspondence in the same coordinate system. Therefore, through normalization calculation, the production capacity data and energy consumption data of CNC machine tools are limited to between 0 and 1. Then, the production capacity curve and the energy consumption curve of CNC machine tools are plotted, and the convergence between the two curves is analyzed to identify data outliers. Example
[0022] Step S300: Obtain real-time orders for CNC machine tools, analyze and process the real-time orders for CNC machine tools, and determine the optimization scheme for CNC machine tools. This specifically includes the following steps: S301. Perform data reading and processing on the order platform to obtain all order data to be processed; S302. Filter all order data to be processed based on time information to obtain real-time orders for CNC machine tools; S303: Read and process real-time orders from CNC machine tools to obtain the quantity of products to be processed; S304. Calculate and process the quantity of products to be processed, equipment capacity and equipment energy consumption to obtain a set of order profit data; It is understandable that a piece of equipment capacity data and a piece of equipment energy consumption data correspond to an order profit data. Therefore, when the equipment capacity data is changed, the equipment energy consumption data will change, and the order profit data will also change accordingly. S305. Based on the complete historical operating data of the CNC machine tool, perform profit correction processing on the order profit data set to obtain the optimal profit for the order.
[0023] Specifically, step S305, which involves performing profit correction processing on the order profit data set based on the complete historical operating data of the CNC machine tool to obtain the optimal order profit, includes the following steps: S3051. Based on the maximum value function, filter the order profit data set to obtain the maximum order profit; S3052. Perform data reading and processing on the maximum profit of an order to obtain the equipment capacity and energy consumption corresponding to the maximum profit of the order. S3053. Using the equipment capacity and energy consumption corresponding to the maximum profit of an order as characteristics, read and process the complete historical operating data of the CNC machine tool to determine the equipment temperature data corresponding to the maximum profit of the order. S3054. Compare and analyze the equipment temperature data corresponding to the maximum profit of the order to determine the optimal profit of the order.
[0024] Specifically, step S3054, which involves comparing and analyzing the equipment temperature data corresponding to the maximum profit of an order to determine the optimal profit, includes the following steps: S30541. Perform judgment and processing on the equipment temperature data corresponding to the maximum profit of the order and the set equipment temperature data threshold. S30542. If the equipment temperature data corresponding to the maximum profit of an order is greater than or equal to the set equipment temperature data threshold, the CNC machine tool will be overloaded. Based on the maximum value function, the remaining data in the order profit data set will be reselected to determine the maximum profit of the order. The maximum profit of the order will be analyzed and processed to determine the optimal profit of the order. S30543. If the equipment temperature data corresponding to the maximum profit of the order is less than the set equipment temperature data threshold, the CNC machine tool will operate normally, and the maximum profit of the order will be set as the optimal profit of the order. It is understandable that when equipment capacity is increased, energy consumption will also increase, and profits may decrease. However, there is a balance between equipment capacity and energy consumption, which allows the production of ordered products within a specified time with high profits. At the same time, the CNC machine tool will not be overloaded, thus extending its service life. Therefore, by combining temperature data analysis, the optimal profit can be determined. It should be noted that the optimal profit is not the maximum profit. The selection of the optimal profit is based on considerations of both protecting the CNC machine tool and reducing costs.
[0025] Reference Figure 2 As shown, a data analysis-based CNC machine tool parameter optimization system is used to implement the data analysis-based CNC machine tool parameter optimization method described above, including: The intelligent analysis terminal is used to control various modules to perform data preprocessing, data normalization, curve plotting, curve analysis, and data comparison analysis on the historical operating data of the CNC machine tool, and to determine the optimization scheme of the CNC machine tool. The intelligent analysis terminal is also used to control the data transmission and information interaction between various modules. A database system for storing historical data of production equipment; The data preprocessing module is used to process the historical operating data of the CNC machine tool to obtain the complete historical operating data of the CNC machine tool; The data normalization processing module is used to normalize the production capacity data and energy consumption data of CNC machine tools to obtain normalized equipment production capacity data and normalized equipment energy consumption data. The curve plotting module plots curves in the same rectangular coordinate system based on the normalized data of equipment capacity and the normalized data of equipment energy consumption, thereby obtaining the capacity curve and energy consumption curve of the CNC machine tool. The curve analysis module is used to calculate and process the production capacity curve and energy consumption curve of the CNC machine tool to obtain the curve approximation value. The data analysis module is used to analyze the curve approximation values to determine whether there are any abnormal points in the operating data of the CNC machine tool. The optimization scheme design module is used to comprehensively analyze and process the real-time orders and complete historical operating data of CNC machine tools to determine the optimization scheme for CNC machine tools.
[0026] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.
Claims
1. A method for optimizing CNC machine tool parameters based on data analysis, characterized in that, include: Acquire historical operating data of CNC machine tools, perform data preprocessing on the historical operating data of CNC machine tools, and obtain complete historical operating data of CNC machine tools; Perform feature analysis on the complete historical operating data of CNC machine tools to determine whether there are any abnormal points in the equipment operating data; If there are no abnormal points in the equipment operation data, obtain the real-time orders of the CNC machine tools, analyze and process the real-time orders of the CNC machine tools, and determine the optimization plan for the CNC machine tools.
2. The method for optimizing CNC machine tool parameters based on data analysis according to claim 1, characterized in that, The process of acquiring historical operating data of CNC machine tools, including data preprocessing of the historical operating data, and obtaining complete historical operating data of CNC machine tools, specifically includes the following steps: The database system is used to read and process data to obtain a diagram of the equipment distribution inside the production plant. Data processing is performed on the equipment distribution diagram inside the production plant to determine the installation location of CNC machine tools; The database system is used to read and process data based on the installation location of the CNC machine tool to obtain the historical operating data of the CNC machine tool; Data analysis and processing are performed on the historical operating data of CNC machine tools to obtain complete historical operating data of CNC machine tools.
3. The method for optimizing CNC machine tool parameters based on data analysis according to claim 2, characterized in that, The process of analyzing and processing historical operating data of CNC machine tools to obtain complete historical operating data specifically includes the following steps: The historical operating data of CNC machine tools are classified and processed based on data type to obtain historical data of CNC machine tools of different data types; By using heatmaps, historical data of CNC machine tools of different data types are traversed to determine the location and type of missing data values. The mean of the historical data of the remaining CNC machine tools of different data types is calculated according to the missing value type to obtain the missing position filling data; wherein, the missing value type is the same as the data type of the historical data of the CNC machine tools of different data types; Data is filled in based on missing locations to obtain complete historical operating data of CNC machine tools.
4. The method for optimizing CNC machine tool parameters based on data analysis according to claim 3, characterized in that, The process of performing feature analysis on the complete historical operating data of CNC machine tools to determine whether there are any abnormal points in the equipment operating data includes the following steps: The complete historical operating data of CNC machine tools are read and processed based on equipment capacity and equipment energy consumption, respectively, to obtain the capacity data and energy consumption data of CNC machine tools; Data analysis and processing are performed on the production capacity data and energy consumption data of CNC machine tools to obtain curve approximation values; Comparative analysis of the curve approximation values is performed to determine whether there are any abnormal points in the equipment operation data.
5. The method for optimizing CNC machine tool parameters based on data analysis according to claim 4, characterized in that, The process of analyzing and processing the production capacity data and energy consumption data of CNC machine tools to obtain the curve approximation value specifically includes the following steps: The production capacity data and energy consumption data of CNC machine tools are normalized separately to obtain normalized equipment production capacity data and normalized equipment energy consumption data. Construct a Cartesian coordinate system, and plot the normalized data of equipment capacity and normalized data of equipment energy consumption in the same Cartesian coordinate system to obtain the capacity curve and energy consumption curve of CNC machine tool. Distance calculations are performed on the production capacity curve and energy consumption curve of CNC machine tools to obtain the curve convergence value.
6. The method for optimizing CNC machine tool parameters based on data analysis according to claim 4, characterized in that, The process of comparing and analyzing the curve convergence values to determine whether there are any abnormal points in the equipment operation data includes the following steps: The system performs judgment and processing on the curve approach value and the set curve approach value threshold. If the curve approach value is greater than or equal to the set first curve approach value threshold, or the curve approach value is less than or equal to the set second curve approach value threshold, there is an abnormal point in the equipment operation data, an abnormality occurs inside the CNC machine tool, and CNC machine tool maintenance information is sent to the maintenance personnel's electronic equipment. If the curve approach value is less than the set first curve approach value threshold and the curve approach value is greater than the set second curve approach value threshold, there are no abnormal points in the equipment operation data, and the CNC machine tool is operating normally.
7. The method for optimizing CNC machine tool parameters based on data analysis according to claim 1, characterized in that, The process of obtaining real-time orders for CNC machine tools, analyzing and processing these orders, and determining the optimal solution for the CNC machine tools specifically includes the following steps: The order platform is used to read and process data to obtain all order data to be processed. All order data to be processed is filtered based on time information to obtain real-time orders for CNC machine tools; The system reads and processes real-time orders from CNC machine tools to obtain the quantity of products to be processed. The quantity of products to be processed, equipment capacity, and equipment energy consumption are calculated and processed to obtain a set of order profit data. The profit data set of orders is adjusted based on the complete historical operating data of CNC machine tools to obtain the optimal profit for each order.
8. The method for optimizing CNC machine tool parameters based on data analysis according to claim 7, characterized in that, The step of performing profit correction processing on the order profit data set based on the complete historical operating data of CNC machine tools to obtain the optimal order profit includes the following steps: Based on the maximum value function, the order profit data set is filtered to obtain the maximum profit of each order; The system reads and processes data on the maximum profit of an order to obtain the corresponding equipment capacity and energy consumption. The complete historical operating data of CNC machine tools is read and processed based on the equipment capacity and energy consumption corresponding to the maximum profit of the order, and the equipment temperature data corresponding to the maximum profit of the order is determined. By comparing and analyzing the equipment temperature data corresponding to the maximum profit of an order, the optimal profit for that order can be determined.
9. The method for optimizing CNC machine tool parameters based on data analysis according to claim 8, characterized in that, The process of comparing and analyzing the equipment temperature data corresponding to the maximum profit of an order to determine the optimal profit specifically includes the following steps: The system performs judgment and processing on the equipment temperature data corresponding to the maximum profit of the order and the set equipment temperature data threshold. If the equipment temperature data corresponding to the maximum profit of an order is greater than or equal to the set equipment temperature data threshold, the CNC machine tool will be overloaded. Based on the maximum value function, the remaining data in the order profit data set will be reselected to determine the maximum profit of the order. Then, the maximum profit of the order will be analyzed and processed to determine the optimal profit of the order. If the equipment temperature data corresponding to the maximum profit of an order is less than the set equipment temperature data threshold, the CNC machine tool will operate normally, and the maximum profit of the order will be set as the optimal profit of the order.
10. A CNC machine tool parameter optimization system based on data analysis, used to implement the CNC machine tool parameter optimization method based on data analysis as described in any one of claims 1-9, characterized in that, include: The intelligent analysis terminal is used to control various modules to perform data preprocessing, data normalization, curve plotting, curve analysis, and data comparison analysis on the historical operating data of the CNC machine tool, and to determine the optimization scheme of the CNC machine tool. The intelligent analysis terminal is also used to control the data transmission and information interaction between various modules. A database system for storing historical data of production equipment; The data preprocessing module is used to process the historical operating data of the CNC machine tool to obtain the complete historical operating data of the CNC machine tool; The data normalization processing module is used to normalize the production capacity data and energy consumption data of CNC machine tools to obtain normalized equipment production capacity data and normalized equipment energy consumption data. The curve plotting module plots curves in the same rectangular coordinate system based on the normalized data of equipment capacity and the normalized data of equipment energy consumption, thereby obtaining the capacity curve and energy consumption curve of the CNC machine tool. The curve analysis module is used to calculate and process the production capacity curve and energy consumption curve of the CNC machine tool to obtain the curve approximation value. The data analysis module is used to analyze the curve approximation values to determine whether there are any abnormal points in the operating data of the CNC machine tool. The optimization scheme design module is used to comprehensively analyze and process the real-time orders and complete historical operating data of CNC machine tools to determine the optimization scheme for CNC machine tools.