Machining simulation optimization system for numerical control machine tool
Through the machining simulation optimization system for CNC machine tools, the problem of difficulty in comprehensively comparing and evaluating different machining strategies in traditional technology is solved, and the machining strategy optimization of CNC machine tools is achieved, processing efficiency and quality is improved, and production costs and risks are reduced.
Patent Information
- Application Number
- CN202411353831.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-27
- Publication Date
- 2024-12-10
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Traditional machining simulation technology is difficult to compare and evaluate the comprehensive effects of different machining strategies, and fails to fully consider the specific requirements of actual production tasks, such as production quantity and time constraints, resulting in a large deviation between the simulation results and the actual production situation.
A machining simulation optimization system for CNC machine tools was designed, including CNC machine tool machining simulation module, machining simulation pre-selected module, machining simulation limited module and machining simulation optimization module. By building machining simulation models, simulation processing testing and analysis, comprehensive selection was selected Pre-selected processing strategies with better comprehensive results, and secondary simulation and analysis are carried out based on actual production tasks, and the most suitable processing strategies are optimized and selected.
The three-dimensional analysis and evaluation of different processing simulation strategies was realized, and the pre-selected processing strategy with better comprehensive results was selected, and the processing strategy that was most suitable for actual production tasks was selected through in-depth analysis and optimization, which improved the processing efficiency and quality and reduced the Production costs and risks.
Smart Images
Figure CN119105407A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of machining simulation, and more specifically, to a machining simulation optimization system for numerically controlled machine tools. Background Art
[0002] With the rapid development of the manufacturing industry, CNC machine tools, as one of the core equipment of modern manufacturing, have a direct relationship between their processing efficiency and quality and the production benefits and market competitiveness of enterprises. However, in actual production, the processing of CNC machine tools is affected by many factors, such as material properties, tool wear, machine tool accuracy, etc. These factors often make the processing results difficult to predict and control. In order to improve the processing efficiency and quality of CNC machine tools and reduce production costs and risks, processing simulation technology came into being.
[0003] Traditional machining simulation technology mainly focuses on the simulation analysis of a single machining strategy or machining parameters, and lacks the comparison and evaluation of the comprehensive effects of different machining strategies. In addition, traditional machining simulation systems often fail to fully consider the specific requirements of actual production tasks, such as production quantity, production time and other constraints, resulting in a large deviation between simulation results and actual production conditions. Summary of the invention
[0004] In view of the deficiencies in the prior art, the present invention aims to provide a machining simulation optimization system for CNC machine tools.
[0005] To achieve the above object, the present invention provides the following technical solutions:
[0006] A machining simulation optimization system for CNC machine tools, comprising a CNC machine tool machining simulation module, a machining simulation preselection module, a machining simulation limitation module, and a machining simulation optimization module;
[0007] The CNC machine tool processing simulation module: sets the process parameters of the CNC machine tool, obtains the initial parameters of the product to be processed and the product requirement parameters, inputs the above parameters into the simulation software, builds the CNC machine tool processing simulation model, and the CNC machine tool processing simulation model generates different processing simulation strategies;
[0008] The processing simulation pre-selection module is used to obtain the simulation re-division value of each processing simulation strategy, and determine whether to mark the processing simulation strategy as the pre-selected processing strategy based on the comparison result between the simulation re-division value and the simulation re-division threshold value;
[0009] The processing simulation limitation module: obtains the production task of the CNC machine tool, the production task includes the production quantity and the production time, limits the production quantity and the production time of the production task in the CNC machine tool processing simulation model, and executes the production task using the pre-selected processing strategy;
[0010] The processing simulation optimization module obtains the task optimization execution value of each pre-selected processing strategy, marks the pre-selected processing strategy with the largest task optimization execution value as the optimized processing strategy, and uses the optimized processing strategy to actually process the production task of the CNC machine tool.
[0011] Furthermore, based on the comparison result between the simulation re-division value and the simulation re-division boundary value, it is determined whether to mark the processing simulation strategy as the pre-selected processing strategy. Specifically, after each processing simulation strategy is used to simulate the processing of the product to be processed, the simulation re-division value of the processing simulation strategy is obtained, and the simulation re-division boundary value is set. When the simulation re-division value of the processing simulation strategy is greater than or equal to the simulation re-division boundary value, the processing simulation strategy is marked as the pre-selected processing strategy. When the simulation re-division value of the processing simulation strategy is less than the simulation re-division boundary value, no corresponding processing is performed.
[0012] Furthermore, the simulation complex value of the processing simulation strategy is obtained by the following steps: obtaining the processing simulation process value Semb and the processing simulation result value Redg, and using the formula The simulation complex value Eptb of the processing simulation strategy is obtained, where i 1 is the process coefficient and i 2 is the result coefficient.
[0013] Furthermore, the machining simulation process value is obtained through the following steps: when using the machining simulation strategy to simulate the machining of the product to be processed, the machining simulation index is obtained in real time. After the machining simulation is completed, a rectangular coordinate system is constructed with the machining simulation index as the X-axis and the machining simulation time as the Y-axis. All machining simulation indices in the machining simulation strategy are plotted in the rectangular coordinate system to obtain the machining simulation curve. The two ends of the machining simulation curve are perpendicular to the X-axis. The machining simulation curve, the two perpendicular lines and the X-axis form a closed figure. The total area of the closed figure is marked as the machining simulation process value.
[0014] Furthermore, the processing simulation index is obtained through the following steps: collecting various types of processing monitoring data at the same time, combining the various types of processing monitoring data in the form of a data set to obtain a monitoring data set, obtaining a processing monitoring model, inputting the detection data set into the processing monitoring model, and outputting the processing monitoring model to obtain a processing simulation index.
[0015] Furthermore, the processing simulation result value is obtained through the following steps: after the simulation processing is completed, a processed product is obtained, various basic parameters of the processed product are obtained, various basic parameters are combined in the form of a data set to obtain a basic parameter set, a parameter analysis model is obtained, the basic parameters are input into the parameter analysis model, and the parameter analysis model outputs the processing simulation result value.
[0016] Furthermore, the task optimization execution value of the pre-selected processing strategy is obtained by the following method: the pre-selected processing strategy is used to execute the production task. When each product to be processed in the production task is processed, a task execution log is generated. The task execution log includes the processing completion time, the processing simulation result value, and the processing simulation process value. When the production task is completed, all task execution logs are sorted in the chronological order of the processing completion time to obtain the result floating quantity Tsyg, the process continuous over-bound quantity Kdsp, and the completion gap quantity Szxb. The formula is used The task optimization execution value Btd of the preselected processing strategy is obtained, where h1 is the floating coefficient, h2 is the over-boundary coefficient, and h3 is the gap coefficient.
[0017] Furthermore, the result floating quantity Tsyg is obtained through the following steps: the processing simulation result values of the two adjacent task execution logs after sorting are differenced and the absolute value is taken to obtain the processing result floating value, and the processing result floating boundary value is set. When the processing result floating value is greater than or equal to the processing result floating boundary value, the result floating quantity is increased by one. When the processing result floating value is less than the processing result floating boundary value, no corresponding processing is performed, and the result floating quantity is marked as Tsyg.
[0018] Furthermore, the number of process duration exceeding the limit Kdsp is obtained through the following steps: summing the processing simulation process values of the two adjacent task execution logs after sorting to obtain the processing process duration value, setting the processing process duration limit value, and when the processing process duration value is greater than or equal to the processing process duration limit value, increasing the number of process duration exceeding the limit by one; when the processing process duration value is less than the processing process duration limit value, no corresponding processing is performed, and the number of process duration exceeding the limit is marked as Kdsp.
[0019] Furthermore, the completion gap quantity Szxb is obtained by the following steps: the time difference between two adjacent processing completion times after sorting is calculated to obtain the completion interval, all the completion intervals are matched into a group, the difference between the two completion intervals in the same group is calculated and the absolute value is taken to obtain the completion interval difference, and the completion interval threshold difference is set. When the completion interval difference is greater than or equal to the completion interval threshold difference, the completion gap quantity is increased by one, and when the completion interval difference is less than the completion interval threshold difference, no corresponding processing is performed, and the completion gap quantity is marked as Szxb.
[0020] Compared with the prior art, the present invention has the following beneficial effects:
[0021] 1. Set up a CNC machine tool processing simulation module and a processing simulation pre-selection module. By building a CNC machine tool processing simulation model, different processing simulation strategies can be simulated and tested through the processing simulation model. The simulation processing strategy can be analyzed and evaluated three-dimensionally from the two directions of simulation processing process and simulation processing results, and the pre-selected processing strategy with the best comprehensive effect can be comprehensively selected;
[0022] 2. Set up a processing simulation limitation module and a processing simulation optimization module, and perform secondary simulation and analysis on each pre-selected processing strategy according to the actual production task, deeply analyze the performance of the pre-selected processing strategy in executing the actual production task, and optimize and select the processing strategy that best suits the actual production task for actual processing. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] Figure 1 It is a system operation flow chart of a machining simulation optimization system for CNC machine tools;
[0024] Figure 2 Flow chart for obtaining process values of machining simulation;
[0025] Figure 3 This is a module diagram of a machining simulation optimization system for CNC machine tools. DETAILED DESCRIPTION
[0026] Reference Figures 1 to 3 A processing simulation optimization system for CNC machine tools includes a CNC machine tool processing simulation module, a processing simulation preselection module, a processing simulation limitation module, and a processing simulation optimization module.
[0027] CNC machine tool processing simulation module: set the process parameters of the CNC machine tool, which include but are not limited to the cutting speed range, tool selection range, and cutting angle range, obtain the initial parameters of the product to be processed (the initial parameters are the material parameters, shape parameters, etc. of the product to be processed in the unprocessed state) and the product requirement parameters (the product requirement parameters are the expected requirements of the product to be processed after the processing is completed, including but not limited to the geometric shape, dimensional accuracy, and surface quality of the product to be processed), input the above parameters into the simulation software, the simulation software includes but is not limited to ANSYS, Mastercam, SolidCAM, build a CNC machine tool processing simulation model, and the CNC machine tool processing simulation model generates different processing simulation strategies.
[0028] Processing simulation pre-selection module: After each processing simulation strategy is used to simulate the processing of the product to be processed, the simulation re-division value of the processing simulation strategy is obtained. The difference between different processing simulation strategies lies in the different settings of processing paths and processing parameters. The simulation re-division threshold is set, and the simulation re-division threshold is set. When the simulation re-division value of the processing simulation strategy is greater than or equal to the simulation re-division threshold, the processing simulation strategy is marked as the pre-selected processing strategy. When the simulation re-division value of the processing simulation strategy is less than the simulation re-division threshold, no corresponding processing is performed.
[0029] The simulation complex value of the machining simulation strategy is obtained by the following steps: obtain the machining simulation process value Semb and the machining simulation result value Redg, and use the formula The simulation complex value Eptb of the processing simulation strategy is obtained, where i1 is the process coefficient, i2 is the result coefficient, the value of i1 is 2.52, and the value of i2 is 1.36.
[0030] The machining simulation process value is obtained through the following steps: when using the machining simulation strategy to simulate the machining of the product to be processed, the machining simulation index is obtained in real time. After the machining simulation is completed, a rectangular coordinate system is constructed with the machining simulation index as the X-axis and the machining simulation time as the Y-axis. All machining simulation indexes in the machining simulation strategy are plotted in the rectangular coordinate system to obtain a machining simulation curve. All machining simulation indexes are continuous, and a curve can be obtained by continuous machining simulation indexes. The curve is the machining simulation curve. Draw perpendicular lines from both ends of the machining simulation curve to the X-axis. The machining simulation curve, the two perpendicular lines and the X-axis form a closed figure. The total area of the closed figure is marked as the machining simulation process value.
[0031] The processing simulation index is obtained through the following steps: collecting various types of processing monitoring data at the same time, the types of processing monitoring data include but are not limited to tool status data, cutting temperature data, and machine tool vibration data, combining various types of processing monitoring data in the form of a data set to obtain a monitoring data set, obtaining a processing monitoring model, inputting the detection data set into the processing monitoring model, and outputting the processing monitoring model to obtain a processing simulation index.
[0032] The processing monitoring model is constructed as follows: multiple monitoring data sets are collected, a deep learning model is constructed, and the monitoring data sets are used as training data for the deep learning model. A processing simulation index is assigned to each training data. The value of the processing simulation index is greater than zero. The closer the processing simulation index is to zero, the fewer unfavorable factors there are in the processing at the current time. The larger the processing simulation index is, the more unfavorable factors there are in the processing at the current time, such as machine tool vibration, high tool wear rate and other factors. The training data is divided into 60% training set and 40% validation set. The training set and validation set are iteratively trained. After the training is completed, the processing monitoring model is obtained.
[0033] The processing simulation result value is obtained through the following steps: after the simulation processing is completed, a processed product is obtained, and various basic parameters of the processed product are obtained. The types of basic parameters include but are not limited to geometric dimension parameters, surface quality parameters, and material performance parameters. Various basic parameters are combined in the form of a data set to obtain a basic parameter set, and a parameter analysis model is obtained. The basic parameters are input into the parameter analysis model, and the parameter analysis model outputs the processing simulation result value.
[0034] The parameter analysis model is constructed as follows: multiple basic parameter sets are collected to construct a deep learning model. The basic parameter sets are used as training data for the deep learning model. A processing simulation result value is assigned to each training data. The value range of the processing simulation result value is (0-5). The closer the processing simulation result value is to 5, the less the processing quality of the processed product meets the standard. The closer the processing simulation result value is to 0, the more the processing quality of the processed product meets the standard. The training data is divided into 80% training set and 20% validation set. The training set and the validation set are iteratively trained. After the training is completed, the parameter analysis model is obtained.
[0035] A CNC machine tool processing simulation module and a processing simulation pre-selection module are set up. By constructing a processing simulation model of a CNC machine tool, different processing simulation strategies can be simulated and tested through the processing simulation model. The simulation processing strategies can be three-dimensionally analyzed and evaluated from two directions: the simulation processing process and the simulation processing results, and the pre-selected processing strategies with better comprehensive effects can be comprehensively selected.
[0036] Processing simulation limitation module: obtain the production task of the CNC machine tool. The production task is the total number of products to be processed that need to be produced in the next period of time. The production task includes the production quantity and production time. The production quantity and production time of the production task are limited in the CNC machine tool processing simulation model, and the pre-selected processing strategy is used to execute the production task.
[0037] Processing simulation optimization module: obtain the task optimization execution value of each pre-selected processing strategy, mark the pre-selected processing strategy with the largest task optimization execution value as the optimized processing strategy, and use the optimized processing strategy to actually process the production task of the CNC machine tool.
[0038] The task optimization execution value of the pre-selected processing strategy is obtained in the following way: the pre-selected processing strategy is used to execute the production task. When each product to be processed in the production task is processed, a task execution log is generated. The task execution log includes the processing completion time (the corresponding time when the product to be processed completes the processing), the processing simulation result value (the processing simulation result value corresponding to the product to be processed), and the processing simulation process value (the processing simulation process value corresponding to the product to be processed during the processing). When the production task is completed, all task execution logs are sorted in the chronological order of the processing completion time, and the difference between the processing simulation result values of the two adjacent task execution logs after sorting is calculated and the absolute value is taken to obtain the processing result floating value, and the processing result floating boundary value is set. The processing result floating boundary value is the set threshold value. When the processing result floating value is greater than or equal to the processing result floating boundary value, the result floating quantity is increased by one. When the processing result floating value is less than the processing result floating boundary value, no corresponding processing is performed, and the result floating quantity is marked as Tsyg. The processing simulation process values of the execution log are summed to obtain the processing duration value, and the processing duration boundary value is set. The processing duration boundary value is the set threshold value. When the processing duration value is greater than or equal to the processing duration boundary value, the process duration exceeding the boundary number is increased by one. When the processing duration value is less than the processing duration boundary value, no corresponding processing is performed. The process duration exceeding the boundary number is marked as Kdsp. The time difference between the two adjacent processing completion times after sorting is calculated (the time difference between the processing completion time of the latter task execution log and the processing completion time of the previous task execution log is calculated) to obtain the completion interval. All completion intervals are matched into a group in pairs, and the difference between the two completion intervals in the same group is calculated and the absolute value is taken to obtain the completion interval difference. The completion interval threshold difference is set. The completion interval threshold difference is the set threshold value. When the completion interval difference is greater than or equal to the completion interval threshold difference, the completion gap number is increased by one. When the completion interval difference is less than the completion interval threshold difference, no corresponding processing is performed. The completion gap number is marked as Szxb. Using the formula The task optimization execution value Btd of the preselected processing strategy is obtained, where h1 is the floating coefficient, h2 is the over-bound coefficient, and h3 is the gap coefficient. The value of h1 is 1.27, the value of h2 is 1.42, and the value of h3 is 1.71.
[0039] By setting up a processing simulation limitation module and a processing simulation optimization module, each pre-selected processing strategy can be simulated and analyzed again according to the actual production task, and the performance of the pre-selected processing strategy in executing the actual production task can be deeply analyzed, so as to optimize and select the processing strategy that best suits the actual production task for actual processing.
[0040] The above formulas are all dimensionless and numerical calculations are performed, and the preset parameters in the formulas are set by technicians in this field according to actual conditions.
[0041] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.
[0042] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
[0043] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.
[0044] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.
[0045] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.
[0046] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.
[0047] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
Claims
1. A machining simulation optimization system for CNC machine tools, characterized in that: It includes CNC machine tool processing simulation module, processing simulation pre-selection module, processing simulation limitation module and processing simulation optimization module; The CNC machine tool processing simulation module: sets the process parameters of the CNC machine tool, obtains the initial parameters of the product to be processed and the product requirement parameters, inputs the above parameters into the simulation software, builds the CNC machine tool processing simulation model, and the CNC machine tool processing simulation model generates different processing simulation strategies; The processing simulation pre-selection module is used to obtain the simulation re-division value of each processing simulation strategy, and determine whether to mark the processing simulation strategy as the pre-selected processing strategy based on the comparison result between the simulation re-division value and the simulation re-division threshold value; The processing simulation limitation module: obtains the production task of the CNC machine tool, the production task includes the production quantity and the production time, limits the production quantity and the production time of the production task in the CNC machine tool processing simulation model, and executes the production task using the pre-selected processing strategy; The processing simulation optimization module obtains the task optimization execution value of each pre-selected processing strategy, marks the pre-selected processing strategy with the largest task optimization execution value as the optimized processing strategy, and uses the optimized processing strategy to actually process the production task of the CNC machine tool.
2. A processing simulation optimization system for CNC machine tools according to claim 1, characterized in that: Based on the comparison result between the simulation re-division value and the simulation re-division boundary value, determine whether to mark the processing simulation strategy as the pre-selected processing strategy. Specifically, after each processing simulation strategy is used to simulate the product to be processed, the simulation re-division value of the processing simulation strategy is obtained, and the simulation re-division boundary value is set. When the simulation re-division value of the processing simulation strategy is greater than or equal to the simulation re-division boundary value, the processing simulation strategy is marked as the pre-selected processing strategy. When the simulation re-division value of the processing simulation strategy is less than the simulation re-division boundary value, no corresponding processing is performed.
3. A processing simulation optimization system for CNC machine tools according to claim 2, characterized in that: The simulation complex value of the machining simulation strategy is obtained by the following steps: obtain the machining simulation process value Semb and the machining simulation result value Redg, and use the formula The simulation complex value Eptb of the processing simulation strategy is obtained, where i1 is the process coefficient and i2 is the result coefficient.
4. A processing simulation optimization system for CNC machine tools according to claim 3, characterized in that: The machining simulation process value is obtained through the following steps: when using the machining simulation strategy to simulate the machining of the product to be processed, the machining simulation index is obtained in real time. After the machining simulation is completed, a rectangular coordinate system is constructed with the machining simulation index as the X-axis and the machining simulation time as the Y-axis. All machining simulation indexes in the machining simulation strategy are plotted in the rectangular coordinate system to obtain the machining simulation curve. The two ends of the machining simulation curve are perpendicular to the X-axis. The machining simulation curve, the two perpendicular lines and the X-axis form a closed figure. The total area of the closed figure is marked as the machining simulation process value.
5. A processing simulation optimization system for CNC machine tools according to claim 4, characterized in that: The processing simulation index is obtained through the following steps: collecting various types of processing monitoring data at the same time, combining various types of processing monitoring data in the form of a data set to obtain a monitoring data set, obtaining a processing monitoring model, inputting the detection data set into the processing monitoring model, and outputting the processing monitoring model to obtain the processing simulation index.
6. The processing simulation optimization system for CNC machine tools according to claim 3 is characterized in that: The processing simulation result value is obtained through the following steps: after the simulation processing is completed, a processed product is obtained, various basic parameters of the processed product are obtained, various basic parameters are combined in the form of a data set to obtain a basic parameter set, a parameter analysis model is obtained, the basic parameters are input into the parameter analysis model, and the parameter analysis model outputs the processing simulation result value.
7. The processing simulation optimization system for CNC machine tools according to claim 1, characterized in that: The task optimization execution value of the pre-selected processing strategy is obtained in the following way: use the pre-selected processing strategy to execute the production task. When each product to be processed in the production task is processed, a task execution log is generated. The task execution log includes the processing completion time, the processing simulation result value, and the processing simulation process value. When the production task is completed, all task execution logs are sorted in the order of the processing completion time to obtain the result floating quantity Tsyg, the process continuous over-bound quantity Kdsp, and the completion gap quantity Szxb. Use the formula The task optimization execution value Btd of the preselected processing strategy is obtained, where h1 is the floating coefficient, h2 is the over-boundary coefficient, and h3 is the gap coefficient.
8. The processing simulation optimization system for CNC machine tools according to claim 7, characterized in that: The result floating quantity Tsyg is obtained through the following steps: the difference between the processing simulation result values of the two adjacent task execution logs after sorting is calculated and the absolute value is taken to obtain the processing result floating value, and the processing result floating boundary value is set. When the processing result floating value is greater than or equal to the processing result floating boundary value, the result floating quantity is increased by one. When the processing result floating value is less than the processing result floating boundary value, no corresponding processing is performed, and the result floating quantity is marked as Tsyg.
9. The processing simulation optimization system for CNC machine tools according to claim 7, characterized in that: The process duration exceeding the limit number Kdsp is obtained by the following steps: summing up the processing simulation process values of the two adjacent task execution logs after sorting to obtain the processing process duration value, setting the processing process duration limit value, and when the processing process duration value is greater than or equal to the processing process duration limit value, increasing the process duration exceeding the limit number by one; when the processing process duration value is less than the processing process duration limit value, no corresponding processing is performed, and the process duration exceeding the limit number is marked as Kdsp.
10. The processing simulation optimization system for CNC machine tools according to claim 7, characterized in that: The completion gap quantity Szxb is obtained by the following steps: the time difference between two adjacent processing completion times after sorting is calculated to obtain the completion interval, all the completion intervals are matched into a group, the difference between the two completion intervals in the same group is calculated and the absolute value is taken to obtain the completion interval difference, and the completion interval threshold difference is set. When the completion interval difference is greater than or equal to the completion interval threshold difference, the completion gap quantity is increased by one. When the completion interval difference is less than the completion interval threshold difference, no corresponding processing is performed and the completion gap quantity is marked as Szxb.