Cutting process parameter optimization method, system, computer equipment and storage medium

Abstract

The present invention provides a cutting process parameter optimization method, system, computer equipment and storage medium, wherein the cutting process parameter optimization method comprises the following steps: obtaining an original processing program of a processing device; replacing the original data of each process parameter in the original processing program with a corresponding macro variable and updating it to an optimized processing program; using the original data of each process parameter as initial processing data, optimizing the initial processing data and obtaining optimized data; assigning each optimized data to the corresponding macro variable in the optimized processing program and processing a workpiece to obtain a processed product; and determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data during the processing of the workpiece by the optimized processing program meets the constraint conditions.

Description

Technical Field

[0001] The present invention relates to the field of mechanical processing, and in particular to a cutting process parameter optimization method, system, computer equipment and storage medium. Background Art

[0002] With the development of society, the degree of automation is getting higher and higher. CNC lathes have become the main choice for mechanical processing with their automated and refined processing methods. In the field of CNC processing, how to optimize the processing parameters to achieve the best processing efficiency is a problem that needs to be solved in the industry. At present, there are mainly the following solutions in the industry:

[0003] 1. Based on CAD drawings, workpiece parameters, tool parameters, etc., use or develop software similar to CAM (computer-aided manufacturing), and recommend NC (Numerical Control) programs based on the software, which contain relatively reasonable process parameters and are supplemented by various processing technology optimization methods. This method requires CAD drawings or three-dimensional models, as well as a large number of workpiece parameters, tool parameters, etc. to determine the parameters of the processing technology, and can only give a recommended processing program. Professional technicians are still required to further modify and test the tool according to the actual situation, and further optimize the process parameters in the program manually, and can only use the most primitive modification method to directly modify the parameter values.

[0004] 2. Based on machine tools, cutting tools, materials, cutting parameter database or establishing a cutting process parameter management system; using this as a process parameter optimization recommendation requires a more comprehensive database and recommendation model, and the parameters are more accurate. It requires a large amount of parameter information, which is difficult to implement, and it is a one-time recommendation, which cannot guarantee comprehensive consideration and further optimization. Although the recommended process parameters are better than method 1, the modification methods for the recommended machining procedures and process parameters are mostly manual operation of the machine tool modification program, and the modification program is complicated.

[0005] 3. Intelligent Cloud Technology's iSESOLBOX (intelligent magic box) product optimizes the processing parameters by modifying the PLC (programmable logic controller) program and NC program. However, this system divides each processing segment of the NC program into optimized segments and non-optimized segments, adds many sub-programs, and makes the modification complex and difficult to operate. It requires high professional skills and a long modification time.

[0006] Based on the complexity of the existing metal cutting process that relies on CAM software to compile NC programs, it is difficult to adapt the recommended process parameters well, resulting in poor optimization effects. The above problems need to be solved urgently. Summary of the invention

[0007] In order to solve the problems existing in the background technology, in a first aspect, the present invention provides a cutting process parameter optimization method, which comprises the following steps:

[0008] Obtain the original processing program of the processing equipment;

[0009] Replacing the original data of each process parameter in the original processing program with the corresponding macro variables and updating the optimized processing program;

[0010] Using original data of each process parameter as initial processing data, optimizing the initial processing data and obtaining optimized data;

[0011] Assigning each optimized data to the corresponding macro variable in the optimized processing program and processing the workpiece to obtain a processed product;

[0012] Whether to terminate the optimization is determined based on the quality of the processed product and whether the equipment operation data when the workpiece is processed by the optimized processing program meets the constraint conditions.

[0013] Furthermore, the optimization model used to optimize the initial processing data is:

[0014]

[0015] Among them, FV i To optimize the feed, FV i-1 To optimize forward feed, SV i For optimized speed, SV i-1 is the speed before optimization, r is the feed optimization amplitude, c is the speed optimization amplitude, fro is the feed ratio, and sro is the speed ratio.

[0016] Furthermore, let the current optimization times be Wi, then the last optimization times be Wi-1, where i is an integer greater than or equal to 1;

[0017] Determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions includes the following steps:

[0018] Get the W i The quality of the processed product after the first processing and the W i The equipment operation data during the first processing;

[0019] Determine whether the quality of the processed product of the workpiece and / or the equipment operation data meets the constraint conditions:

[0020] If, the W i The quality of the processed product after the second processing and / or the W iThe equipment operation data does not meet the constraint conditions during the second processing, and the W i-1 The quality of the processed product after the first processing and the W i-1 When the equipment operation data meets the constraint conditions during the first processing, the optimization ends and the W i-1 The optimized data corresponding to this time is taken as the optimization result;

[0021] If, the W i The quality of the processed product after the first processing and the W i When the equipment operation data meets the constraint conditions during the first processing, the W i The optimization data obtained this time is used as the basis for continued optimization.

[0022] Furthermore, the current number of optimizations is set to W. i , then the number of optimizations last time is W i-1 , where i is an integer greater than or equal to 1;

[0023] Determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions includes the following steps:

[0024] Get the W i The quality of the processed product after the first processing and the W i The equipment operation data during the first processing;

[0025] Determine the W i Whether the quality of the secondary processed products meets the constraints;

[0026] If it meets the requirement, then the W i Whether the equipment operation data meets the constraints during the first processing;

[0027] If not, the optimization is terminated; and the W i-1 The optimization parameters thus obtained are taken as optimization results;

[0028] If it meets the requirements, continue to optimize;

[0029] If not, determine whether the processed product is a product that can be further optimized;

[0030] If yes, then continue the optimization after determining the parameters to be optimized based on the product processing quality;

[0031] If not, output and save W i-1 The optimization data is saved and this optimization is recorded as invalid.

[0032] Furthermore, the constraint conditions include a product quality constraint range and an equipment parameter constraint range, wherein the method for determining the equipment parameter constraint range includes the steps of:

[0033] Run the machining program according to the initial machining parameters to process the workpiece and obtain the equipment operation parameters;

[0034] The device parameter constraint range is generated according to the device operating parameters.

[0035] Furthermore, the constraint condition is:

[0036]

[0037]

[0038] Among them, SV min Set the minimum value, SV, for the speed max Set the maximum value for the speed; FV min Set minimum value, FV, for feed max is the minimum value for feed setting; P is the actual collected process power, P x- is the lower limit of the classification power, x is the optimization level, which can be 1, 2 or 3; P x+ is the upper limit of the classification power, x is the optimization level, which can be 1, 2 or 3; Q is the product quality measured by the optimized processing, Q - is the lower boundary of product quality requirements, Q + It is the upper boundary of product quality requirements.

[0039] In a second aspect, the present invention provides a cutting process parameter optimization system for implementing the above-mentioned cutting process parameter optimization method, wherein the cutting process parameter optimization system comprises:

[0040] A communication module, used to obtain a processing program and equipment operation data of a processing device, and extract initial processing parameters in the processing program;

[0041] A processing module, used for replacing the original data of each process parameter in the original processing program with the corresponding macro variable, and updating it into an optimized processing program;

[0042] An optimization module, used for optimizing the initial processing data and obtaining optimized data;

[0043] An execution module assigns the optimized data to the corresponding macro variables in the optimized processing program, and executes the optimized processing program to process the workpiece to obtain a processed product;

[0044] The judgment module is used to judge whether the quality of the processed product obtained by using the data after each optimization and the equipment operation data when the optimized processing program processes the workpiece meet the constraint conditions, and determine whether to end the optimization.

[0045] In a third aspect, the present invention further provides a computer device, comprising: a processor and a memory, wherein the memory is used to store a computer program;

[0046] The processor implements the above-mentioned cutting process parameter optimization method when executing the computer program.

[0047] In a third aspect, the present invention further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is processed, loaded and executed, the above-mentioned cutting process parameter optimization method is implemented.

[0048] The beneficial effects of the present invention are as follows: the present invention limits the degree of optimization according to equipment operation data and product quality, can well adapt and optimize the processed workpiece, and can improve the processing efficiency by about 20% without reducing the tool life. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a flow chart of the cutting process parameter optimization method of the present invention;

[0050] Figure 2 It is a flow chart when step 5 of the cutting process parameter optimization method of the present invention adopts another method. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used in the specification of the application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0053] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0054] The cutting process parameter optimization method, system, computer device and storage medium according to the present invention are described in detail below with reference to the accompanying drawings.

[0055] Among them, the cutting process parameter optimization method, such as Figure 1 As shown, it includes the following steps S1-5:

[0056] S1. Obtain the original processing program of the processing equipment; S2. Replace the original data of each process parameter in the original processing program with the corresponding macro variables and update it to the optimized processing program; S3. Use the original data of each process parameter as the initial processing data, optimize the initial processing data and obtain the optimized data; S4. Assign the optimized data each time to the corresponding macro variables in the optimized processing program and process the workpiece to obtain the processed product; S5. Determine whether to end the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions. The present invention limits the degree of optimization according to the equipment operation data and product quality, can well adapt and optimize the processed workpiece, and can improve the processing efficiency by about 20% without reducing the tool life.

[0057] The following is a detailed description of the above steps:

[0058] In step S1, the original processing program of the processing equipment is obtained (it can be obtained by starting the CNC machine tool).

[0059] Specifically, the machine tool processing program is obtained through communication technology, and the program is automatically analyzed, such as FOCAS supported by FANUC, EZSocket by Mitsubishi, OPC UA supported by Siemens, etc., and selection is made according to the specific CNC lathe model.

[0060] In step S2, the original data of each process parameter in the original machining program is replaced with the corresponding macro variable and updated to an optimized machining program (the same method as the above machining program can be adopted to obtain the data, or the extracted machining program statement can be displayed on the display and replaced manually);

[0061] Specifically, the original data at least includes the rotation speed and feed rate of the tool.

[0062] For example:

[0063] In the following program segment, the initial processing parameters in the processing segment of the tool number T1 (T1 in the following program segment) in the processing program code include: speed (S2500) and feed (F250); the above two initial processing data are modified to S#501 and F#502, and 2500 is assigned to #501 and 250 is assigned to #502. After the assignment is completed, the modified processing program is uploaded to the CNC machine tool. Thereafter, the initial processing parameters can be modified by changing the macro variable value. For example, the optimized parameter value is assigned to S#501 and F#502, and the processing program is run to realize processing according to the optimized data; when optimizing the initial processing parameters of other processing segments, the same applies.

[0064] M01

[0065] M6T1(D2.9)

[0066] G0G90X-162Y-0.10S2500M3

[0067] G43H1Z20.M8

[0068] G98G83Z-12.R1.Q3.5F250

[0069] In step S3, the original data of each process parameter is used as initial processing data, and the initial processing data is optimized to obtain optimized data;

[0070] Specifically, in the step of optimizing the original data to obtain the optimized data, the following formula is used to calculate the optimized data:

[0071]

[0072] in:

[0073] FV i : Optimized feed; FV i-1 : Optimize forward feed; SV i : Optimized speed; SV i-1 : Speed ​​before optimization; r: Feed optimization amplitude; c: Speed ​​optimization amplitude, r and c can be selected between 5% or 3%-10%; For example: According to the processing technology and the size of the workpiece, the rough processing of large workpieces with hard materials or the initial optimization can be optimized with an amplitude of 10%, and a smaller amplitude can be selected in the opposite situation and from the second optimization onwards; fro: Feed ratio; sro: Speed ​​ratio.

[0074] In step S4, the optimized data is assigned to the corresponding macro variables in the optimization processing program and the workpiece is processed to obtain a processed product;

[0075] That is, the initial processing data (speed / feed) values ​​in the processing program are replaced with optimized data (transferred through macro variables); in actual operation, macro variables are used for substitution. After the processing program is modified, the processing program is uploaded to the CNC machine tool, and the macro variables are associated with the processing parameters adopted by the processing tool one by one. The optimized parameters can replace the original processing parameters in the processing program through macro variables.

[0076] In step S5, the quality of the processed product and the optimized processing program for the workpiece processing equipment operation data whether it meets the constraints, determine whether to end the optimization;

[0077] Specifically, in step S5, judging whether to end the optimization step based on the quality of the processed product (i.e., the processing standard and dimensional deviation of the processed workpiece) and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions includes:

[0078] Let the current optimization times be W i , then the number of optimizations last time is W i-1 , where i is an integer greater than or equal to 1;

[0079] Determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions includes the following steps:

[0080] Get the W i The quality of the processed product after the first processing and the W i The equipment operation data during the first processing;

[0081] Determine whether the quality of the processed product of the workpiece and / or the equipment operation data meets the constraint conditions:

[0082] If, the W i The quality of the processed product after the second processing and / or the W i The equipment operation data does not meet the constraint conditions during the second processing, and the W i-1 The quality of the processed product after the first processing and the W i-1 When the equipment operation data meets the constraint conditions during the first processing, the optimization ends and the W i-1 The optimized data corresponding to this time is taken as the optimization result;

[0083] If, the W i The quality of the processed product after the first processing and the W i When the equipment operation data meets the constraint conditions during the first processing, the W i The optimization data obtained this time is used as the basis for continued optimization.

[0084] In one embodiment, Figure 2 As shown, step S5 determines whether to end the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions. It can also be performed in the following manner:

[0085] Set the current optimization times to W i , then the number of optimizations last time is W i-1 , where i is an integer greater than or equal to 1;

[0086] Determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions includes the following steps:

[0087] S51. Obtain the W i The quality of the processed product after the first processing and the W i The equipment operation data during the second optimization process;

[0088] S52. Determine the W i Whether the quality of the suboptimal processed product meets the constraints;

[0089] S53. If it meets the requirement, then determine the W i Whether the equipment operation data meets the constraint conditions during the secondary optimization process;

[0090] S53A. If it does not meet the requirements, the optimization is terminated; and the W i-1 The optimization parameters thus obtained are taken as optimization results;

[0091] S53B. If it meets the requirements, continue to optimize;

[0092] S54. If not, determine whether the processed product is a product that can be further optimized;

[0093] S54A. If yes, then continue to optimize after determining the parameters to be optimized based on the product processing quality;

[0094] Specifically, in the case of some product quality indicators that are unqualified, further optimization can be achieved by automatically selecting a single optimized speed or feed. For example, if the roughness or end face runout of the product does not meet the quality requirements, it can be determined that it can be optimized, and the failure of this quality item can be solved by slightly increasing (adjusting the range of 10%-25%) the speed or reducing (adjusting the range of 10%-25%) the feed. Preferably, the speed is adjusted first, and if the optimized product quality still does not meet the requirements, then adjust the feed.

[0095] S54B. If not, output and save W i-1 The optimization data is saved and this optimization is recorded as invalid.

[0096] Specifically, the constraint conditions include a product quality constraint range (quality requirements of the processed workpiece) and an equipment parameter constraint range, wherein the equipment parameter constraint range is determined by the following steps:

[0097] Run the machining program according to the initial machining parameters to process the workpiece, and obtain the equipment operating parameters (power or spindle vibration data);

[0098] The device parameter constraint range is generated according to the device operating parameters.

[0099] The constraints adopted in the present invention are as follows:

[0100]

[0101]

[0102] Among them, SV min Set the minimum value, SV, for the speed max Set the maximum value for the speed; FV min Set minimum value, FV, for feed max Set the minimum value for feed; (the range of speed and feed is determined by the CNC machine tool). P is the actual collected process power (actual power), P x- is the lower limit of the graded power, and the power can be replaced by the spindle vibration value (the grade division can refer to the power division standard); x is the optimization level, which can be 1, 2 and 3; P x+ is the upper limit of the classification power, x is the optimization level, which can be 1, 2 or 3; Q is the product quality measured by the optimized processing, Q - is the lower boundary of product quality requirements, Q + It is the upper boundary of product quality requirements.

[0103] The optimization level x level and boundary range can be divided as follows: Level 1: 90%-110%; Level 2: 85%-115%; Level 3: 80%-120%; the upper and lower limits of each level are based on the power data corresponding to each process (processing stage) recorded in the process section of the same existing processing project (which can also be obtained through trial processing), or the spindle vibration data, as the basis;

[0104] The optimization level x is selected according to the following principles: the selection of upper and lower limits is determined by the tool, process and the ability of the material to bear the load, such as: the milling process can set the third-level optimization upper and lower limits for thicker steel and aluminum parts (such as greater than 6mm) in the processing position; the second-level optimization upper limit can be set when turning and drilling conventional parts (thickness greater than 6mm), and the first-level optimization upper and lower limits can be set when turning and drilling thin-walled parts (less than or equal to 6mm); selecting the level within this range can achieve the optimal parameters, such as power reduction or improved processing efficiency.

[0105] The present invention uses equipment operation data and product quality to guide the optimization direction, and uses the operation data collected during the processing and the product quality data after processing to limit the optimized processing parameters. For example, if the roughness or end face runout of the processed product is too large, it can be inferred that the rotation speed and feed are unreasonable points, as well as the optimization direction.

[0106] The optimization range is constrained by equipment operation data and product quality. The equipment operation data of the workpiece processing process can reflect the load usage of the machine tool during the processing process, and each tool has a certain limit on its bearing capacity. The process signal (power or spindle vibration) is graded according to the different workpieces to be processed (mainly thickness, processing technology and materials, etc.). In the case of high cost of workpieces or tools, different levels are selected to make the speed feed more reasonable, thereby achieving the goal of optimizing process parameters, which can improve the processing cycle, ensure product quality, and reduce tool waste.

[0107] Cutting process parameter optimization system, including:

[0108] The communication module is used to obtain the processing program and equipment operation data of the processing equipment (including the data of the process learning stage before step S1 (the data records of the process segments of the same workpiece or the data obtained through the trial processing, such as power or spindle vibration data) and the real-time operation data of the equipment (including the tool position number, equipment status (power), set speed, set feed), and extract the initial processing parameters in the processing program;

[0109] Specifically, the data acquisition module uses IoT (Internet of Things) technology to obtain the CNC machine tool processing program, and can back it up to the system with one click, then load the processing program into the editing interface, replace the process parameters with macro variables, and assign the original process parameters to the macro variables through data acquisition. The subsequent optimization process only needs to change the value of the macro variable, without the need to manually modify the program, which can reduce the complexity of process parameter modification and improve the efficiency of program modification.

[0110] A processing module, used for replacing the original data of each process parameter in the original processing program with the corresponding macro variable, and updating it into an optimized processing program;

[0111] An optimization module, used for optimizing the initial processing data and obtaining optimized data;

[0112] An execution module assigns the optimized data to the corresponding macro variables in the optimized processing program, and executes the optimized processing program to process the workpiece to obtain a processed product;

[0113] The judgment module is used to judge whether the quality of the processed product obtained by using the data after each optimization and the equipment operation data when the optimized processing program processes the workpiece meet the constraint conditions, and determine whether to end the optimization.

[0114] The cutting process parameter optimization system of the present invention is convenient and simple to modify the program, and there is no need to establish a subroutine. The program is directly acquired through the data acquisition interface, and there is no need to operate the machine tool. The user's programming ability requirement is very low. It only needs to find the processing program segment of each tool position and replace the macro variable.

[0115] A computer device, comprising: a processor and a memory, wherein the memory is used to store a computer program;

[0116] The processor implements the above-mentioned cutting process parameter optimization method when executing the computer program.

[0117] A computer-readable storage medium stores a computer program, which implements the above-mentioned cutting process parameter optimization method when the computer program is processed, loaded and executed.

[0118] The present invention uses equipment operation data and product quality to guide the optimization direction, and uses the operation data collected during the processing and the product quality data after processing to limit the optimized processing parameters. For example, if the roughness or end face runout of the processed product is too large, it can be inferred that the rotation speed and feed are unreasonable points, as well as the optimization direction.

[0119] The optimization range is constrained by equipment operation data and product quality. The equipment operation data of the workpiece processing process can reflect the load usage of the machine tool during the processing process, and each tool has a certain limit on its bearing capacity. According to the different workpieces to be processed (mainly thickness, processing technology and materials, etc.), the process signals (power, spindle vibration, etc.) are graded. In case of high cost of workpieces or tools, different levels are selected to make the speed feed more reasonable, thereby achieving the goal of optimizing process parameters, which can improve the processing cycle, ensure product quality, and reduce tool waste.

Claims

1. A cutting process parameter optimization method, characterized in that: The steps include: Obtain the original processing program of the processing equipment; Replacing the original data of each process parameter in the original processing program with the corresponding macro variables and updating the optimized processing program; Using original data of each process parameter as initial processing data, optimizing the initial processing data and obtaining optimized data; Assigning each optimized data to the corresponding macro variable in the optimized processing program and processing the workpiece to obtain a processed product; Determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data when the workpiece is processed by the optimized processing program meets the constraint conditions; The optimization model used to optimize the initial processing data is: Among them, FV i To optimize the feed, FV i-1 To optimize forward feed, SV i For optimized speed, SV i-1 is the speed before optimization, r is the feed optimization amplitude, c is the speed optimization amplitude, fro is the feed rate, sro is the speed rate; Set the current optimization times to W i , then the number of optimizations last time is W i-1 , where i is an integer greater than or equal to 1; Determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions includes the following steps: Get the W i The quality of the processed product after the first processing and the W i The equipment operation data during the first processing; Determine the W i Whether the quality of the secondary processed products meets the constraints; If it meets the requirement, then the W i Whether the equipment operation data meets the constraints during the first processing; If not, the optimization is terminated; and the W i-1 The optimization parameters to be optimized are taken as optimization results; If it meets the requirements, continue to optimize; If not, determine whether the processed product is a product that can be further optimized; If yes, then continue the optimization after determining the parameters to be optimized based on the product processing quality; If not, output and save W i-1 The optimization data is optimized again, and this optimization is recorded as invalid optimization; the constraints are: Among them, SV min Set the minimum value, SV, for the speed max Set the maximum value for the speed; FV min Set minimum value, FV, for feed max is the minimum value for feed setting; P is the actual collected process power, P x- is the lower limit of the classification power, x is the optimization level, which can be 1, 2 or 3; P x+ is the upper limit of the classification power, x is the optimization level, which can be 1, 2 or 3; Q is the product quality measured by the optimized processing, Q - is the lower boundary of product quality requirements, Q + It is the upper boundary of product quality requirements.

2. The cutting process parameter optimization method according to claim 1, characterized in that: Let the current optimization times be Wi, then the last optimization times be Wi-1, where i is an integer greater than or equal to 1; Determining whether to terminate the optimization based on the quality of the processed product and whether the equipment operation data when the optimized processing program processes the workpiece meets the constraint conditions includes the following steps: Get the W i The quality of the processed product after the first processing and the W i The equipment operation data during the first processing; Determine whether the quality of the processed product of the workpiece and / or the equipment operation data meets the constraint conditions: If, the W i The quality of the processed product after the second processing and / or the W i The equipment operation data does not meet the constraint conditions during the second processing, and the W i-1 The quality of the processed product after the first processing and the W i-1 When the equipment operation data meets the constraint conditions during the first processing, the optimization ends and the W i-1 The optimized data corresponding to this time is taken as the optimization result; If, the W i The quality of the processed product after the first processing and the W i When the equipment operation data meets the constraint conditions during the first processing, the W i The optimization data obtained this time is used as the basis for continued optimization.

3. The cutting process parameter optimization method according to claim 1, characterized in that: The constraint conditions include a product quality constraint range and an equipment parameter constraint range, wherein the method for determining the equipment parameter constraint range includes the steps of: Run the machining program according to the initial machining parameters to process the workpiece and obtain the equipment operating parameters; The device parameter constraint range is generated according to the device operating parameters.

4. A cutting process parameter optimization system, used to implement the cutting process parameter optimization method according to any one of claims 1 to 3, characterized in that: The cutting process parameter optimization system comprises: A communication module, used to obtain a processing program and equipment operation data of a processing device, and extract initial processing parameters in the processing program; A processing module, used for replacing the original data of each process parameter in the original processing program with the corresponding macro variable, and updating it into an optimized processing program; An optimization module, used for optimizing the initial processing data and obtaining optimized data; An execution module assigns the optimized data to the corresponding macro variables in the optimized processing program, and executes the optimized processing program to process the workpiece to obtain a processed product; The judgment module is used to judge whether the quality of the processed product obtained by using the data after each optimization and the equipment operation data when the optimized processing program processes the workpiece meet the constraint conditions, and determine whether to end the optimization.

5. A computer device, characterized in that: include: A processor and a memory, wherein the memory is used to store a computer program; When the processor executes the computer program, the cutting process parameter optimization method described in any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is processed, loaded and executed, the cutting process parameter optimization method according to any one of claims 1 to 3 is implemented.

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