Cutting feeding path planning system for metal products

Abstract

The invention discloses a cutting and feeding path planning system for metal products, and particularly relates to the technical field of metal cutting, the method comprises the following steps: firstly, acquiring operation state parameters of a target numerical control machine tool, inputting the operation state parameters into target simulation software to obtain a cutting and feeding path set, acquiring path quality data of each path in the cutting and feeding path set, obtaining a priority use index of each path according to the path quality data; the priority sending indexes of all the paths in the cutting feeding path set are sequenced from large to small, the cutting feeding path corresponding to the maximum priority sending index serves as a target cutting feeding path, the target cutting feeding path is sent to a target numerical control machine tool, cutting feeding is conducted on the target metal product, and the target metal product is obtained. Therefore, the optimal cutting feed path of the metal product can be selected, the cutting feed effect of the metal product is optimal, the final cutting defects of the metal product are reduced, and the rejection rate is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of metal cutting, and in particular to a cutting tool path planning system for metal products. Background Art

[0002] The cutting path planning system for metal products optimizes the cutting process by comprehensively utilizing design drawings, material properties, and path planning algorithms. First, the system inputs the design drawings and material properties into the simulation software. The simulation software uses discretization processing to convert the continuous path into discrete points, and performs path planning through an algorithm. The planned path is then input into the CNC machine tool that performs the cutting pass of the metal product. The CNC machine tool performs the cutting pass on the metal product. This process ensures efficient and precise metal processing, reducing waste and processing time.

[0003] However, in the actual path planning process, the cutting path input to the CNC machine that executes the cutting of metal products may not be optimal, which may result in suboptimal cutting effects on the metal products, and may result in more defects in the final cutting effect and a higher scrap rate. Summary of the Invention

[0004] The purpose of the present invention is to solve the problem that in the actual path planning process, the cutting path input to the CNC machine that executes the cutting path of the metal product may not be optimal, which may lead to the cutting effect of the metal product not being optimal, and may result in more defects in the final cutting effect and a higher scrap rate. A cutting path planning system for metal products is proposed.

[0005] The present invention provides a cutting tool path planning system for metal products, wherein the system is used to input a planned cutting tool path into a target CNC machine tool, wherein:

[0006] Path collection module: obtains the operating state parameters of the target CNC machine tool, obtains the operating state parameter set, and inputs the operating state parameter set into the target simulation software to obtain the cutting path set;

[0007] Priority Index Module: For each path in the cutting path set, the path quality data of each path is obtained, and the priority index of each path is obtained based on the path quality data; the path quality data includes the processing efficiency index, the surface quality index and the path complexity index;

[0008] Sorting module: sorting the priority sending index of each path in the cutting path set from large to small, and taking the cutting path corresponding to the largest priority sending index as the target cutting path;

[0009] Path sending module: sends the target cutting path to the target CNC machine tool to perform cutting on the target metal product.

[0010] Optionally, the processing efficiency index includes:

[0011] For each path in the cutting path set, the volume removed by each path after cutting the target metal product in the simulation software is extracted, and the removed volume is divided by the preset unit time to obtain the material removal rate. The calculation formula is: PG = ΔV / Δt, where PG is the material removal rate, ΔV is the removed volume, and Δt is the preset unit time.

[0012] After extracting the total processing time and actual cutting time of each path in the simulation software to cut the target metal product, the effective cutting time is obtained based on the actual cutting time and total processing time. The calculation formula is: LU = RF / RY, where LU is the effective cutting time, RF is the actual cutting time, and RY is the total processing time.

[0013] After each path cuts the target metal product in the simulation software, the corresponding tool wear and cutting length are extracted, and the tool wear rate is obtained based on the tool wear and cutting length. The calculation formula is: TG = TY / TD, where TG is the tool wear rate, TY is the tool wear, and TD is the cutting length.

[0014] Optionally, the processing efficiency index further includes:

[0015] After each path cuts the target metal product in the simulation software, the corresponding spindle motor power and time consumed, as well as the feed motor power and time consumed, are extracted to obtain the energy consumption coefficient. The calculation formula is: KF = rl × tf + rw × tc, where KF is the energy consumption coefficient, rl and tf are the power and time consumed by the spindle motor, and rw and tc are the power and time consumed by the feed motor, respectively.

[0016] Calculate the processing efficiency index, the calculation formula is:

[0017]

[0018] Where Klh is the machining efficiency index, f1, f2, f3, and f4 are the preset proportional coefficients of material removal rate, effective cutting time, tool wear rate, and energy consumption coefficient, respectively, and f1, f2, f3, and f4 are all greater than 0.

[0019] Optionally, the surface quality index includes:

[0020] For each path in the cutting path set, extract the height value of each sampling point on the surface profile of the target metal product after each path cuts the target metal product in the simulation software, and combine it with the average value of the height of the sampling points on the surface profile of the target metal product to obtain the surface roughness. The calculation formula is:

[0021]

[0022] Where YH is the surface roughness, y i Represents the height value of the i-th sampling point on the surface profile of the target metal product, is the average height of the sampling points on the surface profile of the target metal product; n is the total number of sampling points on the surface profile of the target metal product, and n is a positive integer.

[0023] Optionally, the surface quality index further includes:

[0024] After each path cuts the target metal product in the simulation software, the actual processed dimensions and the preset processed dimensions of the target metal product are extracted to obtain the contour accuracy deviation coefficient. The calculation formula is: ED = |QA-QV|, where ED is the actual processed dimension, QA is the actual cutting time, and QV is the preset processed dimension.

[0025] Calculate the surface quality index using the following formula: Fdh = a1 × YH + a2 × ED; where Fdh is the surface quality index, a1 and a2 are the preset proportional coefficients of the surface roughness and profile accuracy deviation coefficients, respectively, and both a1 and a2 are greater than 0.

[0026] Optionally, the path complexity index includes:

[0027] The number of segments of each path that each path passes through during the cutting of the target metal product in the simulation software is extracted. For each segment of the path, the corresponding adjustment frequency and number of turns are obtained to obtain the complexity index of each path. The path complexity index is obtained based on the complexity index of each path. The calculation formula is:

[0028]

[0029] Where SD is the path complexity index, j represents the number of paths, j = 1, 2, 3, 4, ..., m, and is a positive integer; jh and jn represent the adjustment frequency and the number of turns, respectively; b1 and b2 are the preset proportional coefficients of the adjustment frequency and the number of turns, respectively, and both b1 and b2 are greater than 0.

[0030] Optionally, the priority usage index includes:

[0031] The priority index is obtained based on the processing efficiency index, surface quality index and path complexity index. The calculation formula is:

[0032]

[0033] Where Vaz is the machining efficiency index, Klh, Fdh, and SD are the machining efficiency index, surface quality index, and path complexity index, respectively; c1, c2, and c3 are the preset proportional coefficients of the machining efficiency index, surface quality index, and path complexity index, respectively, and c1, c2, and c3 are all greater than 0.

[0034] Beneficial effects of the present invention:

[0035] The present invention proposes a cutting tool path planning system for metal products. The system first obtains the operating status parameters of the target CNC machine tool and inputs them into the target simulation software to obtain a cutting tool path set. For each path in the cutting tool path set, the path quality data of each path is obtained, and the priority usage index of each path is obtained according to the path quality data; the priority sending index of each path in the cutting tool path set is sorted in descending order, and the cutting tool path corresponding to the maximum priority sending index is used as the target cutting tool path, and the target cutting tool path is sent to the target CNC machine tool to perform cutting on the target metal product. In this way, the optimal cutting tool path for the metal product can be selected, so that the cutting effect of the metal product is optimized, the defects in the final cutting of the metal product are reduced, and the scrap rate is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below with reference to the accompanying drawings.

[0037] Figure 1 A framework diagram of a cutting tool path planning system for metal products is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0039] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0040] The embodiment of the present invention provides a cutting path planning system for metal products. Figure 1 , Figure 1This is a framework diagram of a cutting path planning system for metal products provided by an embodiment of the present invention. The system is used to input the planned cutting path to a target CNC machine tool, wherein:

[0041] Path collection module: obtains the operating state parameters of the target CNC machine tool, obtains the operating state parameter set, and inputs the operating state parameter set into the target simulation software to obtain the cutting path set;

[0042] Priority Index Module: For each path in the cutting path set, the path quality data of each path is obtained, and the priority index of each path is obtained based on the path quality data; the path quality data includes processing efficiency index, surface quality index and path complexity index;

[0043] Sorting module: sorting the priority sending index of each path in the cutting path set from large to small, and taking the cutting path corresponding to the largest priority sending index as the target cutting path;

[0044] Path sending module: sends the target cutting path to the target CNC machine tool to perform cutting on the target metal product.

[0045] Based on a metal product cutting path planning system provided in an embodiment of the present invention, the above method can select the optimal metal product cutting path, so that the cutting effect of the metal product is optimized, the final metal product cutting defects are reduced, and the scrap rate is reduced.

[0046] It should be noted that high-precision sensors are installed at key locations on CNC machine tools to monitor various machine status parameters in real time. These sensors may include: vibration sensors: monitor machine tool or tool vibration; temperature sensors: monitor the temperature of the spindle, tool, workpiece, etc.; cutting force sensors: monitor force changes during the cutting process; position sensors: monitor the relative position of the tool and workpiece to ensure positioning accuracy; and spindle speed and feed rate sensors: record the current spindle speed and feed rate in real time. The data captured by these sensors is organized to form a complete set of actual status parameters. Specific parameters may include: spindle speed: the current actual speed, which may be affected by load and wear; feed rate: the actual feed rate, which may deviate from the preset value; cutting force: the actual cutting force, which is affected by material, tool condition, and other factors; vibration amplitude: the actual vibration, reflecting machine tool rigidity and tool condition; temperature distribution: the temperature of the machine tool and tool, which affects material thermal deformation; and tool wear: real-time wear data acquired by the tool monitoring system.

[0047] According to the actual state parameter set collected, adjust the corresponding parameters in the simulation software to ensure that the parameters used in the simulation are as close to the actual processing environment as possible. Adjust the spindle speed and feed rate: According to the actual measured spindle speed and feed rate, adjust the relevant parameters in the simulation model. Update the cutting force model: According to the actual cutting force data, adjust the mechanical model in the simulation to ensure that the simulation of the cutting force is closer to the actual situation. Vibration compensation in simulation: Using the data from the vibration sensor, introduce the influence of vibration in the simulation, and consider the impact of vibration on the tool path and processing quality. Thermal effect adjustment: According to the data from the temperature sensor, adjust the thermal effect model in the simulation to predict and compensate for the impact of thermal deformation on the cutting path.

[0048] In one implementation, the target CNC machine tool's operating state parameters are captured and fed into simulation software to generate a set of cutting paths, ensuring that path planning more closely matches the actual machining environment. This approach effectively adjusts key simulation parameters such as spindle speed, feed rate, cutting forces, vibration, and thermal effects, thereby reducing cutting errors caused by inconsistencies between the actual machine tool state and the simulation. Ultimately, the generated paths optimize machining efficiency, improve surface quality, reduce tool wear, significantly reduce scrap rates, and enhance overall machining stability and accuracy.

[0049] In one embodiment, the process efficiency index includes:

[0050] For each path in the cutting path set, the volume removed by each path after cutting the target metal product in the simulation software is extracted, and the removed volume is divided by the preset unit time to obtain the material removal rate. The calculation formula is: PG = ΔV / Δt, where PG is the material removal rate, ΔV is the removed volume, and Δt is the preset unit time.

[0051] After extracting the total processing time and actual cutting time of each path in the simulation software to cut the target metal product, the effective cutting time is obtained based on the actual cutting time and total processing time. The calculation formula is: LU = RF / RY, where LU is the effective cutting time, RF is the actual cutting time, and RY is the total processing time.

[0052] After each path cuts the target metal product in the simulation software, the corresponding tool wear and cutting length are extracted, and the tool wear rate is obtained based on the tool wear and cutting length. The calculation formula is: TG = TY / TD, where TG is the tool wear rate, TY is the tool wear, and TD is the cutting length.

[0053] In one embodiment, the process efficiency index further includes:

[0054] After each path cuts the target metal product in the simulation software, the corresponding spindle motor power and time consumed, as well as the feed motor power and time consumed, are extracted to obtain the energy consumption coefficient. The calculation formula is: KF = rl × tf + rw × tc, where KF is the energy consumption coefficient, rl and tf are the power and time consumed by the spindle motor, and rw and tc are the power and time consumed by the feed motor, respectively.

[0055] Calculate the processing efficiency index, the calculation formula is:

[0056]

[0057] Where Klh is the machining efficiency index, f1, f2, f3, and f4 are the preset proportional coefficients of material removal rate, effective cutting time, tool wear rate, and energy consumption coefficient, respectively, and f1, f2, f3, and f4 are all greater than 0.

[0058] It should be noted that the preset unit time is set by professionals based on actual circumstances, and no specific limitations or elaboration are made; in addition, f1, f2, f3, and f4 are also set by professionals based on actual circumstances. Generally, the sum of f1, f2, f3, and f4 is 1. For example, f1, f2, f3, and f4 can be 0.25, 0.25, 0.25, 0.25, respectively, or other numbers, without specific limitations.

[0059] It should be noted that the smaller the material removal rate, the shorter the effective cutting time, the greater the tool wear rate and the greater the energy consumption coefficient, the more it indicates that the corresponding cutting path is not the optimal cutting path for metal products, which may result in the cutting effect of metal products not being optimal, and may result in more defects in the final cutting effect and a higher scrap rate. The reason is that

[0060] The lower the material removal rate: A lower material removal rate means less material is removed per unit time, which can lead to low production efficiency. A low material removal rate often indicates that the cutting parameters are not set optimally, perhaps because the cutting speed or feed rate is too low, or the cutting depth is insufficient, thus failing to fully utilize the machine tool's capabilities. This not only increases the processing time, but also may affect the surface quality of the workpiece.

[0061] The smaller the effective cutting time, the smaller the tool life: The effective cutting time refers to the proportion of time spent in the actual cutting process. A smaller effective cutting time means more time is spent on idle movement, tool changes, or other non-productive activities, which reduces overall machining efficiency. Increased non-cutting time often indicates poor path planning, resulting in frequent tool movement without actual cutting, which not only wastes time but also increases machine energy consumption.

[0062] Excessive tool wear: Excessive tool wear indicates excessive load on the tool during cutting, often due to improper cutting parameters or poor path planning. Excessive tool wear reduces machining accuracy and can lead to poor surface quality and increased workpiece defects. Frequent tool changes can further increase non-productive time, impacting machining efficiency.

[0063] A higher energy consumption coefficient means that the energy used during machining is inefficient, possibly due to excessive cutting resistance, excessive vibration, or increased friction between the machine tool and the workpiece. This not only increases production costs but can also cause thermal deformation of the machine tool, affecting machining accuracy and surface quality.

[0064] Taking all these factors into consideration, if the material removal rate is low, the effective cutting time is short, the tool wear is fast, and the energy consumption is high, the corresponding cutting path is often not optimal. Such path selection may lead to more defects in the processing process.

[0065] In one embodiment, the surface quality index comprises:

[0066] For each path in the cutting path set, extract the height value of each sampling point on the surface profile of the target metal product after each path cuts the target metal product in the simulation software, and combine it with the average value of the height of the sampling points on the surface profile of the target metal product to obtain the surface roughness. The calculation formula is:

[0067]

[0068] Where YH is the surface roughness, y i Represents the height value of the i-th sampling point on the surface profile of the target metal product, is the average height of the sampling points on the surface profile of the target metal product; n is the total number of sampling points on the surface profile of the target metal product, and n is a positive integer.

[0069] In one embodiment, the surface quality index further includes:

[0070] After each path cuts the target metal product in the simulation software, the actual processed dimensions and the preset processed dimensions of the target metal product are extracted to obtain the contour accuracy deviation coefficient. The calculation formula is: ED = |QA-QV|, where ED is the actual processed dimension, QA is the actual cutting time, and QV is the preset processed dimension.

[0071] Calculate the surface quality index using the following formula: Fdh = a1 × YH + a2 × ED; where Fdh is the surface quality index, a1 and a2 are the preset proportional coefficients of the surface roughness and profile accuracy deviation coefficients, respectively, and both a1 and a2 are greater than 0.

[0072] It should be noted that the preset processed dimensions are set by professionals based on actual conditions, and are not specifically limited or elaborated upon. In addition, a1 and a2 are also set by professionals based on actual conditions. Generally, the sum of a1 and a2 is 1. For example, a1 and a2 can be 0.5 and 0.5, respectively, or other numbers, without specific limitation.

[0073] It should be noted that the greater the surface roughness and the greater the profile accuracy deviation coefficient, the more it indicates that the corresponding cutting path is not the optimal cutting path for metal products, which may lead to suboptimal cutting effects on metal products, and may result in more defects in the final cutting effect and a higher scrap rate. The reason is that surface roughness is an indicator of the smoothness of the surface after cutting. Larger roughness usually means that there are obvious tool marks, ripples or uneven textures on the surface. This indicates that the cutting path may not be optimized enough, resulting in uneven cutting effects. High roughness may be caused by tool wear, improper cutting parameter settings (such as too high feed speed, too large cutting depth) or unreasonable tool path planning; the profile accuracy deviation coefficient indicates the difference between the actual contour after processing and the expected contour. A large deviation coefficient indicates that the error between the actual processing contour and the target contour is large. When the surface roughness and profile accuracy deviation coefficients are large, it means that the cutting path may not be fully optimized, resulting in unsatisfactory cutting effects.

[0074] In one embodiment, the path complexity index includes:

[0075] The number of segments of each path that each path passes through during the cutting of the target metal product in the simulation software is extracted. For each segment of the path, the corresponding adjustment frequency and number of turns are obtained to obtain the complexity index of each path. The path complexity index is obtained based on the complexity index of each path. The calculation formula is:

[0076]

[0077] Where SD is the path complexity index, j represents the number of paths, j = 1, 2, 3, 4, ..., m, and is a positive integer; jh and jn represent the adjustment frequency and the number of turns, respectively; b1 and b2 are the preset proportional coefficients of the adjustment frequency and the number of turns, respectively, and both b1 and b2 are greater than 0.

[0078] It should be noted that b1 and b2 are set by professionals according to actual conditions. Generally, the sum of b1 and b2 is 1. For example, b1 and b2 can be 0.5 and 0.5 respectively, or other numbers, which are not specifically limited.

[0079] It should be noted that the path complexity index refers to the adjustment frequency and number of turns in path processing. If the adjustment frequency is greater and the number of turns is greater, it means that the corresponding cutting path is not the optimal cutting path for metal products, which may lead to the cutting effect of metal products not being optimal, and may lead to more defects in the final cutting effect and a higher scrap rate. The reason is that the load on the machine tool is increased: frequent adjustments and turns will increase the load on the machine tool, resulting in increased equipment wear and increased energy consumption, which may affect the long-term stability and reliability of the machine tool.

[0080] Reduced machining efficiency: Complex paths require more time to complete turns and adjustments, resulting in increased cutting time and thus reducing overall machining efficiency.

[0081] Increased operational difficulty: Complex paths are more difficult to operate and are prone to human errors, such as incorrect path planning or improper adjustments, which can affect processing results.

[0082] Impact on processing quality: Frequent path adjustments and turns may cause the tool to have an unstable position during the cutting process, increase surface roughness and contour deviation, and make the quality of the final product fail to meet the expected standards.

[0083] Increased scrap rate: Due to the complexity of the path and potential processing errors, defects may occur in the product, increasing the scrap rate, thereby increasing production costs and wasting resources.

[0084] Therefore, the path complexity index directly reflects the degree of optimization of the cutting path. A higher complexity usually means that the cutting path is not ideal and may need further optimization to reduce the frequency of adjustments and the number of turns, thereby improving cutting results and production efficiency.

[0085] In one embodiment, the priority usage index includes:

[0086] The priority index is obtained based on the processing efficiency index, surface quality index and path complexity index. The calculation formula is:

[0087]

[0088] Where Vaz is the machining efficiency index, Klh, Fdh, and SD are the machining efficiency index, surface quality index, and path complexity index, respectively; c1, c2, and c3 are the preset proportional coefficients of the machining efficiency index, surface quality index, and path complexity index, respectively, and c1, c2, and c3 are all greater than 0.

[0089] It should be noted that c1, c2, and c3 are set by professionals according to actual conditions. Generally, the sum of c1, c2, and c3 is 1. For example, c1, c2, and c3 can be 0.3, 0.3, and 0.4, respectively, or other numbers, without specific limitation.

[0090] It should be noted that the priority index of each path in the cutting path set is sorted from largest to smallest, and the cutting path corresponding to the largest priority index is used as the target cutting path. The target cutting path is then sent to the target CNC machine tool to cut the target metal product. This method helps maximize machining efficiency and ensure that the product surface quality meets the expected standards, while reducing unnecessary path complexity, thereby reducing the difficulty of machine tool operation and the failure rate. Ultimately, this optimization strategy not only improves the stability and accuracy of the cutting effect, but also effectively reduces scrap rate and production costs, improving overall efficiency and economic benefits.

[0091] The above is a detailed description of an embodiment of the present invention. However, the content is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A cutting path planning system for metal products, characterized in that: The system is used to input a planned cutting tool path to a target CNC machine tool, wherein: Path collection module: obtain the operating state parameters of the target CNC machine tool, obtain the operating state parameter set, and input the operating state parameter set into the target simulation software to obtain the cutting path set; Priority index module: for each path in the cutting path set, the path quality data of each path is obtained, and the priority index of each path is obtained according to the path quality data; the path quality data includes processing efficiency index, surface quality index and path complexity index; Sorting module: sorting the priority sending index of each path in the cutting tool path set from large to small, and taking the cutting tool path corresponding to the maximum priority sending index as the target cutting tool path; Path sending module: sends the target cutting path to the target CNC machine tool to perform cutting on the target metal product.

2. A metal product cutting tool path planning system according to claim 1, characterized in that: The processing efficiency index includes: For each path in the cutting path set, the volume removed after each path cuts the target metal product in the simulation software is extracted, and the removed volume is divided by the preset unit time to obtain the material removal rate. The calculation formula is: PG = ΔV / Δt, where PG is the material removal rate, ΔV is the removed volume, and Δt is the preset unit time; After extracting the total processing time and actual cutting time of each path in the simulation software to cut the target metal product, the effective cutting time is obtained according to the actual cutting time and the total processing time. The calculation formula is: LU = RF / RY, where LU is the effective cutting time, RF is the actual cutting time, and RY is the total processing time. The corresponding tool wear and cutting length of each path after cutting the target metal product in the simulation software are extracted, and the tool wear rate is obtained based on the tool wear and cutting length. The calculation formula is: TG=TY / TD, where TG is the tool wear rate, TY is the tool wear, and TD is the cutting length.

3. A metal product cutting tool path planning system according to claim 2, characterized in that: The processing efficiency index also includes: After each path cuts the target metal product in the simulation software, the corresponding power and time consumed by the spindle motor and the power and time consumed by the feed motor are extracted to obtain the energy consumption coefficient. The calculation formula is: KF = rl × tf + rw × tc, where KF is the energy consumption coefficient, rl and tf are the power and time consumed by the spindle motor, and rw and tc are the power and time consumed by the feed motor. Calculate the processing efficiency index, the calculation formula is: Where Klh is the machining efficiency index, f1, f2, f3 and f4 are the preset proportional coefficients of material removal rate, effective cutting time, tool wear rate and energy consumption coefficient, respectively, and f1, f2, f3 and f4 are all greater than 0.

4. A metal product cutting tool path planning system according to claim 1, characterized in that: The surface quality index includes: For each path in the cutting path set, extract the height value of each sampling point on the surface profile of the target metal product after each path cuts the target metal product in the simulation software, and combine it with the average value of the height of the sampling points on the surface profile of the target metal product to obtain the surface roughness. The calculation formula is: Where YH is the surface roughness, y i Represents the height value of the i-th sampling point on the surface profile of the target metal product, is the average height of the sampling points on the surface profile of the target metal product; n is the total number of sampling points on the surface profile of the target metal product, and n is a positive integer.

5. A metal product cutting tool path planning system according to claim 4, characterized in that: The surface quality index also includes: After each path cuts the target metal product in the simulation software, the actual size of the target metal product after processing and the preset size after processing are extracted to obtain the contour accuracy deviation coefficient. The calculation formula is: ED = |QA-QV|, where ED is the actual size after processing, QA is the actual cutting time, and QV is the preset size after processing; Calculate the surface quality index using the following formula: Fdh = a1 × YH + a2 × ED; where Fdh is the surface quality index, a1 and a2 are preset proportional coefficients of the surface roughness and profile accuracy deviation coefficients, respectively, and both a1 and a2 are greater than 0.

6. A metal product cutting tool path planning system according to claim 1, characterized in that: The path complexity index includes: The number of segments of each path passed by in the process of cutting the target metal product in the simulation software is extracted. For each segment of the path, the corresponding adjustment frequency and number of turns are obtained to obtain the complexity index of each path. The path complexity index is obtained according to the complexity index of each path. The calculation formula is: Wherein, SD is the path complexity index, j represents the number of paths, j=1, 2, 3, 4, ..., m, j is a positive integer; jh and jn represent the adjustment frequency and the number of turns, respectively, b1 and b2 are the preset proportional coefficients of the adjustment frequency and the number of turns, respectively, and b1 and b2 are both greater than 0.

7. A metal product cutting tool path planning system according to claim 1, characterized in that: The priority use index includes: The priority index is obtained according to the processing efficiency index, surface quality index and path complexity index. The calculation formula is: Where Vaz is the processing efficiency index, Klh, Fdh, and SD are the processing efficiency index, surface quality index, and path complexity index, respectively; c1, c2, and c3 are the preset proportional coefficients of the processing efficiency index, surface quality index, and path complexity index, respectively, and c1, c2, and c3 are all greater than 0.

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