Metal cutting equipment scheduling method for calculating residual life of cutter

Abstract

The invention discloses a metal cutting equipment scheduling method for calculating the residual life of a cutter, and relates to the technical field of cutter life calculation, and the technical scheme is characterized in that the method comprises the following steps: S1, obtaining the number information of the cutter; s2, cutting parameters of the machined workpiece are input; s3, simulating and calculating the required service life of each numbered cutter when the workpiece is processed; s4, according to the simulated machining conditions of all the numbered cutters, the optimal numbered cutter is selected; s5, judging whether the selected optimal numbered tool has a risk or not, and if not, executing the machining; s6, if the selected optimal numbered tool has the risk, an operator needs to manually confirm the risk, the optimal tool is adopted to execute the machining, or the next-level second optimal numbered tool is adopted to conduct machining; the device has the advantages that the service life of the cutter is monitored more accurately, the cutter is prevented from entering the stage with serious abrasion, and the product quality is further improved.

Description

Technical Field

[0001] The invention relates to the technical field of tool life calculation, and more specifically, to a metal cutting equipment scheduling method for calculating the remaining tool life. Background Art

[0002] For intelligent metal cutting equipment, such as CNC machine tools, one device will be equipped with multiple cutting tools, and there will be multiple cutting equipment in the production workshop. However, most manufacturing companies have the phenomenon of insufficient management of the remaining use time of CNC tools, which will waste tool resource utilization and affect product processing quality and efficiency. Therefore, an effective multi-tool monitoring and scheduling method is needed to better improve this production process and improve production efficiency.

[0003] According to Chinese patent CN202111417063.3, CNC tool monitoring method and system and scheduling management method and system, a method for monitoring and scheduling tools in CNC machine tools is mentioned. However, the remaining service life mentioned therein is the set service life of the blade when it leaves the factory. In fact, the wear and life of the blade are closely related to the cutting parameters. When the parameter settings are different, the service life of the blade is not constant.

[0004] This has limitations for the calculation of tool life, and the calculated life is not accurate enough.

[0005] Therefore, in order to solve the above technical problem, the present invention proposes a metal cutting equipment scheduling method for calculating the remaining life of a tool. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention aims to provide a metal cutting equipment scheduling method for calculating the remaining life of a tool.

[0007] To achieve the above object, the present invention provides the following technical solution: a metal cutting equipment scheduling method for calculating the remaining life of a tool, comprising the following steps:

[0008] S1: Get the tool number information;

[0009] S2: Input cutting parameters for the workpiece;

[0010] S3: Simulate and calculate the lifespan of each numbered tool when machining the workpiece;

[0011] S4: Selecting the optimal numbered tool according to the simulated processing conditions of each numbered tool;

[0012] S5: Determine whether the selected optimal numbered tool has risk, and if not, execute the current processing;

[0013] S6: If the selected optimal numbered tool has risks, the operator needs to manually confirm and use the optimal tool to perform the current processing, or postpone the processing to the next level of suboptimal numbered tool;

[0014] S7: If the operator manually confirms that the next-level suboptimal numbered tool is to be used for processing, the next-level suboptimal numbered tool is replaced with the optimal numbered tool, and the process returns to step S5;

[0015] In step S2, the cutting parameters include cutting speed, feed rate, and back cutting depth;

[0016] In step S3, the service life of each numbered tool when machining the workpiece is calculated as follows:

[0017]

[0018] Where T is life, v is cutting speed, f is feed rate, a p is the depth of cut, n, m, q are indices related to cutting speed, feed rate and depth of cut respectively, C T is a constant, which is related to the tool material, wear and processing conditions. T The calculation formula is:

[0019]

[0020] C0 is the last C value selection, V0 is the last wear amount, α is the wear influence coefficient, k and a are the adjustment coefficient and influence factor related to the influencing factor respectively, where C0, V0, α, k and a are all values ​​recorded in the host.

[0021] Furthermore, in step S2, the cutting parameters are various instructions set in advance, and the workers can quickly set the cutting parameters according to the instructions when using.

[0022] Furthermore, after the numbered tool completes the processing, the host will record the processing status and update the remaining life of the numbered tool after the processing is completed into the host.

[0023] Further, in step S4, the selection of the optimal numbered tool is based on the cutting parameters of the workpiece being processed this time. The host computer determines the number of the numbered tool that can directly complete the processing this time, and selects the optimal numbered tool from the screened numbered tools according to the cutting parameters of this processing;

[0024] According to the selected numbered tools, the adaptation values ​​of the cutting parameters of the last processing and the current processing are compared. The adaptation value of the reference cutting parameters is cutting speed> cutting depth> feed rate.

[0025] Furthermore, if the host computer does not find a suitable numbered tool, a prompt is sent to the staff.

[0026] Furthermore, in step S5, the method for judging whether the numbered tool is risky is to judge whether the life of the numbered tool used to complete the current processing exceeds 95% of the remaining life of the system. If it is higher than 95%, the numbered tool is judged as a risky tool, where the remaining life of the system is calculated based on the host.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] 1. In the present invention, by screening the cutting tools according to their actual working conditions and relevant cutting parameters during operation, the service life of the cutting tools can be monitored more accurately, thus preventing the cutting tools from entering a stage of severe wear and further improving product quality. DETAILED DESCRIPTION

[0029] The present invention provides a metal cutting equipment scheduling method for calculating the remaining life of a tool, comprising the following steps:

[0030] S1: Since the tool box of the machine tool is equipped with multiple tools, in order to distinguish the tools, it is necessary to obtain the tool number information first;

[0031] S2: Input cutting parameters for the workpiece;

[0032] Cutting parameters include cutting speed, feed rate, and back-cutting amount. Cutting parameters are various instructions set in advance. When using, workers can quickly set cutting parameters according to the instructions, which is convenient for workers to operate and can be quickly selected to reduce the tediousness of operation;

[0033] S3: Simulate and calculate the lifespan of each numbered tool when machining the workpiece;

[0034] It should be noted that when the tool is determined to enter the cutting state from the non-cutting state, the tool operation time is recorded from the moment the cutting state begins;

[0035] The calculation method of the simulation analysis of the life of each numbered tool after processing this workpiece is as follows:

[0036]

[0037] Where T is life, v is cutting speed, f is feed rate, a p It is the amount of back knife;

[0038] Cutting parameters such as cutting speed, feed rate, and depth of cut have an extremely important impact on tool durability. Therefore, it is necessary to collect these data to more accurately calculate tool wear and remaining usable time.

[0039] n, m, q are indices related to cutting speed, feed rate, and back cutting depth, respectively;

[0040] This can be done by collecting past cutting parameters and tool life data, which can come from past production records or by consulting materials (for example, the tool manufacturer's instruction manual will give the tool's service life when it continues to work under certain cutting parameters);

[0041] Since the relationship between tool life and cutting parameters is nonlinear according to the life formula, nonlinear regression is used to fit the collected data. Before fitting, the data needs to be preprocessed and standardized or normalized to reduce the impact of different dimensions on the regression; then, statistical software or programming tools, such as Python's scikit-learn library, are used for fitting to obtain the index value;

[0042] C T It is a constant, which is related to the tool material, wear and processing conditions;

[0043] Among them C T The calculation formula is:

[0044]

[0045] C0 is the last C value selection, V0 is the last wear amount, and α is the wear influence coefficient. k and a are the adjustment coefficient and influence factor related to the influencing factor, respectively. These values ​​are recorded by the host every time they work. For example, cutting speed is one of the processing conditions that affect the selection of C value. There is 1+K in the formula C *V C This one, K C It is the adjustment coefficient for the cutting speed when calculating the C value, V C This is a in the above formula. Since there may be multiple influencing factors and there may be different conventional expressions, in order to facilitate the summary of the C value calculation formula, the influencing factors are uniformly expressed as a, and the adjustment coefficients for the influencing factors are uniformly expressed as k;

[0046] Every time a tool completes a job, the remaining available time of the tool will be updated, and the remaining available time will be associated with the cutting parameters used in the last completed job and recorded in the host computer;

[0047] S4: Selecting the optimal numbered tool according to the simulated processing conditions of each numbered tool;

[0048] The selection of the best numbered tool is based on the cutting parameters of the workpiece being processed this time. The host computer will determine the number of the numbered tool that can directly complete the processing this time, and select the best numbered tool from the selected numbered tools according to the cutting parameters of this processing;

[0049] According to the selected numbered tools, compare the adaptation values ​​of the cutting parameters of the last processing and this processing, and select the numbered tools with the same cutting parameters. In the actual production process, such a condition is likely to be impossible to achieve. If there is no numbered tool with the same cutting parameters, the numbered tool with the closest cutting parameters to this work is preferred. The order of influence of cutting parameters is cutting speed> cutting depth> feed rate;

[0050] S5: Determine whether the selected optimal numbered tool has risk, and if not, execute the current processing;

[0051] The method of judging whether a numbered tool is risky is to judge whether the life of the numbered tool used to complete this processing exceeds 95% of the remaining life of the system. If it is higher than 95%, the numbered tool is judged as a risky tool, where the remaining life of the system is calculated based on the host;

[0052] The host will mark the risky tools that are screened out;

[0053] S6: If the selected optimal numbered tool has risks, the operator needs to manually confirm and use the optimal tool to perform the current processing, or postpone the processing to the next level of suboptimal numbered tool;

[0054] S7: If the operator manually confirms that the next-level suboptimal numbered tool is to be used for processing, the next-level suboptimal numbered tool is replaced with the optimal numbered tool, and the process returns to step S5;

[0055] After the numbered tool completes the processing, the host will record the processing situation and update the remaining life of the numbered tool after the processing is completed in the host.

[0056] If the host does not find a suitable numbered tool, a prompt will be sent to the staff to prompt them to replenish or replace the tool.

[0057] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any ordinary technician in the industry can smoothly implement the present invention as shown in the drawings and described above. However, any equivalent changes, modifications and evolutions made by technicians familiar with the profession without departing from the scope of the technical solution of the present invention using the technical content disclosed above are all equivalent embodiments of the present invention. At the same time, any equivalent changes, modifications and evolutions made to the above embodiments based on the essential technology of the present invention are within the protection scope of the technical solution of the present invention.

Claims

1. A metal cutting equipment scheduling method for calculating the remaining life of a tool, characterized in that: The following steps are involved: S1: Get the tool number information; S2: Input cutting parameters for the workpiece; S3: Simulate and calculate the lifespan of each numbered tool when machining the workpiece; S4: Selecting the optimal numbered tool according to the simulated processing conditions of each numbered tool; S5: Determine whether the selected optimal numbered tool has risk, and if not, execute the current processing; S6: If the selected optimal numbered tool has risks, the operator needs to manually confirm and use the optimal tool to perform the current processing, or postpone the processing to the next level of suboptimal numbered tool; S7: If the operator manually confirms that the next-level suboptimal numbered tool is to be used for processing, the next-level suboptimal numbered tool is replaced with the optimal numbered tool, and the process returns to step S5; In step S2, the cutting parameters include cutting speed, feed rate, and back cutting depth; In step S3, the service life of each numbered tool when machining the workpiece is calculated as follows: Where T is life, v is cutting speed, f is feed rate, a p is the depth of cut, n, m, q are indices related to cutting speed, feed rate and depth of cut respectively, C T is a constant, which is related to the tool material, wear and processing conditions. T The calculation formula is: C0 is the last C value selected, V0 is the last wear amount, α is the wear influence coefficient, k and a are the adjustment coefficient and influence factor related to the influencing factor respectively, where C0, V0, α, k and a are all values ​​recorded in the host.

2. A metal cutting equipment scheduling method for calculating the remaining life of a tool according to claim 1, characterized in that: In step S2, the cutting parameters are various instructions set in advance, and the worker can quickly set the cutting parameters according to the instructions when using.

3. A metal cutting equipment scheduling method for calculating the remaining life of a tool according to claim 2, characterized in that: After the numbered tool completes the processing, the host will record the processing situation and update the remaining life of the numbered tool after the processing is completed in the host.

4. A metal cutting equipment scheduling method for calculating the remaining life of a tool according to claim 3, characterized in that: In step S4, the selection of the optimal numbered tool is based on the cutting parameters of the workpiece being processed this time. The host computer determines the number of the numbered tool that can directly complete the processing this time, and selects the optimal numbered tool from the screened numbered tools according to the cutting parameters of this processing; According to the selected numbered tools, the adaptation values ​​of the cutting parameters of the last processing and the current processing are compared. The adaptation value of the reference cutting parameters is cutting speed> cutting depth> feed rate.

5. A metal cutting equipment scheduling method for calculating the remaining life of a tool according to claim 4, characterized in that: If the host does not find the appropriate numbered tool, a prompt will be sent to the staff.

6. A metal cutting equipment scheduling method for calculating the remaining life of a tool according to claim 5, characterized in that: In step S5, whether the numbered tool is risky is determined by judging whether the life of the numbered tool used to complete the current processing exceeds 95% of the remaining life of the system. If it is higher than 95%, the numbered tool is judged to be a risky tool, where the remaining life of the system is calculated based on the host.

7. A metal cutting equipment scheduling method for calculating the remaining life of a tool according to claim 6, characterized in that: The host will mark the risky tools that are screened out.

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