Tool monitoring method and tool monitoring device

Abstract

The application provides a tool monitoring method and a tool monitoring device. The tool monitoring method comprises: acquiring machining process data formed by a tool machining a plurality of products and quality detection results of each detection point of each product; restoring the actual service life of the tool based on the machining process data; establishing a service life quality mapping sequence of the actual service life and the quality detection results based on the actual service life and the quality detection results; determining a service life critical point representing performance degradation of the tool based on the service life quality mapping sequence; and generating a service life warning value of the tool based on the service life critical point, so as to accurately evaluate the tool state, scientifically replace the tool, fully utilize the tool to reduce the tool cost, reduce the generation of high-frequency defective products, and ensure the yield of the products.

Description

Technical Field

[0001] This application relates to the field of tool life technology, specifically to a tool monitoring method and a tool monitoring device. Background Technology

[0002] CNC (Computer Numerical Control) machine tools are one of the core equipment in modern manufacturing, and their machining accuracy and efficiency directly depend on the condition of the cutting tools. In product manufacturing, to control machining quality and cost, factories typically set a fixed maximum tool life based on the standard life values ​​recommended by the cutting tool supplier and combined with experience. When the tool reaches this set life, the system alarms to prompt replacement.

[0003] However, firstly, in actual machining, tool wear is affected by various dynamic factors such as spindle speed, machine tool performance, and workpiece material. Fixed tool life values ​​cannot adapt to complex and changing working conditions, often leading to premature tool replacement while still in good condition, resulting in resource waste; or failure to replace tools in time when their performance has deteriorated, causing batches of defective products. Secondly, to balance cost and risk, on-site operators often rely on experience to manually reset the tool life counter after the tool reaches its set life and continue using it, causing the tool life information recorded by the machine tool to be distorted and unable to reflect the true intensity of tool use, rendering any predictions or analyses based on this distorted data meaningless. Finally, although the quality inspection results after CNC machining can be obtained in real time through the machine tool's in-machine inspection function or external equipment inspection, these quality inspection results lack an effective correlation with the distorted tool life data and cannot be used to assess the tool condition. Summary of the Invention

[0004] To address the problem of weak correlation between tool life and quality inspection results, making it impossible to accurately assess tool condition, this application provides a tool monitoring method and a tool monitoring device.

[0005] This application provides a tool monitoring method. The tool monitoring method includes: acquiring machining process data generated by the tool processing multiple products and quality inspection results for each inspection point of each product; reconstructing the true service life of the tool based on the machining process data; establishing a life-quality mapping sequence related to the true service life and the quality inspection results based on the true service life and the quality inspection results; determining a life-critical point characterizing the performance degradation of the tool based on the life-quality mapping sequence; and generating a life-warning value for the tool based on the life-critical point. In some embodiments, the machining process data includes tool length and machine tool life recorded on the machine. The step of reconstructing the true tool life based on the machining process data includes: monitoring changes in the tool length to determine whether the tool has actually been replaced; resetting the machine tool life recorded on the machine to zero when the tool has actually been replaced; and adding the change in the machine tool life recorded on the machine during the current machining cycle to the machine tool life recorded on the machine, and using this sum as the true tool life.

[0006] In some embodiments, monitoring the change in the tool length to determine whether the tool has actually been replaced includes: determining that the tool has actually been replaced when the change in the tool length is greater than or equal to a preset length threshold; and determining that the tool has not actually been replaced when the change in the tool length is less than the preset length threshold.

[0007] In some embodiments, the tool monitoring method further includes: acquiring the quality value of each of the detection points of the product; comparing the quality value with the detection specification range; determining that the quality detection result of the detection point is good when the quality value is within the detection specification range; and determining that the quality detection result of the detection point is poor when the quality value exceeds the detection specification range.

[0008] In some embodiments, the actual service life is a product processing serial number formed by sequentially numbering each processed product. The step of establishing a life-quality mapping sequence related to the actual service life of the tool and the quality inspection results based on the actual service life and the quality inspection results includes: dividing the tool into multiple consecutive life-life intervals according to preset rules based on the product processing serial number; determining the defect rate of the inspection point for each product within each life-life interval based on the product processing serial number and the corresponding quality inspection results, thus obtaining an initial defect rate sequence; and smoothing the initial defect rate sequence to obtain the life-quality mapping sequence.

[0009] In some implementations, the life quality mapping sequence includes life points associated with the life interval and smoothed defect rates corresponding to the life points. The life critical point includes a risk life point. Determining the life critical point characterizing the tool performance degradation based on the life quality mapping sequence includes: selecting, based on the life quality mapping sequence and a preset tool life, the smoothed defect rate matching the preset tool life from the life quality mapping sequence; and determining a risk life threshold based on the smoothed defect rate matching the preset tool life and a preset life limitation coefficient. For each lifetime point in the lifetime quality mapping sequence, the smoothed defect rate is sequentially determined to be no less than the risk lifetime threshold; and if the smoothed defect rate for N consecutive lifetime points is no less than the risk lifetime threshold, and N is no less than a preset number, then the Nth lifetime point is determined as the risk lifetime point.

[0010] In some implementations, the lifespan critical point further includes a limit lifespan point. Determining the lifespan critical point characterizing the tool performance degradation based on the lifespan quality mapping sequence further includes: using a preset algorithm to divide the lifespan quality mapping sequence into a first dataset and a second dataset, wherein the maximum value of the smoothed defect rate in the first dataset is less than or equal to the minimum value of the smoothed defect rate in the second dataset, and the maximum value of the lifespan point corresponding to the smoothed defect rate in the first dataset is less than the minimum value of the lifespan point corresponding to the smoothed defect rate in the second dataset; and taking the starting point of the lifespan point in the second dataset as the limit lifespan point.

[0011] In some implementations, each product has multiple detection points, multiple quality inspection results, and correspondingly, multiple sets of lifespan quality mapping sequences. The tool monitoring method further includes: based on the set of smoothed defect rates {r1, r2, ... r...} in each set of lifespan quality mapping sequences. n}, calculate the set that satisfies r i+1 ≥k·r i The number of weakly increasing defect rates at detection points, where k is a preset coefficient, r i The smoothed defect rate corresponding to the i-th lifetime point is represented, i=1,2,...,n; if the number of defect rates at the weakly increasing detection points is greater than or equal to a preset threshold, it is determined that the lifetime quality mapping sequence exhibits a preset positive correlation trend; and, based on the lifetime quality mapping sequence exhibiting a preset positive correlation trend, the following is executed: "Based on the lifetime quality mapping sequence, determine the lifetime critical point characterizing the performance degradation of the tool".

[0012] In some implementations, the lifespan quality mapping sequence exhibiting a preset positive correlation trend is multiple, corresponding to multiple risk lifespan points and multiple limit lifespan points, and the lifespan warning value includes a risk lifespan warning value and a limit lifespan warning value. Generating the tool's lifespan warning value based on the lifespan critical point includes: using the minimum value among the multiple risk lifespan points as the tool's risk lifespan warning value; and using the minimum value among the multiple limit lifespan points as the tool's limit lifespan warning value.

[0013] In some embodiments, the tool monitoring method further includes: sending a reminder signal to the machining equipment when the actual service life of the current tool reaches the risk life warning value, so that the monitoring interface of the machining equipment can provide a prompt; or, sending a tool change signal to the machining equipment when the actual service life of the current tool reaches the limit life warning value, so as to trigger an alarm of the machining equipment and prompt for tool change.

[0014] In some embodiments, the monitoring method further includes: if the limit lifetime point is less than or equal to the risk lifetime point, then removing the limit lifetime point; taking all lifetime points before the lifetime point corresponding to the risk lifetime point in the lifetime quality mapping sequence and the corresponding smoothed defect rate as a stable phase, and taking all lifetime points after the lifetime point corresponding to the risk lifetime point in the lifetime quality mapping sequence and the corresponding smoothed defect rate as an increasing phase; and when the maximum value of the smoothed defect rate in the increasing phase exceeds a preset multiple of the maximum value of the smoothed defect rate in the stable phase, then correcting the risk lifetime point to a new limit lifetime point.

[0015] In some embodiments, the monitoring method further includes: taking all life points between the risk life point and the extreme life point in the life quality mapping sequence and their corresponding smoothed defect rates as an increasing phase; taking all life points before the life point corresponding to the risk life point in the life quality mapping sequence and their corresponding smoothed defect rates as a stable phase; and taking all life points after the life point corresponding to the extreme life point in the life quality mapping sequence and their corresponding smoothed defect rates as an explosive phase; and if the maximum smoothed defect rate in the explosive phase does not reach a preset multiple of the maximum smoothed defect rate in the stable phase, then canceling the extreme life point.

[0016] Secondly, this application provides a tool monitoring device, which includes a memory and a processor. The memory stores instructions. The instructions stored in the memory are executed by the processor to implement the tool monitoring method described in any of the above embodiments.

[0017] The tool monitoring method and device provided by this invention reconstruct the true service life of the tool under monitoring through machining process data, avoiding the distortion of tool life information caused by operators manually resetting the life counter based on experience. At this point, the life-quality mapping sequence established from the true service life and quality inspection results can provide an accurate data source for tool monitoring. Then, based on the life-quality mapping sequence, the life critical point is determined, and a life warning value for the tool is generated. Subsequent machining with the same tool can be performed according to the life warning value. By accurately assessing the tool condition and scientifically replacing tools, the tool is fully utilized, tool costs are reduced, and the generation of high-frequency defective products is decreased, ensuring a high product yield.

[0018] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0019] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, wherein: Figure 1 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 2 This is a schematic diagram illustrating the variation of the lifespan of the recording blade in some embodiments of this application; Figure 3 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 4 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 5 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 6 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 7 This is a mapping table of actual service life and quality test results, a schematic table of initial defect rate sequence, and a schematic table of service life quality mapping sequence for some embodiments of this application. Figure 8 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 9 This is a schematic diagram showing the changes in lifetime point and smoothed defect rate in some embodiments of this application; Figure 10 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 11 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 12 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 13 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 14 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 15 This is a flowchart illustrating some embodiments of the tool monitoring method of this application; Figure 16 This is a schematic diagram of the structure of a tool monitoring device according to some embodiments of this application.

[0020] The reference numerals in the detailed embodiments are as follows: Tool monitoring device 100; Memory 10; Processor 30. Detailed Implementation

[0021] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0022] In the description of this application, it should be understood that the terms "center", "length", "upper", "lower", "front", "rear", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0023] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0024] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0025] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0026] CNC machine tools are one of the core pieces of equipment in modern manufacturing, and their machining accuracy and efficiency directly depend on the condition of the cutting tools. To control machining quality and cost, factories typically set a fixed maximum tool life (the theoretical usable time of the tool under specific test conditions such as ideal spindle speed, workpiece material, and cooling conditions) based on the standard life value recommended by the tool supplier and combined with experience. When the tool reaches this set life, the system alarms to prompt replacement.

[0027] However, firstly, in actual machining, tool wear is affected by various dynamic factors such as spindle speed, machine tool performance, and workpiece material. Fixed tool life values ​​cannot adapt to complex and changing working conditions, often leading to premature tool replacement while still in good condition, resulting in waste; or failure to replace tools in time when their performance has deteriorated, causing batch defects. Secondly, to balance cost and risk, on-site operators often manually reset the tool life counter and continue using the tool after it reaches the set life based on experience, causing the tool life information recorded by the machine tool to be distorted and unable to reflect the actual usage intensity of the tool, rendering any predictions or analyses based on this distorted data meaningless. Finally, although the quality inspection results after CNC machining can be obtained in real time through the in-machine inspection function of the CNC machine tool or the inspection of external equipment, these quality inspection results lack an effective correlation with the distorted tool life data and cannot be used to evaluate the tool condition. To solve the above problems, this application provides a tool monitoring method ( Figure 1 , Figures 3 to 6 , Figure 8 , Figures 10 to 15As shown) and the monitoring device 100 for the cutting tool Figure 10 (As shown).

[0028] Please refer to Figure 1 and Figure 2 This application provides a tool monitoring method. The tool monitoring method includes: 01: Obtain the processing data generated by the cutting tool on multiple products and the quality inspection results of each inspection point of each product; 02: Reconstruct the true service life of the cutting tool based on machining process data; 04: Based on actual service life and quality test results, establish a life-quality mapping sequence related to actual service life and quality test results; 06: Based on the life-quality mapping sequence, determine the life critical point characterizing tool performance degradation; and, 08: Based on the lifespan critical point, generate the lifespan warning value for this tool. Correspondingly, please combine Figure 16 This application provides a tool monitoring device 100, which is an apparatus for tool monitoring methods. The monitoring device 100 includes a memory 10 and a processor 30. The memory 10 is used to store instructions, and optionally, to store instructions corresponding to the execution of the tool monitoring method. The memory 10 is electrically connected to the processor 30 and connects various parts of the entire monitoring device 100 through various interfaces and lines. The processor 30 monitors the tool by running or loading instructions stored in the memory 10 and calling data stored in the memory 10. Specifically, the processor 30 executes methods 01, 02, 04, 06, and 08. More specifically, the processor 30 is used to: acquire machining process data formed by the tool processing multiple products and quality inspection results of each inspection point of each product; reconstruct the true service life of the tool based on the machining process data; establish a life-quality mapping sequence related to the true service life and quality inspection results based on the true service life and quality inspection results; determine the life-critical point characterizing the performance degradation of the tool based on the life-quality mapping sequence; and generate a life-warning value for the tool based on the life-critical point.

[0029] It should be noted that a cutting tool is a component with a geometrically shaped cutting edge that removes material from a product through physical shearing or compression. Cutting tools include turning tools, end mills, drills, broaches, etc. The cutting tool moves under the drive of the spindle through its connection to the spindle, flexibly performing the machining process. For example, in the case of a CNC machine tool used for milling, the spindle clamps the end mill (tool) and drives it to rotate at high speed to efficiently and accurately achieve the milling process on the product. It should be noted that, depending on the scale of the machining, the number of cutting tools of the same model can be one or more. The term "one cutting tool" as used below refers to a collective term for one or more cutting tools of the same model.

[0030] Products can be semi-finished products or raw materials at any step in the machining process, or finished products after machining. During the machining process, a CNC machine tool can use one or more cutting tools, and the CNC machine tool typically performs machining in cycles to process multiple products sequentially. During the machining process, one cutting tool can process one or more machining points on the product, and a machining point can also be processed by one or more cutting tools.

[0031] As can be understood, a machining point refers to the specific spatial location in the CNC machine coordinate system where the tool reference point (such as the tool tip or tool position point) makes cutting contact with the product surface and removes material. It is typically uniquely determined by three-dimensional coordinate values ​​(X, Y, Z) and the corresponding machining command. Inspection points refer to the specific content inspected during the machining quality inspection process for each machining point.

[0032] The processor 30 acquires machining process data generated by the sequential machining process performed by the tool on multiple products. This machining process data includes at least one of the following: CNC machine number, tool number, machine-recorded tool life, tool length, machining start time, and machining end time. Simultaneously, the processor 30 also acquires the quality inspection results for each inspection point. For example, the data used to determine the quality inspection results includes at least one of the following: CNC machine number, inspection start time, inspection point code, and inspection result value. It should be noted that the quality inspection results can be obtained from the CNC machine's in-machine inspection, from external inspection equipment, or from a combination of in-machine and external inspection data; this application does not impose any limitations on this. For example, the quality inspection results include whether the product quality after machining is normal or abnormal, good or poor, or qualified or unqualified.

[0033] Furthermore, to avoid situations where the machine's recorded tool life does not reflect the actual number of products processed by the tool due to operator manual adjustment of tool life or other factors, the tool monitoring method in this application also uses processor 30 to analyze and process machining process data to restore the actual usage of the tool, i.e., to restore the tool's true lifespan. It should be noted that the true lifespan is the number of products actually processed by a tool from its initial use to the current moment. Using the true lifespan allows for a more accurate determination of subsequent tool lifespan warning values.

[0034] The life-quality mapping sequence is a sequence used to characterize the correlation between actual service life and quality inspection results. It can be understood that the life-quality mapping sequence accurately reflects the level of quality inspection results that will be reached due to the deterioration of the tool condition when the actual service life reaches a certain level. It can be understood that the longer the actual service life, the greater the possibility of damage, and the more defective results there are in the quality inspection. Based on the actual service life and quality inspection results, the processor 30 calculates the defect rate according to the quality inspection results and constructs the relationship between the actual service life and the defect rate, thereby establishing the life-quality mapping sequence.

[0035] At this point, the lifespan quality mapping sequence accurately reflects the decay of the defect rate with the actual service life, i.e., the degradation of tool performance. If the degree of tool performance degradation is high, i.e., the defect rate is too high (e.g., exceeding a certain set threshold), then the tool is determined to be unusable. At this time, the processor 30 determines a lifespan critical point based on the lifespan quality mapping sequence, using this critical point to characterize a significant degradation in tool performance.

[0036] Furthermore, since the tool may perform machining at multiple machining points, the lifespan critical point of a certain tool may be multiple depending on the detection point (corresponding to the machining point). It can be understood that whether to decommission the tool should be determined by considering all the tool's corresponding lifespan critical points. Therefore, the processor 30 generates a lifespan warning value for the tool based on the lifespan critical points. The lifespan warning value is the lifespan value determined after comprehensively considering all lifespan critical points, indicating that the tool should be scrapped. For example, when the actual lifespan of the tool reaches the lifespan warning value, the processor 30 can trigger a warning or tool change command to ensure machining quality.

[0037] The tool monitoring method and tool monitoring device 100 provided by this invention restore the true service life of the tool to be monitored through machining process data, avoiding the distortion of tool life information caused by operators manually resetting the life counter based on experience. At this time, the life quality mapping sequence established by the true service life and quality inspection results can provide an accurate data source for tool monitoring. Then, the life critical point is determined based on the life quality mapping sequence, and then the life warning value of the tool is generated. Subsequent identical tools can be processed according to the life warning value. By accurately assessing the tool condition, scientifically changing tools, making full use of tools, reducing tool costs, reducing the generation of high-frequency defective products, and ensuring the product yield rate.

[0038] Please refer to Figures 1 to 3 In some implementations, the machining process data includes tool length and machine-recorded tool life. 02: Reconstructing the actual tool life based on the machining process data includes: 021: Monitor changes in tool length to determine if the tool has actually been replaced; 023: When a tool is actually replaced, reset the machine's tool life record to zero; and, 025: If the tool has not been actually replaced, the change in the tool life recorded by the machine during the current machining cycle is added to the tool life recorded by the machine, and this sum is taken as the actual service life.

[0039] Furthermore, please combine Figure 16 The processor 30 is also used to execute the methods in 021, 023, and 025. Specifically, the processor 30 is configured to: monitor changes in tool length to determine whether an actual tool replacement has occurred; when an actual tool replacement has occurred, reset the machine tool life record to zero; and when no actual tool replacement has occurred, add the change in machine tool life recorded during the current machining cycle to the machine tool life record, and use this as the actual service life.

[0040] Specifically, regarding the situation described above where the operator manually adjusted the machine's recorded tool life, to determine the true tool life, it's first necessary to clarify whether the change in the recorded tool life was due to a tool change (in which case the recorded tool life will return to zero) or due to the operator's adjustment (in which case the recorded tool life will return to zero or decrease to a value other than zero). At this point, the logic for determining whether a tool change has occurred needs to be clearly defined. Because both the tool and the tool holder are replaced during a CNC tool change, and since the depth to which each tool is inserted into the tool holder is a random number, the length of each tool extending out of the tool holder is not constant. Therefore, monitoring changes in the tool length can determine whether an actual tool change has occurred.

[0041] If the processor 30 determines that an actual tool change has occurred, the control machine will reset the tool life record to zero. For example... Figure 2As shown, if it is determined that the tool was actually replaced at point B, then the machining before point B is the machining performed by the old tool, and the machining after point B is the machining performed by the new tool. At point B, the tool life recorded by the machine will be reset to zero, and the actual service life after point B will be recalculated.

[0042] If the processor 30 determines that no actual tool replacement has occurred, i.e., the operator manually adjusted the recorded tool life as described above, then the processor 30 adds the change in the recorded tool life during the current machining cycle to the recorded tool life before the tool length change was monitored, and uses the sum as the actual tool life. For example... Figure 2 As shown, if it is determined that the tool was not actually replaced at point A, then the machining before and after point A is all performed with the same tool. Therefore, the actual service life of the tool at this time is the sum of the change in tool life recorded by the machine tool within the current machining cycle and the tool life recorded by the machine tool before the change in tool length, i.e., 200 + 90 = 280. If it is determined that the tool was not actually replaced at point B, then the machining before and after point B is all performed with the same tool. Therefore, the actual service life of the tool at this time is the sum of the change in tool life recorded by the machine tool within the current machining cycle and the tool life recorded by the machine tool before the change in tool length, i.e., 200 + 80 (change in tool life recorded by the machine tool within the machining cycle after point A) + 90 (change in tool life recorded by the machine tool within the current machining cycle after point B) = 370.

[0043] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, the tool length is used to determine whether the tool has actually been replaced. Then, the tool life is recorded by the machine tool to restore the real service life for different situations, so as to ensure that the real service life can truly reflect the number of products processed by the tool, ensure the authenticity of the generated life quality mapping sequence, and thus ensure the reliability of the obtained life warning value, providing a reliable basis for subsequent tool monitoring. Please refer to Figures 1 to 4 In some implementations, 021: Monitoring changes in tool length to determine whether a tool has actually been replaced includes: 0211: When the change in tool length is greater than or equal to a preset length threshold, it is determined that an actual tool replacement has occurred; and, 0213: If the change in the monitored tool length is less than the preset length threshold, it is determined that the tool has not actually been replaced.

[0044] Furthermore, please combine Figure 16The processor 30 is also used to execute the methods in 0211 and 0213. Specifically, the processor 30 is configured to: determine that an actual tool replacement has occurred when the change in tool length is greater than or equal to a preset length threshold; and determine that no actual tool replacement has occurred when the change in tool length is less than the preset length threshold.

[0045] Specifically, as mentioned above, when a CNC machine tool is changing tools, since the length of each tool extending from the tool holder is not constant, a significant change in tool length indicates an actual tool change. The preset length threshold is the minimum change in tool length that occurs when an actual tool change takes place. This preset length threshold is a fixed value; it can be an unmodifiable value stored in the memory 10 by the monitoring device 100 before leaving the factory, or a value written, adjusted, or replaced by the operator in the memory 10.

[0046] If the processor 30 detects a change in tool length greater than or equal to a preset length threshold, the processor 30 determines that the change in tool length is significant, and thus determines that the tool has actually been replaced; if the processor 30 detects a change in tool length less than the preset length threshold, the processor 30 determines that the change in tool length is small, usually caused by measurement error, and thus determines that the tool has not actually been replaced.

[0047] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, by monitoring the relative magnitude of the change in tool length and the preset length threshold, it is possible to accurately determine whether the tool has actually been replaced, so as to ensure the accuracy and reliability of the restoration process of the real service life, and ensure that an accurate life warning value is obtained in the future, thereby providing a reliable basis for subsequent tool monitoring. Please refer to Figure 1 and Figure 5 In some embodiments, the tool monitoring method further includes: 031: Obtain the quality value of each testing point of the product; 033: Compare the quality value with the testing specification range; 035: When the quality value is within the specified range, the quality inspection result of the inspection point is deemed good; and, 037: When the quality value exceeds the test specification range, the quality test result of the test point is judged as unqualified.

[0048] Furthermore, please combine Figure 16The processor 30 is also used to execute the methods in 031, 033, 035 and 037. Specifically, the processor 30 is configured to: acquire the quality value of each inspection point of the product; compare the quality value with the inspection specification range; determine the quality inspection result of the inspection point as good when the quality value is within the inspection specification range; and determine the quality inspection result of the inspection point as poor when the quality value exceeds the inspection specification range.

[0049] Specifically, the following describes the method for determining the quality inspection results for each inspection point of each product. For each inspection point, the processor 30 obtains the quality value of each inspection point of the product through internal or external inspection data. It can be understood that the quality value is the specific inspection data of that inspection point in the inspection data, such as the product's length value, depth value, angle value, etc.

[0050] The inspection specification range is the range of allowable quality values ​​for a specific inspection point under the condition that the processing quality meets the requirements. The processor 30 compares the quality values ​​with the inspection specification range and determines the quality inspection result of that inspection point based on the comparison result.

[0051] Specifically, if the processor 30 determines that the quality value is within the inspection specification range, the processor 30 determines that the machining of the inspection point by one or more cutting tools meets the quality requirements, thus judging the quality inspection result of the inspection point as good; if the processor 30 determines that the quality value exceeds the inspection specification range, the processor 30 determines that the machining of the inspection point by one or more cutting tools does not meet the quality requirements, thus judging the quality inspection result of the inspection point as poor. In this case, the defect rate can be obtained by statistically analyzing a certain number of quality inspection results. To facilitate the subsequent processing of the quality inspection results by the processor 30, such as... Figure 7 As shown in (A), "0" indicates that the quality inspection result of the product processed by the tool is good; "1" indicates that the quality inspection result of the product processed by the tool is poor. Of course, in other embodiments, letters, characters or numbers can also be used to represent good and poor.

[0052] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, by comparing the quality value of the detection point with the detection specification range, the quality detection result of the detection point can be accurately determined, so as to use the quality detection result to establish a life quality mapping sequence and provide data support for the determination of life warning value. At this time, the tool monitoring method has good accuracy and reliability. Please refer to Figure 1 , Figure 6 and Figure 7In some implementations, the actual service life is the product processing sequence number formed by sequentially numbering each processed product. 04: Based on the actual service life and quality inspection results, establish a life-quality mapping sequence with the actual service life and quality inspection results of the cutting tool, including: 041: Based on the product processing serial number, it is divided into multiple consecutive lifespan intervals according to preset rules; 043: Based on the product processing serial number and corresponding quality inspection results within each lifespan interval, determine the defect rate at each inspection point for the product within each lifespan interval, thus obtaining an initial defect rate sequence; and, 045: Smooth the initial defect rate sequence to obtain the life quality mapping sequence.

[0053] Furthermore, please combine Figure 16 The processor 30 is also configured to execute the methods in 031, 033, 035, and 037. Specifically, the processor 30 is configured to: divide the product processing serial number into multiple consecutive lifespan intervals according to preset rules; determine the defect rate of the inspection points of the corresponding products in each lifespan interval based on the product processing serial number and the corresponding quality inspection results, thereby obtaining an initial defect rate sequence; and smooth the initial defect rate sequence to obtain a lifespan quality mapping sequence.

[0054] Specifically, in the subsequent product processing, the processing sequence number formed by sequentially numbering each product processed is defined as the actual service life of the tool. For example, when the tool processes the first product, the processing sequence number is marked as 1 (i.e., the actual service life is 1); when the tool processes the second product, the processing sequence number is marked as 2 (i.e., the actual service life is 2), and so on until the tool is replaced. For an example, please refer to [reference needed]. Figure 7 (A) The processing data also includes the start processing time, end processing time and inspection point code (such as FAI49, FA509, FAI40...). During the start processing time and end processing time, the product processing serial number and the corresponding quality inspection results are associated to form a mapping table between the actual service life and the quality inspection results.

[0055] The preset rule is a method for dividing the product processing serial number between the start and end processing times. It can be understood that the preset rule divides the actual service life into multiple sequentially distributed stages. The preset rule is a fixed, pre-defined rule, which can be an unmodifiable rule stored in the memory 10 before leaving the factory by the monitoring device 100, or a rule written, adjusted, or replaced by the operator in the memory 10. In this case, the processor 30 divides the product processing serial number into multiple consecutive service life intervals according to the preset rule. In some embodiments, the service life interval is divided into intervals of 50 within the product processing serial number. In other embodiments, the preset rule is: data in the product processing serial number less than or equal to 300 is divided into service life intervals of 50; data in the product processing serial number greater than 300 is divided into service life intervals of 100 each. In other embodiments, the service life interval can also be divided into intervals of 30, 80, 150, etc., which can be set according to the probability of tool wear.

[0056] At this point, within any given lifespan interval, the specific value of the product processing serial number increases sequentially. Each product processing serial number corresponds to a unique quality inspection result. The processor 30 calculates the defect rate at the inspection points corresponding to each lifespan interval based on the quality inspection results, thereby constructing an initial defect rate sequence from the defect rates at the inspection points corresponding to the same tool in each lifespan interval, such as... Figure 7 As shown in (B). Here, "R1" represents the defect rate of tool 1 at the inspection point with code FAI49, when the lifespan is between 0-50. "R1" is determined by... Figure 7 (A) shows the quality inspection results for product processing serial numbers from 1 to 50 at the inspection point with code FAI49, obtained through statistical analysis and calculation. "R2" represents the defect rate of tool 1 at the inspection point with code FAI49, when its lifespan is between 51 and 100. "R2" is determined by... Figure 7 In (A), the quality inspection results of products with processing serial numbers from 51 to 100 at the inspection point with code FAI49 were obtained through statistics and calculation.

[0057] It should be noted that the defect rate at the inspection point here refers to the overall defect rate of a specific tool at a specific inspection point within a specific lifespan. For example, if there are 100 toolboxes of tool model 1, then each tool will have a corresponding defect rate... Figure 7In Table (A), at this time, the defect rate of tool 1 at the inspection point with code FAI49 and a life range of 0-50 is: the ratio of the total number of "defects" (e.g., 123) of 100 tools 1 in the quality inspection results of product processing serial numbers from 1 to 50 to the total number of workpieces processed in the life range of 0-50, i.e., 123 / (50*100) = 0.0246.

[0058] Furthermore, to avoid excessive concentration of defect rates within a certain lifespan range, which could reduce data reliability, processor 30 smooths the initial defect rate sequence to remove intervals and uses an average value to more accurately reflect the relationship between the defect rate and the actual lifespan. The resulting smoothed sequence is a lifespan-quality mapping sequence, such as... Figure 7 The combination of each row in (C) and the first row is shown.

[0059] For example, the moving average algorithm is as follows: Let Figure 7 (B) shows the set of defect rates at detection points in the initial defect rate sequence as {R1, R2, ..., R}. n}, where R i Let represent the defect rate of the detection point corresponding to the i-th lifespan interval, where i = 1, 2, ..., n; and let {r1, r2, ..., rn} be the set of smoothed defect rates (i.e., the set of smoothed defect rates described below) in the smoothed lifespan quality mapping sequence. n-1 In}, the j-th r j The formula for calculating the value is: r j =(R j +R j+1 ) / 2, where j=1,2,……,n-1.

[0060] Therefore, in the tool monitoring method and tool monitoring device 100 provided by this invention, a life quality mapping sequence with good accuracy and high reliability is obtained through the division of life intervals, the construction of an initial defect rate sequence, and smoothing processing. At this time, the determination of the life critical point and the data source of the life warning value are relatively reliable, which fully ensures the authenticity of the life warning value, improves the utilization rate of the tool, and effectively guarantees the processing quality and yield of the product. Please refer to Figure 1 , Figure 8 and Figure 9 In some implementations, the life quality mapping sequence includes life points associated with a life range and smoothed defect rates corresponding to those life points. Life critical points include risky life points. 06: Based on the life quality mapping sequence, determine the life critical points characterizing tool performance degradation, including: 061: Based on the life quality mapping sequence and the preset tool life, select the smoothed defect rate that matches the preset tool life from the life quality mapping sequence; 062: Determine the risk life threshold based on the smoothed defect rate matched with the preset tool life and the preset limited life coefficient; 063: For each lifetime point in the lifetime quality mapping sequence, sequentially determine whether the smoothed defect rate is not less than the risk lifetime threshold; and, 064: If the smoothed failure rate corresponding to N consecutive lifespan points is not less than the risk lifespan threshold, and N is not less than the preset number, then the Nth lifespan point is determined as the risk lifespan point.

[0061] Furthermore, please combine Figure 16 The processor 30 is also configured to execute the methods in 063, 062, 063, and 064. Specifically, the processor 30 is configured to: select a smoothed defect rate matching the preset tool life from the life quality mapping sequence based on the life quality mapping sequence; determine a risk life threshold based on the smoothed defect rate matching the preset tool life and a preset life limit coefficient; sequentially determine whether the smoothed defect rate corresponding to each life point in the life quality mapping sequence is not less than the risk life threshold; and if the smoothed defect rates corresponding to N consecutive life points are not less than the risk life threshold, and N is not less than a preset number, then the Nth life point is determined as a risk life point.

[0062] For details, please refer to Figure 7 (C) The lifespan quality mapping sequence includes the lifespan point obtained from the lifespan interval in the first row and the smoothed defect rate of the detection point in each of the following rows. It can be understood that the lifespan point is associated with the lifespan interval, and the smoothed defect rate is the same as the smoothed defect rate of the detection point, and there is a unique correspondence between them and the lifespan point.

[0063] The risk lifespan point represents the point in the tool's lifespan where the initial deterioration of its condition may lead to a decrease in machining quality; this is the number of products processed, also known as the product machining sequence number mentioned above. The preset tool lifespan is the lifespan of a tool provided by the manufacturer at the time of manufacture, corresponding to the point where significant performance deterioration is likely to occur. In this case, by comparing the lifespan points in the lifespan-quality mapping sequence with the preset tool lifespan, the smoothed defect rate corresponding to the lifespan point in the lifespan-quality mapping sequence that matches the preset tool lifespan is selected as the smoothed defect rate.

[0064] For example, if the preset tool life is 150, then find the closest tool life point to 150, and use the smoothed defect rate corresponding to this tool life point and the tool life points before this point as the smoothed defect rate that matches the preset tool life. For example, using... Figure 7(C) Taking the tool 1 at the FAI49 detection point as an example, the selected smoothed defect rates that match the preset tool life are r1, r2 and r3.

[0065] The preset lifespan limit coefficient is a coefficient used to determine the risk lifespan threshold. The preset lifespan limit coefficient is a fixed, pre-set value; it can be an unmodifiable value stored in the memory 100 before the monitoring device 100 leaves the factory, or a value written, adjusted, or replaced by the operator in the memory 10. The processor 30 obtains the risk lifespan threshold based on the smoothed defect rate matched with the preset tool lifespan and the preset lifespan limit coefficient. For example, the risk lifespan threshold is the product of the maximum smoothed defect rate matched with the preset tool lifespan and the preset lifespan limit coefficient.

[0066] Further, the processor 30 compares the smoothed defect rate corresponding to each lifetime point in the lifetime quality mapping sequence with the risk lifetime threshold in turn, and determines whether each smoothed defect rate is not less than, i.e., greater than or equal to, the risk lifetime threshold. At this point, if the processor 30 determines that the smoothed defect rate corresponding to N consecutive lifetime points is not less than the risk lifetime threshold, the processor 30 stops the judgment. Here, N is a pre-set fixed value, and N is not less than a preset number.

[0067] At this point, the processor 30 determines that the smoothed defect rate corresponding to the N consecutive lifespan points has fluctuated significantly compared to the risk lifespan threshold, and that these N consecutive lifespan points are all lifespan points after the tool properties have initially deteriorated. Therefore, the processor 30 determines the Nth lifespan point as the risk lifespan point. For example, r1, r2, and r3 are 0.1, 0.15, and 0.2 respectively, and the preset lifespan limit coefficient is 1.1. Then, the risk lifespan threshold = 1.1 * max{0.1, 0.15, 0.2} = 0.22, and N is 5. If the smoothed defect rate corresponding to each lifespan point in a certain lifespan quality mapping sequence is {0.1, 0.15, 0.2, 0.25, 0.25, 0.3, 0.29, 0.3, 0.32}, and {0.25, 0.25, 0.3, 0.29, 0.3} is not less than 0.22, then the lifespan point corresponding to the first 0.25 is determined as the risk lifespan point.

[0068] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, based on the determination of the risk life threshold, the smoothed defect rate corresponding to each life point in the life quality mapping sequence is sequentially compared with the risk life threshold to determine the risk life point. In this way, the process of determining the risk life point is simple and reliable, fully ensuring that the risk life point can effectively reflect the time point when the tool's condition begins to deteriorate, which is beneficial for providing reliable data support for determining the life warning value.

[0069] Please refer to Figure 1 , Figure 9 and Figure 10 In some implementations, the lifespan critical point also includes the ultimate lifespan point. 06: Determining the lifespan critical point characterizing tool performance degradation based on the lifespan quality mapping sequence further includes: 065: Using a preset algorithm, the lifetime quality mapping sequence is divided into a first dataset and a second dataset. The maximum smoothed defect rate in the first dataset is less than or equal to the minimum smoothed defect rate in the second dataset, and the maximum lifetime point corresponding to the smoothed defect rate in the first dataset is less than the minimum lifetime point corresponding to the smoothed defect rate in the second dataset; and... 066: Take the starting point of the lifetime point in the second dataset as the limit lifetime point.

[0070] Furthermore, please combine Figure 16 The processor 30 is also used to execute the methods in 065 and 066. Specifically, the processor 30 is configured to: use a preset algorithm to divide the lifetime quality mapping sequence into a first dataset and a second dataset, wherein the maximum value of the smoothed defect rate in the first dataset is less than or equal to the minimum value of the smoothed defect rate in the second dataset, and the maximum value of the lifetime point corresponding to the smoothed defect rate in the first dataset is less than the minimum value of the lifetime point corresponding to the smoothed defect rate in the second dataset; and take the starting point of the lifetime point in the second dataset as the limit lifetime point.

[0071] Specifically, the limit life point represents the point in the tool's lifespan where its condition significantly deteriorates, potentially leading to a sharp decline in machining quality. This is represented by the number of products processed, or the product processing sequence number mentioned above. It can be understood that the limit life point is greater than the risk life point and corresponds to the longest usable lifespan of the tool.

[0072] The preset algorithm is used to determine the limit lifespan point. The preset algorithm can be a fixed, pre-set algorithm, an unmodifiable algorithm stored in the memory 100 before the monitoring device 100 leaves the factory, or an algorithm written, adjusted, or replaced by the operator in the memory 10. The processor 30 inputs the lifespan quality mapping sequence into the preset algorithm, which divides the lifespan quality mapping sequence into a first dataset and a second dataset.

[0073] It should be noted that the preset algorithm divides the lifetime quality mapping sequence based on the change of the smoothed defect rate with lifetime points. The first dataset represents a dataset where the smoothed defect rate changes relatively smoothly with lifetime points, while the second dataset represents a dataset where the smoothed defect rate changes more drastically with lifetime points. Furthermore, the first and second datasets also satisfy the following conditions: the maximum smoothed defect rate in the first dataset is less than or equal to the minimum smoothed defect rate in the second dataset, and the maximum lifetime point corresponding to the smoothed defect rate in the first dataset is less than the minimum lifetime point corresponding to the smoothed defect rate in the second dataset.

[0074] For example, the preset algorithm is the k-means algorithm, a partition-based unsupervised clustering algorithm. Its goal is to divide a given dataset into K (here, 2) disjoint clusters, maximizing the similarity of samples within a cluster and minimizing the similarity between clusters. The algorithm first randomly initializes K cluster centers, then iteratively executes two steps: an assignment step, assigning each sample to the cluster corresponding to the nearest cluster center; and an update step, recalculating the mean of all samples within each cluster as the new cluster center. This process is repeated until the cluster centers no longer change significantly or the preset number of iterations is reached. The k-means algorithm uses minimizing the sum of squared errors between all samples and their respective cluster centers as its optimization criterion, enabling rapid clustering of data.

[0075] At this point, the processor 30 takes the starting point of the lifespan point in the second dataset where the smoothed defect rate changes drastically with the lifespan point, i.e., the first lifespan point, as the limit lifespan point. For example, if the set of smoothed defect rates in the lifespan quality mapping sequence is {0.1, 0.15, 0.11, 0.13, 0.15, 0.2, 0.21, 0.22, 0.3, 0.35, 0.4, 0.5, 0.6, 0.65}, the smoothed defect rates in the first dataset after partitioning are {0.1, 0.15, 0.11, 0.13, 0.15, 0.2, 0.21, 0.22}, and the smoothed defect rates in the second dataset are {0.3, 0.35, 0.4, 0.5, 0.6, 0.65}, then the lifespan point corresponding to 0.3 is determined as the limit lifespan point.

[0076] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, the limit life point is determined by a preset algorithm. In this way, the process of determining the limit life point is simple and reliable, fully ensuring that the limit life point can effectively reflect the time point when the tool's condition significantly deteriorates, which is beneficial for providing reliable data support for determining the life warning value.

[0077] Please refer to Figure 1 and Figure 11In some implementations, each product has multiple inspection points and multiple quality inspection results; correspondingly, there are multiple sets of life-quality mapping sequences. The tool monitoring method also includes: 051: The set of smoothed defect rates {r1, r2, ... r} based on each set of lifetime quality mapping sequences. n}, calculate the set that satisfies r i+1 ≥k·r i The number of weakly increasing defect rates at detection points, where k is a preset coefficient, r i Let represent the smoothed defect rate corresponding to the i-th lifetime point, i=1,2,...,n; 053: If the number of defect rates at weakly increasing detection points is greater than or equal to a preset threshold, then the lifespan quality mapping sequence is determined to exhibit a preset positive correlation trend; and, 055: Based on the life quality mapping sequence that presents a preset positive correlation trend, execute: "06: Based on the life quality mapping sequence, determine the life critical point that characterizes the degradation of tool performance".

[0078] Furthermore, please combine Figure 16 The processor 30 is also used to execute the methods in 051, 053, and 055. Specifically, the processor 30 is configured to: based on the set of smoothed defect rates {r1, r2, ... r} in each set of lifetime quality mapping sequences. n}, calculate the set that satisfies r i+1 ≥k·r i The number of weakly increasing defect rates at detection points, where k is a preset coefficient, r i Let i represent the smoothed defect rate corresponding to the i-th lifespan point, i=1,2,...,n; if the number of defect rates at weakly increasing detection points is greater than or equal to a preset threshold, then the lifespan quality mapping sequence is determined to show a preset positive correlation trend; and, based on the lifespan quality mapping sequence showing a preset positive correlation trend, execute: "Based on the lifespan quality mapping sequence, determine the lifespan critical point characterizing the degradation of tool performance".

[0079] Specifically, in the above embodiments, for each cutting tool, each product includes multiple inspection points. Each inspection point has a quality inspection result, so there are also multiple quality inspection results. Correspondingly, the lifespan quality mapping sequence consists of multiple sets, for example... Figure 7 As shown in (C). At this time, the processor 30 obtains the set of smoothed defect rates {r1, r2, ... r1} in the lifetime quality mapping sequence corresponding to each detection point. n}, and analyze the above sets.

[0080] As can be understood, as mentioned above, with the repetition of the machining process, the defect rate at inspection points generally increases with the increase of the actual service life of the cutting tool. Therefore, for each set {r1, r2, ... r... n The elements in {r1, r2, ... r} (smoothed defect rate) should generally show an increasing trend. It is understandable that, due to the existence of systematic errors, it is permissible for the set {r1, r2, ... r} to have an increasing trend. n The smoothed defect rate in the} does not increase sequentially, but the overall trend should not be stable or decreasing.

[0081] Define a set of smoothed defect rates {r1, r2, ... r}. n In}, r satisfies i+1 ≥k·r i The smoothed defect rate is the defect rate at weakly increasing detection points, where k is a preset coefficient, and r i Let represent the defect rate after smoothing, where i = 1, 2, ..., n. At this point, processor 30 calculates and counts the number of defect rates at weakly increasing detection points in the set.

[0082] The preset threshold is the minimum number of weakly increasing defect rates at detection points when the lifetime quality mapping sequence exhibits a preset positive correlation trend. The processor 30 compares the number of weakly increasing defect rates at detection points with the preset threshold. If the number of weakly increasing defect rates at detection points is greater than or equal to the preset threshold, it determines that the lifetime quality mapping sequence exhibits a preset positive correlation trend, i.e., it determines that the reliability of the lifetime quality mapping sequence is good.

[0083] In some implementations, the set of smoothed defect rates {r1, r2, ... r} in the lifetime quality mapping sequence will also be included. n In}, r is not satisfied i+1 ≥k·r i The smoothed defect rate is the defect rate of non-weakly increasing detection points. The second preset threshold is the maximum number of non-weakly increasing detection point defect rates when the lifetime quality mapping sequence shows a preset positive correlation trend. The processor 30 compares the number of weakly increasing detection point defect rates with the preset threshold and the number of non-weakly increasing detection point defect rates with the second preset threshold. If the number of weakly increasing detection point defect rates is greater than or equal to the preset threshold and the number of non-weakly increasing detection point defect rates is less than the second preset threshold, then it is determined that the lifetime quality mapping sequence shows a preset positive correlation trend, that is, it is determined that the reliability of the lifetime quality mapping sequence is good.

[0084] At this time, the processor 30 uses only the lifetime quality mapping sequence that presents a preset positive correlation trend to execute: "06: Based on the lifetime quality mapping sequence, determine the lifetime critical point that characterizes the degradation of tool performance" to ensure that the generated lifetime critical point is relatively accurate and reliable.

[0085] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, by screening the life quality mapping sequence that presents a preset positive correlation trend and using it to generate the life critical point, the accuracy and reliability of the data source in the life critical point determination process are ensured, the authenticity of the life warning value is fully ensured, and it is beneficial to implement reliable tool monitoring. Please refer to Figure 1 and Figure 12 In some implementations, the life quality mapping sequence exhibiting a preset positive correlation trend is divided into multiple sets. Correspondingly, there are multiple risk life points and limit life points, and the life warning value includes a risk life warning value and a limit life warning value. 08: Based on the life critical point, the tool life warning value is generated, including: 081: The minimum value among multiple risk life points is used as the tool's risk life warning value; and, 083: The minimum value among multiple limit life points is used as the limit life warning value for the tool.

[0086] Furthermore, please combine Figure 16 The processor 30 is also used to execute the methods in 081 and 083. Specifically, the processor 30 is configured to: use the minimum value among a plurality of risk life points as the risk life warning value of the tool; and use the minimum value among a plurality of limit life points as the limit life warning value of the tool.

[0087] Specifically, when there are multiple sets of life-quality mapping sequences exhibiting a preset positive correlation trend, a tool has multiple sets of available data for solving the life-critical point. Correspondingly, the tool can derive multiple risk life points and limit life points using multiple sets of life-quality mapping sequences exhibiting a preset positive correlation trend. The risk life warning value is a comprehensive value of risk life points with good warning effect, obtained by a tool from multiple sets of life-quality mapping sequences exhibiting a preset positive correlation trend; the limit life warning value is a comprehensive value of limit life points with good warning effect, obtained by a tool from multiple sets of life-quality mapping sequences exhibiting a preset positive correlation trend.

[0088] It is understandable that multiple sets of lifespan quality mapping sequences showing a preset positive correlation trend are data corresponding to a tool at different processing points. Since the tool needs to process multiple processing points sequentially during the processing of a product, if the risk lifespan of the detection point corresponding to a certain processing point is relatively small, while the risk lifespan of the detection point corresponding to another processing point is relatively large, if the larger risk lifespan is used as the benchmark, the yield rate of the processing point with the smaller risk lifespan will be greatly reduced after exceeding the smaller risk lifespan. At this time, even if the defect rate of the processing point with the larger risk lifespan is low, it is meaningless for the tool's early warning in the entire product processing process.

[0089] Based on the above logic, the determination of risk life warning values ​​and limit life warning values ​​should focus on the "shortcomings" between the risk life point and the limit life point. Therefore, processor 30 uses the minimum value among multiple risk life points as the tool's risk life warning value to ensure that the risk life warning value plays a reasonable warning role for the entire product processing. Simultaneously, processor 30 also uses the minimum value among multiple limit life points as the tool's limit life warning value to ensure that the limit life warning value plays a reasonable warning role for the entire product.

[0090] For example, the life quality mapping sequence of tool A at the FAI49 detection point is a life quality mapping sequence showing a preset positive correlation trend, with a risk life point of 100 and a limit life point of 400; the life quality mapping sequence of tool A at the FAI509 detection point is a life quality mapping sequence showing a preset positive correlation trend, with a risk life point of 120 and a limit life point of 300; the life quality mapping sequence of tool A at the FAI40 detection point is a life quality mapping sequence showing a preset positive correlation trend, with a risk life point of 150 and a limit life point of 420; then the risk life warning value of tool A is 100, and the limit life warning value is 300.

[0091] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, in multiple sets of life quality mapping sequences that present a preset positive correlation trend, the minimum value among multiple risk life points and the minimum value among multiple limit life points are respectively determined as the risk life warning value and the limit life warning value of the tool, which fully ensures the rationality of the life warning value and is conducive to ensuring the overall product yield. Please refer to Figure 1 and Figure 13 In some embodiments, the tool monitoring method further includes: 091: When the actual service life of the current tool reaches the risk life warning value, a reminder signal is sent to the machining equipment so that the monitoring interface of the machining equipment can display a prompt; and / or, 093: When the actual service life of the current tool reaches the limit life warning value, a tool change signal is sent to the machining equipment to trigger an alarm and prompt the machining equipment to change the tool.

[0092] Furthermore, please combine Figure 16 The processor 30 is also used to execute the methods in 091 and 093. Specifically, the processor 30 is configured to: send a reminder signal to the processing equipment when the actual service life reaches the risk service life warning value, so that the monitoring interface of the processing equipment will provide a prompt; and send a tool change signal to the processing equipment when the actual service life reaches the limit service life warning value, so as to trigger an alarm in the processing equipment and prompt for tool change.

[0093] Specifically, it can be understood that, under normal circumstances, the risk life warning value is lower than the limit life warning value, and the performance of the tool corresponding to the risk life warning value is better than the performance of the tool corresponding to the limit life warning value. Once the life warning value of a certain tool is obtained, current tools of the same model as that tool can be monitored.

[0094] In some embodiments, the processor 30 continuously monitors the actual service life of the current tool, and when the actual service life reaches a risk life warning value, the processor 30 determines that the performance of the current tool may be deteriorating. At this time, the processor 30 sends a reminder signal to the machining equipment where the current tool is located to alert the operator. This prompts the operator through a pop-up window or similar means on the machining equipment's monitoring interface, allowing the operator to determine whether the current tool needs to be addressed, such as replaced or calibrated. In some embodiments, the machining equipment's monitoring interface also displays the defect rate of detection points corresponding to at least a portion of the tool's service life for the operator's reference.

[0095] In other embodiments, the processor 30 continuously monitors the actual service life of the current tool. When the actual service life reaches a critical warning value, the processor 30 determines that the current tool's performance may have reached its limit, and the tool may need to be replaced to avoid a large number of defective products. At this time, the processor 30 controls the machining equipment containing the current tool to trigger an alarm signal. This alarm is then triggered by a pop-up window, an audible alert, or other means, prompting the operator to replace the tool. In some embodiments, the monitoring interface of the machining equipment also displays the defect rate at at least a portion of the tool's service life for the operator's reference.

[0096] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, during the monitoring of the current tool, when the actual service life reaches the risk life warning value and / or the limit life warning value, corresponding prompting measures are adopted respectively to implement reliable monitoring of the performance of the current tool, ensuring that the current tool will not produce a large number of defective products due to excessive use time, significantly improving the processing yield, and realizing intelligent and reliable management of the processing process. Please refer to Figure 1 , Figure 9 and Figure 14 In some implementations, the monitoring method further includes: 071: If the limit lifetime point is less than or equal to the risk lifetime point, then the limit lifetime point is removed. 073: The lifespan points preceding the risk lifespan point in the lifespan-quality mapping sequence and their corresponding smoothed defect rates are considered the stable phase; and the lifespan points following the risk lifespan point in the lifespan-quality mapping sequence and their corresponding smoothed defect rates are considered the incremental phase; and... 075: When the maximum smoothed defect rate in the gradual increase phase exceeds the preset multiple of the maximum smoothed defect rate in the stable phase, the risk life point will be corrected to the new limit life point.

[0097] Furthermore, please combine Figure 16 The processor 30 is also configured to execute the methods in 071, 073, and 075. Specifically, the processor 30 is configured to: remove the limit lifetime point if it is less than or equal to the risk lifetime point; take all lifetime points before the lifetime point corresponding to the risk lifetime point in the lifetime quality mapping sequence and their corresponding smoothed defect rates as a stable phase, and take all lifetime points after the lifetime point corresponding to the risk lifetime point in the lifetime quality mapping sequence and their corresponding smoothed defect rates as an increasing phase; and, when the maximum smoothed defect rate in the increasing phase exceeds a preset multiple of the maximum smoothed defect rate in the stable phase, correct the risk lifetime point to a new limit lifetime point.

[0098] Specifically, since the algorithms for determining the risk lifetime point and the ultimate lifetime point are two independent algorithms, ideally, the ultimate lifetime point should be greater than the risk lifetime point, and the smoothed defect rates of the multiple stages divided by the risk lifetime point and the ultimate lifetime point in the lifetime-quality mapping sequence should have significant differences. The smoothed defect rate after the risk lifetime point should be smaller and grow slowly, the smoothed defect rate between the risk lifetime point and the ultimate lifetime point should be smaller and grow slightly faster, and the smoothed defect rate after the ultimate lifetime point should be larger and grow rapidly. Figure 9 As shown.

[0099] However, due to the complexity of the actual life quality mapping sequence and the potential for systematic errors, the correlation between risk life points and ultimate life points, as well as the division of the life quality mapping sequence by risk life points and ultimate life points, may differ from the ideal situation described above.

[0100] Processor 30 compares the risk lifetime point with the limit lifetime point, and if the limit lifetime point is less than or equal to the risk lifetime point, it determines that the limit lifetime point is unreasonable and removes it. At this point, only the risk lifetime point remains in this lifetime quality mapping sequence.

[0101] Furthermore, the processor 30 uses this risk lifetime point to divide the lifetime quality mapping sequence. Specifically, it divides all lifetime points before the lifetime point corresponding to the risk lifetime point and their corresponding smoothed defect rates into a stable phase, and divides all lifetime points after the lifetime point corresponding to the risk lifetime point and their corresponding smoothed defect rates into an increasing phase. After the division is completed, the lifetime quality mapping sequence is further analyzed.

[0102] At this time, the processor 30 obtains the maximum smoothed defect rate during the gradual increase phase and the maximum smoothed defect rate during the stable phase, and performs calculations using these two values. The preset multiple is the ratio of the maximum smoothed defect rate during the rapid increase phase to the maximum smoothed defect rate during the stable phase under ideal conditions. The preset multiple is a preset fixed value, which can be an unmodifiable value stored in the memory 10 before the monitoring device 100 leaves the factory, or a value written, adjusted, or replaced by the operator in the memory 10.

[0103] If the processor 30 determines that the maximum smoothed defect rate in the incremental phase exceeds a preset multiple of the maximum smoothed defect rate in the stable phase, it judges that all life points after the risk life point and the corresponding smoothed defect rates are large, and the performance of the tool may have degraded to a poor level after this risk life point. At this time, the processor 30 corrects the risk life point to a new limit life point to ensure the early warning effect.

[0104] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, the reliability of the generated risk life point or limit life point is ensured by the correction process of the risk life point and limit life point, thereby ensuring the rationality and reliability of the subsequent step of generating life warning value, which is conducive to reliable monitoring of the tool.

[0105] Please refer to Figure 1 , Figure 9 and Figure 15 In some implementations, the monitoring method further includes: 077: All lifespan points between the risk lifespan point and the extreme lifespan point in the lifespan quality mapping sequence, along with their corresponding smoothed defect rates, are considered the increasing phase; all lifespan points before the lifespan point corresponding to the risk lifespan point in the lifespan quality mapping sequence, along with their corresponding smoothed defect rates, are considered the stable phase; and all lifespan points after the lifespan point corresponding to the extreme lifespan point in the lifespan quality mapping sequence, along with their corresponding smoothed defect rates, are considered the explosive phase; and... 079: If the maximum defect rate after smoothing during the outbreak phase does not reach the preset multiple of the maximum defect rate after smoothing during the stable phase, then the limit life point is cancelled.

[0106] Furthermore, please combine Figure 16 The processor 30 is also configured to execute the methods in 077 and 079. Specifically, the processor 30 is configured to: use all lifetime points between the risk lifetime point and the limit lifetime point in the lifetime quality mapping sequence and their corresponding smoothed defect rates as an increasing phase; use all lifetime points before the lifetime point corresponding to the risk lifetime point in the lifetime quality mapping sequence and their corresponding smoothed defect rates as a stable phase; and use all lifetime points after the lifetime point corresponding to the limit lifetime point in the lifetime quality mapping sequence and their corresponding smoothed defect rates as an explosive phase; and if the maximum smoothed defect rate in the explosive phase does not reach a preset multiple of the maximum smoothed defect rate in the stable phase, then the limit lifetime point is canceled.

[0107] Specifically, when the lifetime quality mapping sequence deviates only slightly from the ideal situation, the lifetime quality mapping sequence can be further classified into similar categories. Figure 9 The aforementioned stage. At this point, the processor 30 divides the lifetime quality mapping sequence using the risk lifetime point and the limit lifetime point. Specifically, all lifetime points before the lifetime point corresponding to the risk lifetime point and their corresponding smoothed defect rates are classified as a stable stage; all lifetime points after the lifetime point corresponding to the limit lifetime point and their corresponding smoothed defect rates are classified as a burst stage; and all lifetime points after the lifetime point between the risk lifetime point and the limit lifetime point and their corresponding smoothed defect rates are classified as an increasing stage. After the division is completed, the lifetime quality mapping sequence is further analyzed.

[0108] At this point, the processor 30 obtains the maximum smoothed defect rate during the burst phase and the maximum smoothed defect rate during the stable phase, and performs calculations using these two values. The preset multiple is explained as above and will not be repeated here. When the processor 30 determines that the maximum smoothed defect rate during the burst phase is a preset multiple of the maximum smoothed defect rate during the stable phase, it judges that all lifespan points after the limit lifespan point and their corresponding smoothed defect rates are relatively small. This indicates that the tool's performance may not have degraded to a poor level after this risk lifespan point. In this case, the processor 30 cancels the limit lifespan point and only retains the risk lifespan point to ensure full utilization of the tool.

[0109] Therefore, in the tool monitoring method and tool monitoring device 100 provided by the present invention, the reliability of the generated risk life point or limit life point is ensured by the correction process of the risk life point and limit life point, while avoiding the underestimation of the tool's service life, which would lead to waste of tool use, and ensuring full utilization of the tool, which is conducive to reducing processing costs.

[0110] The technical features of the embodiments described above can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. Furthermore, other implementation methods can be derived from the above embodiments, allowing for structural and logical substitutions and changes without departing from the scope of this disclosure.

[0111] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A tool monitoring method, characterized in that, include: Acquire machining process data generated by the cutting tool processing multiple products and quality inspection results for each inspection point of each product; The actual service life of the cutting tool can be determined based on the machining process data. Based on the actual service life and the quality test results, establish a service life quality mapping sequence related to the actual service life and the quality test results; Based on the life quality mapping sequence, determine the life critical point that characterizes the performance degradation of the tool; and, Based on the aforementioned lifespan critical point, a lifespan warning value for the cutting tool is generated.

2. The tool monitoring method according to claim 1, characterized in that, The machining process data includes tool length and machine tool life recorded; the process of reconstructing the actual tool life based on the machining process data includes: Monitor changes in the tool length to determine whether the tool has actually been replaced; When the tool is actually replaced, the tool life record of the machine tool is reset to zero; and, If the cutting tool has not been actually replaced, the change in the tool life recorded by the machine tool during the current machining cycle is added to the tool life recorded by the machine tool, and this sum is taken as the actual service life.

3. The tool monitoring method according to claim 2, characterized in that, The monitoring of changes in the tool length to determine whether the tool has actually been replaced includes: When the change in the tool length is greater than or equal to a preset length threshold, it is determined that the tool has been actually replaced; and, If the change in the tool length is less than the preset length threshold, it is determined that the tool has not actually been replaced.

4. The tool monitoring method according to claim 1, characterized in that, Also includes: Obtain the quality value of each of the detection points of the product; Compare the quality value with the testing specification range; When the quality value is within the range of the detection specifications, the quality detection result of the detection point is determined to be good; and, When the quality value exceeds the range of the detection specifications, the quality detection result of the detection point is determined to be unsatisfactory.

5. The tool monitoring method according to claim 1, characterized in that, The actual service life is the product processing serial number formed by sequentially numbering each processed product. The step of establishing a life-quality mapping sequence related to the actual service life of the tool and the quality inspection results, based on the actual service life and the quality inspection results, includes: Based on the product processing serial number, it is divided into multiple consecutive lifespan intervals according to preset rules; Based on the product processing serial number and corresponding quality inspection results within each of the lifespan intervals, the defect rate at each inspection point of the product within each of the lifespan intervals is determined to obtain an initial defect rate sequence; and, The initial defect rate sequence is smoothed to obtain the lifetime quality mapping sequence.

6. The tool monitoring method according to claim 5, characterized in that, The lifetime quality mapping sequence includes lifetime points associated with the lifetime interval and smoothed defect rates corresponding to the lifetime points; The critical lifespan point includes a risky lifespan point; determining the critical lifespan point characterizing the tool performance degradation based on the lifespan quality mapping sequence includes: Based on the life quality mapping sequence and the preset tool life, the smoothed defect rate that matches the preset tool life is selected from the life quality mapping sequence; Based on the smoothed defect rate matched with the preset lifespan and the preset lifespan limit coefficient, the risk lifespan threshold is determined. For each lifetime point in the lifetime quality mapping sequence, the smoothed defect rate is sequentially determined to be not less than the risk lifetime threshold; and, If the smoothed defect rate corresponding to N consecutive lifetime points is not less than the risk lifetime threshold, and N is not less than a preset number, then the Nth lifetime point is determined as the risk lifetime point.

7. The monitoring method according to claim 6, characterized in that, The critical life point also includes the ultimate life point. The step of determining the critical life point characterizing the tool performance degradation based on the life quality mapping sequence further includes: Using a preset algorithm, the lifetime quality mapping sequence is divided into a first dataset and a second dataset. The maximum smoothed defect rate in the first dataset is less than or equal to the minimum smoothed defect rate in the second dataset, and the maximum lifetime point corresponding to the smoothed defect rate in the first dataset is less than the minimum lifetime point corresponding to the smoothed defect rate in the second dataset. The starting point of the lifetime point in the second dataset is taken as the ultimate lifetime point.

8. The tool monitoring method according to any one of claims 6 or 7, characterized in that, Each product has multiple detection points, multiple quality detection results, and correspondingly, multiple sets of life-quality mapping sequences. The tool monitoring method further includes: Based on the set of smoothed defect rates {r1, r2, ... r} in each set of the life quality mapping sequence. n }, calculate the set that satisfies r i+1 ≥k·r i The number of weakly increasing defect rates at detection points, where k is a preset coefficient, r i This represents the smoothed defect rate corresponding to the i-th lifetime point, where i = 1, 2, ..., n; If the number of defect rates at the weakly increasing detection points is greater than or equal to a preset threshold, then the lifespan quality mapping sequence is determined to exhibit a preset positive correlation trend; and, Based on the life quality mapping sequence that presents a preset positive correlation trend, the following is executed: "Based on the life quality mapping sequence, determine the life critical point that characterizes the performance degradation of the tool." 9. The tool monitoring method according to claim 7, characterized in that, The life quality mapping sequence, which presents a preset positive correlation trend, is divided into multiple sets. Correspondingly, there are multiple risk life points and limit life points. The life warning value includes a risk life warning value and a limit life warning value. The step of generating the tool's life warning value based on the life critical point includes: The minimum value among the multiple risk life points is used as the risk life warning value for the tool; and, The minimum value among the multiple limit life points is used as the limit life warning value of the tool.

10. The tool monitoring method according to claim 9, characterized in that, Also includes: When the actual service life of the current tool reaches the risk life warning value, a reminder signal is sent to the machining equipment so that the monitoring interface of the machining equipment will issue a prompt; and / or, When the actual service life of the current tool reaches the limit life warning value, a tool change signal is sent to the machining equipment to trigger an alarm and prompt the machining equipment to change the tool.

11. The monitoring method according to claim 7, characterized in that, Also includes: If the critical lifetime point is less than or equal to the risk lifetime point, then the critical lifetime point is eliminated. The lifespan points preceding the risk lifespan point in the lifespan quality mapping sequence and their corresponding smoothed defect rates are defined as a stable phase, and the lifespan points following the risk lifespan point in the lifespan quality mapping sequence and their corresponding smoothed defect rates are defined as an increasing phase; and... If the maximum smoothed defect rate in the gradual increase phase exceeds a preset multiple of the maximum smoothed defect rate in the stable phase, then the risk life point is corrected to a new limit life point.

12. The monitoring method according to claim 7, characterized in that, Also includes: The following stages are defined as follows: all lifespan points between the risk lifespan point and the extreme lifespan point in the lifespan quality mapping sequence, along with their corresponding smoothed defect rates, constitute the gradual increase stage; all lifespan points before the lifespan point corresponding to the risk lifespan point in the lifespan quality mapping sequence, along with their corresponding smoothed defect rates, constitute the stable stage; and all lifespan points after the lifespan point corresponding to the extreme lifespan point in the lifespan quality mapping sequence, along with their corresponding smoothed defect rates, constitute the burst stage. If the maximum smoothed defect rate in the burst phase does not reach a preset multiple of the maximum smoothed defect rate in the stable phase, then the limit life point is cancelled.

13. A tool monitoring device, comprising a memory and a processor 30, wherein the memory is used to store instructions, characterized in that, The instructions stored in the memory are executed by the processor 30 to implement the tool monitoring method according to any one of claims 1-12.

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